The Association Between Diet Quality Scores with Inflammation and Treatment Outcomes in Children with Acute Lymphoblastic Leukemia; A Cross-Sectional Study

The Association Between Diet Quality Scores with Inflammation and Treatment Outcomes in Children with Acute Lymphoblastic Leukemia; A Cross-Sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Association Between Diet Quality Scores with Inflammation and Treatment Outcomes in Children with Acute Lymphoblastic Leukemia; A Cross-Sectional Study Mehrdad jamali, Maryam Behroz, Pedram Pam, Hosna Ghorbani, Yousef Tavakolifar, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4332670/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Acute Lymphoblastic Leukemia is the most common childhood cancer. Considering the importance of diet in the treatment process of cancer patients, the purpose of this study was to investigate the relationship between diet quality and inflammatory/therapeutic outcomes. Methods In this cross-sectional study, 147-item Food Frequency Questionnaire was used to collect dietary data from patients. Diet quality was evaluated by the Healthy Eating Index 2015 (HEI-2015), Dietary Diversity Score (DDS), Dietary Acid Load (DAL), and Planet Base Diet Index (PDI). Linear regression analysis was then employed to explore potential associations between dietary scores and the C-reactive protein (CRP), Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), Platelet-to-Lymphocyte Ratio (PLR), Prognostic Nutrition Index (PNI), Prognostic Index (PI), Glasgow prognostic score (GPS), Febrile neutropenia (FN), and Hospitalization duration outcomes. Result In this study with 54 patients, we found that a higher DDS score is linked to a reduction in NLR (ß: -0.30, P-value: 0.057) and an increase in PNI among women (ß: 3.90, P-value: 0.01). Furthermore, an inverse relationship was observed between the PDI score and both CRP (ß: -0.63, P-value: 0.02) and GPS (ß: -0.02, P-value: 0.052) in men. However, the length of hospital stay was seen to rise with an increase in PDI, both in crude models (ß: 0.36, P-value: 0.03) and when adjusted for other factors (ß: 0.40, P-value: 0.02). No additional significant links were discovered between food scores and the outcomes studied. Conclusion In conclusion, a diet that is both higher in quality and more varied leads to a reduction in inflammation-related outcomes. Furthermore, closely following PDI guidelines is linked to longer hospital stays. To achieve more dependable findings, further research in this area is necessary. Acute Lymphoblastic Leukemia Diet Quality Scores Inflammation Outcomes Treatment Outcomes Cross-Sectional Study 1. Introduction Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children, representing about 25% of cancer diagnoses among those under 15, characterized by the overproduction of immature white blood cells, known as lymphoblasts, in the bone marrow [ 1 , 2 ]. The incidence of childhood leukemia appears to be increasing and the overall age-standardized incidence rate of leukemia is 48.4 per million person-years in children aged 0–14 years [ 3 ]. The incidence of ALL is particularly high among children aged 2 to 5, with approximately 3,000 new cases diagnosed in the United States each year. Also, in Iran the average annual incidence rate of ALL was 2.25 per 100 000 children under 15 years of age according to study conducted by Sajjad Rahimi Pordanjani et al [ 4 ]. Despite its prevalence, due to the improvements in the treatment of pediatrics ALL over the past several decades, the 5-year survival rate now exceeds 90% in most developed countries [ 5 ]. The treatment of ALL typically involves a multi-phased approach, including induction, consolidation, and maintenance phases, to achieve and sustain remission. Chemotherapy is key in treating diseases, but its intensity can cause issues like neutropenia, a low neutrophil count leading to infection susceptibility, hospital stays, and treatment interruptions [ 6 ]. Inflammation, vital for defense, can worsen conditions like ALL [ 7 , 8 ], exacerbated by treatments like chemotherapy, complicating recovery. This condition necessitates intensive medical intervention and can prolong hospital stays, disrupt achieving remission, and pose severe health risks. The interplay between inflammation and treatment outcomes in ALL is intricate, with increased inflammatory markers often indicating a poorer prognosis and influencing the effectiveness of chemotherapy [ 9 – 11 ]. Managing inflammation alongside targeting cancer cells is crucial for treatment effectiveness, remission likelihood, and minimizing complications in ALL [ 12 ]. Nutrition and diet are considered a modifiable risk factor for chronic diseases associated with systemic inflammation [ 13 , 14 ]. Diet quality is generally defined as a dietary pattern or an index of diversity among crucial food groups consumed by individuals compared to those recommended in nutritional guidelines [ 15 , 16 ]. With regard to ALL, particularly before during the induction phase of treatment, diet quality assumes a significant role. The induction phase is the initial and most critical phase of treatment, aiming to achieve complete remission by eradicating leukemia cells [ 17 ]. Diet quality can have a profound impact in this condition. A high-quality diet can support the body's immune response, help manage inflammation, and provide the strength needed for the body to cope with the aggressive treatment regimen [ 18 ]. Moreover, the relationship between diet quality, inflammation, and treatment outcomes is particularly relevant in the induction phase of ALL treatment. Proper diet can help mitigate the side effects of chemotherapy, reduce the risk of severe complications like infections, and improve the body's resilience [ 19 ]. For instance, certain dietary components can have anti-inflammatory properties, helping to manage the systemic inflammation associated with ALL and its treatment. This, in turn, can influence treatment outcomes by potentially shortening hospital stays, reducing the incidence of complications such as febrile neutropenia, and supporting the overall effectiveness of the induction therapy [ 20 ]. To evaluate the diet quality, several indices are used that examine the quality of diet from various aspects such as variety, balance, adequacy, anti-inflammatory potential and dietary diversity, and in several studies, the relationship of these indicators with different outcomes of childhood cancer patients has been evaluated [ 21 ]. The results of the study by Sophie Bérard et al showed that 36.9% of ALL survivors had poor adherence to the World Health Organization (WHO) recommendations and 76.3% had a diet to be improved according to the HEI-2015 score. also, this study suggested that Low HDL-C was associated with a more inflammatory diet and higher intake of ultra-processed foods. A greater E DII score was associated with elevated insulin resistance (HOMA-IR), and consumption of ultra-processed foods was correlated with high triglycerides [ 22 ]. Also based on the results of Catharine Fleming's study childhood cancer survivors who have recently completed cancer treatment have poor diet quality compared to age-matched controls and have high rates of picky eating [ 23 ]. about active cases of ALL, the result of the study by Asma’ Athifah et al. showed that 40% of patients with ALL have poor nutritional status and 11% of them did not achieve remission [ 24 ]. Moreover, based on the results of a study conducted by Jennifer Cohen, Children receiving cancer treatment were not consuming adequate intake of vegetables, fruit, and milk/alternatives [ 25 ]. In addition, based on the results of the study by S Y Tan et al., children with acute leukemia did not have a proper nutritional status and received less dietary intake than they needed [ 26 ]. Since previous studies have mostly examined the diet quality of survivors or assessed nutritional status (rather than diet quality) in active patients, this study aimed to explore the diet quality of ALL patients before starting the induction phase and its relationship with inflammation status and treatment outcomes at the end of the induction phase. 2. Methods and materials 2.1. Setting and study design This cross-sectional study was conducted at Mardani Azar Children's Hospital located in Tabriz, Iran, between January 2023 to January 2024. The setting included the pediatric oncology department and associated outpatient clinics within the hospital. The study protocol was approved by the ethics committee of Tabriz University of Medical Sciences (ethic number: IR.TBZMED.REC.1401.1080). Informed consent was obtained from all participants or their guardians before data collection. Confidentiality and anonymity of the participants' information were strictly maintained throughout the study. 2.2. Study population The target population consisted of newly diagnosed pediatric patients with ALL receiving treatment. Participants were included if they were between the ages of 5 and 13, diagnosed with ALL, and candidates for the induction phase of chemotherapy. Patients were excluded if they had co-existing chronic diseases that could independently affect dietary intake or inflammatory markers. Due to the low number of these patients, a convenience sampling method in a period of one year was used. 2.3. Anthropometric, clinical, and biochemical assessment The weight (kg) of people was measured by a digital scale with an accuracy of 0.5 kg. The height (cm) of people was calculated by a special anthropometric meter and BMI (kg/cm2) was obtained. For patients aged 3 to 20 years, the BMI z-score was calculated using the Centers for Disease Control and Prevention (CDC) growth chart for children [ 27 ]. Obesity as BMI z-score ≥ 1.645 (≥ 95th percentile), overweight as BMI z-score = 1.036–1.644 (85th-94.9th percentile) and healthy weight as BMI z-score = -1.645-1.035 (5th- 84.9 percentile) was considered based on the current recommendations of the CDC [ 28 ]. low-grade and visceral inflammation [C-reactive protein (CRP, mg/L) and albumin (gr/dl) were measured on fasting blood. To measure CRP, we used the CRP turbidimetry kit manufactured by DELTA DARMAN PART 2.4. Inflammation outcomes assessment The inflammatory status of patients was evaluated using neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Monocyte-to-lymphocyte ratio (MLR), Prognostic nutritional index (PNI), Glasgow prognostic index (GPS) and Prognostic index (PI) indices. NLR was obtained by dividing the absolute number of neutrophils by the absolute number of lymphocytes. MLR by dividing the absolute number of monocytes by the absolute number of lymphocytes and PLR by dividing the direct number of platelets by the direct number of lymphocytes. GPS was obtained by CRP (g/L) and serum ALB (g/L) as 0, 1 and 2. A GPS score of 0 is given to individuals with CRP 35 g/L. A GPS score of 1 for those with CRP greater than 10 g/L, or ALB 10 g/L and ALB 50 is considered normal. PNI value 45 indicates mild malnutrition. A PNI value 40 indicates moderate malnutrition. A PNI value 1mg/dl and the number of white blood cells > 11*10^9/L, PI = 1 for people with either CRP > 1 mg/dl or the number of White blood cells > 11* 10^9/L (not both) and PI = 0 for people with both numbers in the normal range [ 31 ]. 2.5. Treatment outcomes assessment The treatment outcomes include the complete remission achievement, the hospitalization duration in the induction phase of the treatment, and the duration of febrile neutropenia. Achievement to remission was determined by examining blast cells so that less than 5% of the bone marrow is blast cells [ 32 ]. 2.6. Data collection and analysis for dietary intake Information regarding the demographic details of participants' families, including ethnicity, occupation, and education, was gathered through a questionnaire administered via face-to-face interviews. To assess the dietary intake of subjects, a validated semi-quantitative Food Frequency Questionnaire (FFQ) with 147 items was utilized [ 33 ]. The assessment of dietary intake was for one year before the interview. The trained interviewer asked all participants to indicate their daily, weekly, and monthly consumption. Accordingly, the frequency of consumption of each food item the evaluation of dietary intake covered the year preceding the interview. The interviewer, who was trained for this purpose, requested participants to specify their daily, weekly, and monthly food consumption. Subsequently, the frequency of each food item's intake was categorized into nine groups: "never or less than once a month," "1 to 3 times a month," "once a week," "2 to 4 times a week," "5 to 6 times a week," "once a day," "2 to 3 times a day," "4 to 5 times a day," and "6 or more times a day." Participants were also asked about the average consumption per meal based on the portion size of each food item, with portion sizes explained using a food album. The daily gram intake of each food item was then calculated considering both the frequency and amount of consumption. Nutrient intake for each participant was estimated using data from the United States Department of Agriculture (USDA) food composition and Nutritionist 4 software. In cases where traditional Iranian foods were not present in the USDA database, the Iranian food composition table was utilized [ 34 ]. 2.7. Diet quality assessment Data collected with the food frequency questionnaires were used to calculate the dietary scores including HEI-2015, Dietary Diversity score (DDS), Dietary acid load (DAL) and Plant based dietary score (PDI). 2.7.1. HEI-2015 : A method described by Susan M. Krebs-Smith et al. was used for scoring HEI-2015 [ 35 ]. This method considered 13 components including whole fruit, total fruit, total vegetables, whole grains, green and beans, dairy, total protein foods, sea food and plant protein, fatty acids in adequacy section and refined grains, sodium, added sugar and saturated fats in moderation section. Individuals in the highest decile of whole grains, fatty acid ratio, and dairy were given the score of 10 and those in the lowest decile received the score of 0. Individuals in other deciles received the corresponding scores. In contrast, individuals with the highest intake of refined grains, added sugar, sodium and saturated fat, were given the score of 0 and those with the lowest consumption of these components received the score of 10. Also, Individuals in the highest quintiles of whole fruit, total fruit, total vegetables, green and beans, total protein foods, sea food and plant protein were given score 5 and those in the lowest decile received the score of 0. Total HEI-2015 score for each participant was then computed by summing up the scores for these 13 components. It was varied from 0 to 100. 2.7.2. DDS : A method described by Kant et al. was used for scoring dietary diversity [ 36 ]. This method was based on five groups including grains, vegetables, fruits, meats and dairy, all food groups in the USDA food guide pyramid. The grains group was composed of seven components: refined bread, macaroni, whole grain bread, corn flakes, biscuits, refined flour, and rice. Fruit was defined by summing up fruit and fruit juice, berries and citrus fruits. The story about vegetables was summing up of potato, tomato, other starchy vegetables, legumes, yellow vegetables, green vegetables, and other vegetables. The group of meat was composed of red meat, poultry, fish and eggs) and the group of dairies was composed of milk, yoghurt and cheese. 2.7.3. DAL : We constructed dietary acid load score based on dietary intakes of several nutrients using potential renal acid load method (PRAL) [ 37 ]: (protein [g/d] × 0.49) + (Phosphorous [mg/d] × 0.037) – (potassium [mg/d] × 0.021) – (Calcium [mg/d] × 0.013) – (magnesium [mg/d] × 0.026). Dietary acid load score obtained from this method, was used for statistical analysis. 2.7.4. PDI : The method by Satija et al. was used to calculate the plant-based dietary pattern [ 38 ]. This score includes three indices of total Plant-based Diet Index (PDI), healthful PDI (H.PDI), and unhealthful PDI (UnH.PDI). Based on the similarity of nutrient components, food items were categorized into 18 groups, which included three main categories of animal, healthy, and unhealthy plant-based foods. Whole grains, fruits, vegetables, nuts, legumes, vegetable oils, and tea/coffee were considered healthy plant foods, while unhealthy plant foods included fruit juices, sugar-sweetened beverages, refined grains, potatoes, and sweets/desserts. In addition, animal fat, dairy, egg, fish/seafood, meat, and miscellaneous animal-based foods were considered animal food items. These food items were then converted to quintiles of consumption and a score of 1 to 5 was applied to each item. For PDI, scores of 5 and 1 were given to participants at the highest and lowest quintiles of plant food consumption, respectively. In addition, scores of 1 and 5 were given to the participants in the highest and lowest quintiles of animal foods consumption, respectively. To calculate H.PDI, scores of 5 and 1 were applied to participants with the highest and lowest consumption of healthy plant foods, respectively. A score of 1 for the highest consumption and 5 for the lowest consumption of unhealthy plant foods and animal food items was also determined. To calculate UnH.PDI, a score between 5 and 1 was given to the highest through the lowest consumption of unhealthy plant foods. Further, participants with the highest to lowest consumption of animal foods and healthy plant foods were given a score between 1 and 5. Scores were summed to obtain a score ranging from 18 to 90 for each PDI, H.PDI, and UnH.PDI index. Higher total scores for each index indicated higher adherence to that dietary pattern. 2.8. Statistical Analysis The SPSS Version 26 was utilized as the main tool for data handling and analysis. We summarized the data distribution by presenting descriptive statistics, including the average values with standard deviation and the median (Min–Max). The Kolmogorov-Smirnov test was applied to evaluate the normality of the data distribution before proceeding with further analyses. For data that was skewed, log transformation was performed to normalize the distribution. To investigate the relationship between dietary scores and inflammatory/treatment outcomes, linear regression analysis was conducted in two forms: a crude model and a model adjusted for confounding factors. The adjusted model took into account Age, Sex, and BMI, which are factors known to affect the studied relationship. We also carried out subgroup analyses focusing on age and sex differences. A p-value < 0.05 was considered statistically significant, denoting meaningful findings. 3. Result 3.1. Descriptive Statistics Table 1 provides a summary of participants' characteristics. This study includes 54 participants with an average age of 8.51 years (SD= 2.94). Among them, 36 were male and 18 were female. Based on the percentile, the mean BMI was 53.25 (SD= 36.63), and 46% of patients' BMI was in the normal range. The descriptive statistics for dietary intake are summarized in Table 2. The mean energy intake of the patients was 2067 kcal (SD= 614.45). Also, their mean daily protein intake was 76.56 grams (SD= 25.89), and the protein intake of all patients was within the normal range. The range of daily carbohydrate intake was from 136.31 to 470.13, and one of the participants had intake less than the normal range. Moreover, the median fat intake of the patients was 62.45 grams, and seven participants had less than normal range intake. Table 3 shows a summary of the descriptive data for the dietary scores. According to the results obtained and based on the HEI-2015 score, 25% of the patients had poor adheres with the dietary guideline and the rest of the patients had moderate adheres. Moreover, the DAL scores ranged from -36.95 (least dietary acidity score) to +24.49 (most dietary acidity score). Additionally, the mean scores of DDS and Total PDI were 4.90 (SD= 1.82) and 54.20 (SD= 6.33), respectively. Also, concerning the treatment outcomes, the patients' mean hospitalization days were 34.52 days (SD= 8.24). Four patients developed febrile neutropenia during the induction phase treatment, the mean of which was 0.24 (SD=0.86) days. Also, out of 54 patients, there were only two patients who did not achieve remission. Descriptive information related to inflammatory and treatment outcomes is also provided in Table 4 . 3.2. Association between Dietary Scores and Inflammation outcomes Our study's results show a tendency for a protective association between DDS and NLR in the crude analysis model so that with an increase of one unit of DDS, the NLR value decreases by 0.30 (ß: -0.30, CI: -0.61 to 0.009, P-value: 0.057) (Table 5) . Also, according to the subgroup analysis results, following a more adheres to a PDI has caused a significant decrease in CRP in male group (ß: -0.63, CI: -1.20 to -0.07, P-value: 0.02). A significant (marginal) decrease in GPS in the male group has been observed following the one-point increase in the total PDI score (ß: -0.02, CI: -0.05 to 0.00, P-value: 0.052). Additionally, there is a significant direct relationship between the increase in the dietary diversity score and the increase in the PNI index in females (ß: 3.90, CI: 0.94 to 6.85, P-value: 0.01) (Table 6) . Table 7 provides the mutual association between the individual components of the HEI-2015 score and inflammatory treatment outcomes. The findings indicate that as the dairy group's score rises, there is a substantial increase in the MLR for both the crude (ß: 0.02, CI: 0.003 to 0.05, P-value: 0.03) and adjusted models (ß: 0.001, CI: 0.06 to 0.00, P-value: 0.04). On the other hand, each unit increase in total fruit score causes a significant decrease of 0.05 MLR in both crude (ß: -0.05, CI: -0.10 to -0.004, P-value: 0.03) and adjusted models (ß: -0.05, CI: -0.10 to 0.002, P-value: 0.059). However, this significance is marginal in the adjusted model. The relationship between the score of vegetables and GPS -as an index of the inflammation assessment- has also been significant in both crude (ß: 0.18, CI: 0.01 to 0.35, P-value: 0.03) and adjusted analysis models (ß: 0.19, CI: 0.005 to 0.39, P-value: 0.04), so with the increase in the score of total vegetables, GPS also increases significantly. Increasing the fatty acids score can also reduce inflammation. With the increase of one score in fatty acid component, the MLR decreased by 0.03 in the crude model (ß: -0.03, CI: -0.06 to -0.004, P-value: 0.02) and 0.02 in the adjusted model (ß: -0.02, CI: -0.05 to -0.002, P-value: 0.03). Also, in response to the increase of one score in fatty acids component, the PLR in the crude and adjusted models has decreased by 19.35 (ß: -19.35, CI: -35.75 to -3.31, P-value: 0.01) and 20.88 (ß: -38.77, CI: -35.75 to -2.99, P-value: 0.02), respectively. The results of 4 analysis were significant. 3.3. Association between Dietary Scores and treatment outcomes The findings of this study show that there is a direct relationship between PDI and hospitalization duration and in both crude and adjusted analysis models, the hospitalization duration significantly increased with the increase of PDI score. Crude model: (ß: 0.36, CI: 0.03 to 0.7, P-value: 0.03), adjusted model: (ß: 0.40, CI: 0.01 to 0.79, P-value: 0.02) (Table 5) . Based on the subgroup analysis, there is no significant relationship between dietary scores and treatment outcomes. On the other hand, the analysis of the HEI-2015 components showed that the febrile neutropenia duration increases significantly with the increase of green and beans group score (ß: 0.12, CI: 0.001 to 0.25, P-value: 0.04). Additionally, with the increase of each point of whole grains, the hospitalization duration has increased significantly in both crude (ß: 1.17, CI: 0.28 to 2.07, P-value: 0.01) and adjusted model (ß: 1.17, CI: 0.25 to 2.09, P-value: 0.01) by 1.17 days (Table 7) . 4. Discussion Our research revealed that patients with ALL demonstrated moderate adherence to the HEI-2015 guidelines. Similarly, their scores for dietary diversity and plant-based diets were moderate. Furthermore, our findings suggest that as the DDS increases in the crude analysis model, there's a notable (albeit marginal) reduction in the NLR, and the PNI significantly improves in females. In addition, a rise in the PDI markedly extends the duration of hospital stays and substantially lowers CRP and GPS levels in males. Additionally, higher intake scores for dairy products and total vegetables have been linked to increased inflammation, as evidenced by rises in the MLR and GPS across both analytical models. Conversely, enhancing the scores for total fruits and fatty acids significantly reduces inflammation markers, including MLR and PLR. Moreover, the treatment outcomes, such as hospitalization duration and increased instances of febrile neutropenia, have been significantly associated with higher scores for whole grains, as well as greens and beans. We cannot directly compare our results with other observational studies since no previous study has researched the association between diet quality and inflammatory treatment outcomes, on patients with hematological malignancy. However, this study was carried out on patients prior to the commencement of the induction phase of their treatment, which means that the impact of treatments like chemotherapy cannot be regarded as a confounding factor. While the elevated inflammation levels in these patients before diagnosis can lead to a reduced appetite, the rapid onset of symptoms and quicker diagnosis associated with ALL, as compared to chronic lymphocytic leukemia (CLL), means that this inflammation does not significantly affect long-term dietary intake [ 39 ]. It is commonly known that the general pediatrics population's diet quality and adherence to recommendations are not at their best that is similar to our result [ 40 , 41 ]. By using 4 scores in this study, it has been tried to evaluate the overall quality and diversity of the diet, fully and well. In our study, the increase in DDS score was inversely associated with NLR and has a direct relationship with PNI in women. Enhancing DDS is linked to decreased inflammation and better nutritional health, primarily due to adherence to healthful diets like the Mediterranean and anti-inflammatory diets. These eating patterns, rich in a variety of nutrient-dense foods, are associated with reduced levels of inflammatory markers, such as CRP and IL-6, as observed in cross-sectional studies [ 42 ]. This indicates that a varied diet, abundant in anti-inflammatory foods, has a beneficial effect on inflammation levels. Expanding DDS enhances nutritional health by promoting the intake of a broader array of essential nutrients. Varied diets are more likely to meet the body's requirements for both macronutrients (carbohydrates, proteins, and fats) and micronutrients (vitamins and minerals), thereby minimizing the risk of nutritional deficiencies and related health issues. Incorporating a wide range of foods from all food groups (grains, vegetables, fruits, proteins, and dairy) is crucial for balanced nutrition, as each group offers distinct nutrients vital for energy, growth, and overall bodily functions. Contrastingly, a study by Z. Malihi et al. [ 43 ], which assessed dietary diversity in patients with ALL prior to chemotherapy, found no significant link between DDS and nutritional status, as measured by the Patients Subjective Global Assessment (PG-SGA) Questionnaire. This discrepancy with the current study's findings may be attributed to factors such as a smaller sample size and potential reporting bias in the nutritional status questionnaire. Based on the obtained results, PDI has a significant inverse relationship with CRP and GPS in males. The study led by Soraeya Kharaty and colleagues [ 44 ], which explored the link between the Plant-based Diet Index (PDI) and inflammation levels, found that a higher PDI correlates with lower CRP levels, aligning with our findings. This inverse relationship may be due to the high content of fiber, antioxidants (like vitamins C and E), polyphenols, and other phytochemicals in plant-based diets, known for their anti-inflammatory properties. These elements help diminish the production of pro-inflammatory cytokines, thereby reducing CRP levels in the bloodstream [ 45 ]. Additionally, foods abundant in omega-3 fatty acids, such as flaxseeds and walnuts, along with fruits, vegetables, whole grains, and legumes, possess anti-inflammatory qualities that can influence the inflammatory process and decrease CRP levels [ 46 , 47 ]. Moreover, a healthy PDI is linked to lower levels of TNF-alpha, whereas an unhealthy PDI tends to elevate NLR, CRP, and TNF-alpha. In our research, however, we didn't observe a significant association between healthy or unhealthy PDI and inflammation markers, possibly due to the small sample size or differences in the populations studied. The result indicated that increasing the PDI score increases the duration of hospitalization. This can be due to the following possible reasons: Plant-based diets, while rich in many nutrients, may lack certain essential vitamins and minerals crucial for children undergoing cancer treatment, such as vitamin B12, iron, zinc, and omega-3 fatty acids. These deficiencies could potentially impact recovery and immune function, leading to longer hospital stays [ 48 ]. Also, Plant-based foods tend to be lower in calories compared to diets that include animal products. During the induction phase of treatment, the metabolic demands of children with ALL may increase. If the energy and protein intake are insufficient to meet these demands, it could slow down recovery, necessitating a longer hospital stay [ 49 ]. Moreover, the induction phase for ALL treatment is intense and can significantly impact the gastrointestinal system. High-fiber foods, common in plant-based diets, might exacerbate gastrointestinal issues such as diarrhea or lead to difficulty in managing nutrition due to decreased appetite or treatment-related mucositis [ 50 ]. This can complicate nutritional management, potentially prolonging hospitalization. The analysis, both in its preliminary and adjusted forms as well as in subgroup evaluations, revealed no significant link between the DAL and inflammation markers. A diet with a high acid load has been hypothesized to induce a low-grade systemic acidosis, which could potentially lead to an increase in inflammation. Some studies suggest that higher DAL may be associated with inflammatory markers such as CRP, although findings are not universally consistent across all research. For instance, the research conducted by Tianying Wu [ 51 ] on survivors of breast cancer identified a notable positive correlation between dietary acid load and inflammation. Conversely, a study by Alireza Jafar [ 52 ], focusing on the elderly, found that an increase in the diet's acid potential was associated with a notable decrease in CRP levels, indicating a reduction in inflammation. There are no direct studies and evidence regarding the relationship between DAL and treatment outcomes in different patients. but it seems that the acidic potential of the diet can indirectly affect the treatment outcomes, including the length of hospitalization, through the effect on inflammation and metabolic alterations such as insulin resistance, diabetes, hypertension, and chronic kidney disease[ 53 ]. However, more evidence is needed. Based on the results of our study, no significant association between HEI-2015 and inflammatory and therapeutic outcomes was observed. According to the results of a number of studies, adherence to HEI in children with the disease or survivors of childhood cancers is moderate or poor [ 22 , 54 , 55 ]. several studies have been conducted in relation to investigating HEI and its relationship with inflammation in healthy and unhealthy children and adolescents. In a study by Pilar Navarro et al., higher score in the HEI was associated with lower levels of CRP in females, but not males from a healthy cohort [ 56 ]. In contrast, two studies found that moderate HEI scores (moderately healthy diet) were not associated with CRP or IL-6 in males or females in cohorts of patients with type-1 diabetes [ 54 , 57 ]. Also, the study by Sophie Bérard et al., which was conducted on ALL survivors, points out that Participants who had a better adherence to the HEI-2015 score had lower levels of TNF-alpha [ 22 ]. It appears that factors such as the disease's type and severity, the size of the sample, and the study's design contribute to the lack of significant findings in this study. Nonetheless, examining how the scores from the HEI-2015 components correlate with inflammation and treatment outcomes yields meaningful results. The results show that by increasing the score of dairy products, inflammation by the MLR index increases significantly. Also, by increasing the score of fatty acids, inflammation is significantly reduced by MLR and PLR markers. Saturated fatty acids are a key factor to consider in this context. The score for fatty acids is derived from the ratio of omega-3 and omega-6 fatty acids to saturated fatty acids. Moreover, the dairy products consumed by these patients are predominantly high-fat, which are high in saturated fatty acids. Numerous studies have explored the link between saturated fatty acids and an increase in inflammation. Although the study by Carla P. Harris et al.[ 58 ] indicates that consuming saturated fatty acids (SFA) correlates with a reduction in hs-CRP, an index of inflammation, other research points to a detrimental impact of SFA intake on inflammation levels. According to the findings from Carla P. Harris and colleagues,[ 59 ] a higher intake of SFA and lower levels of n-6 PUFA are linked to elevated low-grade inflammation in children, while a higher intake of major dietary n-6 PUFA and total PUFA seems to diminish inflammation. Furthermore, research by Jin Mei et al. [ 60 ] suggests that a diet high in SFA might increase the risk of developing breast, prostate, and colorectal cancers. Patients with ALL inherently experience high levels of spontaneous inflammation due to the disease itself, implying that consuming sources rich in saturated fatty acids may exacerbate inflammation, potentially negatively affecting the treatment process. Conversely, a higher consumption of omega-3 and omega-6 fatty acids in comparison to saturated fatty acids could contribute to the reduction of inflammation. The results obtained demonstrate a notable negative correlation between the rise in whole grain and greens and beans scores and the enhancement of treatment outcomes, such as shorter hospital stays and reduced periods of fever and neutropenia. The induction phase of chemotherapy presents challenging conditions for patients. During this phase, patients require a high intake of energy and protein to successfully navigate this stage of treatment. Consequently, prioritizing the consumption of foods high in energy and protein becomes essential [ 61 , 62 ]. Conversely, increasing the consumption of more grains and green and beans may hinder the improvement of treatment outcomes. Furthermore, the findings reveal that a higher consumption of vegetables correlates with an increase in the GPS, while a higher consumption of fruits is associated with a reduction in the MLR. It's important to note that patients in these cases require significant energy levels; thus, the rapid consumption of high-energy foods plays a crucial role in their treatment. The intake of fruits can be particularly beneficial due to their high energy content and quick absorption, which in turn can enhance the management of inflammation [ 63 ]. Regarding vegetables, various sources have said that high consumption of vegetables is useful in cancer patients, which contradicts the findings of our study. It seems more research could help [ 64 ]. To the best of our understanding, this research represents the inaugural exploration into how diet quality impacts treatment responses in children with ALL. A notable advantage of our study is its application of various food scores to assess diet quality comprehensively. Additionally, we employed an adjusted analysis model to mitigate the influence of confounding factors on our results. Furthermore, for enhanced accuracy and reliability, subgroup analysis was performed. However, the study faces limitations, including its small sample size. Another drawback is its cross-sectional nature, which, due to the absence of a non-cancer control group, hinders comparative analysis with the patients. The reliance on FFQ for dietary intake assessment introduces a potential for reporting bias, marking another limitation. Ultimately, while our findings reveal correlations, they do not clarify how various diet components might influence inflammatory or treatment outcomes. Conclusions Our research indicates that patients with ALL tend to poorly follow dietary guidelines. The findings underscore the benefits of enhancing dietary variety and greater compliance with the PDI score to diminish inflammation among these patients. Moreover, reducing saturated SFA while increasing intake of omega-3 and omega-6 fatty acids is crucial in mitigating inflammation. Gaining deeper insights into the impact of diet and its components on the well-being of ALL patients will enable the creation of customized dietary recommendations and nutritional plans for this vulnerable group. Declarations Ethical Approval: The study protocol was approved by the ethics committee of Tabriz University of Medical Sciences (ethic number: IR.TBZMED.REC.1401.1080). All participants (or their guardians) provided written informed consent to participate in the study. Consent for Publication: Consent for publication of the results was obtained from all participants (or their guardians) as part of the informed consent process Funding: This research was funded by Research Assistant of Tabriz University of Medical Sciences, grant number 71254. Availability of data and materials: The data underlying this article will be shared on reasonable request to the corresponding author Conflict of interest: The authors have nothing to disclose Authors’ contribution MJ: Drafting of the manuscript, Acquisition of data, critical revision of the manuscript for important intellectual content MB: Drafting of the manuscript, Acquisition of data PP: Drafting of the manuscript, Acquisition of data HG : Drafting of the manuscript, Acquisition of data YT: Acquisition of data AH: Drafting of the manuscript, Acquisition of data ZG: Interpretation of data, critical revision of the manuscript for important intellectual content, content, Study concept and design. 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Conigliaro T, Boyce LM, Lopez CA, Tonorezos ES: Food Intake During Cancer Therapy: A Systematic Review. Am J Clin Oncol 2020, 43: 813-819. Nutrition in Cancer Care (PDQ®) [https://www.cancer.gov/about-cancer/treatment/side-effects/appetite-loss/nutrition-hp-pdq] Expert Tips for Adding Calories and Overcoming Appetite Loss during. [https://www.mskcc.org/news/expert-tips-adding-calories-and-overcoming-appetite-loss-during-cancer-treatment] Tables Table 1. Demographic and clinical characteristics of participants. Note. Data were expressed as Mean ± SD or Frequency (percentage) Table 2. Dietary intake of patients Variables Mean (SD) Median Minimum Maximum Energy (kc/d) 2067.55 (614.45) 1924.80 1248.72 3605.61 Fruits (gr/d) 200.09 (127.25) 180.78 32.45 553.86 Vegetables (gr/d) 207.5 (131.27) 173.64 44.37 612.19 Grains (gr/d) 378.39 (150.01) 365.87 65.88 767.72 Beans (gr/d) 20.43 (18.30) 16.08 0.0 78.02 Meat group (gr/d) 126.75 (56.27) 120.5 13.48 301.43 Dairy (gr/d) 430.76 (228.80) 397.67 58.27 1004.43 Fats and Oils (gr/d) 34.33 (16.73) 30.96 7.12 82.27 Sweets and Added Sugars (gr/d) 22.84 (153.88) 182.87 23.97 728.88 Beverages (gr/d) 235.63 (258) 240 0.00 1216 Total protein (gr/d) 75.56 (25.89) 71.77 35.90 168.87 Total carbohydrate (gr/d) 288.24 (84.27) 279.15 136.31 470.13 Total fat (gr/d) 70.17 (25.09) 62.45 33.24 146.35 Note. Data were expressed as Mean ± SD Table 3. Descriptive statistics of the dietary scores Score (range) Mean (SD) Median Minimum Maximum HEI-2015 (0-100) 55.52 (7.61) 56.50 40 73 DDS (0-10) 4.90 (1.82) 4.38 2.21 8.60 DAL -3.60 (12.61) -4.17 -36.95 24.49 Total PDI (18-90) 54.20 (6.33) 53.5 42 70 Healthy PDI (18-90) 53.83 (6.50) 53.5 40 70 Unhealthy PDI (18-90) 53.87 (6.34) 54 40 71 Note. Data were expressed as Mean ± SD; Median; Min–Max Table 4. Descriptive statistics of the Inflammatory Markers and treatment outcomes Markers Mean (SD) Median Minimum Maximum CRP 15.13 (19.60) 5.99 0.35 76.37 NLR 1.55 (2.72) 0.36 0.03 13.03 MLR 0.24 (0.13) 0.12 0.02 2.46 PLR 109.96 (168.69) 32.65 0.47 754.55 GPS 0.52 (0.6) 0.0 0 2 PNI 63.79 (43.02) 47.36 32.20 259 PI 0.57 (0.57) 1 0 2 Hospitalization duration 34.52 (8.24) 34 17 66 FN 0.24 (0.86) 0.0 0 5 Note. Data were expressed as Mean ± SD; Median; Min–Max Table 5. Association Between Diet quality indices and Inflammation/Treatment outcomes HEI-2015 DDS DAL PDI H.PDI Unh.PDI Variables ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value CRP Crude model Adjusted model 0.56 0.23 -0.97 0.56 0.28 0.13 -0.44 0.21 0.41 0.21 0.03 0.95 0.62 0.24 -0.95 0.57 0.28 0.18 -0.44 0.22 0.42 0.31 0.09 0.86 NLR Crude model Adjusted model -0.03 0.62 -0.3 0.057 0.04 0.14 -0.03 0.61 0.03 0.50 0.04 0.41 -0.03 0.59 -0.31 0.09 0.05 0.13 -0.04 0.58 0.03 0.50 0.03 0.54 MLR Crude model Adjusted model 0.005 0.44 -0.03 0.1 0.002 0.47 -0.005 0.60 0.005 0.42 0.003 0.56 0.006 0.43 -0.04 0.09 0.001 0.69 -0.002 0.82 0.008 0.34 0.005 0.45 PLR Crude model Adjusted model 1.49 0.62 -11.98 0.19 1.61 0.34 0.09 0.98 2.85 0.49 0.16 0.95 1.27 0.74 -12.06 0.25 1.72 0.34 0.10 0.98 3.15 0.46 -0.33 0.91 GPS Crude model Adjusted model 0.08 0.40 -0.04 0.32 0.009 0.13 -0.02 0.09 0.002 0.90 0.01 0.46 0.007 0.52 -0.05 0.27 0.01 0.14 -0.02 0.09 0.001 0.95 0.009 0.51 PNI Crude model Adjusted model -0.85 0.43 3.92 0.33 -0.64 0.30 1.00 0.25 -1.35 0.13 -0.63 0.47 -0.76 0.42 2.63 0.56 -0.77 0.23 1.24 0.19 -1.16 0.20 -0.29 0.75 PI Crude model Adjusted model -0.004 0.70 -0.03 0.42 0.004 0.56 -0.01 0.39 -0.009 0.45 0.005 0.69 -0.003 0.81 -0.05 0.31 0.003 0.66 -0.01 0.43 -0.008 0.51 0.009 0.52 Hospitalization duration Crude model Adjusted model 0.25 0.14 0.02 0.96 0.11 0.2 0.36 0.03 0.18 0.35 -0.15 0.29 0.26 0.09 0.002 0.99 0.10 0.23 0.40 0.04 0.22 0.37 -0.15 0.31 Febrile neutropenia Crude model Adjusted model 0.01 0.46 -0.02 0.40 0.003 0.63 -0.02 0.22 0.009 0.59 -0.007 0.76 0.01 0.52 -0.02 0.48 0.004 0.56 -0.02 0.19 0.009 0.61 -0.01 0.62 Note. Linear regression analysis examined the potential relationship between dietary scores and the inflammatory/ treatment outcomes. Model 1: Crude Model 2: Adjusted for Age, Sex, and BMI. Table 6. Association Between Diet quality indices and Inflammation/Treatment outcomes according to subgroup analysis HEI-2015 DDS DAL PDI H.PDI Unh.PDI Variables (by gender) ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value CRP Female Male 0.30 0.64 -2.47 0.21 0.80 0.30 -0.07 0.94 -0.19 0.77 0.44 0.54 0.68 0.29 -0.23 0.91 0.08 0.63 -0.63 0.02 0.65 0.23 -0.42 0.63 NLR Female Male -0.07 0.91 -0.27 0.32 0.02 0.74 0.007 0.95 0.13 0.35 0.06 0.48 -0.03 0.66 -0.33 0.16 0.05 0.12 -0.06 0.53 -0.002 0.97 0.02 0.75 MLR Female Male -0.05 0.45 -0.03 0.06 0.004 0.11 -0.008 0.18 -0.005 0.51 0.007 0.25 0.09 0.35 -0.04 0.21 <0.001 0.96 -0.002 0.88 0.01 0.30 <0.001 0.999 PLR Female Male 2.26 0.56 -21.9 0.24 -2.30 0.27 -5.58 0.33 7.93 0.38 1.33 0.75 1.24 0.79 -8.5 0.49 3.28 0.11 2.56 0.63 0.89 0.85 -1.12 0.77 GPS Female Male 0.03 0.07 -0.05 0.57 0.01 0.41 -0.008 0.81 0.005 0.85 <0.001 0.999 -0.02 0.88 -0.05 0.41 0.007 0.36 -0.02 0.052 0.001 0.95 0.02 0.31 PNI Female Male -0.40 0.41 3.90 0.01 -0.35 0.15 0.97 0.27 -0.58 0.67 -0.27 0.34 -1.013 0.45 2.35 0.70 -0.86 0.34 1.29 0.33 -1.28 0.26 -0.95 0.60 PI Female Male 0.01 0.57 -0.009 0.92 0.009 0.57 0.02 0.43 -0.002 0.95 0.004 0.85 -0.01 0.50 -0.06 0.30 0.001 0.87 -0.02 0.16 -0.009 0.54 0.007 0.70 Hospitalization duration Female Male 0.3 0.07 0.62 0.53 -0.08 0.51 0.35 0.21 -0.05 0.67 -0.02 0.87 0.22 0.35 -0.30 0.72 0.19 0.07 0.38 0.09 0.31 0.33 -0.28 0.26 Febrile neutropenia Female Male 0.08 0.46 0.03 0.58 0.002 0.83 -0.005 0.78 -0.005 0.70 -0.006 0.82 0.01 0.53 -0.05 0.19 0.004 0.67 -0.03 0.22 0.01 0.55 -0.008 0.84 Variables (by age) ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value CRP < 9 ≥ 9 -0.01 0.98 -1.99 0.07 0.40 0.17 -0.25 0.58 0.50 0.26 0.44 0.44 1.16 0.16 0.89 0.85 0.11 0.71 -0.74 0.19 0.18 0.69 -0.93 0.43 NLR < 9 ≥ 9 -0.02 0.65 -0.20 0.26 0.04 0.16 -0.03 0.70 0.04 0.55 -0.004 0.96 -0.04 0.70 -0.49 0.17 0.05 0.44 -0.05 0.71 0.02 0.82 0.14 0.20 MLR < 9 ≥ 9 0.004 0.51 -0.01 0.29 0.002 0.49 -0.01 0.08 -0.001 0.79 -0.002 0.79 0.01 0.55 -0.06 0.21 0.001 0.86 0.009 0.72 0.02 0.33 0.02 0.33 PLR < 9 ≥ 9 -2.63 0.69 -9.51 0.43 2.83 0.27 -0.85 0.88 1.86 0.73 -2.01 0.59 4.40 0.40 -15.85 0.36 -0.02 0.99 0.68 0.92 4.73 0.49 3.38 0.58 GPS < 9 ≥ 9 -0.007 0.68 -0.06 0.25 0.01 0.21 -0.01 0.23 0.005 0.77 0.01 0.55 0.01 0.23 -0.01 0.87 0.007 0.43 -0.02 0.22 -0.009 0.69 <0.001 0.98 PNI < 9 ≥ 9 0.66 0.29 8.56 0.14 -1.27 0.15 1.41 0.25 -0.63 0.33 -1.41 0.21 -1.94 0.29 -4.83 0.34 0.22 0.79 0.72 0.56 -2.86 0.24 1.83 0.29 PI < 9 ≥ 9 -0.007 0.70 -0.004 0.94 0.003 0.73 -0.01 0.43 -0.002 0.91 -0.006 0.70 0.001 0.94 -0.09 0.25 0.005 0.73 -0.004 0.85 -0.02 0.30 0.03 0.14 Hospitalization duration < 9 ≥ 9 0.51 0.10 -0.02 0.95 0.08 0.25 0.19 0.3 0.13 0.43 -0.16 0.35 0.02 0.88 0.10 0.93 0.16 0.47 0.64 0.09 0.29 0.62 -0.12 0.69 Febrile neutropenia < 9 ≥ 9 0.02 0.52 -0.01 0.71 0.006 0.64 -0.40 0.25 0.01 0.54 -0.02 0.47 -0.003 0.38 -0.02 0.35 0.001 0.43 -0.004 0.36 -0.008 0.36 0.01 0.35 Note. Linear regression subgroup analysis examined the potential relationship between dietary scores and the inflammatory/ treatment outcomes. Table 7. Association Between HEI-2015 components and Inflammation/Treatment outcomes CRP NLR MLR PLR GPS PNI PI H. D F. N Variables ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value ß P-value Dairy Crude model 0.89 0.52 0.31 0.10 0.02 0.03 14.52 0.07 0.01 0.66 -4.51 0.10 -0.007 0.82 -0.63 0.23 0.07 0.12 Adjusted model 0.99 0.53 0.31 0.12 0.03 0.04 14.89 0.08 0.01 0.78 -4.52 0.10 -0.008 0.81 -0.59 0.25 0.07 0.14 Total fruits Crude model 3.47 0.10 -0.38 0.23 -0.05 0.03 -12.79 0.38 0.01 0.79 -1.78 0.73 -0.02 0.72 -0.46 0.66 -0.17 0.09 Adjusted model 3.46 0.11 -0.39 0.19 -0.05 0.059 -12.48 0.39 0.01 0.81 -1.37 0.80 -0.02 0.72 -0.41 0.70 -0.18 0.08 Whole fruits Crude model 3.07 0.07 -0.17 0.67 -0.02 0.52 24.55 0.13 0.04 0.54 0.002 1.00 0.02 0.78 -0.75 0.60 -0.10 0.46 Adjusted model 3.10 0.10 -0.17 0.68 -0.01 0.71 27.26 0.17 0.04 0.59 -0.21 0.96 0.02 0.86 -0.66 0.65 -0.11 0.45 Total vegetables Crude model 3.37 0.19 0.09 0.79 0.05 0.30 7.74 0.81 0.18 0.03 -7.85 0.18 0.03 0.69 -0.35 0.64 0.07 0.42 Adjusted model 3.85 0.24 0.03 0.93 0.07 0.28 4.15 0.91 0.19 0.04 -4.91 0.38 0.07 0.44 -0.34 0.71 0.05 0.61 Green and beans Crude model -2.35 0.42 -0.39 0.21 -0.01 0.66 -3.23 0.85 -0.003 0.95 2.10 0.50 -0.01 0.85 -1.18 0.23 0.12 0.04 Adjusted model -2.45 0.44 -0.43 0.18 -0.01 0.59 -6.5 0.75 0.008 0.92 3.97 0.27 0.006 0.94 -1.34 0.19 0.13 0.06 Whole grains Crude model 1.55 0.15 -0.003 0.98 0.03 0.31 6.62 0.49 0.02 0.35 -1.95 0.10 0.01 0.50 1.17 0.01 0.04 0.50 Adjusted model 1.59 0.16 -0.005 0.97 0.03 0.31 6.43 0.52 0.02 0.38 -1.94 0.14 0.01 0.51 1.17 0.01 0.04 0.50 Total proteins Crude model 3.16 0.25 -0.10 0.81 -0.01 0.72 -36.88 0.16 0.04 0.63 -1.49 0.78 0.008 0.92 0.80 0.47 -0.09 0.54 Adjusted model 3.25 0.31 -0.07 0.87 -0.03 0.59 -37.32 0.19 0.05 0.60 -3.64 0.47 -0.004 0.96 0.73 0.51 -0.09 0.58 Seafood and plant proteins Crude model -1.90 0.45 0.22 0.42 -0.005 0.80 8.60 0.62 -0.08 0.23 6.29 0.13 -0.008 0.90 0.45 0.66 0.13 0.11 Adjusted model -1.96 0.50 0.22 0.48 0.006 0.79 9.64 0.56 -0.09 0.18 7.33 0.10 -0.008 0.90 0.59 0.60 0.13 0.15 Fatty acids Crude model -1.93 0.18 -0.25 0.15 -0.03 0.02 -19.35 0.01 -0.02 0.72 1.41 0.66 -0.02 0.53 1.20 0.09 -0.04 0.35 Adjusted model -1.80 0.22 -0.29 0.12 -0.02 0.03 -20.88 0.02 -0.03 0.54 1.96 0.60 -0.02 0.57 1.37 0.09 -0.06 0.26 Refined grains Crude model 0.98 0.53 -0.07 0.42 -0.005 0.62 -8.97 0.11 -0.01 0.56 -0.64 0.72 0.007 0.84 0.71 0.12 -0.02 0.44 Adjusted model 1.02 0.53 -0.07 0.44 -0.04 0.70 -8.65 0.13 -0.02 0.57 -0.93 0.66 0.004 0.91 0.73 0.11 -0.02 0.44 Sodium Crude model 0.98 0.31 -0.02 0.87 0.01 0.40 5.70 0.34 0.01 0.48 -1.40 0.50 -0.003 0.89 0.14 0.72 0.01 0.58 Adjusted model 1.06 0.32 -0.02 0.86 0.01 0.47 5.23 0.41 0.02 0.46 -1.42 0.47 <0.001 0.998 0.10 0.83 0.01 0.55 Added sugar Crude model 0.26 0.84 -0.19 0.33 -0.01 0.65 -1.06 0.93 0.02 0.52 -0.15 0.91 0.002 0.94 -0.47 0.17 0.08 0.09 Adjusted model 0.15 0.91 -0.19 0.37 -0.01 0.63 -0.81 0.95 0.02 0.46 -0.13 0.94 0.002 0.95 -0.51 0.19 0.09 0.11 Saturated fats Crude model -1.24 0.37 0.07 0.62 0.01 0.56 2.15 0.80 -0.03 0.38 1.49 0.39 -0.04 0.18 0.56 0.12 -0.06 0.25 Adjusted model -1.15 0.48 0.06 0.70 0.01 0.41 1.53 0.87 -0.04 0.31 1.72 0.25 -0.04 0.19 0.63 0.08 -0.08 0.16 Note. Linear regression analysis examined the potential relationship between HEI-2015 components and the inflammatory/ treatment outcomes. Model 1: Crude; Model 2: Adjusted for Age, Sex, and BMI. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4332670","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":297445499,"identity":"c222deed-1358-4f82-ad6c-c8f098287aa5","order_by":0,"name":"Mehrdad jamali","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mehrdad","middleName":"","lastName":"jamali","suffix":""},{"id":297445502,"identity":"5b619b1c-a194-49f2-8838-49a04465fc0c","order_by":1,"name":"Maryam Behroz","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"","lastName":"Behroz","suffix":""},{"id":297445506,"identity":"7b6abfe0-1559-4102-950c-9853d47f52f9","order_by":2,"name":"Pedram Pam","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Pedram","middleName":"","lastName":"Pam","suffix":""},{"id":297445510,"identity":"17644433-e800-49c5-8424-f09bddc66ad8","order_by":3,"name":"Hosna Ghorbani","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Hosna","middleName":"","lastName":"Ghorbani","suffix":""},{"id":297445514,"identity":"b3243b8a-42c8-4a7b-bd94-a8633cb16cd6","order_by":4,"name":"Yousef Tavakolifar","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yousef","middleName":"","lastName":"Tavakolifar","suffix":""},{"id":297445517,"identity":"50782cd3-229d-4192-ab67-26e234bddbfa","order_by":5,"name":"Abbasali Hosseinpour Feizi","email":"","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abbasali","middleName":"Hosseinpour","lastName":"Feizi","suffix":""},{"id":297445518,"identity":"8d24e41a-2b83-4d6e-b884-ac31587c9834","order_by":6,"name":"Zohreh Ghoreyshi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie2SsUrEQBCGJyyszRDbtTGvMCHgy9jsErASCaSPwkJsFNscFr7CpbFeWDgbfYIV8fAFFgS12MLc2QiSRTuL/Yop/uHjZ2AAEon/iNgMAsmBGbZNzFfyG4Ur/QcFQAJg+U2JUBzqlfdNd5Lv3r+/NOF2Pzds7aF5mlXKx1W9GMi2HB5GPaCr9gyvBFA7rwzHFUMyqs8uR43CqaWBg+kWGVcCdapnuNZI7nRpdt6iSiEmBYipnmOmUTpJBuMtJI7q7IKs6pGX14Nx5cJiK2SsZagtfIRO3VzZ59cmuCK/Ox+9D5EW8yPa/MC8MLWcRZaJRCKR2PIJpKxTdkAleLcAAAAASUVORK5CYII=","orcid":"","institution":"Tabriz University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zohreh","middleName":"","lastName":"Ghoreyshi","suffix":""}],"badges":[],"createdAt":"2024-04-27 06:40:37","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4332670/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4332670/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":56036461,"identity":"ec5d9ac1-8c33-4ff3-96b2-7ceb61c09062","added_by":"auto","created_at":"2024-05-07 18:44:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2999470,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4332670/v1/0849a221-0dd1-454c-ae93-b8b4e72c790c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Association Between Diet Quality Scores with Inflammation and Treatment Outcomes in Children with Acute Lymphoblastic Leukemia; A Cross-Sectional Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcute Lymphoblastic Leukemia (ALL) is the most common cancer in children, representing about 25% of cancer diagnoses among those under 15, characterized by the overproduction of immature white blood cells, known as lymphoblasts, in the bone marrow [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The incidence of childhood leukemia appears to be increasing and the overall age-standardized incidence rate of leukemia is 48.4 per million person-years in children aged 0\u0026ndash;14 years [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The incidence of ALL is particularly high among children aged 2 to 5, with approximately 3,000 new cases diagnosed in the United States each year. Also, in Iran the average annual incidence rate of ALL was 2.25 per 100 000 children under 15 years of age according to study conducted by Sajjad Rahimi Pordanjani et al [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Despite its prevalence, due to the improvements in the treatment of pediatrics ALL over the past several decades, the 5-year survival rate now exceeds 90% in most developed countries [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. The treatment of ALL typically involves a multi-phased approach, including induction, consolidation, and maintenance phases, to achieve and sustain remission. Chemotherapy is key in treating diseases, but its intensity can cause issues like neutropenia, a low neutrophil count leading to infection susceptibility, hospital stays, and treatment interruptions [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Inflammation, vital for defense, can worsen conditions like ALL [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], exacerbated by treatments like chemotherapy, complicating recovery. This condition necessitates intensive medical intervention and can prolong hospital stays, disrupt achieving remission, and pose severe health risks. The interplay between inflammation and treatment outcomes in ALL is intricate, with increased inflammatory markers often indicating a poorer prognosis and influencing the effectiveness of chemotherapy [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Managing inflammation alongside targeting cancer cells is crucial for treatment effectiveness, remission likelihood, and minimizing complications in ALL [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Nutrition and diet are considered a modifiable risk factor for chronic diseases associated with systemic inflammation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Diet quality is generally defined as a dietary pattern or an index of diversity among crucial food groups consumed by individuals compared to those recommended in nutritional guidelines [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. With regard to ALL, particularly before during the induction phase of treatment, diet quality assumes a significant role. The induction phase is the initial and most critical phase of treatment, aiming to achieve complete remission by eradicating leukemia cells [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Diet quality can have a profound impact in this condition. A high-quality diet can support the body's immune response, help manage inflammation, and provide the strength needed for the body to cope with the aggressive treatment regimen [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Moreover, the relationship between diet quality, inflammation, and treatment outcomes is particularly relevant in the induction phase of ALL treatment. Proper diet can help mitigate the side effects of chemotherapy, reduce the risk of severe complications like infections, and improve the body's resilience [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. For instance, certain dietary components can have anti-inflammatory properties, helping to manage the systemic inflammation associated with ALL and its treatment. This, in turn, can influence treatment outcomes by potentially shortening hospital stays, reducing the incidence of complications such as febrile neutropenia, and supporting the overall effectiveness of the induction therapy [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To evaluate the diet quality, several indices are used that examine the quality of diet from various aspects such as variety, balance, adequacy, anti-inflammatory potential and dietary diversity, and in several studies, the relationship of these indicators with different outcomes of childhood cancer patients has been evaluated [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The results of the study by Sophie B\u0026eacute;rard et al showed that 36.9% of ALL survivors had poor adherence to the World Health Organization (WHO) recommendations and 76.3% had a diet to be improved according to the HEI-2015 score. also, this study suggested that Low HDL-C was associated with a more inflammatory diet and higher intake of ultra-processed foods. A greater E DII score was associated with elevated insulin resistance (HOMA-IR), and consumption of ultra-processed foods was correlated with high triglycerides [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Also based on the results of Catharine Fleming's study childhood cancer survivors who have recently completed cancer treatment have poor diet quality compared to age-matched controls and have high rates of picky eating [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. about active cases of ALL, the result of the study by Asma\u0026rsquo; Athifah et al. showed that 40% of patients with ALL have poor nutritional status and 11% of them did not achieve remission [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Moreover, based on the results of a study conducted by Jennifer Cohen, Children receiving cancer treatment were not consuming adequate intake of vegetables, fruit, and milk/alternatives [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In addition, based on the results of the study by S Y Tan et al., children with acute leukemia did not have a proper nutritional status and received less dietary intake than they needed [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Since previous studies have mostly examined the diet quality of survivors or assessed nutritional status (rather than diet quality) in active patients, this study aimed to explore the diet quality of ALL patients before starting the induction phase and its relationship with inflammation status and treatment outcomes at the end of the induction phase.\u003c/p\u003e"},{"header":"2. Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Setting and study design\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted at Mardani Azar Children's Hospital located in Tabriz, Iran, between January 2023 to January 2024. The setting included the pediatric oncology department and associated outpatient clinics within the hospital. The study protocol was approved by the ethics committee of Tabriz University of Medical Sciences (ethic number: IR.TBZMED.REC.1401.1080). Informed consent was obtained from all participants or their guardians before data collection. Confidentiality and anonymity of the participants' information were strictly maintained throughout the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Study population\u003c/h2\u003e \u003cp\u003eThe target population consisted of newly diagnosed pediatric patients with ALL receiving treatment. Participants were included if they were between the ages of 5 and 13, diagnosed with ALL, and candidates for the induction phase of chemotherapy. Patients were excluded if they had co-existing chronic diseases that could independently affect dietary intake or inflammatory markers. Due to the low number of these patients, a convenience sampling method in a period of one year was used.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Anthropometric, clinical, and biochemical assessment\u003c/h2\u003e \u003cp\u003eThe weight (kg) of people was measured by a digital scale with an accuracy of 0.5 kg. The height (cm) of people was calculated by a special anthropometric meter and BMI (kg/cm2) was obtained. For patients aged 3 to 20 years, the BMI z-score was calculated using the Centers for Disease Control and Prevention (CDC) growth chart for children [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Obesity as BMI z-score\u0026thinsp;\u0026ge;\u0026thinsp;1.645 (\u0026ge;\u0026thinsp;95th percentile), overweight as BMI z-score\u0026thinsp;=\u0026thinsp;1.036\u0026ndash;1.644 (85th-94.9th percentile) and healthy weight as BMI z-score = -1.645-1.035 (5th- 84.9 percentile) was considered based on the current recommendations of the CDC [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. low-grade and visceral inflammation [C-reactive protein (CRP, mg/L) and albumin (gr/dl) were measured on fasting blood. To measure CRP, we used the CRP turbidimetry kit manufactured by DELTA DARMAN PART\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Inflammation outcomes assessment\u003c/h2\u003e \u003cp\u003eThe inflammatory status of patients was evaluated using neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), Monocyte-to-lymphocyte ratio (MLR), Prognostic nutritional index (PNI), Glasgow prognostic index (GPS) and Prognostic index (PI) indices. NLR was obtained by dividing the absolute number of neutrophils by the absolute number of lymphocytes. MLR by dividing the absolute number of monocytes by the absolute number of lymphocytes and PLR by dividing the direct number of platelets by the direct number of lymphocytes. GPS was obtained by CRP (g/L) and serum ALB (g/L) as 0, 1 and 2. A GPS score of 0 is given to individuals with CRP\u0026thinsp;\u0026lt;\u0026thinsp;10 g/L and ALB\u0026thinsp;\u0026gt;\u0026thinsp;35 g/L. A GPS score of 1 for those with CRP greater than 10 g/L, or ALB\u0026thinsp;\u0026lt;\u0026thinsp;35 g/L, and a GPS score of 2 for those with CRP\u0026thinsp;\u0026gt;\u0026thinsp;10 g/L and ALB\u0026thinsp;\u0026lt;\u0026thinsp;35 g/L [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The PNI was calculated from the sum of serum ALB (g/L) plus the total number of lymphocytes per microliter multiplied by 0.005 (ALB\u0026thinsp;+\u0026thinsp;TLC\u0026times;0.005). A PNI value\u0026thinsp;\u0026gt;\u0026thinsp;50 is considered normal. PNI value\u0026thinsp;\u0026lt;\u0026thinsp;50, \u0026gt;45 indicates mild malnutrition. A PNI value\u0026thinsp;\u0026lt;\u0026thinsp;45\u0026thinsp;\u0026gt;\u0026thinsp;40 indicates moderate malnutrition. A PNI value\u0026thinsp;\u0026lt;\u0026thinsp;40 is considered to indicate severe malnutrition [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The PI was determined as follows: PI\u0026thinsp;=\u0026thinsp;2 for people with CRP\u0026thinsp;\u0026gt;\u0026thinsp;1mg/dl and the number of white blood cells\u0026thinsp;\u0026gt;\u0026thinsp;11*10^9/L, PI\u0026thinsp;=\u0026thinsp;1 for people with either CRP\u0026thinsp;\u0026gt;\u0026thinsp;1 mg/dl or the number of White blood cells\u0026thinsp;\u0026gt;\u0026thinsp;11* 10^9/L (not both) and PI\u0026thinsp;=\u0026thinsp;0 for people with both numbers in the normal range [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Treatment outcomes assessment\u003c/h2\u003e \u003cp\u003eThe treatment outcomes include the complete remission achievement, the hospitalization duration in the induction phase of the treatment, and the duration of febrile neutropenia. Achievement to remission was determined by examining blast cells so that less than 5% of the bone marrow is blast cells [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Data collection and analysis for dietary intake\u003c/h2\u003e \u003cp\u003eInformation regarding the demographic details of participants' families, including ethnicity, occupation, and education, was gathered through a questionnaire administered via face-to-face interviews. To assess the dietary intake of subjects, a validated semi-quantitative Food Frequency Questionnaire (FFQ) with 147 items was utilized [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The assessment of dietary intake was for one year before the interview. The trained interviewer asked all participants to indicate their daily, weekly, and monthly consumption. Accordingly, the frequency of consumption of each food item the evaluation of dietary intake covered the year preceding the interview. The interviewer, who was trained for this purpose, requested participants to specify their daily, weekly, and monthly food consumption. Subsequently, the frequency of each food item's intake was categorized into nine groups: \"never or less than once a month,\" \"1 to 3 times a month,\" \"once a week,\" \"2 to 4 times a week,\" \"5 to 6 times a week,\" \"once a day,\" \"2 to 3 times a day,\" \"4 to 5 times a day,\" and \"6 or more times a day.\" Participants were also asked about the average consumption per meal based on the portion size of each food item, with portion sizes explained using a food album. The daily gram intake of each food item was then calculated considering both the frequency and amount of consumption. Nutrient intake for each participant was estimated using data from the United States Department of Agriculture (USDA) food composition and Nutritionist 4 software. In cases where traditional Iranian foods were not present in the USDA database, the Iranian food composition table was utilized [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7. Diet quality assessment\u003c/h2\u003e \u003cp\u003eData collected with the food frequency questionnaires were used to calculate the dietary scores including HEI-2015, Dietary Diversity score (DDS), Dietary acid load (DAL) and Plant based dietary score (PDI).\u003c/p\u003e\u003cp\u003e\u003cb\u003e2.7.1. HEI-2015\u003c/b\u003e: A method described by Susan M. Krebs-Smith et al. was used for scoring HEI-2015 [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This method considered 13 components including whole fruit, total fruit, total vegetables, whole grains, green and beans, dairy, total protein foods, sea food and plant protein, fatty acids in adequacy section and refined grains, sodium, added sugar and saturated fats in moderation section. Individuals in the highest decile of whole grains, fatty acid ratio, and dairy were given the score of 10 and those in the lowest decile received the score of 0. Individuals in other deciles received the corresponding scores. In contrast, individuals with the highest intake of refined grains, added sugar, sodium and saturated fat, were given the score of 0 and those with the lowest consumption of these components received the score of 10. Also, Individuals in the highest quintiles of whole fruit, total fruit, total vegetables, green and beans, total protein foods, sea food and plant protein were given score 5 and those in the lowest decile received the score of 0. Total HEI-2015 score for each participant was then computed by summing up the scores for these 13 components. It was varied from 0 to 100.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2.7.2. DDS\u003c/b\u003e: A method described by Kant et al. was used for scoring dietary diversity [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. This method was based on five groups including grains, vegetables, fruits, meats and dairy, all food groups in the USDA food guide pyramid. The grains group was composed of seven components: refined bread, macaroni, whole grain bread, corn flakes, biscuits, refined flour, and rice. Fruit was defined by summing up fruit and fruit juice, berries and citrus fruits. The story about vegetables was summing up of potato, tomato, other starchy vegetables, legumes, yellow vegetables, green vegetables, and other vegetables. The group of meat was composed of red meat, poultry, fish and eggs) and the group of dairies was composed of milk, yoghurt and cheese.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2.7.3. DAL\u003c/b\u003e: We constructed dietary acid load score based on dietary intakes of several nutrients using potential renal acid load method (PRAL) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]: (protein [g/d] \u0026times; 0.49) + (Phosphorous [mg/d] \u0026times; 0.037) \u0026ndash; (potassium [mg/d] \u0026times; 0.021) \u0026ndash; (Calcium [mg/d] \u0026times; 0.013) \u0026ndash; (magnesium [mg/d] \u0026times; 0.026). Dietary acid load score obtained from this method, was used for statistical analysis.\u003c/p\u003e\u003cp\u003e\u003cb\u003e2.7.4. PDI\u003c/b\u003e: The method by Satija et al. was used to calculate the plant-based dietary pattern [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This score includes three indices of total Plant-based Diet Index (PDI), healthful PDI (H.PDI), and unhealthful PDI (UnH.PDI). Based on the similarity of nutrient components, food items were categorized into 18 groups, which included three main categories of animal, healthy, and unhealthy plant-based foods. Whole grains, fruits, vegetables, nuts, legumes, vegetable oils, and tea/coffee were considered healthy plant foods, while unhealthy plant foods included fruit juices, sugar-sweetened beverages, refined grains, potatoes, and sweets/desserts. In addition, animal fat, dairy, egg, fish/seafood, meat, and miscellaneous animal-based foods were considered animal food items. These food items were then converted to quintiles of consumption and a score of 1 to 5 was applied to each item. For PDI, scores of 5 and 1 were given to participants at the highest and lowest quintiles of plant food consumption, respectively. In addition, scores of 1 and 5 were given to the participants in the highest and lowest quintiles of animal foods consumption, respectively. To calculate H.PDI, scores of 5 and 1 were applied to participants with the highest and lowest consumption of healthy plant foods, respectively. A score of 1 for the highest consumption and 5 for the lowest consumption of unhealthy plant foods and animal food items was also determined. To calculate UnH.PDI, a score between 5 and 1 was given to the highest through the lowest consumption of unhealthy plant foods. Further, participants with the highest to lowest consumption of animal foods and healthy plant foods were given a score between 1 and 5. Scores were summed to obtain a score ranging from 18 to 90 for each PDI, H.PDI, and UnH.PDI index. Higher total scores for each index indicated higher adherence to that dietary pattern.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8. Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe SPSS Version 26 was utilized as the main tool for data handling and analysis. We summarized the data distribution by presenting descriptive statistics, including the average values with standard deviation and the median (Min\u0026ndash;Max). The Kolmogorov-Smirnov test was applied to evaluate the normality of the data distribution before proceeding with further analyses. For data that was skewed, log transformation was performed to normalize the distribution. To investigate the relationship between dietary scores and inflammatory/treatment outcomes, linear regression analysis was conducted in two forms: a crude model and a model adjusted for confounding factors. The adjusted model took into account Age, Sex, and BMI, which are factors known to affect the studied relationship. We also carried out subgroup analyses focusing on age and sex differences. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant, denoting meaningful findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cp\u003e\u003cstrong\u003e3.1. Descriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e provides a summary of participants\u0026apos; characteristics. This study includes 54 participants with an average age of 8.51 years (SD= 2.94). Among them, 36 were male and 18 were female. Based on the percentile, the mean BMI was 53.25 (SD= 36.63), and 46% of patients\u0026apos; BMI was in the normal range. The descriptive statistics for dietary intake are summarized in \u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eThe mean energy intake of the patients was 2067 kcal (SD= 614.45). Also, their mean daily protein intake was 76.56 grams (SD= 25.89), and the protein intake of all patients was within the normal range. The range of daily carbohydrate intake was from 136.31 to 470.13, and one of the participants had intake less than the normal range. Moreover, the median fat intake of the patients was 62.45 grams, and seven participants had less than normal range intake. \u003cstrong\u003eTable 3\u003c/strong\u003e shows a summary of the descriptive data for the dietary scores. According to the results obtained and based on the HEI-2015 score, 25% of the patients had poor adheres with the dietary guideline and the rest of the patients had moderate adheres. Moreover, the DAL scores ranged from\u0026nbsp;-36.95\u0026nbsp;(least dietary acidity score) to +24.49 (most dietary acidity score). Additionally, the mean scores of DDS and Total PDI were 4.90 (SD= 1.82) and 54.20 (SD= 6.33), respectively. Also, concerning the treatment outcomes, the patients\u0026apos; mean hospitalization days were 34.52 days (SD= 8.24). Four patients developed febrile neutropenia during the induction phase treatment, the mean of which was 0.24 (SD=0.86) days. Also, out of 54 patients, there were only two patients who did not achieve remission. Descriptive information related to inflammatory and treatment outcomes is also provided in \u003cstrong\u003eTable 4\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Association between Dietary Scores and Inflammation outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study\u0026apos;s results show a tendency for a protective association between DDS and NLR in the crude analysis model so that with an increase of one unit of DDS, the NLR value decreases by 0.30 (\u0026szlig;: -0.30, CI: -0.61 to 0.009, P-value: 0.057) \u003cstrong\u003e(Table 5)\u003c/strong\u003e. Also, according to the subgroup analysis results, following a more adheres to a PDI has caused a significant decrease in CRP in male group (\u0026szlig;: -0.63, CI: -1.20 to -0.07, P-value: 0.02). A significant (marginal) decrease in GPS in the male group has been observed following the one-point increase in the total PDI score (\u0026szlig;: -0.02, CI: -0.05 to 0.00, P-value: 0.052). Additionally, there is a significant direct relationship between the increase in the dietary diversity score and the increase in the PNI index in females (\u0026szlig;: 3.90, CI: 0.94 to 6.85, P-value: 0.01) \u003cstrong\u003e(Table 6)\u003c/strong\u003e. \u003cstrong\u003eTable 7\u003c/strong\u003e provides the mutual association between the individual components of the HEI-2015 score and inflammatory treatment outcomes. The findings indicate that as the dairy group\u0026apos;s score rises, there is a substantial increase in the MLR for both the crude (\u0026szlig;: 0.02, CI: 0.003 to 0.05, P-value: 0.03) and adjusted models (\u0026szlig;: 0.001, CI: 0.06 to 0.00, P-value: 0.04). On the other hand, each unit increase in total fruit score causes a significant decrease of 0.05 MLR in both crude (\u0026szlig;: -0.05, CI: -0.10 to -0.004, P-value: 0.03) and adjusted models (\u0026szlig;: -0.05, CI: -0.10 to 0.002, P-value: 0.059). However, this significance is marginal in the adjusted model. The relationship between the score of vegetables and GPS -as an index of the inflammation assessment- has also been significant in both crude (\u0026szlig;: 0.18, CI: 0.01 to 0.35, P-value: 0.03) and adjusted analysis models (\u0026szlig;: 0.19, CI: 0.005 to 0.39, P-value: 0.04), so with the increase in the score of total vegetables, GPS also increases significantly. Increasing the fatty acids score can also reduce inflammation. With the increase of one score in fatty acid component, the MLR decreased by 0.03 in the crude model (\u0026szlig;: -0.03, CI: -0.06 to -0.004, P-value: 0.02) and 0.02 in the adjusted model (\u0026szlig;: -0.02, CI: -0.05 to -0.002, P-value: 0.03). Also, in response to the increase of one score in fatty acids component, the PLR in the crude and adjusted models has decreased by 19.35 (\u0026szlig;: -19.35, CI: -35.75 to -3.31, P-value: 0.01) and 20.88 (\u0026szlig;: -38.77, CI: -35.75 to -2.99, P-value: 0.02), respectively. The results of 4 analysis were significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Association between Dietary Scores and treatment outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings of this study show that there is a direct relationship between PDI and hospitalization duration and in both crude and adjusted analysis models, the hospitalization duration significantly increased with the increase of PDI score. Crude model: (\u0026szlig;: 0.36, CI: 0.03 to 0.7, P-value: 0.03), adjusted model: (\u0026szlig;: 0.40, CI: 0.01 to 0.79, P-value: 0.02) \u003cstrong\u003e(Table 5)\u003c/strong\u003e. Based on the subgroup analysis, there is no significant relationship between dietary scores and treatment outcomes. On the other hand, the analysis of the HEI-2015 components showed that the febrile neutropenia duration increases significantly with the increase of green and beans group score (\u0026szlig;: 0.12, CI: 0.001 to 0.25, P-value: 0.04). Additionally, with the increase of each point of whole grains, the hospitalization duration has increased significantly in both crude (\u0026szlig;: 1.17, CI: 0.28 to 2.07, P-value: 0.01) and adjusted model (\u0026szlig;: 1.17, CI: 0.25 to 2.09, P-value: 0.01) by 1.17 days \u003cstrong\u003e(Table 7)\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e Our research revealed that patients with ALL demonstrated moderate adherence to the HEI-2015 guidelines. Similarly, their scores for dietary diversity and plant-based diets were moderate. Furthermore, our findings suggest that as the DDS increases in the crude analysis model, there's a notable (albeit marginal) reduction in the NLR, and the PNI significantly improves in females. In addition, a rise in the PDI markedly extends the duration of hospital stays and substantially lowers CRP and GPS levels in males. Additionally, higher intake scores for dairy products and total vegetables have been linked to increased inflammation, as evidenced by rises in the MLR and GPS across both analytical models. Conversely, enhancing the scores for total fruits and fatty acids significantly reduces inflammation markers, including MLR and PLR. Moreover, the treatment outcomes, such as hospitalization duration and increased instances of febrile neutropenia, have been significantly associated with higher scores for whole grains, as well as greens and beans.\u003c/p\u003e \u003cp\u003eWe cannot directly compare our results with other observational studies since no previous study has researched the association between diet quality and inflammatory treatment outcomes, on patients with hematological malignancy. However, this study was carried out on patients prior to the commencement of the induction phase of their treatment, which means that the impact of treatments like chemotherapy cannot be regarded as a confounding factor. While the elevated inflammation levels in these patients before diagnosis can lead to a reduced appetite, the rapid onset of symptoms and quicker diagnosis associated with ALL, as compared to chronic lymphocytic leukemia (CLL), means that this inflammation does not significantly affect long-term dietary intake [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. It is commonly known that the general pediatrics population's diet quality and adherence to recommendations are not at their best that is similar to our result [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. By using 4 scores in this study, it has been tried to evaluate the overall quality and diversity of the diet, fully and well. In our study, the increase in DDS score was inversely associated with NLR and has a direct relationship with PNI in women. Enhancing DDS is linked to decreased inflammation and better nutritional health, primarily due to adherence to healthful diets like the Mediterranean and anti-inflammatory diets. These eating patterns, rich in a variety of nutrient-dense foods, are associated with reduced levels of inflammatory markers, such as CRP and IL-6, as observed in cross-sectional studies [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This indicates that a varied diet, abundant in anti-inflammatory foods, has a beneficial effect on inflammation levels. Expanding DDS enhances nutritional health by promoting the intake of a broader array of essential nutrients. Varied diets are more likely to meet the body's requirements for both macronutrients (carbohydrates, proteins, and fats) and micronutrients (vitamins and minerals), thereby minimizing the risk of nutritional deficiencies and related health issues. Incorporating a wide range of foods from all food groups (grains, vegetables, fruits, proteins, and dairy) is crucial for balanced nutrition, as each group offers distinct nutrients vital for energy, growth, and overall bodily functions. Contrastingly, a study by Z. Malihi et al. [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which assessed dietary diversity in patients with ALL prior to chemotherapy, found no significant link between DDS and nutritional status, as measured by the Patients Subjective Global Assessment (PG-SGA) Questionnaire. This discrepancy with the current study's findings may be attributed to factors such as a smaller sample size and potential reporting bias in the nutritional status questionnaire. Based on the obtained results, PDI has a significant inverse relationship with CRP and GPS in males. The study led by Soraeya Kharaty and colleagues [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], which explored the link between the Plant-based Diet Index (PDI) and inflammation levels, found that a higher PDI correlates with lower CRP levels, aligning with our findings. This inverse relationship may be due to the high content of fiber, antioxidants (like vitamins C and E), polyphenols, and other phytochemicals in plant-based diets, known for their anti-inflammatory properties. These elements help diminish the production of pro-inflammatory cytokines, thereby reducing CRP levels in the bloodstream [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Additionally, foods abundant in omega-3 fatty acids, such as flaxseeds and walnuts, along with fruits, vegetables, whole grains, and legumes, possess anti-inflammatory qualities that can influence the inflammatory process and decrease CRP levels [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moreover, a healthy PDI is linked to lower levels of TNF-alpha, whereas an unhealthy PDI tends to elevate NLR, CRP, and TNF-alpha. In our research, however, we didn't observe a significant association between healthy or unhealthy PDI and inflammation markers, possibly due to the small sample size or differences in the populations studied. The result indicated that increasing the PDI score increases the duration of hospitalization. This can be due to the following possible reasons: Plant-based diets, while rich in many nutrients, may lack certain essential vitamins and minerals crucial for children undergoing cancer treatment, such as vitamin B12, iron, zinc, and omega-3 fatty acids. These deficiencies could potentially impact recovery and immune function, leading to longer hospital stays [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Also, Plant-based foods tend to be lower in calories compared to diets that include animal products. During the induction phase of treatment, the metabolic demands of children with ALL may increase. If the energy and protein intake are insufficient to meet these demands, it could slow down recovery, necessitating a longer hospital stay [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Moreover, the induction phase for ALL treatment is intense and can significantly impact the gastrointestinal system. High-fiber foods, common in plant-based diets, might exacerbate gastrointestinal issues such as diarrhea or lead to difficulty in managing nutrition due to decreased appetite or treatment-related mucositis [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. This can complicate nutritional management, potentially prolonging hospitalization. The analysis, both in its preliminary and adjusted forms as well as in subgroup evaluations, revealed no significant link between the DAL and inflammation markers. A diet with a high acid load has been hypothesized to induce a low-grade systemic acidosis, which could potentially lead to an increase in inflammation. Some studies suggest that higher DAL may be associated with inflammatory markers such as CRP, although findings are not universally consistent across all research. For instance, the research conducted by Tianying Wu [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] on survivors of breast cancer identified a notable positive correlation between dietary acid load and inflammation. Conversely, a study by Alireza Jafar [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], focusing on the elderly, found that an increase in the diet's acid potential was associated with a notable decrease in CRP levels, indicating a reduction in inflammation. There are no direct studies and evidence regarding the relationship between DAL and treatment outcomes in different patients. but it seems that the acidic potential of the diet can indirectly affect the treatment outcomes, including the length of hospitalization, through the effect on inflammation and metabolic alterations such as insulin resistance, diabetes, hypertension, and chronic kidney disease[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. However, more evidence is needed. Based on the results of our study, no significant association between HEI-2015 and inflammatory and therapeutic outcomes was observed. According to the results of a number of studies, adherence to HEI in children with the disease or survivors of childhood cancers is moderate or poor [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. several studies have been conducted in relation to investigating HEI and its relationship with inflammation in healthy and unhealthy children and adolescents. In a study by Pilar Navarro et al., higher score in the HEI was associated with lower levels of CRP in females, but not males from a healthy cohort [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In contrast, two studies found that moderate HEI scores (moderately healthy diet) were not associated with CRP or IL-6 in males or females in cohorts of patients with type-1 diabetes [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Also, the study by Sophie Bérard et al., which was conducted on ALL survivors, points out that Participants who had a better adherence to the HEI-2015 score had lower levels of TNF-alpha [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. It appears that factors such as the disease's type and severity, the size of the sample, and the study's design contribute to the lack of significant findings in this study. Nonetheless, examining how the scores from the HEI-2015 components correlate with inflammation and treatment outcomes yields meaningful results. The results show that by increasing the score of dairy products, inflammation by the MLR index increases significantly. Also, by increasing the score of fatty acids, inflammation is significantly reduced by MLR and PLR markers. Saturated fatty acids are a key factor to consider in this context. The score for fatty acids is derived from the ratio of omega-3 and omega-6 fatty acids to saturated fatty acids. Moreover, the dairy products consumed by these patients are predominantly high-fat, which are high in saturated fatty acids. Numerous studies have explored the link between saturated fatty acids and an increase in inflammation. Although the study by Carla P. Harris et al.[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] indicates that consuming saturated fatty acids (SFA) correlates with a reduction in hs-CRP, an index of inflammation, other research points to a detrimental impact of SFA intake on inflammation levels. According to the findings from Carla P. Harris and colleagues,[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] a higher intake of SFA and lower levels of n-6 PUFA are linked to elevated low-grade inflammation in children, while a higher intake of major dietary n-6 PUFA and total PUFA seems to diminish inflammation. Furthermore, research by Jin Mei et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] suggests that a diet high in SFA might increase the risk of developing breast, prostate, and colorectal cancers. Patients with ALL inherently experience high levels of spontaneous inflammation due to the disease itself, implying that consuming sources rich in saturated fatty acids may exacerbate inflammation, potentially negatively affecting the treatment process. Conversely, a higher consumption of omega-3 and omega-6 fatty acids in comparison to saturated fatty acids could contribute to the reduction of inflammation. The results obtained demonstrate a notable negative correlation between the rise in whole grain and greens and beans scores and the enhancement of treatment outcomes, such as shorter hospital stays and reduced periods of fever and neutropenia. The induction phase of chemotherapy presents challenging conditions for patients. During this phase, patients require a high intake of energy and protein to successfully navigate this stage of treatment. Consequently, prioritizing the consumption of foods high in energy and protein becomes essential [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Conversely, increasing the consumption of more grains and green and beans may hinder the improvement of treatment outcomes. Furthermore, the findings reveal that a higher consumption of vegetables correlates with an increase in the GPS, while a higher consumption of fruits is associated with a reduction in the MLR. It's important to note that patients in these cases require significant energy levels; thus, the rapid consumption of high-energy foods plays a crucial role in their treatment. The intake of fruits can be particularly beneficial due to their high energy content and quick absorption, which in turn can enhance the management of inflammation [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]. Regarding vegetables, various sources have said that high consumption of vegetables is useful in cancer patients, which contradicts the findings of our study. It seems more research could help [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo the best of our understanding, this research represents the inaugural exploration into how diet quality impacts treatment responses in children with ALL. A notable advantage of our study is its application of various food scores to assess diet quality comprehensively. Additionally, we employed an adjusted analysis model to mitigate the influence of confounding factors on our results. Furthermore, for enhanced accuracy and reliability, subgroup analysis was performed. However, the study faces limitations, including its small sample size. Another drawback is its cross-sectional nature, which, due to the absence of a non-cancer control group, hinders comparative analysis with the patients. The reliance on FFQ for dietary intake assessment introduces a potential for reporting bias, marking another limitation. Ultimately, while our findings reveal correlations, they do not clarify how various diet components might influence inflammatory or treatment outcomes.\u003c/p\u003e "},{"header":"Conclusions","content":"\u003cp\u003e Our research indicates that patients with ALL tend to poorly follow dietary guidelines. The findings underscore the benefits of enhancing dietary variety and greater compliance with the PDI score to diminish inflammation among these patients. Moreover, reducing saturated SFA while increasing intake of omega-3 and omega-6 fatty acids is crucial in mitigating inflammation. Gaining deeper insights into the impact of diet and its components on the well-being of ALL patients will enable the creation of customized dietary recommendations and nutritional plans for this vulnerable group.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval:\u0026nbsp;\u003c/strong\u003eThe study protocol was approved by the ethics committee of Tabriz University of Medical Sciences (ethic number: IR.TBZMED.REC.1401.1080). All participants (or their guardians) provided written informed consent to participate in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication:\u0026nbsp;\u003c/strong\u003eConsent for publication of the results was obtained from all participants (or their guardians) as part of the informed consent process\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research was funded by Research Assistant of Tabriz University of Medical Sciences, grant number 71254.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eThe data underlying this article will be shared on reasonable request to the corresponding author\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest: \u0026nbsp;\u003c/strong\u003eThe authors have nothing to disclose\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMJ:\u0026nbsp;\u003c/strong\u003eDrafting of the manuscript, Acquisition of data, critical revision of the manuscript for important intellectual content\u003cstrong\u003e\u0026nbsp;MB:\u0026nbsp;\u003c/strong\u003eDrafting of the manuscript, Acquisition of data\u003cstrong\u003e\u0026nbsp;PP:\u0026nbsp;\u003c/strong\u003eDrafting of the manuscript, Acquisition of data\u003cstrong\u003e\u0026nbsp;HG\u003c/strong\u003e: Drafting of the manuscript, Acquisition of data\u003cstrong\u003e\u0026nbsp;YT:\u003c/strong\u003e Acquisition of data\u003cstrong\u003e\u0026nbsp;AH:\u003c/strong\u003e Drafting of the manuscript, Acquisition of data\u003cstrong\u003e\u0026nbsp;ZG:\u003c/strong\u003e Interpretation of data,\u0026nbsp;critical revision of the manuscript for important intellectual content,\u0026nbsp;content,\u0026nbsp;Study concept and design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe would like to thank the clinical research development unit of children educational, research and treatment center, Tabriz university of medical sciences, Tabriz, Iran, and Danesh-2 Pathology Specialized Laboratory for their assistance in this research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBhojwani D, Yang JJ, Pui CH: \u003cstrong\u003eBiology of childhood acute lymphoblastic leukemia.\u003c/strong\u003e \u003cem\u003ePediatr Clin North Am \u003c/em\u003e2015, \u003cstrong\u003e62:\u003c/strong\u003e47-60.\u003c/li\u003e\n\u003cli\u003ePuckett Y CO: \u003cem\u003eAcute Lymphocytic Leukemia. 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\u003cstrong\u003eFood Intake During Cancer Therapy: A Systematic Review.\u003c/strong\u003e \u003cem\u003eAm J Clin Oncol \u003c/em\u003e2020, \u003cstrong\u003e43:\u003c/strong\u003e813-819.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eNutrition in Cancer Care (PDQ\u0026reg;) \u003c/strong\u003e[https://www.cancer.gov/about-cancer/treatment/side-effects/appetite-loss/nutrition-hp-pdq]\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eExpert Tips for Adding Calories and Overcoming Appetite Loss during. \u003c/strong\u003e[https://www.mskcc.org/news/expert-tips-adding-calories-and-overcoming-appetite-loss-during-cancer-treatment]\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Demographic and clinical characteristics of participants.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\" width=\"632\" height=\"494\"\u003e\u003c/p\u003e\n\u003cp\u003eNote. Data were expressed as Mean \u0026plusmn; SD or Frequency (percentage)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Dietary intake of patients\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003eMean (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003eMinimum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003eMaximum\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eEnergy (kc/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e2067.55 (614.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e1924.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e1248.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e3605.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eFruits (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e200.09 (127.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e180.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e32.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e553.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eVegetables (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e207.5 (131.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e173.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e44.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e612.19\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eGrains (gr/d)\u003c/p\u003e\n \u003cp\u003e\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e378.39 (150.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e365.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e65.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e767.72\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eBeans (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e20.43 (18.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e78.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eMeat group (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e126.75 (56.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e120.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e13.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e301.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eDairy (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e430.76 (228.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e397.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e58.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e1004.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eFats and Oils (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e34.33 (16.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e30.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e7.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e82.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eSweets and Added Sugars (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e22.84 (153.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e182.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e23.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e728.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eBeverages (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e235.63 (258)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e1216\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eTotal protein (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e75.56 (25.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e71.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e35.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e168.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eTotal carbohydrate (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e288.24 (84.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e279.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e136.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e470.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"32.69230769230769%\" valign=\"top\"\u003e\n \u003cp\u003eTotal fat (gr/d)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.153846153846153%\" valign=\"top\"\u003e\n \u003cp\u003e70.17 (25.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.346153846153847%\" valign=\"top\"\u003e\n \u003cp\u003e62.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.384615384615385%\" valign=\"top\"\u003e\n \u003cp\u003e33.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.423076923076923%\" valign=\"top\"\u003e\n \u003cp\u003e146.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Data were expressed as Mean \u0026plusmn; SD\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e Descriptive statistics of the dietary scores\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore (range)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u003cstrong\u003eMaximum\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;HEI-2015 (0-100)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e55.52 (7.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e56.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;DDS (0-10)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e4.90 (1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e8.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;DAL\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e-3.60 (12.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e-4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e-36.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e24.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003eTotal PDI (18-90)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e54.20 (6.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e53.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003eHealthy PDI (18-90)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e53.83 (6.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e53.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.057803468208093%\" valign=\"top\"\u003e\n \u003cp\u003eUnhealthy PDI (18-90)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.497109826589597%\" valign=\"top\"\u003e\n \u003cp\u003e53.87 (6.34)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.028901734104046%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.341040462427745%\" valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.07514450867052%\" valign=\"top\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Data were expressed as Mean \u0026plusmn; SD; Median; Min\u0026ndash;Max\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Descriptive statistics of the Inflammatory Markers and treatment outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarkers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean (SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u003cstrong\u003eMaximum\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e15.13 (19.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e5.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e76.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e1.55 (2.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e13.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e0.24 (0.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e2.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e109.96 (168.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e32.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e754.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eGPS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e0.52 (0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e63.79 (43.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e47.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e32.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e0.57 (0.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eHospitalization duration\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e34.52 (8.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.579964850615113%\" valign=\"top\"\u003e\n \u003cp\u003eFN\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.035149384885763%\" valign=\"top\"\u003e\n \u003cp\u003e0.24 (0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.695957820738137%\" valign=\"top\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.817223198594025%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.87170474516696%\" valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Data were expressed as Mean \u0026plusmn; SD; Median; Min\u0026ndash;Max\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"948\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"13\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Association Between Diet quality indices and Inflammation/Treatment outcomes\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; HEI-2015 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DDS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DAL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; PDI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;H.PDI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Unh.PDI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.962025316455696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.751054852320675%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.9071729957805905%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.751054852320675%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.590717299578059%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.2784810126582276%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.962025316455696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.962025316455696%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.329113924050633%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.594936708860759%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.962025316455696%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.594936708860759%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.057\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-11.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e2.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-12.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGPS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Crude model\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e3.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e-0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e-1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e-0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e-1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eHospitalization duration\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eFebrile neutropenia\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Crude model\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Adjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.235142118863049%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.268733850129198%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.847545219638243%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.914728682170542%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.751937984496124%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.527131782945736%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.30232558139535%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Linear regression analysis examined the potential relationship between dietary scores and the inflammatory/ treatment outcomes.\u003c/p\u003e\n\u003cp\u003eModel 1: Crude\u003c/p\u003e\n\u003cp\u003eModel 2: Adjusted for Age, Sex, and BMI.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"948\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"13\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Association Between Diet quality indices and Inflammation/Treatment outcomes according to subgroup analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHEI-2015\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDAL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePDI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eH.PDI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnh.PDI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.373812038014783%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables (by gender)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.546990496304118%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.75818373812038%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.124604012671594%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.652587117212249%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.2302006335797255%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.286166842661035%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.863780359028511%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.863780359028511%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.335797254487856%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.497360084477297%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.969376979936642%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.497360084477297%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-2.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e2.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-21.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e-2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-5.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e7.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-8.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGPS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female \u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.052\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e-0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e-0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Female\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eHospitalization duration\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eFebrile neutropenia\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.020698576972833%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.279430789133247%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.503234152652005%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.15006468305304%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.632600258732213%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.926261319534282%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.408796895213454%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.7619663648124195%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.538163001293661%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.184993531694696%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.31578947368421%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables (by age)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.947368421052632%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.526315789473684%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7368421052631575%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.2631578947368425%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.947368421052632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.947368421052632%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.315789473684211%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.947368421052632%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.578947368421052%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eCRP\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-1.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e1.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt; 9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-9.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e1.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-2.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-15.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e4.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGPS\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026lt; 9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePNI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e8.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-4.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-2.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eHospitalization duration\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt; 9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"18.354430379746834%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eFebrile neutropenia\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026lt; 9\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026ge; 9\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"81.64556962025317%\" colspan=\"12\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.989690721649485%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.24742268041237%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.829896907216495%\" valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.891752577319588%\" valign=\"top\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.731958762886598%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.505154639175258%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.278350515463918%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Linear regression subgroup analysis examined the potential relationship between dietary scores and the inflammatory/ treatment outcomes.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"1218\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"90.14778325123153%\" colspan=\"17\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 7.\u003c/strong\u003e Association Between HEI-2015 components and Inflammation/Treatment outcomes\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.852216748768473%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.866995073891626%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35960591133005%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35960591133005%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35960591133005%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.35960591133005%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGPS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.866995073891626%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePNI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.852216748768473%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.866995073891626%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eH. D\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.852216748768473%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eF. N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026szlig;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDairy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e14.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e14.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-4.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal fruits\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-12.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.059\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-12.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhole fruits\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e24.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e27.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal vegetables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-7.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e4.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-4.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGreen and beans\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e2.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.04\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eWhole grains\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e6.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e6.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal proteins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-36.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-37.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-3.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeafood and plant proteins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e8.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e9.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e7.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFatty acids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-19.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-20.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.02\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRefined grains\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-8.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-8.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSodium\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.998\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdded sugar\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSaturated fats\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"83.74384236453201%\" colspan=\"18\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eCrude model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.25615763546798%\" valign=\"top\"\u003e\n \u003cp\u003eAdjusted model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e1.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.433497536945813%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e1.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.9408866995073892%\" valign=\"top\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e-0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"4.926108374384237%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. Linear regression analysis examined the potential relationship between HEI-2015 components and the inflammatory/ treatment outcomes. Model 1: Crude; Model 2: Adjusted for Age, Sex, and BMI.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Acute Lymphoblastic Leukemia, Diet Quality Scores, Inflammation Outcomes, Treatment Outcomes, Cross-Sectional Study","lastPublishedDoi":"10.21203/rs.3.rs-4332670/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4332670/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eAcute Lymphoblastic Leukemia is the most common childhood cancer. Considering the importance of diet in the treatment process of cancer patients, the purpose of this study was to investigate the relationship between diet quality and inflammatory/therapeutic outcomes.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this cross-sectional study, 147-item Food Frequency Questionnaire was used to collect dietary data from patients. Diet quality was evaluated by the Healthy Eating Index 2015 (HEI-2015), Dietary Diversity Score (DDS), Dietary Acid Load (DAL), and Planet Base Diet Index (PDI). Linear regression analysis was then employed to explore potential associations between dietary scores and the C-reactive protein (CRP), Neutrophil-to-Lymphocyte Ratio (NLR), Monocyte-to-Lymphocyte Ratio (MLR), Platelet-to-Lymphocyte Ratio (PLR), Prognostic Nutrition Index (PNI), Prognostic Index (PI), Glasgow prognostic score (GPS), Febrile neutropenia (FN), and Hospitalization duration outcomes.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eIn this study with 54 patients, we found that a higher DDS score is linked to a reduction in NLR (\u0026szlig;: -0.30, P-value: 0.057) and an increase in PNI among women (\u0026szlig;: 3.90, P-value: 0.01). Furthermore, an inverse relationship was observed between the PDI score and both CRP (\u0026szlig;: -0.63, P-value: 0.02) and GPS (\u0026szlig;: -0.02, P-value: 0.052) in men. However, the length of hospital stay was seen to rise with an increase in PDI, both in crude models (\u0026szlig;: 0.36, P-value: 0.03) and when adjusted for other factors (\u0026szlig;: 0.40, P-value: 0.02). No additional significant links were discovered between food scores and the outcomes studied.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn conclusion, a diet that is both higher in quality and more varied leads to a reduction in inflammation-related outcomes. Furthermore, closely following PDI guidelines is linked to longer hospital stays. To achieve more dependable findings, further research in this area is necessary.\u003c/p\u003e","manuscriptTitle":"The Association Between Diet Quality Scores with Inflammation and Treatment Outcomes in Children with Acute Lymphoblastic Leukemia; A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-07 07:26:31","doi":"10.21203/rs.3.rs-4332670/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bc194841-6b36-4093-9cd2-0a6ae7f36e29","owner":[],"postedDate":"May 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-11T03:17:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-07 07:26:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4332670","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4332670","identity":"rs-4332670","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}