Enhancing Treatment Precision: Evaluating The Validity and Reliability of Modified NutricheQ in Detecting Iron Deficiency in Children Aged 1-3 Years in Indonesia

Enhancing Treatment Precision: Evaluating The Validity and Reliability of Modified NutricheQ in Detecting Iron Deficiency in Children Aged 1-3 Years in Indonesia | 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 Enhancing Treatment Precision: Evaluating The Validity and Reliability of Modified NutricheQ in Detecting Iron Deficiency in Children Aged 1-3 Years in Indonesia Damayanti Rusli Sjarif, Steven Tjia, Klara Yuliarti, Aria Kekalih This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6566656/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 Iron deficiency anemia remains a persistent issue in developing countries, including Indonesia, prompting recommendations for routine iron supplementation. However, supplementation is often provided without prior screening, increasing the risk of unnecessary treatment and potential side effects. Validated, non-invasive screening tools could be especially valuable in these settings. This study aimed to evaluate the validity and reliability of a modified NutricheQ Questionnaire for identifying iron deficiency risk in the Indonesian pediatric population. Method A two-step cross-sectional study was conducted among 300 children aged 1–3 years across Jakarta, Indonesia. The first step assessed the validity of the modified NutricheQ Questionnaire, followed by analysing its correlation with dietary iron intake and serum ferritin level. Validity was assessed through Spearman correlation test. Internal consistency was measured using Cronbach’s alpha, and inter-rater reliability was assessed using Cohen’s kappa. Receiver operating characteristic (ROC) analysis was performed to identify optimal threshold scores based on sensitivity, specificity, and area under the curve (AUC). Results The modified questionnaire demonstrated acceptable construct validity, with Spearman correlation coefficients >0.30 for all items except red meat intake. Inter-rater reliability ranged from fair to perfect agreement (Cohen’s kappa: 0.40–1.00). There was moderate correlation with dietary iron intake (r = 0.39, p < 0.01) and serum ferritin levels (r = 0.29, p < 0.01). The 5-question version had an optimal threshold score of 5, yielding a sensitivity of 80.4% and specificity of 48.3% in predicting iron intake; AUC was 0.709 (CI 95%: 0.648-0.770). A shortened 3-question version with a threshold of 4 maintained the same sensitivity (80.4%) and improved specificity (67.0%) for predicting iron intake (AUC = 0.768; 95% CI: 0.712–0.825), with sensitivity of 71.6% and specificity of 61.5% for predicting low serum ferritin (AUC = 0.682; 95% CI: 0.597–0.758). Conclusion The modified NutricheQ Questionnaire demonstrated good validity and reliability for identifying risk factors of iron deficiency in Indonesian children aged 1–3 years. The shortened three-item version, in particular, shows promise as a non-invasive screening tool for use in low-resource settings. diet dietary deficiency iron deficiency iron deficiency anemia nutritional questionnaire preschooler NutricheQ screening Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Iron deficiency anemia remains one of the most significant global health problems in both developed and developing countries. The prevalence of pediatric anemia in Southeast Asia is 65.5%, equivalent to approximately 115.3 million children. 1 First national data from Indonesia showed a prevalence of 40–45% in children aged 1–5 years old in the year 2007, with even higher rates in rural areas, reaching 75–76%. 2,3 As recommended by the World Health Organization (WHO), iron supplementation is deemed necessary when the national prevalence reaches 40%. 4 Consequently, the Indonesian Pediatric Society recommends iron supplementation for all children, prioritizing those aged 0–5 years without the need for prior screening. 5 The American Academy of Pediatrics (AAP), on the other hand, recommends all babies to be screened and tested to determine Hb concentration by the age of 12 months, with decisions regarding iron supplementation made based on various factors, including exclusive breastfeeding status and the composition of complementary feeding. 6 Whilst iron supplementation without prior screening provides practical benefits, it is important to acknowledge that iron is a potent pro-oxidant which may lead to the formation of free radicals. Some health problems that may rise due to inappropriate iron supplementations are growth problems, increased infection risk, as well as increased mortality and morbidity in malaria endemic areas. 7 – 10 However, confirming iron status needs facilities and funds that may not be available in many areas of developing countries, such as Indonesia. Therefore, the usage of a valid and reliable questionnaire to screen for iron deficiency prior to blood tests can be beneficial to such a population, requiring less funds. In 2010, the NutricheQ questionnaire was developed in Ireland to identify micronutrient deficiency risk factors and dietary imbalances. The questionnaire was tested for its validity by Sjarif in 2011 for the Indonesian population and was found invalid due to the terms used as well as the significant difference in the Indonesian diet from European. 11 Sjarif then modified the questionnaire according to the Indonesian diet. 12 However, the modified NutricheQ has yet to be tested for its validity and correlation with iron intake and ferritin levels, which are the two parameters that provide insight towards adequacy of dietary iron intake and iron storage; often reflecting the state of iron deficiency before anemia occurs. 6 , 13 , 14 Hence, this study aims to test the validity and reliability of modified NutricheQ in identifying iron intake and ferritin levels as iron deficiency risk factors in the Indonesian population. 2 Methods 2.1 Study design This cross-sectional study was conducted in two steps. The first step validated the Modified NutricheQ Questionnaire as a screening tool for iron deficiency anemia and the second step tested the correlation of the questionnaire towards iron intake and ferritin levels, aimed to find the score threshold which gives the best diagnostic value. This study adhered to the Declaration of Helsinki and received ethical approval from The Clinical Ethics Committee of Cipto Mangunkusumo National General Hospital (ref-no: 662/H2.F1/ETIK/2013). Written informed consent forms were provided and signed by all participants. The modified NutricheQ Questionnaire consists of 5 questions, which were modified from the iron-intake related section of the original 12-question NutricheQ questionnaire. The 5 question item included questions on the frequency of formula milk (growing-up milk) intake, chicken or beef liver intake, red meat intake, red-meat based food intake, and egg intake. Each question is scored on a scale of 0 to 2, where a score of 0 indicates higher intake/portion and a score of 2 indicates lower intake/portion (see Supplementary Materials 1 and 2). 2.2 Study population This study took place in 5 integrated service posts (Posyandu) across East and Central Jakarta. Data is sampled from December 2013 to January 2014. The target population for this study is children aged 1–3 years old who fulfilled the inclusion and exclusion criteria. The inclusion criteria were children aged 1–3 years whose parents are literate (able to read and write), permanently reside in Jakarta, and agreed to participate in the study. Children who were severely undernourished, suspected or diagnosed with thalassemia, on a routine iron supplementation of minimal 2 weeks prior participating, erythrocyte sedimentation rate of more than 15 mm, as well as children with acute or chronic infection and history of recent blood transfusion (1 month prior study) were excluded from this study. 2.3 Sample size determination and sampling method Sample size of this study was determined using the 10% rule. As this study was a part of a bigger study of the same questionnaire which included all 12 questions, the sample size was determined by the following formula: N = 12x(10–15) N = 120–180 subjects x 1,3* N = 234 subjects *Dropout rate took into consideration the estimated subjects with ESR > 15 mm/hour to be 30% 15 The researchers rounded up the sample size to 300 subjects which were then recruited in integrated service posts. The integrated service posts were selected using stratified random sampling, while subjects were recruited through consecutive sampling until the minimum required sample of 300 subjects was achieved. For the validity, reliability, and correlation tests, subjects were sampled consecutively, with a total of 30 subjects for the validity and reliability tests and 60 subjects for the correlation test. 2.4 Study timeline and procedures All interviewers and dieticians involved in this study received prior training. All parents or guardians with children aged 1–3 years were given explanations on the purpose, procedures, benefits and risks of this study. Prospective subjects who fulfilled the inclusion and exclusion criteria were recruited. Peripheral blood was collected from consenting subjects for hematological profiles and serum ferritin level analyses. All samples underwent processing using consistent machines and techniques. Hematological profiles were analyzed using ADVIA 2120 through flow cytometry, and serum ferritin levels were analyzed using Immulite 2000 through immunochemiluminescent methods. Subjects with erythrocyte sedimentation rates (ESR) ≥ 15mm/hour were excluded from the analysis. Additionally, dietary analysis was conducted for all subjects, involving parents who were asked to maintain a food diary detailing all consumed items over a 72-hour period (2 weekdays and 1 weekend) following the meeting. All parents and/or caregivers received training on maintaining a food diary from the research team. The food diaries were subsequently evaluated and analyzed by dieticians using the NutriSurvey 2007 software. 2.5 Data analysis Data analysis was conducted using the SPSS software. Validity was tested using Spearman correlation test. Internal consistency was measured using Cronbach’s alpha and inter-rater reliability was assessed using Cohen’s kappa. The questionnaire’s level of agreement for iron intake and ferritin level was determined using Pearson correlation test. Diagnostic test was determined using the receiver operating characteristic (ROC) area under the curve. Sensitivity, specificity, positive predictive value, and negative predictive value were also presented in this study. 3 Results 3.1 Validity and reliability of the modified NutricheQ questionnaire First, internal consistency was assessed by calculating the Cronbach’s alpha for the questionnaire. Cronbach's alpha was 0,208. Inter-rater reliability was found to have Cohen’s kappa of 0,4-1. Spearman correlation test showed all questions to be >0,3, except for the question on red meat intake. Table 3.1.1 Internal validity dan reliability of modified NutricheQ*,** Question Item Correlation Coefficient Amount of growing-up milk intake in a day 0,605 (p≤0,005) Portion of chicken or beef liver consumed in a week 0,379 (p≤0,005) Portion of red meat consumed in a week 0,233 (p≤0,005) Frequency of red-meat-based food consumption in a week 0,550 (p≤0,005) Portion of chicken, duck, or quail eggs consumed in a week 0,531 (p≤0,005) * Data was calculated using Spearman correlation test and Cronbach’s alpha of 0,208. Correlation coefficient was significant if ≥0,3. **Question item has been translated into English for readers’ understanding. Readers may find the original version (Bahasa Indonesia) in Supplementary Materials. Tabel 3.1.2. Inter-rater reliability of the Modified NutricheQ . Question Kappa Score Rater 1-control Rater 2-control Amount of growing-up milk intake in a day 1.000 0.697 Portion of chicken or beef liver consumed in a week 0.583 0.348 Portion of red meat consumed in a week 0.455 0.455 Frequency of red-meat based food consumption in a week 0.615 0.615 Portion of chicken, duck, or quail eggs consumed in a week 0.643 0.643 Kappa: < 0 = no agreement, 0,01-0,2 = slight agreement, 0,21-0,4 = fair agreement 0,41-0,6 = moderate agreement, 0,61-0,8 = substantial agreement, 0,81-0,99 = near perfect agreement, 1 = perfect agreement 3.2 Demographics A total of 60 healthy children between the age of 1-3 years from each PHCs participated in this study, resulting in a total of 300 subjects. The average age in the study population was 24.1 months. 47% were male and 53% were female. Majority of the subjects had normal nutritional status. Majority of the parents’ education status were high school and had middle-to-low income (56%), with 67.3% of the respondents’ mothers were stay-at-home mothers. Clinical characteristics of the study subject may be found in Table 3.2. Table 3.2. Demographics Characteristic N=300(%) Age (month) 24.1 * Gender ● Male ● Female 141 (47%) 159 (53%) Delivery method ● Spontaneous/vaginal birth ● Cesarian section 278 (81%) 57(19%) Nutritional status ● Undernutrition ● Normal ● Overweight ● Obese 12 (4%) 264 (88%) 9 (3%) 15 (5%) Father’s age (year) 32 * Father’s education level ● Primary school ● Middle school ● High school ● Academy or University 20 (6.7%) 47 (15.7%) 198 (66%) 35 (11.7%) Mother’s age (year) 28,8 * Mother’s education level ● Primary school ● Middle school ● High school ● Academy or University 27 (9%) 69 (23%) 185 (61.7%) 19 (6.3%) Mother’s employment status ● Self-employed ● State official ● Private employee ● Laborer ● Stay-at-home 26 (8.7%) 2 (0.7%) 61 (20.3%) 9 (3%) 202 (67.3%) Family economic status ● Low ● Middle-low ● Middle-high ● High 18 (6%) 168 (56%) 110 (36,7%) 4 (1,3%) *Data is presented in mean 3.3 Peripheral blood analysis 74 out of 300 subjects were not included in the questionnaire’s analysis for ferritin level due to high ESR levels of ≥15mm/hour. 11 subjects who had non-iron-deficient anemia were also excluded from analysis. All subjects received explanations on good feeding practices and options of iron-rich diet. Children with iron-deficiency anemia as well as non-iron-deficient anemia were referred to be treated in primary healthcare centers or regional general hospitals. Flow diagram on subject’s inclusion and exclusion into the analysis can be found in Figure 3.3 According to the peripheral blood and ferritin analysis, subjects can be categorized into 4 groups: normal iron status, iron deficient, iron-deficiency anemia, and non-iron-deficient anemia (Table 3.3) Table 3.3. Categories of subject according to their iron profile status Categories N=226(%) Normal iron profile 148 (65,5%) Iron deficient 34(15%) Iron deficiency anemia 33 (14,6%) Non-iron-deficient anemia 11(4,9%) 3.4 Modified NutricheQ profile according to responses 46% of all children consumed growing-up milk more than 600mL daily. While 73.7% and 89.7% only consumed less than 1 portion of liver and red meat weekly, respectively. 42% of subjects consumed around 2 to 4 portions of red-meat-based food and 49.3% consumed more than 5 portions of eggs weekly. Profile of the questionnaire according to responses may be found in Table 3.4. Table 3.4. Questionnaire’s profile according to responses Question Score N % Amount of growing-up milk intake in a day 0 138 46.0% 1 44 14.7% 2 118 39.3% Portion of chicken or beef liver consumed in a week 0 8 2.7% 1 72 24.0% 2 220 73.3% Portion of red meat consumed in a week 0 8 2.7% 1 23 7.7% 2 269 89.7% Frequency of red-meat-based food consumption in a week 0 118 39.3% 1 126 42.0% 2 56 18.7% Portion of chicken, duck or quail eggs in a week 0 148 49.3% 1 105 35.0% 2 47 15.7% 3.5 The correlation of Modified NutricheQ profile with iron intake Questions on the intake of growing up milk formula, liver and red meat intake may give an insight on the respondent’s iron intake, as seen in the difference of mean iron intake between subjects who had higher intake versus lower intake (Table 3.5.1). Table 3.5.1 . Profile of each question towards iron intake. Question Score Iron intake (mg) Median SD Min Max Amount of growing-up milk intake in a day 0 12.28 5.36 2.69 34.86 1 11.16 4.31 2.83 22.41 2 6.20 3.10 1.09 21.09 Portion of chicken or beef liver consumed in a week 0 14.35 4.65 6.19 18.88 1 10.18 5.66 1.98 34.86 2 9.04 5.17 1.09 31.69 Portion of red meat consumed in a week 0 11.99 5.08 3.76 19.61 1 9.30 4.39 5.06 23.92 2 9.28 5.37 1.09 34.86 Frequency of red-meat-based food consumption in a week 0 9.98 5.70 1.98 34.86 1 8.91 5.10 1.95 29.46 2 9.39 4.80 1.09 21.44 Portion of chicken, duck or quail eggs in a week 0 9.75 5.48 2.15 34.86 1 8.85 4.90 1.95 31.69 2 8.86 5.47 1.09 23.92 SD: standard deviation In order to analyze the correlation between each question item with iron intake, we used Pearson correlation test. The results of the test revealed that only the intake of growing-up milk exhibited a statistically significant correlation (Table 3.5.2). When combined, the total score of the 5-item modified NutricheQ showed a moderate, statistically significant negative correlation with iron intake (r = –0.397, p < 0.01). Table 3.5.2 Correlation score of each question item with iron intake.* Question Correlation coefficient Sig. (2-tailed) Amount of growing-up milk intake in a day -0.541 0.000 Portion of chicken or beef liver consumed in a week -0.069 0.233 Portion of red meat consumed in a week -0.037 0.528 Frequency of red-meat-based food consumption in a week -0.055 0.340 Portion of chicken, duck or quail eggs in a week -0.066 0.253 * Pearson correlation significant if sig(2-tailed) ≤0,01 3.6 The correlation of Modified NutricheQ profile with serum ferritin According to the profile of each questionnaire’s item on ferritin level, questions on the intake of growing up formula, liver, red meat and red-meat-based food showed a promising trend in distinguishing ferritin levels as the score increased (Table 3.6.1). Table 3.6.1. Profile of each question towards serum ferritin levels. Question Score Serum ferritin (ng/mL) Median SD Min Median Amount of growing-up milk intake in a day 0 28.85 17.43 2.80 83.70 1 22.60 17.34 2.40 64.90 2 9.80 12.18 1.50 56.70 Portion of chicken or beef liver consumed in a week 0 27.10 7.84 9.80 29.00 1 21.00 17.40 1.50 61.60 2 19.15 17.74 1.50 115.00 Portion of red meat consumed in a week 0 27.10 16.96 6.60 59.40 1 16.50 20.21 1.50 63.40 2 19.90 17.30 1.50 83.70 Frequency of red-meat-based food consumption in a week 0 20.55 17.69 1.50 80.20 1 20.40 17.39 1.50 83.70 2 18.00 17.51 1.50 60.20 Portion of chicken, duck or quail eggs in a week 0 20.30 16.48 1.50 83.70 1 20.15 18.41 1.50 80.20 2 20.25 18.60 1.50 63.40 According to Pearson correlation test, question on growing-up milk intake is the only question that has significant correlation with serum ferritin level. When combined, the total score showed a statistically significant correlation with iron intake (r = 0.291, p < 0.01). Table 3.6.2 Correlation score of each question item with serum ferritin.* Question Correlation coefficient Sig. (2-tailed) Amount of growing-up milk intake in a day -0.487 0.000 Portion of chicken or beef liver consumed in a week -0.029 0.667 Portion of red meat consumed in a week 0.008 0.904 Frequency of red-meat-based food consumption in a week 0.016 0.815 Portion of chicken, duck or quail eggs in a week -0.002 0.977 * Pearson correlation significant if sig(2-tailed) ≤0,01 3.7 Threshold score of modified NutricheQ as a tool to predict iron deficiency risk This study analyzed the threshold scores of the modified NutricheQ as a tool to predict iron deficiency through iron intake and serum ferritin level. We first identified the threshold score of the modified NutricheQ to predict the risk if inadequate iron intake (<7 mg/day) by calculating the area under the receiver operating characteristic (ROC) curve (AUC). According to the 5 question items, we found an area of 0.709 (CI 95%: 0.648-0.770). In this questionnaire, the lowest and highest score that can be achieved is 0 and 10, respectively. Through sensitivity and specificity tests, we found an optimal threshold score of 5. Table 3.7.1 presents the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of multiple threshold scores in predicting iron intake. Table 3.7.1 Threshold scores of the NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting iron intake. Total score Sensitivity (%) Specificity (%) PPV (%) NPV(%) ≥ 5 80.4% 48.3% 42.6% 83.8% ≥ 6 56.7% 70.4% 47.8% 77.3% PPV: positive predictive value. NPV: negative predictive value In regard to serum ferritin level, the AUC was 0.598 (CI 95%: 0.514-0.682). The score 5 showed better diagnostic test results compared to the other prospective threshold (Table 3.7.2). Table 3.7.2 Threshold scores of the NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting serum ferritin level. Total score Sensitivity (%) Specificity (%) PPV (%) NPV(%) ≥ 5 73,1% 43,4% 35,3% 79,3% ≥ 6 49,3% 67,3% 38,8% 75,9% Taking into account the trend in the question item on growing-up milk, liver and red meat consumption, we further analyzed the 3 questions. The total score of the questionnaire in relation to iron intake and ferritin level still showed moderate to strong correlation, with each correlation coefficient to be -0.527 and -0.41, sig(2-tailed) <0.01, respectively. The AUC of the 3 selected questions on iron intake was higher compared to the complete, 5-question Modified NutricheQ Questionnaire: 0.768 (CI 95%: 0.712-0.825) (Figure 3.7.1). The lowest and higher scores of the 3 questions were 0 and 6, respectively. We found an optimal threshold score of 4, which provided sensitivity, specificity, PPV and NPV of 90.4%, 67%, 53.8% and 87.7%. (Table 3.7.3). Table 3.7.3 Threshold scores of the 3 selected questions in the modified NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting iron intake. Total score Sensitivity (%) Specificity (%) PPV (%) NPV(%) ≥ 2 100.0% 7.4% 34.0% 100.0% ≥ 3 95.9% 23.2% 37.3% 92.2% ≥ 4 80.4% 67.0% 53.8% 87.7% The diagnostic tests of the 3 questions were also higher in predicting ferritin levels compared to the 5 questions, showing an AUC of 0.682 (CI 95%: 0.597-0.758) (Figure 3.7.2). The optimal threshold score with the best diagnostic value for the 3 questions in predicting serum ferritin level is also 4, presenting a sensitivity, specificity, PPV and NPV of 71.6%, 61.5%, 45.7% and 82.7%, respectively (Table 3.7.4). Table 3.7.4 Threshold scores of the 3 selected questions in the modified NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting serum ferritin level. Total score Sensitivity (%) Specificity (%) PPV (%) NPV(%) ≥ 2 95,5% 4,4% 29,6% 70% ≥ 3 88.1% 17.6% 31.1% 77.8% ≥ 4 71,6% 61,5% 45,7% 82,7% 4 Discussion The NutricheQ Questionnaire has long been recognized as a valuable tool to help health care providers in detecting nutritional risks in toddlers, encompassing risks related to macronutrient and micronutrient deficiency as well as poor feeding behavior. The original questionnaire has 4 question items that were correlated to iron intake: age and amount of cow’s milk or formula milk intake, meat or oily fish intake, and fortified cereal intake. 16 , 17 Due to the difference in dietary habits in Indonesia, the questionnaire was found to be inapplicable. Hence, Sjarif modified the questionnaire to better align with the Indonesian population, consisting of question items on formula milk intake, red meat intake, liver intake, red-meat-based food intake and egg intake, as well as providing more understandable terms to describe the portion, based on familiar measurements used by the population. In our study, the Modified NutricheQ Questionnaire has shown to be a valid and reliable tool in assessing iron deficiency risks in toddlers. Most questions exhibited correlation coefficients exceeding 0.3, indicating validity. However, the questionnaire's reliability, measured by Cronbach’s alpha, was 0.208, lower than the study in Ireland, which reported 0.4. 17 Neither the modified nor the original NutricheQ Questionnaire achieved the desired reliability threshold of > 0.6. This discrepancy may be attributed due to the difference in the number of questions. The Modified NutricheQ Questionnaire comprises only 5 questions, while the NutricheQ Questionnaire has 18, allowing for a broader assessment beyond iron deficiency risk factors. Nevertheless, the Modified NutricheQ Questionnaire demonstrated a fair to perfect agreement in inter-rater reliability, with a Cohen’s kappa score of 0.4-1. Amongst all questions in the Modified NutricheQ Questionnaire, only the question on growing-up milk showed statistical significance in its relationship with iron intake. This may be attributed to the question's design, which directly asks respondents for the daily volume in milliliters, potentially reducing recall bias. Even though the questions on liver and red meat consumption weren’t statistically significant, the question utilized a relatively more objective measurement unit compared to other questions. For instance, the questionnaire used a matchbox to describe the portion of red meat, aiding respondents in visualizing their intake accurately. However, red-meat based food, such as sausages, meatballs, and meatloaf, have various unstandardized portions, posing a limitation. Similarly, while eggs are easy to quantify, many mothers prepare eggs alongside other ingredients and often feed multiple children from the same plate at the same time. This may lead to inaccuracies in recalling the amount of egg consumed by a single toddler. Likewise, only the question on growing-up milk has statistical significance in its relation to ferritin levels. However, relying solely on a single question about formula milk consumption to predict iron deficiency would not be able to accommodate children with dietary habits of consuming iron-rich foods without formula milk. The area under the ROC curve for the Modified NutricheQ associated with iron intake and serum ferritin are 0.709 and 0.598, respectively. Threshold score of 5 resulted in optimal sensitivity of 80.4% and optimal specificity of 48.3% when correlated to iron intake. On the other hand, when correlated to serum ferritin, optimal sensitivity and specificity were 73.1% and 43.4%. Ideally, a screening tool should have both sensitivity and specificity of at least 80%. Considering the consistent trend among 3 questions (formula milk intake, liver intake and red meat intake), we conducted a further analysis on the AUC of the 3 questions and compared it to the 5-question set. The 3 questions presented a better result, with an AUC of 0.768 when associated with iron intake and 0.678 with serum ferritin level. Furthermore, the significance of their correlation coefficients were also preserved. The 3-question set showed an optimal threshold score of 4, presenting with sensitivity and specificity of 80.4% and 67% in predicting iron intake and 71.6% and 61% in predicting serum ferritin level. Summary of the diagnostic tests of the 3 questions and 5 questions may be found in Table 4 . Table 4 Summary of diagnostic tests performed in this study for the Modified NutricheQ Questionnaire. Option AUC Sensitivity (%) Specificity (%) PPV (%) NPV (%) Iron intake 5 questions 3 questions 0,709 0,768 80.4 80,4 48.3 67 42.6 53.8 83.8 87,7 Serum ferritin 5 questions 3 questions 0,598 0,678 73,1 71,6 43,4 61 35,3 43,6 79,3 83,6 Threshold score for 5-question questionnaire was ≥ 5 Threshold score for 3-question questionnaire was ≥ 4 When compared to the questionnaire developed by Bogen et al 16 , out of all the nutritional risk factors presented in the questionnaires, only a few may be used to predict iron deficiency, which are intake of fruit juice, soda, cow’s milk more than 2 glass daily and iron-rich food intake less than 5 portions a week. Bogen’s questionnaire showed higher sensitivity of 91.5%, but lower specificity of 29%. Additionally, the questionnaire comprises of a higher number of questions (15 items). Overall, Bogen et al did not recommend the usage of their questionnaire to predict iron deficiency nor iron deficiency anemia. On the other hand, the questionnaire by Boutry et al had an overall higher diagnostic value, showing sensitivity, specificity, PPV and NPV of 71%, 79%, 22% and 97%. 18 However, it is worth noting that the questionnaire was primarily aimed for iron deficiency anemia (defined as hemoglobin of < 11g/dL and MCV < 73 fl). In our study, we aimed to look for a questionnaire capable of predicting iron deficiency before iron deficiency anemia occurs. Hence, we evaluated the Modified NutricheQ Questionnaire for its correlation with iron intake and serum ferritin level. Additionally, our 3-question Modified NutricheQ was evaluated on a population in which the ESR was ≤ 15 mm/hour. In real-life situations, ESR levels may not be readily available, hence its application in real life may pose a different diagnostic value. Addressing this concern, we also assessed the diagnostic values by including subjects with ESR ≥ 15 mm/hour. The AUC was 0.616 with sensitivity, specificity, PPV and NPV of 60.3%, 61.1%, 56.6% and 64.7%, respectively. Lastly, this study was conducted only in Central and East Jakarta due to financial and time limitations, representing only half of the Jakarta population. Hence, we recommend a similar study conducted on a bigger scale, allowing a better representation of the population. To the best of our knowledge, this study is the first to develop a non-invasive method in identifying iron deficiency risk factors in Indonesia. 5 Conclusion The Modified NutricheQ Questionnaire has good validity and reliability in identifying iron deficiency risk factors in the Indonesian population of age 1–3 years old, particularly the 3-question version. Threshold score of 4 provides sensitivity, specificity, PPV and NPV of 80.4%, 67%, 53.8% and 87.7% in predicting iron intake and 71.6%, 61%, 43.6% and 83% in predicting serum ferritin level, respectively. It is hoped that this simple and easy-to-use questionnaire will aid health care providers to screen iron deficiency risks in toddlers, allowing them to refer those at risks for confirmatory tests and therefore providing a more targeted and cost-efficient iron deficiency supplementation. Declarations 1 Ethics approval and consent to participate This study adhered to the Declaration of Helsinki and received ethical approval from The Clinical Ethics Committee of Cipto Mangunkusumo National General Hospital (ref-no: 662/H2.F1/ETIK/2013). Written informed consent forms were provided and signed by all participants. 2 Consent for publication Not applicable 3 Availability of data and materials Data is available upon request to the corresponding author’s email. 4 Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships and hereby declare that they have no competing interests. 5 Funding This research received no external funding. 6 Authors’ contributions DRS participated in conceptualization, analysis, methodology and validation; ST participated in conceptualization, analysis and writing of the original draft; KY participated in conceptualization, analysis, and review; AK participated in methodology and review. 7 Acknowledgements The authors would like to acknowledge Vellia Justian (Faculty of Medicine, Universitas Indonesia) for the assistance with this manuscript. 8 Author Affiliations Department of Child Health, Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia Damayanti Rusli Sjarif, Steven Tjia, Klara Yuliarti Department of Community Medicine, University of Indonesia, Jakarta, Indonesia Aria Kekalih References World Health Organization. Worldwide Prevalence of Anemia 1993‒2005: WHO Global Database on Anaemia. WHO. 2008. Available from: https://iris.who.int/bitstream/handle/10665/43894/9789241596657_eng.pdf?sequence=1 Riset Kesehatan Dasar (RISKESDAS) 2007. Badan Penelitian dan Pengembangan Kesehatan, Departemen Kesehatan. 2008. Available from: https://repository.badankebijakan.kemkes.go.id/id/eprint/4378/1/Laporan%20Riset%20Kesehatan%20Dasar%20Nasiona%3B%202007.pdf The Indonesian Crisis Bulletin 2004: Nutrition and health surveillance in urban poor Jakarta, key results from period Dec 1999 - Sep 2003. Hellen Keller International Indonesia. 2004 Guideline: daily iron supplementation in infants and children. Geneva: World Health Organization. 2016 Gatot D, Idjradinata P, Abdulsalam M, Lubis B, Soedjatmiko, Hendarto A, Ringoringo HP, et al. Rekomendasi Ikatan Dokter Anak Indonesia: Suplementasi besi untuk anak. Badan Penerbit IDAI. 2011 Baker RB, Greer FR. The Committee on Nutrition; Diagnosis and Prevention of Iron Deficiency and Iron-Deficiency Anemia in Infants and Young Children (0–3 Years of Age). Pediatrics. 2010; 126 (5): 1040–1050. 10.1542/peds.2010-2576 Sazawal S, Black RE, Ramsan M, Chwaya HM, Stoltzfus RJ, Dutta A, et al. Effects of routine prophylactic supplementation with iron and folic acid on admission to hospital and mortality in preschool children in a high malaria transmission setting: community-based, randomised, placebo-controlled trial. Lancet. 2006;367:133-43. Idjradinata P, Watkins W, Pollitt E. Adverse effect of iron supplementation on weight gain of iron-replete young children. Lancet. 1994;343:1252–4. Dewey KG, Domello M, Cohen RJ, Rivera LL, Hernell O, and Lonnerdal B. Iron Supplementation Affects Growth and Morbidity of Breast-Fed Infants: Results of a Randomized Trial in Sweden and Honduras. J Nutr. 2002;132:3249-55. Majumdar I, Paul P, Talib VH, Ranga S. The effect of iron therapy on the growth of iron-replete and iron-deplete children. J Trop Pediatr. 2003;49:84-8. Sjarif DR, Yuliarti K. Survey awal pola makan anak batita menurut kuesioner adopsi NutricheQ . Unpublished Manuscript. 2011 Sjarif DR, Yuliarti K, Tjia S, Kekalih A. Validasi kuesioner NutricheQ Modifikasi: sebuah penelitian pendahuluan. Unpublished Manuscript. 2012 Jäger L, Rachamin Y, Senn O, Burgstaller JM, Rosemann T, Markun S. Ferritin cutoffs and diagnosis of iron deficiency in primary care. JAMA Netw Open. 2024 Aug 1;7(8):e2425692. Mantadakis E. Serum ferritin threshold for iron deficiency screening in one-year-old children. J Pediatr. 2022 Jun;245:12–4. Tambing DI, Sjarif DS. The impact of growing-up milk consumption on serum ferritin levels compared to UHT milk consumption in children aged 18-36 months. Jakarta: Fakutlas Kedokteran Universitas Indonesia. 2013 Bogen DL, Duggan AK, Dover GJ, Wilson MH. Screening for iron deficiency anemia by dietary history in a high-risk population. Pediatr. 2000;105:1254-9. Gibbons H, McNulty BA, Rice N, Gibney MJ, Nugent AP. Validation and reliability of the preschooler’s nutrition screening tool; NutricheQ. Proc Nutr Soc. 2012;71(OCE3). Boutry M, Needlman R. Screening for iron deficiency by dietary history in a high-risk population. Pediatr. 2001;108:823. Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial1ModifiedNutricheQforIronIntakeinIndonesianPopulationIndonesianVersion.docx SupplementaryMaterial2ModifiedNutricheQforIronIntakeinIndonesianPopulationTranslatedVersion1.docx 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. 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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-6566656","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":461228044,"identity":"640c8ac2-fcf7-4136-b966-859cb8d49622","order_by":0,"name":"Damayanti Rusli Sjarif","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACHjYIzcaQwHDgA4jBToqWgzNADGZitTAAtTDzgGhCWgzOHEtgLtyxjYGPPfnhYZtf2+T5mBkYP3zMwaPlbNsB5plnbjOw8TwzOJzbd9uwjZmBWXLmNjxazrM3MPO2AbVIJAC19NxmBGphY+YlTkv6h8OWPbftCWsBOQyiJcfgMMOP24kEtUgCvX+Y98xtHjaeNwUHextuJ7cxMzbj9QvfmTTDx7w7bsvJt6dv/vDjz23b+e3NBz98xKMFBA4wNjCAY4SBsQ1MNuBXj6rmD2HFo2AUjIJRMPIAAEs6UFfMkpktAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Child Health, Dr Cipto Mangunkusumo National General Hospital, Faculty of Medicine, Universitas Indonesia","correspondingAuthor":true,"prefix":"","firstName":"Damayanti","middleName":"Rusli","lastName":"Sjarif","suffix":""},{"id":461228045,"identity":"b286ece6-496b-41c6-8ced-c7725e2551c9","order_by":1,"name":"Steven Tjia","email":"","orcid":"","institution":"Department of Child Health, Dr Cipto Mangunkusumo National General Hospital, Faculty of Medicine, Universitas Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Steven","middleName":"","lastName":"Tjia","suffix":""},{"id":461228048,"identity":"32cf47b0-5f37-4c00-8739-eb986518f9cc","order_by":2,"name":"Klara Yuliarti","email":"","orcid":"","institution":"Department of Child Health, Dr Cipto Mangunkusumo National General Hospital, Faculty of Medicine, Universitas Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Klara","middleName":"","lastName":"Yuliarti","suffix":""},{"id":461228051,"identity":"83f6d3ac-0002-4090-aecd-b6e50293c527","order_by":3,"name":"Aria Kekalih","email":"","orcid":"","institution":"Department of Community Medicine, Faculty of Medicine, University of Indonesia","correspondingAuthor":false,"prefix":"","firstName":"Aria","middleName":"","lastName":"Kekalih","suffix":""}],"badges":[],"createdAt":"2025-04-30 16:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6566656/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6566656/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83514493,"identity":"47ebc4ec-65f5-48f9-b89d-c1b580d77783","added_by":"auto","created_at":"2025-05-27 17:53:46","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":20055,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.3\u003c/strong\u003e Flow diagram for inclusion and exclusion in laboratorial result analysis.\u003cbr\u003e\n*Subjects who were excluded due to ESR \u0026gt; 15mm/hour. \u003cbr\u003e\n҂Subjects who were excluded due to non-iron-deficient anemia\u003c/p\u003e","description":"","filename":"3.3.png","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/fdc401fa4b50101ee98400ae.png"},{"id":83514496,"identity":"1b4d7068-0020-451f-8656-16662436d319","added_by":"auto","created_at":"2025-05-27 17:53:46","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":60702,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.5.\u003c/strong\u003e Total of the modified NutricheQ score compared to iron intake.\u003c/p\u003e","description":"","filename":"3.5.png","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/1db815cb4c1c1048645e71df.png"},{"id":83514497,"identity":"aaa8578a-d32e-47d8-a900-cdeec84da8c7","added_by":"auto","created_at":"2025-05-27 17:53:46","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":76134,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.7.1 \u003c/strong\u003eComparison of AUCs of the selected 3 questions and 5 questions in predicting iron intake.\u003c/p\u003e","description":"","filename":"3.7.1.png","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/7f2859b80a3fca8d449dffe5.png"},{"id":83514498,"identity":"b37c3df9-f21e-4c8a-afdf-5ad2611bd52b","added_by":"auto","created_at":"2025-05-27 17:53:46","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":83570,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3.7.2 \u003c/strong\u003eComparison of AUCs of the selected 3 questions and 5 questions in predicting serum ferritin level.\u003c/p\u003e","description":"","filename":"3.7.2.png","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/338ea30db54e515240a588e1.png"},{"id":85496586,"identity":"449dc8d6-1792-40f7-bb58-cc00df439cad","added_by":"auto","created_at":"2025-06-26 13:54:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1505661,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/6cc850a8-baab-498b-97e3-c02bed0d6efe.pdf"},{"id":83514919,"identity":"d750cb53-1cdc-4ef1-9139-c0c0dc75cf92","added_by":"auto","created_at":"2025-05-27 18:01:46","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":14101,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial1ModifiedNutricheQforIronIntakeinIndonesianPopulationIndonesianVersion.docx","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/fdf38c7a6249297648c688e4.docx"},{"id":83514495,"identity":"14a1eed3-d9f4-4428-a9ce-f20973e99f54","added_by":"auto","created_at":"2025-05-27 17:53:46","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14294,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterial2ModifiedNutricheQforIronIntakeinIndonesianPopulationTranslatedVersion1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6566656/v1/0284a6109e7ac3328c76ef00.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing Treatment Precision: Evaluating The Validity and Reliability of Modified NutricheQ in Detecting Iron Deficiency in Children Aged 1-3 Years in Indonesia","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eIron deficiency anemia remains one of the most significant global health problems in both developed and developing countries. The prevalence of pediatric anemia in Southeast Asia is 65.5%, equivalent to approximately 115.3\u0026nbsp;million children.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e First national data from Indonesia showed a prevalence of 40\u0026ndash;45% in children aged 1\u0026ndash;5 years old in the year 2007, with even higher rates in rural areas, reaching 75\u0026ndash;76%.\u003csup\u003e2,3\u003c/sup\u003e As recommended by the World Health Organization (WHO), iron supplementation is deemed necessary when the national prevalence reaches 40%.\u003csup\u003e4\u003c/sup\u003e Consequently, the Indonesian Pediatric Society recommends iron supplementation for all children, prioritizing those aged 0\u0026ndash;5 years without the need for prior screening.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e The American Academy of Pediatrics (AAP), on the other hand, recommends all babies to be screened and tested to determine Hb concentration by the age of 12 months, with decisions regarding iron supplementation made based on various factors, including exclusive breastfeeding status and the composition of complementary feeding.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhilst iron supplementation without prior screening provides practical benefits, it is important to acknowledge that iron is a potent pro-oxidant which may lead to the formation of free radicals. Some health problems that may rise due to inappropriate iron supplementations are growth problems, increased infection risk, as well as increased mortality and morbidity in malaria endemic areas.\u003csup\u003e\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e However, confirming iron status needs facilities and funds that may not be available in many areas of developing countries, such as Indonesia. Therefore, the usage of a valid and reliable questionnaire to screen for iron deficiency prior to blood tests can be beneficial to such a population, requiring less funds. In 2010, the NutricheQ questionnaire was developed in Ireland to identify micronutrient deficiency risk factors and dietary imbalances. The questionnaire was tested for its validity by Sjarif in 2011 for the Indonesian population and was found invalid due to the terms used as well as the significant difference in the Indonesian diet from European.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Sjarif then modified the questionnaire according to the Indonesian diet.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e However, the modified NutricheQ has yet to be tested for its validity and correlation with iron intake and ferritin levels, which are the two parameters that provide insight towards adequacy of dietary iron intake and iron storage; often reflecting the state of iron deficiency before anemia occurs.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e Hence, this study aims to test the validity and reliability of modified NutricheQ in identifying iron intake and ferritin levels as iron deficiency risk factors in the Indonesian population.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted in two steps. The first step validated the Modified NutricheQ Questionnaire as a screening tool for iron deficiency anemia and the second step tested the correlation of the questionnaire towards iron intake and ferritin levels, aimed to find the score threshold which gives the best diagnostic value. This study adhered to the Declaration of Helsinki and received ethical approval from The Clinical Ethics Committee of Cipto Mangunkusumo National General Hospital (ref-no: 662/H2.F1/ETIK/2013). Written informed consent forms were provided and signed by all participants.\u003c/p\u003e \u003cp\u003eThe modified NutricheQ Questionnaire consists of 5 questions, which were modified from the iron-intake related section of the original 12-question NutricheQ questionnaire. The 5 question item included questions on the frequency of formula milk (growing-up milk) intake, chicken or beef liver intake, red meat intake, red-meat based food intake, and egg intake. Each question is scored on a scale of 0 to 2, where a score of 0 indicates higher intake/portion and a score of 2 indicates lower intake/portion (see Supplementary Materials 1 and 2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study population\u003c/h2\u003e \u003cp\u003eThis study took place in 5 integrated service posts (Posyandu) across East and Central Jakarta. Data is sampled from December 2013 to January 2014. The target population for this study is children aged 1\u0026ndash;3 years old who fulfilled the inclusion and exclusion criteria. The inclusion criteria were children aged 1\u0026ndash;3 years whose parents are literate (able to read and write), permanently reside in Jakarta, and agreed to participate in the study. Children who were severely undernourished, suspected or diagnosed with thalassemia, on a routine iron supplementation of minimal 2 weeks prior participating, erythrocyte sedimentation rate of more than 15 mm, as well as children with acute or chronic infection and history of recent blood transfusion (1 month prior study) were excluded from this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sample size determination and sampling method\u003c/h2\u003e \u003cp\u003eSample size of this study was determined using the 10% rule. As this study was a part of a bigger study of the same questionnaire which included all 12 questions, the sample size was determined by the following formula:\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;12x(10\u0026ndash;15)\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;120\u0026ndash;180 subjects x 1,3*\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;234 subjects\u003c/p\u003e \u003cp\u003e*Dropout rate took into consideration the estimated subjects with ESR\u0026thinsp;\u0026gt;\u0026thinsp;15 mm/hour to be 30%\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe researchers rounded up the sample size to 300 subjects which were then recruited in integrated service posts.\u003c/p\u003e \u003cp\u003eThe integrated service posts were selected using stratified random sampling, while subjects were recruited through consecutive sampling until the minimum required sample of 300 subjects was achieved. For the validity, reliability, and correlation tests, subjects were sampled consecutively, with a total of 30 subjects for the validity and reliability tests and 60 subjects for the correlation test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Study timeline and procedures\u003c/h2\u003e \u003cp\u003eAll interviewers and dieticians involved in this study received prior training. All parents or guardians with children aged 1\u0026ndash;3 years were given explanations on the purpose, procedures, benefits and risks of this study. Prospective subjects who fulfilled the inclusion and exclusion criteria were recruited.\u003c/p\u003e \u003cp\u003ePeripheral blood was collected from consenting subjects for hematological profiles and serum ferritin level analyses. All samples underwent processing using consistent machines and techniques. Hematological profiles were analyzed using ADVIA 2120 through flow cytometry, and serum ferritin levels were analyzed using Immulite 2000 through immunochemiluminescent methods. Subjects with erythrocyte sedimentation rates (ESR)\u0026thinsp;\u0026ge;\u0026thinsp;15mm/hour were excluded from the analysis.\u003c/p\u003e \u003cp\u003eAdditionally, dietary analysis was conducted for all subjects, involving parents who were asked to maintain a food diary detailing all consumed items over a 72-hour period (2 weekdays and 1 weekend) following the meeting. All parents and/or caregivers received training on maintaining a food diary from the research team. The food diaries were subsequently evaluated and analyzed by dieticians using the NutriSurvey 2007 software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Data analysis\u003c/h2\u003e \u003cp\u003eData analysis was conducted using the SPSS software. Validity was tested using Spearman correlation test. Internal consistency was measured using Cronbach\u0026rsquo;s alpha and inter-rater reliability was assessed using Cohen\u0026rsquo;s kappa. The questionnaire\u0026rsquo;s level of agreement for iron intake and ferritin level was determined using Pearson correlation test. Diagnostic test was determined using the receiver operating characteristic (ROC) area under the curve. Sensitivity, specificity, positive predictive value, and negative predictive value were also presented in this study.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 \u0026nbsp; \u0026nbsp; Validity and reliability of the modified NutricheQ questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, internal consistency was assessed by calculating the Cronbach\u0026rsquo;s alpha for the questionnaire. Cronbach\u0026apos;s alpha was 0,208. Inter-rater reliability was found to have Cohen\u0026rsquo;s kappa of 0,4-1. Spearman correlation test showed all questions to be \u0026gt;0,3, except for the question on red meat intake.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.1.1 Internal validity dan reliability of modified \u003cem\u003eNutricheQ*,**\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"511\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 296px;\"\u003e\n \u003cp\u003eQuestion Item\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 215px;\"\u003e\n \u003cp\u003eCorrelation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 296px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003e0,605 (p\u0026le;0,005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 296px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003e0,379 (p\u0026le;0,005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 296px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003e0,233 (p\u0026le;0,005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 296px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003e0,550 (p\u0026le;0,005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 296px;\"\u003e\n \u003cp\u003ePortion of chicken, duck, or quail eggs consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 215px;\"\u003e\n \u003cp\u003e0,531 (p\u0026le;0,005)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e*\u003c/strong\u003eData was calculated using \u003cem\u003eSpearman correlation test and Cronbach\u0026rsquo;s alpha\u0026nbsp;\u003c/em\u003eof 0,208. Correlation coefficient was significant if \u0026ge;0,3.\u003c/p\u003e\n\u003cp\u003e**Question item has been translated into English for readers\u0026rsquo; understanding. Readers may find the original version (Bahasa Indonesia) in Supplementary Materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTabel 3.1.2. Inter-rater reliability of the Modified \u003cem\u003eNutricheQ\u003c/em\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"591\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eQuestion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 357px;\"\u003e\n \u003cp\u003e\u003cem\u003eKappa Score\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eRater 1-control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003eRater 2-control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eFrequency of red-meat based food consumption in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003ePortion of chicken, duck, or quail eggs consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 216px;\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eKappa: \u0026lt; 0 = no agreement, 0,01-0,2 = slight agreement, 0,21-0,4 = fair agreement 0,41-0,6 = moderate agreement, 0,61-0,8 = substantial agreement, 0,81-0,99 = near perfect agreement, 1 = perfect agreement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 \u0026nbsp; \u0026nbsp; Demographics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 60 healthy children between the age of 1-3 years from each PHCs participated in this study, resulting in a total of 300 subjects. The average age in the study population was 24.1 months. 47% were male and 53% were female. Majority of the subjects had normal nutritional status.\u003c/p\u003e\n\u003cp\u003eMajority of the parents\u0026rsquo; education status were high school and had middle-to-low income (56%), with 67.3% of the respondents\u0026rsquo; mothers were stay-at-home mothers. Clinical characteristics of the study subject may be found in Table 3.2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.2. Demographics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"491\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=300(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eAge (month)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e24.1\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e141 (47%)\u003c/p\u003e\n \u003cp\u003e159 (53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eDelivery method\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Spontaneous/vaginal birth \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Cesarian section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e278 (81%)\u003c/p\u003e\n \u003cp\u003e57(19%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eNutritional status\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Undernutrition\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Normal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Overweight\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Obese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e12 (4%)\u003c/p\u003e\n \u003cp\u003e264 (88%)\u003c/p\u003e\n \u003cp\u003e9 (3%)\u003c/p\u003e\n \u003cp\u003e15 (5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eFather\u0026rsquo;s age (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e32\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eFather\u0026rsquo;s education level\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Primary school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Middle school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;High school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Academy or University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e20 (6.7%)\u003c/p\u003e\n \u003cp\u003e47 (15.7%)\u003c/p\u003e\n \u003cp\u003e198 (66%)\u003c/p\u003e\n \u003cp\u003e35 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s age (year)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e28,8\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s education level\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Primary school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Middle school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;High school\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Academy or University\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e27 (9%)\u003c/p\u003e\n \u003cp\u003e69 (23%)\u003c/p\u003e\n \u003cp\u003e185 (61.7%)\u003c/p\u003e\n \u003cp\u003e19 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eMother\u0026rsquo;s employment status\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; Self-employed\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; State official\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; Private employee\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; Laborer\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; Stay-at-home\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26 (8.7%)\u003c/p\u003e\n \u003cp\u003e2 (0.7%)\u003c/p\u003e\n \u003cp\u003e61 (20.3%)\u003c/p\u003e\n \u003cp\u003e9 (3%)\u003c/p\u003e\n \u003cp\u003e202 (67.3%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 297px;\"\u003e\n \u003cp\u003eFamily economic status\u003c/p\u003e\n \u003cp\u003e● Low\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Middle-low\u003c/p\u003e\n \u003cp\u003e● \u0026nbsp; \u0026nbsp;Middle-high\u003c/p\u003e\n \u003cp\u003e● High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 194px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18 (6%)\u003c/p\u003e\n \u003cp\u003e168 (56%)\u003c/p\u003e\n \u003cp\u003e110 (36,7%)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e4 (1,3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Data is presented in mean\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 \u0026nbsp; \u0026nbsp; Peripheral blood analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e74 out of 300 subjects were not included in the questionnaire\u0026rsquo;s analysis for ferritin level due to high ESR levels of \u0026ge;15mm/hour. 11 subjects who had non-iron-deficient anemia were also excluded from analysis. All subjects received explanations on good feeding practices and options of iron-rich diet. Children with iron-deficiency anemia as well as non-iron-deficient anemia were referred to be treated in primary healthcare centers or regional general hospitals.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFlow diagram on subject\u0026rsquo;s inclusion and exclusion into the analysis can be found in Figure 3.3\u003c/p\u003e\n\u003cp\u003eAccording to the peripheral blood and ferritin analysis, subjects can be categorized into 4 groups: normal iron status, iron deficient, iron-deficiency anemia, and non-iron-deficient anemia (Table 3.3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.3.\u003c/strong\u003e Categories of subject according to their iron profile status\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN=226(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eNormal iron profile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e148 (65,5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eIron deficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e34(15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eIron deficiency anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e33 (14,6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003eNon-iron-deficient anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 274px;\"\u003e\n \u003cp\u003e11(4,9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 \u0026nbsp; \u0026nbsp; Modified NutricheQ profile according to responses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e46% of all children consumed growing-up milk more than 600mL daily. While 73.7% and 89.7% only consumed less than 1 portion of liver and red meat weekly, respectively. 42% of subjects consumed around 2 to 4 portions of red-meat-based food and 49.3% consumed more than 5 portions of eggs weekly. Profile of the questionnaire according to responses may be found in Table 3.4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.4.\u0026nbsp;\u003c/strong\u003eQuestionnaire\u0026rsquo;s profile according to responses\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"556\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 320px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 112px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e46.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e14.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e24.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e73.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e2.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e7.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e269\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e89.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e39.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e42.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e18.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 320px;\"\u003e\n \u003cp\u003ePortion of chicken, duck or quail eggs in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e49.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e35.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 49px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 112px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e15.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 \u0026nbsp; \u0026nbsp; The correlation of Modified NutricheQ profile with iron intake\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eQuestions on the intake of growing up milk formula, liver and red meat intake may give an insight on the respondent\u0026rsquo;s iron intake, as seen in the difference of mean iron intake between subjects who had higher intake versus lower intake (Table 3.5.1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.5.1\u003c/strong\u003e. Profile of each question towards iron intake.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"585\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIron intake (mg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e12.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e11.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e22.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e6.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e3.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e21.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e14.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e6.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e18.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e10.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e31.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e11.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e3.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e19.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e5.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e23.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e29.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e21.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u0026nbsp;Portion of chicken, duck or quail eggs in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e9.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e34.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e4.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e31.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e8.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\n \u003cp\u003e5.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e23.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e\n\u003cp\u003eIn order to analyze the correlation between each question item with iron intake, we used Pearson correlation test. The results of the test revealed that only the intake of growing-up milk exhibited a statistically significant correlation (Table 3.5.2). When combined, the total score of the 5-item modified NutricheQ showed a moderate, statistically significant negative correlation with iron intake (r = \u0026ndash;0.397, p \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.5.2\u003c/strong\u003e Correlation score of each question item with iron intake.*\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"570\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2-tailed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 235px;\"\u003e\n \u003cp\u003ePortion of chicken, duck or quail eggs in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e-0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e*\u003c/strong\u003ePearson correlation significant if sig(2-tailed) \u0026le;0,01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 \u0026nbsp; \u0026nbsp; The correlation of Modified NutricheQ profile with serum ferritin\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the profile of each questionnaire\u0026rsquo;s item on ferritin level, questions on the intake of growing up formula, liver, red meat and red-meat-based food showed a promising trend in distinguishing ferritin levels as the score increased (Table 3.6.1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.6.1.\u003c/strong\u003e Profile of each question towards serum ferritin levels.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"563\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eScore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 243px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSerum ferritin (ng/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 257px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e28.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e83.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e22.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e2.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e64.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e9.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e12.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e56.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e27.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e7.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e9.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e29.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e21.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e61.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e19.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e115.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 257px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e27.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e16.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e59.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e16.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e20.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e63.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e19.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e83.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 257px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e80.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e83.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e18.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e17.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e60.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 257px;\"\u003e\n \u003cp\u003ePortion of chicken, duck or quail eggs in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e16.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e83.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e18.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e80.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70px;\"\u003e\n \u003cp\u003e20.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 55px;\"\u003e\n \u003cp\u003e18.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 57px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e63.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;According to Pearson correlation test, question on growing-up milk intake is the only question that has significant correlation with serum ferritin level. When combined, the total score showed a statistically significant correlation with iron intake (r = 0.291, p \u0026lt; 0.01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.6.2\u003c/strong\u003e Correlation score of each question item with serum ferritin.*\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"570\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eQuestion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation coefficient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSig.\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(2-tailed)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003eAmount of growing-up milk intake in a day\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e-0.487\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003ePortion of chicken or beef liver consumed in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e-0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003ePortion of red meat consumed in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.904\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003eFrequency of red-meat-based food consumption in a week\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 170px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 271px;\"\u003e\n \u003cp\u003ePortion of chicken, duck or quail eggs in a week\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 129px;\"\u003e\n \u003cp\u003e-0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e*\u003c/strong\u003ePearson correlation significant if sig(2-tailed) \u0026le;0,01\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003e3.7\u0026nbsp; \u0026nbsp; \u0026nbsp;Threshold score of modified NutricheQ as a tool to predict iron deficiency risk\u0026nbsp;\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study analyzed the threshold scores of the modified NutricheQ as a tool to predict iron deficiency through iron intake and serum ferritin level.\u003c/p\u003e\n\u003cp\u003eWe first identified the threshold score of the modified NutricheQ to predict the risk if inadequate iron intake (\u0026lt;7 mg/day) by calculating the area under the receiver operating characteristic (ROC) curve (AUC). According to the 5 question items, we found an area of 0.709 (CI 95%: 0.648-0.770).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this questionnaire, the lowest and highest score that can be achieved is 0 and 10, respectively. Through sensitivity and specificity tests, we found an optimal threshold score of 5. Table 3.7.1 presents the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of multiple threshold scores in predicting iron intake.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.7.1\u0026nbsp;\u003c/strong\u003eThreshold scores of the NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting iron intake.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"565\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026ge; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e80.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e48.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e42.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e83.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026ge; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e56.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e70.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e47.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e77.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePPV: positive predictive value. NPV: negative predictive value\u003c/p\u003e\n\u003cp\u003eIn regard to serum ferritin level, the AUC was 0.598 (CI 95%: 0.514-0.682). The score 5 showed better diagnostic test results compared to the other prospective threshold (Table 3.7.2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.7.2\u0026nbsp;\u003c/strong\u003eThreshold scores of the NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting serum ferritin level.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"565\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e73,1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e43,4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e35,3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e79,3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e49,3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e67,3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e38,8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 102px;\"\u003e\n \u003cp\u003e75,9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTaking into account the trend in the question item on growing-up milk, liver and red meat consumption, we further analyzed the 3 questions. The total score of the questionnaire in relation to iron intake and ferritin level still showed moderate to strong correlation, with each correlation coefficient to be -0.527 and -0.41, sig(2-tailed) \u0026lt;0.01, respectively.\u003c/p\u003e\n\u003cp\u003eThe AUC of the 3 selected questions on iron intake was higher compared to the complete, 5-question Modified NutricheQ Questionnaire: 0.768 (CI 95%: 0.712-0.825) (Figure 3.7.1).\u003c/p\u003e\n\u003cp\u003eThe lowest and higher scores of the 3 questions were 0 and 6, respectively. We found an optimal threshold score of 4, which provided sensitivity, specificity, PPV and NPV of 90.4%, 67%, 53.8% and 87.7%. (Table 3.7.3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.7.3\u0026nbsp;\u003c/strong\u003eThreshold scores of the 3 selected questions in the modified NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting iron intake.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e7.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e34.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e100.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e95.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e23.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e37.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e92.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e80.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e67.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e53.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e87.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe diagnostic tests of the 3 questions were also higher in predicting ferritin levels compared to the 5 questions, showing an AUC of 0.682 (CI 95%: 0.597-0.758) (Figure 3.7.2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe optimal threshold score with the best diagnostic value for the 3 questions in predicting serum ferritin level is also 4, presenting a sensitivity, specificity, PPV and NPV of 71.6%, 61.5%, 45.7% and 82.7%, respectively (Table 3.7.4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.7.4\u0026nbsp;\u003c/strong\u003eThreshold scores of the 3 selected questions in the modified NutricheQ questionnaire and its sensitivity, specificity, PPV, and NPV in predicting serum ferritin level.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePPV (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNPV(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e95,5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e4,4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e29,6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e88.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e17.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e31.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e77.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 104px;\"\u003e\n \u003cp\u003e\u0026ge; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 122px;\"\u003e\n \u003cp\u003e71,6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e61,5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 103px;\"\u003e\n \u003cp\u003e45,7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e82,7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThe NutricheQ Questionnaire has long been recognized as a valuable tool to help health care providers in detecting nutritional risks in toddlers, encompassing risks related to macronutrient and micronutrient deficiency as well as poor feeding behavior. The original questionnaire has 4 question items that were correlated to iron intake: age and amount of cow\u0026rsquo;s milk or formula milk intake, meat or oily fish intake, and fortified cereal intake.\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Due to the difference in dietary habits in Indonesia, the questionnaire was found to be inapplicable. Hence, Sjarif modified the questionnaire to better align with the Indonesian population, consisting of question items on formula milk intake, red meat intake, liver intake, red-meat-based food intake and egg intake, as well as providing more understandable terms to describe the portion, based on familiar measurements used by the population.\u003c/p\u003e \u003cp\u003eIn our study, the Modified NutricheQ Questionnaire has shown to be a valid and reliable tool in assessing iron deficiency risks in toddlers. Most questions exhibited correlation coefficients exceeding 0.3, indicating validity. However, the questionnaire's reliability, measured by Cronbach\u0026rsquo;s alpha, was 0.208, lower than the study in Ireland, which reported 0.4.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Neither the modified nor the original NutricheQ Questionnaire achieved the desired reliability threshold of \u0026gt;\u0026thinsp;0.6. This discrepancy may be attributed due to the difference in the number of questions. The Modified NutricheQ Questionnaire comprises only 5 questions, while the NutricheQ Questionnaire has 18, allowing for a broader assessment beyond iron deficiency risk factors. Nevertheless, the Modified NutricheQ Questionnaire demonstrated a fair to perfect agreement in inter-rater reliability, with a Cohen\u0026rsquo;s kappa score of 0.4-1.\u003c/p\u003e \u003cp\u003eAmongst all questions in the Modified NutricheQ Questionnaire, only the question on growing-up milk showed statistical significance in its relationship with iron intake. This may be attributed to the question's design, which directly asks respondents for the daily volume in milliliters, potentially reducing recall bias. Even though the questions on liver and red meat consumption weren\u0026rsquo;t statistically significant, the question utilized a relatively more objective measurement unit compared to other questions. For instance, the questionnaire used a matchbox to describe the portion of red meat, aiding respondents in visualizing their intake accurately. However, red-meat based food, such as sausages, meatballs, and meatloaf, have various unstandardized portions, posing a limitation. Similarly, while eggs are easy to quantify, many mothers prepare eggs alongside other ingredients and often feed multiple children from the same plate at the same time. This may lead to inaccuracies in recalling the amount of egg consumed by a single toddler.\u003c/p\u003e \u003cp\u003eLikewise, only the question on growing-up milk has statistical significance in its relation to ferritin levels. However, relying solely on a single question about formula milk consumption to predict iron deficiency would not be able to accommodate children with dietary habits of consuming iron-rich foods without formula milk.\u003c/p\u003e \u003cp\u003eThe area under the ROC curve for the Modified NutricheQ associated with iron intake and serum ferritin are 0.709 and 0.598, respectively. Threshold score of 5 resulted in optimal sensitivity of 80.4% and optimal specificity of 48.3% when correlated to iron intake. On the other hand, when correlated to serum ferritin, optimal sensitivity and specificity were 73.1% and 43.4%. Ideally, a screening tool should have both sensitivity and specificity of at least 80%.\u003c/p\u003e \u003cp\u003eConsidering the consistent trend among 3 questions (formula milk intake, liver intake and red meat intake), we conducted a further analysis on the AUC of the 3 questions and compared it to the 5-question set. The 3 questions presented a better result, with an AUC of 0.768 when associated with iron intake and 0.678 with serum ferritin level. Furthermore, the significance of their correlation coefficients were also preserved. The 3-question set showed an optimal threshold score of 4, presenting with sensitivity and specificity of 80.4% and 67% in predicting iron intake and 71.6% and 61% in predicting serum ferritin level. Summary of the diagnostic tests of the 3 questions and 5 questions may be found in Table\u0026nbsp;\u003cspan refid=\"Tab13\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of diagnostic tests performed in this study for the Modified NutricheQ Questionnaire.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOption\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePPV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNPV (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIron intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 questions\u003c/p\u003e \u003cp\u003e3 questions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,709\u003c/p\u003e \u003cp\u003e0,768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80.4\u003c/p\u003e \u003cp\u003e80,4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.3\u003c/p\u003e \u003cp\u003e67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.6\u003c/p\u003e \u003cp\u003e53.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e83.8\u003c/p\u003e \u003cp\u003e87,7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum ferritin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 questions\u003c/p\u003e \u003cp\u003e3 questions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0,598\u003c/p\u003e \u003cp\u003e0,678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73,1\u003c/p\u003e \u003cp\u003e71,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43,4\u003c/p\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e35,3\u003c/p\u003e \u003cp\u003e43,6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79,3\u003c/p\u003e \u003cp\u003e83,6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThreshold score for 5-question questionnaire was \u0026ge;\u0026thinsp;5\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eThreshold score for 3-question questionnaire was \u0026ge;\u0026thinsp;4\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen compared to the questionnaire developed by Bogen et al\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, out of all the nutritional risk factors presented in the questionnaires, only a few may be used to predict iron deficiency, which are intake of fruit juice, soda, cow\u0026rsquo;s milk more than 2 glass daily and iron-rich food intake less than 5 portions a week. Bogen\u0026rsquo;s questionnaire showed higher sensitivity of 91.5%, but lower specificity of 29%. Additionally, the questionnaire comprises of a higher number of questions (15 items). Overall, Bogen et al did not recommend the usage of their questionnaire to predict iron deficiency nor iron deficiency anemia.\u003c/p\u003e \u003cp\u003eOn the other hand, the questionnaire by Boutry et al had an overall higher diagnostic value, showing sensitivity, specificity, PPV and NPV of 71%, 79%, 22% and 97%.\u003csup\u003e18\u003c/sup\u003e However, it is worth noting that the questionnaire was primarily aimed for iron deficiency anemia (defined as hemoglobin of \u0026lt;\u0026thinsp;11g/dL and MCV\u0026thinsp;\u0026lt;\u0026thinsp;73 fl). In our study, we aimed to look for a questionnaire capable of predicting iron deficiency before iron deficiency anemia occurs. Hence, we evaluated the Modified NutricheQ Questionnaire for its correlation with iron intake and serum ferritin level.\u003c/p\u003e \u003cp\u003eAdditionally, our 3-question Modified NutricheQ was evaluated on a population in which the ESR was \u0026le;\u0026thinsp;15 mm/hour. In real-life situations, ESR levels may not be readily available, hence its application in real life may pose a different diagnostic value. Addressing this concern, we also assessed the diagnostic values by including subjects with ESR\u0026thinsp;\u0026ge;\u0026thinsp;15 mm/hour. The AUC was 0.616 with sensitivity, specificity, PPV and NPV of 60.3%, 61.1%, 56.6% and 64.7%, respectively.\u003c/p\u003e \u003cp\u003eLastly, this study was conducted only in Central and East Jakarta due to financial and time limitations, representing only half of the Jakarta population. Hence, we recommend a similar study conducted on a bigger scale, allowing a better representation of the population.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this study is the first to develop a non-invasive method in identifying iron deficiency risk factors in Indonesia.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe Modified NutricheQ Questionnaire has good validity and reliability in identifying iron deficiency risk factors in the Indonesian population of age 1\u0026ndash;3 years old, particularly the 3-question version. Threshold score of 4 provides sensitivity, specificity, PPV and NPV of 80.4%, 67%, 53.8% and 87.7% in predicting iron intake and 71.6%, 61%, 43.6% and 83% in predicting serum ferritin level, respectively.\u003c/p\u003e \u003cp\u003eIt is hoped that this simple and easy-to-use questionnaire will aid health care providers to screen iron deficiency risks in toddlers, allowing them to refer those at risks for confirmatory tests and therefore providing a more targeted and cost-efficient iron deficiency supplementation.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e1 Ethics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study adhered to the Declaration of Helsinki and received ethical approval from The Clinical Ethics Committee of Cipto Mangunkusumo National General Hospital (ref-no: 662/H2.F1/ETIK/2013). Written informed consent forms were provided and signed by all participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2 Consent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3 Availability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available upon request to the corresponding author’s email.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4 Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships and hereby declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5 Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6 Authors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDRS participated in conceptualization, analysis, methodology and validation; ST participated in conceptualization, analysis and writing of the original draft; KY participated in conceptualization, analysis, and review; AK participated in methodology and review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e7 Acknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to acknowledge Vellia Justian (Faculty of Medicine, Universitas Indonesia) for the assistance with this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e8 Author Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Child Health, Cipto Mangunkusumo National General Hospital, Jakarta, Indonesia\u003c/p\u003e\n\u003cp\u003eDamayanti Rusli Sjarif, Steven Tjia, Klara Yuliarti\u003c/p\u003e\n\u003cp\u003eDepartment of Community Medicine, University of Indonesia, Jakarta, Indonesia\u003c/p\u003e\n\u003cp\u003eAria Kekalih\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Worldwide Prevalence of Anemia 1993‒2005: WHO Global Database on Anaemia. WHO. 2008. Available from: https://iris.who.int/bitstream/handle/10665/43894/9789241596657_eng.pdf?sequence=1\u003c/li\u003e\n\u003cli\u003eRiset Kesehatan Dasar (RISKESDAS) 2007. Badan Penelitian dan Pengembangan Kesehatan, Departemen Kesehatan. 2008. Available from: https://repository.badankebijakan.kemkes.go.id/id/eprint/4378/1/Laporan%20Riset%20Kesehatan%20Dasar%20Nasiona%3B%202007.pdf\u003c/li\u003e\n\u003cli\u003eThe Indonesian Crisis Bulletin 2004: Nutrition and health surveillance in urban poor Jakarta, key results from period Dec 1999 - Sep 2003. Hellen Keller International Indonesia. 2004\u003c/li\u003e\n\u003cli\u003eGuideline: daily iron supplementation in infants and children. Geneva: World Health Organization. 2016\u003c/li\u003e\n\u003cli\u003eGatot D, Idjradinata P, Abdulsalam M, Lubis B, Soedjatmiko, Hendarto A, Ringoringo HP, et al. Rekomendasi Ikatan Dokter Anak Indonesia: Suplementasi besi untuk anak. Badan Penerbit IDAI. 2011\u003c/li\u003e\n\u003cli\u003eBaker RB, Greer FR. The Committee on Nutrition; Diagnosis and Prevention of Iron Deficiency and Iron-Deficiency Anemia in Infants and Young Children (0\u0026ndash;3 Years of Age). Pediatrics. 2010; 126 (5): 1040\u0026ndash;1050. 10.1542/peds.2010-2576\u003c/li\u003e\n\u003cli\u003eSazawal S, Black RE, Ramsan M, Chwaya HM, Stoltzfus RJ, Dutta A, et al. Effects of routine prophylactic supplementation with iron and folic acid on admission to hospital and mortality in preschool children in a high malaria transmission setting: community-based, randomised, placebo-controlled trial. Lancet. 2006;367:133-43.\u003c/li\u003e\n\u003cli\u003eIdjradinata P, Watkins W, Pollitt E. Adverse effect of iron supplementation on weight gain of iron-replete young children. Lancet. 1994;343:1252\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eDewey KG, Domello M, Cohen RJ, Rivera LL, Hernell O, and Lonnerdal B. Iron Supplementation Affects Growth and Morbidity of Breast-Fed Infants: Results of a Randomized Trial in Sweden and Honduras. J Nutr. 2002;132:3249-55.\u003c/li\u003e\n\u003cli\u003eMajumdar I, Paul P, Talib VH, Ranga S. The effect of iron therapy on the growth of iron-replete and iron-deplete children. J Trop Pediatr. 2003;49:84-8.\u003c/li\u003e\n\u003cli\u003eSjarif DR, Yuliarti K. Survey awal pola makan anak batita menurut kuesioner adopsi \u003cem\u003eNutricheQ\u003c/em\u003e. Unpublished Manuscript. 2011\u003c/li\u003e\n\u003cli\u003eSjarif DR, Yuliarti K, Tjia S, Kekalih A. Validasi kuesioner \u003cem\u003eNutricheQ\u003c/em\u003e Modifikasi: sebuah penelitian pendahuluan. Unpublished Manuscript. 2012\u003c/li\u003e\n\u003cli\u003eJ\u0026auml;ger L, Rachamin Y, Senn O, Burgstaller JM, Rosemann T, Markun S. Ferritin cutoffs and diagnosis of iron deficiency in primary care. JAMA Netw Open. 2024 Aug 1;7(8):e2425692.\u003c/li\u003e\n\u003cli\u003eMantadakis E. Serum ferritin threshold for iron deficiency screening in one-year-old children. J Pediatr. 2022 Jun;245:12\u0026ndash;4.\u003c/li\u003e\n\u003cli\u003eTambing DI, Sjarif DS. The impact of growing-up milk consumption on serum ferritin levels compared to UHT milk consumption in children aged 18-36 months. Jakarta: Fakutlas Kedokteran Universitas Indonesia. 2013\u003c/li\u003e\n\u003cli\u003eBogen DL, Duggan AK, Dover GJ, Wilson MH. Screening for iron deficiency anemia by dietary history in a high-risk population. Pediatr. 2000;105:1254-9.\u003c/li\u003e\n\u003cli\u003eGibbons H, McNulty BA, Rice N, Gibney MJ, Nugent AP. Validation and reliability of the preschooler\u0026rsquo;s nutrition screening tool; NutricheQ. Proc Nutr Soc. 2012;71(OCE3). \u003c/li\u003e\n\u003cli\u003eBoutry M, Needlman R. Screening for iron deficiency by dietary history in a high-risk population. Pediatr. 2001;108:823.\u003c/li\u003e\n\u003c/ol\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":"diet, dietary deficiency, iron deficiency, iron deficiency anemia, nutritional questionnaire, preschooler, NutricheQ, screening","lastPublishedDoi":"10.21203/rs.3.rs-6566656/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6566656/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003cbr\u003e\n \u003c/strong\u003eIron deficiency anemia remains a persistent issue in developing countries, including Indonesia, prompting recommendations for routine iron supplementation. However, supplementation is often provided without prior screening, increasing the risk of unnecessary treatment and potential side effects. Validated, non-invasive screening tools could be especially valuable in these settings. This study aimed to evaluate the validity and reliability of a modified NutricheQ Questionnaire for identifying iron deficiency risk in the Indonesian pediatric population.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003cbr\u003e\n \u003c/strong\u003eA two-step cross-sectional study was conducted among 300 children aged 1–3 years across Jakarta, Indonesia. The first step assessed the validity of the modified NutricheQ Questionnaire, followed by analysing its correlation with dietary iron intake and serum ferritin level. Validity was assessed through Spearman correlation test. Internal consistency was measured using Cronbach’s alpha, and inter-rater reliability was assessed using Cohen’s kappa. Receiver operating characteristic (ROC) analysis was performed to identify optimal threshold scores based on sensitivity, specificity, and area under the curve (AUC).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003cbr\u003e\n \u003c/strong\u003eThe modified questionnaire demonstrated acceptable construct validity, with Spearman correlation coefficients \u0026gt;0.30 for all items except red meat intake. Inter-rater reliability ranged from fair to perfect agreement (Cohen’s kappa: 0.40–1.00). There was moderate correlation with dietary iron intake (r = 0.39, p \u0026lt; 0.01) and serum ferritin levels (r = 0.29, p \u0026lt; 0.01). The 5-question version had an optimal threshold score of 5, yielding a sensitivity of 80.4% and specificity of 48.3% in predicting iron intake; AUC was 0.709 (CI 95%: 0.648-0.770). A shortened 3-question version with a threshold of 4 maintained the same sensitivity (80.4%) and improved specificity (67.0%) for predicting iron intake (AUC = 0.768; 95% CI: 0.712–0.825), with sensitivity of 71.6% and specificity of 61.5% for predicting low serum ferritin (AUC = 0.682; 95% CI: 0.597–0.758).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003cbr\u003e\n \u003c/strong\u003eThe modified NutricheQ Questionnaire demonstrated good validity and reliability for identifying risk factors of iron deficiency in Indonesian children aged 1–3 years. The shortened three-item version, in particular, shows promise as a non-invasive screening tool for use in low-resource settings.\u003c/p\u003e","manuscriptTitle":"Enhancing Treatment Precision: Evaluating The Validity and Reliability of Modified NutricheQ in Detecting Iron Deficiency in Children Aged 1-3 Years in Indonesia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-27 17:53:41","doi":"10.21203/rs.3.rs-6566656/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":"c4c3350d-202d-4d3d-ab2e-2103cb4d959e","owner":[],"postedDate":"May 27th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-26T13:53:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-27 17:53:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6566656","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6566656","identity":"rs-6566656","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}