The Carbohydrate-to-fiber ratio (CFR) is a useful marker of central obesity in patients with type 2 diabetes: a cross-sectional study

The Carbohydrate-to-fiber ratio (CFR) is a useful marker of central obesity in patients with type 2 diabetes: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Carbohydrate-to-fiber ratio (CFR) is a useful marker of central obesity in patients with type 2 diabetes: a cross-sectional study Cuiqi Jing, Haimeng Zhang, Fan Zhang, Xiaoyu xu, Jiajia Ren, Xiaomei Ji, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4072825/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 (1) Background: The carbohydrate-to-fiber ratio (CFR) is an important indicator of dietary carbohydrate quality. However, few studies have focused on obesity in patients with type 2 diabetes. Therefore, the aim of this study was to investigate the association between the CFR and central obesity in type 2 diabetic patients in the community. (2) Methods: This was a cross-sectional study. A general demographic information questionnaire and a semiquantitative food frequency questionnaire were used to investigate the demographic characteristics and dietary intake information of type 2 diabetic patients in the community, and the daily amounts of carbohydrates and dietary fiber were obtained by calculating the carbohydrate-to-fiber ratio (CFR) using Nutrition Calculator (v2.7.3k) software. Participants' CFR was categorized into Q1, Q2, and Q3 groups from high to low. Central obesity was defined as a waist circumference ≥90 cm for men and ≥85 cm for women. (3) Results: The prevalence of central obesity in community-dwelling type 2 diabetic patients was 66.77%. The CFR was associated with waist circumference (r=0.153, p=0.008), insulin (r=0.118, p=0.040), high-density lipoprotein cholesterol (r=-0.126, p=0.028), and diabetes distress (r=0.197, p=0.001). With Q1 as a reference, the CFR was still significantly associated with central obesity in the Q3 after adjusting for variables (OR=2.166, 95% CI: 1.083-4.334). Carbohydrate intake was not associated with central obesity (OR=1.003, 95% CI: 0.998-1.007). The CFR is a stronger protective factor against central obesity than either fiber or carbohydrate alone. (4) Conclusions: A higher CFR leads to increased central obesity in patients with type 2 diabetes. Diets with a low CFR can be recommended for the dietary management of patients with type 2 diabetes. dietary carbohydrate-to-fiber ratio type 2 diabetes central obesity Figures Figure 1 Figure 2 Figure 3 1. Introduction Diabetes mellitus is a major public health problem in China. Studies have shown that 41.0% and 24.3% of diabetes patients are overweight/obese, respectively 1 . Studies have shown that overweight/obese type 2 diabetes patients account for approximately 58.3% of all diabetes patients 2,3 . Obesity and diabetes are closely related, and obesity exacerbates insulin resistance in diabetic patients, increasing the difficulty of blood glucose control, while insulin resistance in diabetic patients further increases the difficulty of weight loss, resulting in a vicious cycle 4 . On the other hand, in centrally obese T2DM patients glucose-lipid metabolism dysfunction and insulin resistance are aggravated due to the abnormal accumulation of abdominal fat, thus increasing the risk of complications. A meta-analysis showed that central obesity increases the risk of all-cause mortality 5 . Studies have shown that central obesity is more closely associated with hypertension, diabetes mellitus, stroke, etc., placing a heavy burden on our healthcare system 6 . Obesity is characterized by a prolonged period of positive energy balance in which energy intake exceeds energy expenditure and excess nutrients accumulate in white adipose tissue (WAT) as triglycerides (TGs). One way to influence the body's metabolism and energy balance is to modulate thermogenic pathways in white adipose tissue (WAT) and brown adipose tissue (BAT) to help control energy expenditure and contribute to weight loss, while environmental factors such as diet, exercise, and sleep can greatly influence energy metabolism 7 . In the management strategy for obesity, weight loss through dietary control is approximately 2–8% 8 . The Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus (2020 Edition) recommend that the weight loss goal for adult patients with overweight/obese T2DM be a 5–10% reduction in body weight 3 . In addition, the American Diabetes Association Standards for the Medical Management of Diabetes recommend that dietary, physical activity, and behavioral therapies be initiated in overweight/obese patients with type 2 diabetes to achieve and maintain ≥ 5% weight loss, with greater weight loss providing greater benefit for diabetes prevention and control and cardiovascular risk factor reduction 9 . Carbohydrates, a major source of energy, are a risk factor for obesity. Excessive carbohydrate intake tends to impair glycemic control and increase islet stress. Studies have shown that the effects of reducing carbohydrate intake on weight management remain ambiguous 10 . Dietary fiber, through its physiological properties, reduces the absorption of nutrients in the body and thus provides some weight control 11–13 . In addition, dietary fiber also regulates body weight by influencing the gut microbiota. The gut microbiota can produce a variety of metabolites that affect energy metabolism by regulating nutrient absorption and utilization, regulating appetite, and influencing adipose tissue development and function 7,14 . The mechanisms by which carbohydrates and dietary fiber may have an effect on central obesity (Fig. 2 ) are as follows. Notably the carbohydrate-to-fiber ratio (CFR) has more beneficial effects on human health than individual carbohydrates or fibers 15 , and the dietary CFR provides a more complete picture of a patient's diet 16 . Studies have shown that fiber-rich whole grains can be identified by a CFR of < 10:1 17 . Previous studies have demonstrated the positive role of the CFR in predicting changes in waist circumference 18 . Environmental factors influence obesity by affecting the thermogenic pathways of white adipose tissue, and CFR as a dietary factor may also play an influential role in obesity (Fig. 1 ). However, there are few studies on the relationship between the carbohydrate-to-fiber ratio (CFR) and central obesity in type 2 diabetic patients, and investigations on the relationship between the CFR and central obesity in type 2 diabetes patients are needed to provide more theoretical support. The aim of this study was to investigate the relationship between the CFR and central obesity in type 2 diabetic patients in the community. The study hypothesized that as the CFR increases, central obesity increases in type 2 diabetic patients. 2. Materials and Methods 2.1. Design and Study Participants In this study, community-dwelling T2DM patients > 18 years old (the population of patients diagnosed with diabetes mellitus by the hospital before the survey) in the 2019 Bengbu Community Specialized Disease Database were included as study subjects, and the inclusion criteria were as follows: ① met the diagnostic criteria for diabetes mellitus formulated by the WHO in 1999; ② were aged > 18 years; ③ had clear consciousness and normal communication; ④ and voluntarily participated in this study. The exclusion criteria were as follows: ① acute complications of diabetes mellitus (e.g., diabetic ketoacidosis); ② and serious diseases of other major organs of the body. After excluding 28 T2DM patients with incomplete demographic and dietary information, a total of 304 patients were included in the study. The study was approved by the Ethics Committee of Bengbu Medical College. All the subjects provided informed consent by signing the informed consent form. 2.2. General questionnaires A questionnaire validated by the group's deliberation 19 was used, which included patients' demographic information (gender, age, education level, monthly income), disease-related conditions (including duration of the disease, whether or not they were taking medication, etc.), lifestyle information (level of smoking, alcohol consumption, and physical activity), and psychological information (diabetes pain, stigma of the disease). 2.3. Dietary Survey A validated semiquantitative food frequency questionnaire (FFQ) combined with food forms was used to collect dietary information from patients 19 , including information on staple foods (rice, noodles, etc.), meats (pork, beef, etc.), sugary drinks (beverages such as cola, soy milk, etc.), vegetables, fruits, and pastries and snacks (bread, cream cakes, etc.). 2.4. Carbohydrate-to-fiber ratio The mean daily intake of each food group (g/d or ml/d) and the level of total daily energy intake (kcal/d) were calculated by the investigator using a food calculator. The carbohydrate-to-fiber ratio was calculated by dividing the daily carbohydrate intake (g) by the daily fiber intake (g). 2.5. Central obesity Central obesity, also known as abdominal obesity, refers to the excessive accumulation of fat in the lumbar and abdominal subcutaneous or abdominal visceral organs, the mesentery, around the aorta. The measuring device designated by the Provincial Chronic Disease Prevention and Control Demonstration Area Program was used. When waist circumference was measured, the subject was instructed to breathe quietly, and the examiner used a leather ruler to make a horizontal circle 1 cm above the navel and recorded the measurements in cm. In this study, central obesity was defined as a waist circumference ≥ 90 cm for men and ≥ 85 cm for women according to the Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus 2020 Edition 3 . 2.6. Statistical analysis The data were analyzed using SPSS 26.0. Normally distributed continuous variables are expressed as the mean ± standard deviation, and nonnormally distributed continuous variables are expressed as the median (P25, P75). Categorical variables are expressed as frequencies or percentages. ANOVA or the Pearson chi-squared test was used to assess the statistical significance of the difference between patients with and without central obesity. Spearman's rank correlation coefficient was used to test the relationships between carbohydrate intake, carbohydrate energy/total energy intake, fiber intake, and the CFR with demographic information and biochemical metabolic parameters. The restricted cubic spline (RCS) was plotted using the ggplot2 and rms packages of R software 4.0.2 with nodes assigned at the 5th, 35th, 65th, and 95th percentiles to assess the shape of the relationship between the CFR and central adiposity in patients with T2DM. Binary logistic regression analysis was used to investigate the associations relationship between CFR, carbohydrate intake alone, fiber intake and central obesity in T2DM patients. The two-tailed test level was α = 0.05. 3. Results 3.1. General Characteristics of Participants A total of 304 patients with type 2 diabetes mellitus were included in this study, of whom 203 were centrally obese. Sex, monthly income, and physical activity level were associated with central obesity in patients with type 2 diabetes. Participants with central obesity were more likely to be female, and have a moderate monthly income and low physical activity. Participants with central obesity also had a greater body weight. In addition, type 2 diabetic patients who are centrally obese have worse diabetic pain. There were statistically significant differences between centrally obese and noncentrally obese patients in glycated hemoglobin, diastolic blood pressure, insulin, and triglycerides. In addition, the ratio of carbohydrate to fiber was greater in centrally obese patients than in noncentrally obese patients. (Table 1 ) Table 1 General information, biochemical parameters, and nutritional intake of study subjects with central obesity in patients with type 2 diabetes mellitus central obesity(+) central obesity(-) P 203 101 Age(year) 65.14 ± 8.45 64.30 ± 8.83 0.419 Sex Male 82(40.40%) 53(52.50%) 0.046 Female 121(59.60%) 48(47.50%) Educational degree Primary and below 42(20.70%) 15(14.90%) 0.229 Junior 92(45.30%) 50(49.50%) High School and Junior College 56(27.60%) 24(23.80%) College and above 13(6.40%) 12(11.90%) Monthly income (Yuan) 4000 17(8.40%) 15(14.90%) Alcohol status No 153(75.40%) 72(71.30%) 0.445 Yes 50(24.60%) 29(28.70%) Smoking status No 165(81.30%) 80(79.20%) 0.667 Yes 38(18.70%) 21(20.80%) Taking drugs No 48(23.60%) 32(31.70%) 0.134 Yes 155(76.40%) 69(68.30%) Physical activity level(MET-min/w) 5641.04 ± 2583.34 6723.03 ± 2964.74 0.001 Weight(kg) 70.29 ± 10.58 59.10 ± 8.28 0.000 WC(cm) 97.62 ± 7.82 81.46 ± 7.33 0.000 FPG(mmol/L) 8.64 ± 2.64 8.20 ± 2.26 0.153 HbA1lc(%) 7.65 ± 1.46 7.13 ± 1.53 0.004 Insulin(pmol/L) 69.70(48.90,119.10) 45.10 (28.50,71.40) 0.000 SBP(mmHg) 134.05 ± 15.70 130.85 ± 15.78 0.096 DBP(mmHg) 78.37 ± 9.89 75.93 ± 8.97 0.037 TG(mmol/L) 1.59(1.24,2.39) 1.32(0.89,2.26) 0.009 TC(mmol/L) 4.74 ± 1.02 4.70 ± 1.04 0.757 HDL-c(mmol/L) 1.37 ± 0.28 1.41 ± 0.33 0.272 LDL-c(mmol/L) 2.52 ± 0.69 2.52 ± 0.77 0.976 Energy(kcal) 2086.00(1540.00,2932.00) 2090.00(1548.50,2632.00) 0.476 Protein(g) 87.10(61.10,119.80) 82.80(58.15,109.80) 0.345 Fat(g) 87.00(61.00,117.30) 87.90(66.00,114.65) 0.872 Carbohydrate(g) 248.00(170.90,343.40) 223.10(162.25,302.60) 0.139 Dietary Fiber(g) 13.10(8.20,20.60) 13.60(8.70,23.70) 0.411 CFR 18.52(13.84,23.15) 16.46(11.96,20.50) 0.009 Diabetes pain 34.65 ± 11.98 31.48 ± 10.49 0.024 Sense of shame 13.34 ± 5.65 12.43 ± 5.53 0.182 Note: WC, waist circumference;FPG, fasting plasma glucose; HbA1lc, glycated hemoglobin; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride, TC, total cholesterol; HDL-c, high density lipoprotein cholesterol, LDL-c, low density lipoprotein cholesterol, CFR, Carbohydrate-to-fiber ratio. 3.2. The Carbohydrate-to-fiber ratio and central obesity in patients with type 2 diabetes mellitus There were 203 patients with central obesity, with a higher rate of central obesity in Q3 (37.4%) and the lowest rate of central obesity in Q1 (29.1%). (Table 2 ) Table 2 Prevalence of central obesity in T2DM patients with different carbohydrate to dietary fiber ratios central obesity, n(%) noncentral obesity, n(%) CFR N = 203 N = 101 X 2 p Q1 (≤14.74) 59(29.1%) 43(42.6%) 6.950 0.031 Q2 (14.75–20.63) 68(33.5%) 33(32.7%) Q3 (≥20.64) 76(37.4%) 25(24.8%) 3.3. Correlations between carbohydrate intake, carbohydrate energy intake to total energy intake, fiber intake, the carbohydrate-to-fiber ratio, and blood biochemical indices The results showed no correlation between carbohydrate intake, carbohydrate energy to total energy intake, fiber intake, and age, weight, waist circumference, insulin, triglycerides, and HDL cholesterol. Carbohydrate intake was correlated with sex (r=-0.122, p = 0.034) and monthly income (r = 0.128, p = 0.025); carbohydrate energy to total energy was correlated with sex (r = 0.138, p = 0.016) and diastolic blood pressure (r=-0.127, p = 0.027); Dietary fiber intake was associated with monthly income (r = 0.165, p = 0.004). On the other hand, there was a correlation between the carbohydrate-to-fiber ratio and clinical biochemical metabolic parameters and psychological indicators, including body weight (r = 0.127, p = 0.027), waist circumference (r = 0.153, p = 0.008), insulin (r = 0.118, p = 0.04) and high-density lipoprotein cholesterol (r=-0.126, p = 0.028), and diabetes mellitus pain (r = 0.197, p = 0.001). (Table 3 ) Table 3 Correlation between carbohydrate intake, carbohydrate energy ratio to total energy, dietary fiber intake, carbohydrate to dietary fiber ratio and blood biochemical parameters carbohydrate intake carbohydrate energy ratio to total energy dietary fiber intake CFR r p r p r p r p Age 0.069 0.228 0.107 0.062 0.063 0.276 0.012 0.835 Sex -0.122 0.034 0.138 0.016 -0.066 0.251 -0.076 0.184 Monthly income 0.128 0.025 -0.047 0.416 0.165 0.004 -0.106 0.066 Physical activity level -0.008 0.889 0.034 0.561 0.050 0.387 -0.106 0.065 Weight 0.069 0.230 -0.100 0.083 -0.017 0.767 0.127 0.027 WC 0.066 0.254 0.019 0.738 -0.045 0.431 0.153 0.008 HbA1lc -0.053 0.354 -0.036 0.532 -0.030 0.599 -0.012 0.840 Insulin 0.034 0.558 0.070 0.223 -0.046 0.428 0.118 0.040 DBP 0.041 0.472 -0.127 0.027 0.007 0.901 0.027 0.640 SBP 0.082 0.153 -0.050 0.383 0.080 0.162 -0.052 0.365 TC 0.038 0.509 -0.041 0.477 0.086 0.135 -0.092 0.108 TG -0.016 0.783 -0.014 0.810 -0.054 0.352 0.055 0.341 HDL-C 0.005 0.936 -0.063 0.277 0.090 0.119 -0.126 0.028 LDL-C 0.070 0.222 -0.055 0.336 0.100 0.082 -0.078 0.104 Diabetes pain 0.002 0.972 0.090 0.116 -0.125 0.029 0.197 0.001 Note: WC, waist circumference; HbA1lc, glycated hemoglobin; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride, TC, total cholesterol; HDL-c, high density lipoprotein cholesterol, LDL-c, low density lipoprotein cholesterol, CFR, Carbohydrate-to-fiber ratio. Associations between carbohydrate intake, carbohydrate energy to total energy ratio, fiber intake, and carbohydrate to fiber ratio and demographic information, biochemical metabolic parameters, and psychological indicators were examined using Spearman's rank correlation coefficient. 3.4. Association of Carbohydrate-to-Fiber Ratio with Central Obesity in Patients with Type 2 Diabetes Mellitus Unadjusted multivariate RCS analysis revealed a linear relationship between the continuous variable CFR and central obesity in patients with type 2 diabetes mellitus (Fig. 3). An increased risk of central obesity was observed in patients with type 2 diabetes mellitus when the CFR was > 17.62 (OR > 1). In univariate logistic regression analysis, taking Q1 as the reference group, the carbohydrate-to-fiber ratio was significantly associated with central obesity in patients with type 2 diabetes mellitus in Q3. After adjusting for general demographic information, blood biochemical indices, energy intake, and psychological indices, the CFR was still significantly associated with central obesity in patients with type 2 diabetes mellitus in Q3 (OR = 2.166, 95% CI: 1.083–4.334). Figure 3 Correlation curves between CFR and central obesity in patients with type 2 diabetes . The solid line indicates the estimated risk of central obesity, and the shaded area indicates the 95% confidence interval (CI). In addition, analysis of carbohydrate and fiber alone had no association with central obesity in patients with type 2 diabetes. After adjusting for the same covariates, carbohydrate intake remained unassociated with central obesity in patients with type 2 diabetes mellitus (OR = 1.003, 95%CI: 0.998–1.007). The greater the dietary fiber intake, the lower the rate of central obesity in patients with type 2 diabetes mellitus (OR = 0.956, 95% CI: 0.918–0.994). (Table 4 ). Table 4 Multiple regression analysis of central obesity in T2DM patients Variable Crude Model 1 Model 2 Q1(≤14.74) 1(Ref.) 1(Ref.) 1(Ref.) CFR Q2(14.75–20.63) 1.502(0.847–2.661) 1.606(0.883–2.920) 1.686(0.870–3.268) Q3(≥20.64) 2.216(1.217–4.033)** 2.018(1.080–3.770)* 2.166(1.083–4.334)* carbohydrate 1.001(0.999–1.003) 1.002(1.000-1.004) 1.003(0.998–1.007) dietary fiber 0.989(0.969–1.009) 0.994(0.973–1.016) 0.956(0.918–0.994)* Sex - - 1.867(1.032–3.378)* Monthly income - - - Physical activity level - 1.000(1.000–1.000)** 1.000(1.000–1.000)* Covariates Energy - - 1.000(1.000-1.001)* Diabetes pain - - 1.034(1.007–1.061)* Insulin - - 1.007(1.002–1.013)* HbA1lc - - 1.237(1.019–1.501)* TG - - - DBP - - 1.034(1.004–1.064)* Note: **: p < 0.01; *: p < 0.05; Model 1, adjusted for gender, monthly income, and physical activity level; Model 2, based on Model 1 + insulin, glycosylated hemoglobin, triglycerides, blood pressure, diabetes pain, and total energy.; HbA1lc, glycated hemoglobin; TG, triglyceride; DBP, diastolic blood pressure. 4. Discussion The results of the study showed that the carbohydrate-to-fiber ratio was associated with central obesity in patients with type 2 diabetes. The odds of central obesity in type 2 diabetic patients were significantly greater in the high CFR group than in the low CFR group, which is generally consistent with our study hypothesis. This study showed that the prevalence of central obesity in patients with type 2 diabetes mellitus was 66.78%, a result comparable to that of a study conducted in Shanghai, which was slightly greater 20 . The results showed that compared with noncentrally obese T2DM patients, centrally obese T2DM patients were more likely to be women with low levels of physical activity and moderate monthly incomes. This finding is different from that of our studies 6 , probably due to the age of the women in this study. It has been found that menopausal women experience a decrease in estrogen levels, an increase in circulating androgen levels, changes in sex hormone levels, and alterations in lipid metabolism and endocrine metabolism, which predispose them to changes in body morphology, muscle loss and abdominal obesity 21 . The Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus 2020 Edition states that exercise plays an important role in the comprehensive management of type 2 diabetes mellitus; therefore, increasing the level of physical activity while avoiding hypoglycemic events can increase insulin sensitivity and improve body composition 3 . To achieve ≥ 5% weight loss, the weekly exercise time should be 300 minutes, and the exercise intensity should be moderate-to-vigorous intensity exercise or an exercise energy expenditure of 2000 kcal/week and above 22 . Interestingly, diabetes distress scores were greater in centrally obese individuals with T2DM. Diabetic pain decreases patient adherence, impairs glycemic control 23 , and exacerbates insulin resistance, creating a vicious cycle that affects weight change. The results of this study revealed poor glycemic control and higher insulin levels in patients with high diabetes distress scores. Therefore, community health workers should pay more attention to patients' psychological problems, actively guide patients' misconceptions about diabetes, improve treatment compliance, and promote patients' physical and mental health. The results showed that dietary fiber was protective against diabetic distress (r=-0.125, p = 0.029), carbohydrate intake did not correlate with diabetic distress (r = 0.090, p = 0.116), whereas the CFR was positively associated with diabetic distress (r = 0.197, p = 0.001). Sarah S Makhani et al 16 reported that a higher CFR increased the risk of moderate to severe depression. The gut microbiota and the gut-brain axis are effective psychological intervention pathways, and dietary fiber is well able to modulate the gut microbiota and produce short-chain fatty acids. This may be the reason why dietary fiber plays a protective role against diabetic pain. The CFR was positively correlated with weight (r = 0.127, p = 0.027) and waist circumference (r = 0.153, p = 0.008). This finding is similar to that of the Framingham Offspring Cohort, which revealed that a greater ratio of carbohydrates to fiber was associated with increased waist circumference in adults 18 . In this study, there was no correlation between carbohydrate intake, fiber intake, carbohydrate energy to total energy intake, and insulin and HDL cholesterol. Only the CFR was correlated with insulin (r = 0.118, p = 0.040) and HDL cholesterol (r=-0.126, p = 0.028). This is consistent with the findings of Yoshitaka Hashimoto et al 24 . These finding indicate that the carbohydrate-to-fiber ratio plays an important role in human health. In this study, the risk of central obesity in type 2 diabetic patients was increased (OR > 1) at CFR > 17.62, which is much greater than the 10:1 CFR value of cereals, which have been shown to be healthier 17 , suggesting that type 2 diabetic centrally obese individuals consume excessive low-quality carbohydrates. A higher CFR increased the odds of central obesity in patients with type 2 diabetes (OR = 2.216, 95% CI: 1.217–4.033). After adjusting for variables, we still found that a higher CFR was associated with central obesity in T2DM patients (OR = 2.166, 95% CI: 1.083–4.334). In addition, after adjusting for the same variables, the association between the CFR and central obesity in T2DM patients was stronger than carbohydrate intake (OR = 1.003, 95% CI: 0.998–1.007) and fiber intake (OR = 0.956, 95% CI: 0.918–0.994) alone. In recent years, a number of studies have shown that carbohydrate quality is more beneficial to human health than quantity 25–27 . Studies have shown that high-quality carbohydrates reduce weight gain and are the best recipe for weight control in middle-aged adults 28 . In addition, after adjusting for covariates, we found that diabetes distress increased the odds of central obesity in patients with type 2 diabetes (OR = 1.034, 95% CI: 1.007–1.061). Studies have shown that changes in body size and appearance caused by obesity and its somatic complications, in turn, cause negative psychological feelings such as low self-esteem and self-blame, leading to depressive disorders, and further exacerbating patients' overeating behaviors 29–31 . Prolonged diabetic suffering will aggravate diabetic suffering by causing patients to develop various psychological problems. Psychotherapy can improve the psychological aspects of patients' unhealthy eating habits, leading to better implementation of weight loss dietary programs and behavioral training to achieve weight control and lower BMI and waist circumference. Previous studies have shown that the carbohydrate-to-fiber ratio is effective for identifying high-quality carbohydrates or whole grains 17 . Higher ratios reflect poorer carbohydrate quality and are associated with a greater risk of T2DM 32 and coronary heart disease 33 . Taken together, carbohydrate intake and dietary fiber intake alone cannot accurately reflect the physical and mental health of people, CFR as a dietary quality indicator can more sensitively reflect the physical and mental health of people, and dietary CFR as an indicator to assess the quality of carbohydrates is more easily understood and accepted by the public. 5. Conclusions A higher CFR leads to increased central obesity in patients with type 2 diabetes. Diets with a low CFR can be recommended for the dietary management of patients with type 2 diabetes. Strengths and Limitations The strengths of this study are the focus on the association of carbohydrate-to-fiber ratio (CFR), an indicator of carbohydrate quality, with central obesity in patients with type 2 diabetes, and to include psychological indicators (diabetes distress, disease stigma) to conduct an analysis of the impact on central obesity in patients with type 2 diabetes. A higher CFR was found to be associated with central obesity in patients with type 2 diabetes, reflecting the greater impact of a low-quality carbohydrate diet on central obesity in patients with type 2 diabetes. The limitations of this study must be considered; First, this was a cross-sectional study, and causality could not be established. Second, dietary data were collected by recall using a semiquantitative food frequency questionnaire, which may be subject to recall and self-report bias. Abbreviations T2DM: Type 2 diabetes mellitus WAT：White adipose tissue BAT：Brown adipose tissue TGs：Triglycerides CFR：Carbohydrate-to-fiber ratio FFQ：Food frequency questionnaire WC：Waist circumference FPG：Fasting plasma glucose HbA1c：Glycated hemoglobin SBP：Systolic blood pressure DBP：Diastolic blood pressure TC：Total cholesterol HDL-c：High density lipoprotein cholesterol LDL-c：Low density lipoprotein cholesterol Declarations Availability of data and materials The data presented in this article are available on request from the corresponding author. Acknowledgments We are very grateful to the people with type 2 diabetes in our community who volunteered to participate in this survey. We are equally thankful to the students and teachers who participated in this survey and whose helpful support enabled us to complete this study. Funding Statement This research was funded by the Humanities and Social Sciences Planning Fund of the Ministry of Education (15YJAZH085). Author information Authors and Affiliations School of Public Health, Bengbu Medical University, Bengbu, China Cui-qi Jing, Hai-meng Zhang, Fan Zhang, Xiao-yu Xu, Jia-jia Ren, School of Nursing, Bengbu Medical University, Bengbu, China Xiao-mei Ji Corresponding authors * Correspondence: [email protected] School of Public Health, Bengbu Medical University, Bengbu, China Hong Xie Contributions C.J.: Methodology, Data curation, Formal analysis, and initial draft writing; H.Z.: Data curation, Writing Suggestions; F.Z., X.X., and J.R.: Data curation; X.J.: Data collection and organization; H.X.: Study design, methodology, source, and supervision, Writing-review and editing. Ethics declarations Ethics approval and consent to participate The study was conducted according to the guidelines of the Declaration of Helsinki. The study was approved by the Ethics Committee of Bengbu Medical College [ethical approval number: (2016 )No.015]. All the subjects provided informed consent by signing the informed consent form. Institutional Review Board Statement The study was approved by the Ethics Committee of Bengbu Medical College. Informed Consent Statement Informed consent was obtained from all subjects involved in the study. Data availability statement The data in this study involve privacy issues, and the data should not be shared. Conflicts of interest The authors declare no conflicts of interest. References Hou X, Lu J, Weng J, et al. Impact of Waist Circumference and Body Mass Index on Risk of Cardiometabolic Disorder and Cardiovascular Disease in Chinese Adults: A National Diabetes and Metabolic Disorders Survey. PLoS ONE. 2013;8(3):e57319. 10.1371/journal.pone.0057319 . Ji L, Hu D, Pan C, et al. Primacy of the 3B approach to control risk factors for cardiovascular disease in type 2 diabetes patients. 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Obesity Management for the Treatment of Type 2 Diabetes: Standards of Medical Care in Diabetes-2021. Diabetes Care. 2021;44(Suppl 1):S100–10. 10.2337/dc21-S008 . Landry MJ, Crimarco A, Gardner CD. Benefits of Low Carbohydrate Diets: a Settled Question or Still Controversial? Curr Obes Rep. 2021;10(3):409–22. 10.1007/s13679-021-00451-z . 刘秋艳 连欣悦. 容格清 et al 膳食纤维生理功能研究进展 粮食与食品工业. 2021;28(4):25–8. Dietary fibre and satiety - Slavin – 2007 - Nutrition Bulletin - Wiley Online Library. Accessed July 18. 2023. https://onlinelibrary.wiley.com/doi/ 10.1111/j.1467-3010.2007.00603.x . Cho SS, Qi L, Fahey GC, Klurfeld DM. Consumption of cereal fiber, mixtures of whole grains and bran, and whole grains and risk reduction in type 2 diabetes, obesity, and cardiovascular disease. Am J Clin Nutr. 2013;98(2):594–619. 10.3945/ajcn.113.067629 . Hagberg CE, Spalding KL. White adipocyte dysfunction and obesity-associated pathologies in humans. Nat Rev Mol Cell Biol Published online Dec. 2023;12. 10.1038/s41580-023-00680-1 . Dong Q, Wang L, Hu H, et al. Greater Protection of Lower Dietary Carbohydrate to Fiber Ratio (CFR) against Poor Blood Pressure Control in Patients with Essential Hypertension: A Cross-Sectional Study. Nutrients. 2022;14(21):4443. 10.3390/nu14214443 . Makhani SS, Davies C, George KA, Castro G, de la Rodriguez P, Barengo NC. Carbohydrate-to-Fiber Ratio, a Marker of Dietary Intake, as an Indicator of Depressive Symptoms. Cureus 13(9):e17996. 10.7759/cureus.17996 . Fontanelli M, de Micha M, Sales R, Liu CH, Mozaffarian J, Fisberg D. Application of the ≤ 10:1 carbohydrate to fiber ratio to identify healthy grain foods and its association with cardiometabolic risk factors. Eur J Nutr. 2020;59(7):3269–79. 10.1007/s00394-019-02165-4 . Sawicki CM, Lichtenstein AH, Rogers GT, et al. Comparison of Indices of Carbohydrate Quality and Food Sources of Dietary Fiber on Longitudinal Changes in Waist Circumference in the Framingham Offspring Cohort. Nutrients. 2021;13(3):997. 10.3390/nu13030997 . 谢虹. 社区居民膳食现况与糖尿病的关系研究. 博士. 安徽医科大学; 2020. 10.26921/d.cnki.ganyu.2020.000015 . 王羽洁 柯蒋风, 马艺琳 王俊薇. 李连喜 新诊断2型糖尿病患者尿酸排泄与肥胖及腹型肥胖相关性的研究 中国糖尿病杂志. 2023;31(12):898–902. 李瑾 张培珍. 有氧运动对绝经后女性性激素水平及其与代谢综合征风险因素关系的研究. In: 第十三届全国体育科学大会论文摘要集——专题报告(运动生理与生物化学分会). 中国体育科学学会; 2023:3. 10.26914/c.cnkihy.2023.061886 . 中国超重/肥胖医学营养治疗指南(. 2021). 中国医学前沿杂志(电子版). 2021;13(11):1–55. Bruno BA, Choi D, Thorpe KE, Yu CH. Relationship Among Diabetes Distress, Decisional Conflict, Quality of Life, and Patient Perception of Chronic Illness Care in a Cohort of Patients With Type 2 Diabetes and Other Comorbidities. Diabetes Care. 2019;42(7):1170–7. 10.2337/dc18-1256 . Hashimoto Y, Tanaka M, Miki A, et al. Intake of Carbohydrate to Fiber Ratio Is a Useful Marker for Metabolic Syndrome in Patients with Type 2 Diabetes: A Cross-Sectional Study. Ann Nutr Metab. 2018;72(4):329–35. 10.1159/000486550 . Lloyd-Jones DM, Hong Y, Labarthe D, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association’s strategic Impact Goal through 2020 and beyond. Circulation. 2010;121(4):586–613. 10.1161/CIRCULATIONAHA.109.192703 . Reynolds A, Mann J, Cummings J, Winter N, Mete E, Te Morenga L. Carbohydrate quality and human health: a series of systematic reviews and meta-analyses. Lancet. 2019;393(10170):434–45. 10.1016/S0140-6736(18)31809-9 . Tan D, Drewnowski A, Lê KA. New metrics of dietary carbohydrate quality. Curr Opin Clin Nutr Metab Care. 2023;26(4):358–63. 10.1097/MCO.0000000000000933 . Wan Y, Tobias DK, Dennis KK, et al. Association between changes in carbohydrate intake and long term weight changes: prospective cohort study. BMJ. 2023;382:e073939. 10.1136/bmj-2022-073939 . Wang S, Sun Q, Zhai L, Bai Y, Wei W, Jia L. The Prevalence of Depression and Anxiety Symptoms among Overweight/Obese and Non-Overweight/Non-Obese Children/Adolescents in China: A Systematic Review and Meta-Analysis. Int J Environ Res Public Health. 2019;16(3):340. 10.3390/ijerph16030340 . Rajan TM, Menon V. Psychiatric disorders and obesity: A review of association studies. J Postgrad Med. 2017;63(3):182–90. 10.4103/jpgm.JPGM_712_16 . Guedes EP, Madeira E, Mafort TT, et al. Body composition and depressive/anxiety symptoms in overweight and obese individuals with metabolic syndrome. Diabetol Metab Syndr. 2013;5(1):82. 10.1186/1758-5996-5-82 . Cui Z, Wu M, Liu K, et al. Associations between Conventional and Emerging Indicators of Dietary Carbohydrate Quality and New-Onset Type 2 Diabetes Mellitus in Chinese Adults. Nutrients. 2023;15(3):647. 10.3390/nu15030647 . AlEssa HB, Cohen R, Malik VS, et al. Carbohydrate quality and quantity and risk of coronary heart disease among US women and men. Am J Clin Nutr. 2018;107(2):257–67. 10.1093/ajcn/nqx060 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4072825","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":281804498,"identity":"7d40ccf7-318d-4e1c-a67f-b16379d55305","order_by":0,"name":"Cuiqi Jing","email":"","orcid":"","institution":"Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Cuiqi","middleName":"","lastName":"Jing","suffix":""},{"id":281804499,"identity":"3d1099fe-be09-4608-b5a0-ca9401a73732","order_by":1,"name":"Haimeng Zhang","email":"","orcid":"","institution":"Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haimeng","middleName":"","lastName":"Zhang","suffix":""},{"id":281804502,"identity":"636da56b-82c8-441f-a660-c4a877216ce7","order_by":2,"name":"Fan Zhang","email":"","orcid":"","institution":"Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Zhang","suffix":""},{"id":281804504,"identity":"33481ba1-4456-44bf-a731-ebf18cda014f","order_by":3,"name":"Xiaoyu xu","email":"","orcid":"","institution":"Bengbu Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyu","middleName":"","lastName":"xu","suffix":""},{"id":281804505,"identity":"b7871971-d5ba-47dc-a91c-4ac294f9fe13","order_by":4,"name":"Jiajia Ren","email":"","orcid":"","institution":"Bengbu Medical 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University","correspondingAuthor":true,"prefix":"","firstName":"Hong","middleName":"","lastName":"Xie","suffix":""}],"badges":[],"createdAt":"2024-03-11 10:20:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4072825/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4072825/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":53198323,"identity":"2cb3b578-4c36-4719-844c-0814d7075c03","added_by":"auto","created_at":"2024-03-21 18:44:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":12009,"visible":true,"origin":"","legend":"\u003cp\u003eTheoretical frameworks\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4072825/v1/98a2196b7fd6c3e2237b285e.png"},{"id":53198324,"identity":"1a922f7b-fad5-49e0-ba4c-927640dc3654","added_by":"auto","created_at":"2024-03-21 18:44:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":23013,"visible":true,"origin":"","legend":"\u003cp\u003eCarbohydrate and Dietary Fiber Influence on Central Obesity Mechanisms\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4072825/v1/bff2932174b2e618dc858236.png"},{"id":53198336,"identity":"8ed7a509-5a01-41b7-ac5d-cd1459f460aa","added_by":"auto","created_at":"2024-03-21 18:44:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22447,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCorrelation curves between CFR and central obesity in patients with type 2 diabetes\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eThe solid line indicates the estimated risk of central obesity, and the shaded area indicates the 95% confidence interval (CI).\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4072825/v1/0519372e3452c39d501dc1a2.jpg"},{"id":54497687,"identity":"860a7d7b-8b83-4635-842f-7514bd44d463","added_by":"auto","created_at":"2024-04-11 12:05:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":538989,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4072825/v1/7840f969-5f23-4242-b991-2d5cc7743e01.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Carbohydrate-to-fiber ratio (CFR) is a useful marker of central obesity in patients with type 2 diabetes: a cross-sectional study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDiabetes mellitus is a major public health problem in China. Studies have shown that 41.0% and 24.3% of diabetes patients are overweight/obese, respectively\u003csup\u003e1\u003c/sup\u003e. Studies have shown that overweight/obese type 2 diabetes patients account for approximately 58.3% of all diabetes patients\u003csup\u003e2,3\u003c/sup\u003e. Obesity and diabetes are closely related, and obesity exacerbates insulin resistance in diabetic patients, increasing the difficulty of blood glucose control, while insulin resistance in diabetic patients further increases the difficulty of weight loss, resulting in a vicious cycle\u003csup\u003e4\u003c/sup\u003e. On the other hand, in centrally obese T2DM patients glucose-lipid metabolism dysfunction and insulin resistance are aggravated due to the abnormal accumulation of abdominal fat, thus increasing the risk of complications. A meta-analysis showed that central obesity increases the risk of all-cause mortality\u003csup\u003e5\u003c/sup\u003e. Studies have shown that central obesity is more closely associated with hypertension, diabetes mellitus, stroke, etc., placing a heavy burden on our healthcare system\u003csup\u003e6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eObesity is characterized by a prolonged period of positive energy balance in which energy intake exceeds energy expenditure and excess nutrients accumulate in white adipose tissue (WAT) as triglycerides (TGs). One way to influence the body's metabolism and energy balance is to modulate thermogenic pathways in white adipose tissue (WAT) and brown adipose tissue (BAT) to help control energy expenditure and contribute to weight loss, while environmental factors such as diet, exercise, and sleep can greatly influence energy metabolism\u003csup\u003e7\u003c/sup\u003e. In the management strategy for obesity, weight loss through dietary control is approximately 2\u0026ndash;8%\u003csup\u003e8\u003c/sup\u003e. The Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus (2020 Edition) recommend that the weight loss goal for adult patients with overweight/obese T2DM be a 5\u0026ndash;10% reduction in body weight\u003csup\u003e3\u003c/sup\u003e. In addition, the American Diabetes Association Standards for the Medical Management of Diabetes recommend that dietary, physical activity, and behavioral therapies be initiated in overweight/obese patients with type 2 diabetes to achieve and maintain\u0026thinsp;\u0026ge;\u0026thinsp;5% weight loss, with greater weight loss providing greater benefit for diabetes prevention and control and cardiovascular risk factor reduction\u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCarbohydrates, a major source of energy, are a risk factor for obesity. Excessive carbohydrate intake tends to impair glycemic control and increase islet stress. Studies have shown that the effects of reducing carbohydrate intake on weight management remain ambiguous\u003csup\u003e10\u003c/sup\u003e. Dietary fiber, through its physiological properties, reduces the absorption of nutrients in the body and thus provides some weight control\u003csup\u003e11\u0026ndash;13\u003c/sup\u003e. In addition, dietary fiber also regulates body weight by influencing the gut microbiota. The gut microbiota can produce a variety of metabolites that affect energy metabolism by regulating nutrient absorption and utilization, regulating appetite, and influencing adipose tissue development and function\u003csup\u003e7,14\u003c/sup\u003e. The mechanisms by which carbohydrates and dietary fiber may have an effect on central obesity (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) are as follows. Notably the carbohydrate-to-fiber ratio (CFR) has more beneficial effects on human health than individual carbohydrates or fibers\u003csup\u003e15\u003c/sup\u003e, and the dietary CFR provides a more complete picture of a patient's diet\u003csup\u003e16\u003c/sup\u003e. Studies have shown that fiber-rich whole grains can be identified by a CFR of \u0026lt;\u0026thinsp;10:1\u003csup\u003e17\u003c/sup\u003e. Previous studies have demonstrated the positive role of the CFR in predicting changes in waist circumference\u003csup\u003e18\u003c/sup\u003e. Environmental factors influence obesity by affecting the thermogenic pathways of white adipose tissue, and CFR as a dietary factor may also play an influential role in obesity (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, there are few studies on the relationship between the carbohydrate-to-fiber ratio (CFR) and central obesity in type 2 diabetic patients, and investigations on the relationship between the CFR and central obesity in type 2 diabetes patients are needed to provide more theoretical support.\u003c/p\u003e \u003cp\u003eThe aim of this study was to investigate the relationship between the CFR and central obesity in type 2 diabetic patients in the community. The study hypothesized that as the CFR increases, central obesity increases in type 2 diabetic patients.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Design and Study Participants\u003c/h2\u003e \u003cp\u003eIn this study, community-dwelling T2DM patients\u0026thinsp;\u0026gt;\u0026thinsp;18 years old (the population of patients diagnosed with diabetes mellitus by the hospital before the survey) in the 2019 Bengbu Community Specialized Disease Database were included as study subjects, and the inclusion criteria were as follows: ① met the diagnostic criteria for diabetes mellitus formulated by the WHO in 1999; ② were aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years; ③ had clear consciousness and normal communication; ④ and voluntarily participated in this study. The exclusion criteria were as follows: ① acute complications of diabetes mellitus (e.g., diabetic ketoacidosis); ② and serious diseases of other major organs of the body. After excluding 28 T2DM patients with incomplete demographic and dietary information, a total of 304 patients were included in the study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e The study was approved by the Ethics Committee of Bengbu Medical College. All the subjects provided informed consent by signing the informed consent form.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. General questionnaires\u003c/h2\u003e \u003cp\u003eA questionnaire validated by the group's deliberation \u003csup\u003e19\u003c/sup\u003ewas used, which included patients' demographic information (gender, age, education level, monthly income), disease-related conditions (including duration of the disease, whether or not they were taking medication, etc.), lifestyle information (level of smoking, alcohol consumption, and physical activity), and psychological information (diabetes pain, stigma of the disease).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Dietary Survey\u003c/h2\u003e \u003cp\u003eA validated semiquantitative food frequency questionnaire (FFQ) combined with food forms was used to collect dietary information from patients\u003csup\u003e19\u003c/sup\u003e, including information on staple foods (rice, noodles, etc.), meats (pork, beef, etc.), sugary drinks (beverages such as cola, soy milk, etc.), vegetables, fruits, and pastries and snacks (bread, cream cakes, etc.).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Carbohydrate-to-fiber ratio\u003c/h2\u003e \u003cp\u003eThe mean daily intake of each food group (g/d or ml/d) and the level of total daily energy intake (kcal/d) were calculated by the investigator using a food calculator. The carbohydrate-to-fiber ratio was calculated by dividing the daily carbohydrate intake (g) by the daily fiber intake (g).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Central obesity\u003c/h2\u003e \u003cp\u003eCentral obesity, also known as abdominal obesity, refers to the excessive accumulation of fat in the lumbar and abdominal subcutaneous or abdominal visceral organs, the mesentery, around the aorta. The measuring device designated by the Provincial Chronic Disease Prevention and Control Demonstration Area Program was used. When waist circumference was measured, the subject was instructed to breathe quietly, and the examiner used a leather ruler to make a horizontal circle 1 cm above the navel and recorded the measurements in cm. In this study, central obesity was defined as a waist circumference\u0026thinsp;\u0026ge;\u0026thinsp;90 cm for men and \u0026ge;\u0026thinsp;85 cm for women according to the Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus 2020 Edition\u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Statistical analysis\u003c/h2\u003e \u003cp\u003eThe data were analyzed using SPSS 26.0. Normally distributed continuous variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and nonnormally distributed continuous variables are expressed as the median (P25, P75). Categorical variables are expressed as frequencies or percentages. ANOVA or the Pearson chi-squared test was used to assess the statistical significance of the difference between patients with and without central obesity. Spearman's rank correlation coefficient was used to test the relationships between carbohydrate intake, carbohydrate energy/total energy intake, fiber intake, and the CFR with demographic information and biochemical metabolic parameters. The restricted cubic spline (RCS) was plotted using the ggplot2 and rms packages of R software 4.0.2 with nodes assigned at the 5th, 35th, 65th, and 95th percentiles to assess the shape of the relationship between the CFR and central adiposity in patients with T2DM. Binary logistic regression analysis was used to investigate the associations relationship between CFR, carbohydrate intake alone, fiber intake and central obesity in T2DM patients. The two-tailed test level was α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1. General Characteristics of Participants\u003c/h2\u003e \u003cp\u003eA total of 304 patients with type 2 diabetes mellitus were included in this study, of whom 203 were centrally obese. Sex, monthly income, and physical activity level were associated with central obesity in patients with type 2 diabetes. Participants with central obesity were more likely to be female, and have a moderate monthly income and low physical activity. Participants with central obesity also had a greater body weight. In addition, type 2 diabetic patients who are centrally obese have worse diabetic pain. There were statistically significant differences between centrally obese and noncentrally obese patients in glycated hemoglobin, diastolic blood pressure, insulin, and triglycerides. In addition, the ratio of carbohydrate to fiber was greater in centrally obese patients than in noncentrally obese patients. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral information, biochemical parameters, and nutritional intake of study subjects with central obesity in patients with type 2 diabetes mellitus\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ecentral obesity(+)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecentral obesity(-)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge(year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.14\u0026thinsp;\u0026plusmn;\u0026thinsp;8.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.30\u0026thinsp;\u0026plusmn;\u0026thinsp;8.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.419\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82(40.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53(52.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121(59.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48(47.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary and below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42(20.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(14.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJunior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92(45.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50(49.50%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh School and Junior College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56(27.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(23.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(6.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(11.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly income (Yuan)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;2000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(21.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(9.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2000ཞ3999\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e143(70.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76(75.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;4000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(8.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15(14.90%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e153(75.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e72(71.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50(24.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29(28.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165(81.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e80(79.20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38(18.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21(20.80%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTaking drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48(23.60%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32(31.70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155(76.40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69(68.30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity level(MET-min/w)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5641.04\u0026thinsp;\u0026plusmn;\u0026thinsp;2583.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6723.03\u0026thinsp;\u0026plusmn;\u0026thinsp;2964.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight(kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.29\u0026thinsp;\u0026plusmn;\u0026thinsp;10.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e59.10\u0026thinsp;\u0026plusmn;\u0026thinsp;8.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWC(cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97.62\u0026thinsp;\u0026plusmn;\u0026thinsp;7.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.46\u0026thinsp;\u0026plusmn;\u0026thinsp;7.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.64\u0026thinsp;\u0026plusmn;\u0026thinsp;2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.20\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1lc(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.65\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.13\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin(pmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69.70(48.90,119.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.10\u003c/p\u003e \u003cp\u003e(28.50,71.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134.05\u0026thinsp;\u0026plusmn;\u0026thinsp;15.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130.85\u0026thinsp;\u0026plusmn;\u0026thinsp;15.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.37\u0026thinsp;\u0026plusmn;\u0026thinsp;9.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.93\u0026thinsp;\u0026plusmn;\u0026thinsp;8.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.59(1.24,2.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.32(0.89,2.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.70\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.757\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-c(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-c(mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.976\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnergy(kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2086.00(1540.00,2932.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2090.00(1548.50,2632.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.476\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein(g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.10(61.10,119.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.80(58.15,109.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat(g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.00(61.00,117.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87.90(66.00,114.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.872\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCarbohydrate(g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e248.00(170.90,343.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e223.10(162.25,302.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary Fiber(g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.10(8.20,20.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.60(8.70,23.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.411\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.52(13.84,23.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.46(11.96,20.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.65\u0026thinsp;\u0026plusmn;\u0026thinsp;11.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.48\u0026thinsp;\u0026plusmn;\u0026thinsp;10.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSense of shame\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.34\u0026thinsp;\u0026plusmn;\u0026thinsp;5.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.43\u0026thinsp;\u0026plusmn;\u0026thinsp;5.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNote: WC, waist circumference;FPG, fasting plasma glucose; HbA1lc, glycated hemoglobin; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride, TC, total cholesterol; HDL-c, high density lipoprotein cholesterol, LDL-c, low density lipoprotein cholesterol, CFR, Carbohydrate-to-fiber ratio.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2. The Carbohydrate-to-fiber ratio and central obesity in patients with type 2 diabetes mellitus\u003c/h2\u003e \u003cp\u003eThere were 203 patients with central obesity, with a higher rate of central obesity in Q3 (37.4%) and the lowest rate of central obesity in Q1 (29.1%). (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrevalence of central obesity in T2DM patients with different carbohydrate to dietary fiber ratios\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecentral obesity,\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enoncentral obesity,\u003c/p\u003e \u003cp\u003en(%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eX\u003c/em\u003e \u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003cp\u003e(\u0026le;14.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59(29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43(42.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ2\u003c/p\u003e \u003cp\u003e(14.75\u0026ndash;20.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68(33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33(32.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003cp\u003e(\u0026ge;20.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76(37.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(24.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3.3. Correlations between carbohydrate intake, carbohydrate energy intake to total energy intake, fiber intake, the carbohydrate-to-fiber ratio, and blood biochemical indices\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe results showed no correlation between carbohydrate intake, carbohydrate energy to total energy intake, fiber intake, and age, weight, waist circumference, insulin, triglycerides, and HDL cholesterol. Carbohydrate intake was correlated with sex (r=-0.122, p\u0026thinsp;=\u0026thinsp;0.034) and monthly income (r\u0026thinsp;=\u0026thinsp;0.128, p\u0026thinsp;=\u0026thinsp;0.025); carbohydrate energy to total energy was correlated with sex (r\u0026thinsp;=\u0026thinsp;0.138, p\u0026thinsp;=\u0026thinsp;0.016) and diastolic blood pressure (r=-0.127, p\u0026thinsp;=\u0026thinsp;0.027); Dietary fiber intake was associated with monthly income (r\u0026thinsp;=\u0026thinsp;0.165, p\u0026thinsp;=\u0026thinsp;0.004). On the other hand, there was a correlation between the carbohydrate-to-fiber ratio and clinical biochemical metabolic parameters and psychological indicators, including body weight (r\u0026thinsp;=\u0026thinsp;0.127, p\u0026thinsp;=\u0026thinsp;0.027), waist circumference (r\u0026thinsp;=\u0026thinsp;0.153, p\u0026thinsp;=\u0026thinsp;0.008), insulin (r\u0026thinsp;=\u0026thinsp;0.118, p\u0026thinsp;=\u0026thinsp;0.04) and high-density lipoprotein cholesterol (r=-0.126, p\u0026thinsp;=\u0026thinsp;0.028), and diabetes mellitus pain (r\u0026thinsp;=\u0026thinsp;0.197, p\u0026thinsp;=\u0026thinsp;0.001). (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between carbohydrate intake, carbohydrate energy ratio to total energy, dietary fiber intake, carbohydrate to dietary fiber ratio and blood biochemical parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003ecarbohydrate intake\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003ecarbohydrate energy ratio to total energy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003edietary fiber intake\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c13\" namest=\"c12\"\u003e \u003cp\u003eCFR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.138\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.076\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonthly income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical activity level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.230\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.767\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHbA1lc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.840\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.127\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.640\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.054\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.936\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.063\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.336\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.078\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.104\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.090\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"13\" nameend=\"c13\" namest=\"c1\"\u003e \u003cp\u003eNote: WC, waist circumference; HbA1lc, glycated hemoglobin; SBP, systolic blood pressure; DBP, diastolic blood pressure; TG, triglyceride, TC, total cholesterol; HDL-c, high density lipoprotein cholesterol, LDL-c, low density lipoprotein cholesterol, CFR, Carbohydrate-to-fiber ratio. Associations between carbohydrate intake, carbohydrate energy to total energy ratio, fiber intake, and carbohydrate to fiber ratio and demographic information, biochemical metabolic parameters, and psychological indicators were examined using Spearman's rank correlation coefficient.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Association of Carbohydrate-to-Fiber Ratio with Central Obesity in Patients with Type 2 Diabetes Mellitus\u003c/h2\u003e \u003cp\u003eUnadjusted multivariate RCS analysis revealed a linear relationship between the continuous variable CFR and central obesity in patients with type 2 diabetes mellitus (Fig.\u0026nbsp;3). An increased risk of central obesity was observed in patients with type 2 diabetes mellitus when the CFR was \u0026gt;\u0026thinsp;17.62 (OR\u0026thinsp;\u0026gt;\u0026thinsp;1). In univariate logistic regression analysis, taking Q1 as the reference group, the carbohydrate-to-fiber ratio was significantly associated with central obesity in patients with type 2 diabetes mellitus in Q3. After adjusting for general demographic information, blood biochemical indices, energy intake, and psychological indices, the CFR was still significantly associated with central obesity in patients with type 2 diabetes mellitus in Q3 (OR\u0026thinsp;=\u0026thinsp;2.166, 95% CI: 1.083\u0026ndash;4.334).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3 Correlation curves between CFR and central obesity in patients with type 2 diabetes\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe solid line indicates the estimated risk of central obesity, and the shaded area indicates the 95% confidence interval (CI).\u003c/p\u003e \u003cp\u003eIn addition, analysis of carbohydrate and fiber alone had no association with central obesity in patients with type 2 diabetes. After adjusting for the same covariates, carbohydrate intake remained unassociated with central obesity in patients with type 2 diabetes mellitus (OR\u0026thinsp;=\u0026thinsp;1.003, 95%CI: 0.998\u0026ndash;1.007). The greater the dietary fiber intake, the lower the rate of central obesity in patients with type 2 diabetes mellitus (OR\u0026thinsp;=\u0026thinsp;0.956, 95% CI: 0.918\u0026ndash;0.994). (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultiple regression analysis of central obesity in T2DM patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCrude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eModel 1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ1(\u0026le;14.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(Ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ2(14.75\u0026ndash;20.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.502(0.847\u0026ndash;2.661)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.606(0.883\u0026ndash;2.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.686(0.870\u0026ndash;3.268)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ3(\u0026ge;20.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.216(1.217\u0026ndash;4.033)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.018(1.080\u0026ndash;3.770)*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.166(1.083\u0026ndash;4.334)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecarbohydrate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.001(0.999\u0026ndash;1.003)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.002(1.000-1.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.003(0.998\u0026ndash;1.007)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003edietary fiber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.989(0.969\u0026ndash;1.009)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.994(0.973\u0026ndash;1.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.956(0.918\u0026ndash;0.994)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.867(1.032\u0026ndash;3.378)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMonthly income\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhysical activity level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.000(1.000\u0026ndash;1.000)**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000(1.000\u0026ndash;1.000)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCovariates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnergy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.000(1.000-1.001)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.034(1.007\u0026ndash;1.061)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInsulin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.007(1.002\u0026ndash;1.013)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHbA1lc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.237(1.019\u0026ndash;1.501)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.034(1.004\u0026ndash;1.064)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eNote: **: p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; *: p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Model 1, adjusted for gender, monthly income, and physical activity level; Model 2, based on Model 1\u0026thinsp;+\u0026thinsp;insulin, glycosylated hemoglobin, triglycerides, blood pressure, diabetes pain, and total energy.; HbA1lc, glycated hemoglobin; TG, triglyceride; DBP, diastolic blood pressure.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe results of the study showed that the carbohydrate-to-fiber ratio was associated with central obesity in patients with type 2 diabetes. The odds of central obesity in type 2 diabetic patients were significantly greater in the high CFR group than in the low CFR group, which is generally consistent with our study hypothesis.\u003c/p\u003e \u003cp\u003eThis study showed that the prevalence of central obesity in patients with type 2 diabetes mellitus was 66.78%, a result comparable to that of a study conducted in Shanghai, which was slightly greater\u003csup\u003e20\u003c/sup\u003e. The results showed that compared with noncentrally obese T2DM patients, centrally obese T2DM patients were more likely to be women with low levels of physical activity and moderate monthly incomes. This finding is different from that of our studies \u003csup\u003e6\u003c/sup\u003e, probably due to the age of the women in this study. It has been found that menopausal women experience a decrease in estrogen levels, an increase in circulating androgen levels, changes in sex hormone levels, and alterations in lipid metabolism and endocrine metabolism, which predispose them to changes in body morphology, muscle loss and abdominal obesity\u003csup\u003e21\u003c/sup\u003e. The Chinese Guidelines for the Prevention and Control of Type 2 Diabetes Mellitus 2020 Edition states that exercise plays an important role in the comprehensive management of type 2 diabetes mellitus; therefore, increasing the level of physical activity while avoiding hypoglycemic events can increase insulin sensitivity and improve body composition\u003csup\u003e3\u003c/sup\u003e. To achieve\u0026thinsp;\u0026ge;\u0026thinsp;5% weight loss, the weekly exercise time should be 300 minutes, and the exercise intensity should be moderate-to-vigorous intensity exercise or an exercise energy expenditure of 2000 kcal/week and above\u003csup\u003e22\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInterestingly, diabetes distress scores were greater in centrally obese individuals with T2DM. Diabetic pain decreases patient adherence, impairs glycemic control\u003csup\u003e23\u003c/sup\u003e, and exacerbates insulin resistance, creating a vicious cycle that affects weight change. The results of this study revealed poor glycemic control and higher insulin levels in patients with high diabetes distress scores. Therefore, community health workers should pay more attention to patients' psychological problems, actively guide patients' misconceptions about diabetes, improve treatment compliance, and promote patients' physical and mental health.\u003c/p\u003e \u003cp\u003eThe results showed that dietary fiber was protective against diabetic distress (r=-0.125, p\u0026thinsp;=\u0026thinsp;0.029), carbohydrate intake did not correlate with diabetic distress (r\u0026thinsp;=\u0026thinsp;0.090, p\u0026thinsp;=\u0026thinsp;0.116), whereas the CFR was positively associated with diabetic distress (r\u0026thinsp;=\u0026thinsp;0.197, p\u0026thinsp;=\u0026thinsp;0.001). Sarah S Makhani et al \u003csup\u003e16\u003c/sup\u003e reported that a higher CFR increased the risk of moderate to severe depression. The gut microbiota and the gut-brain axis are effective psychological intervention pathways, and dietary fiber is well able to modulate the gut microbiota and produce short-chain fatty acids. This may be the reason why dietary fiber plays a protective role against diabetic pain. The CFR was positively correlated with weight (r\u0026thinsp;=\u0026thinsp;0.127, p\u0026thinsp;=\u0026thinsp;0.027) and waist circumference (r\u0026thinsp;=\u0026thinsp;0.153, p\u0026thinsp;=\u0026thinsp;0.008). This finding is similar to that of the Framingham Offspring Cohort, which revealed that a greater ratio of carbohydrates to fiber was associated with increased waist circumference in adults\u003csup\u003e18\u003c/sup\u003e. In this study, there was no correlation between carbohydrate intake, fiber intake, carbohydrate energy to total energy intake, and insulin and HDL cholesterol. Only the CFR was correlated with insulin (r\u0026thinsp;=\u0026thinsp;0.118, p\u0026thinsp;=\u0026thinsp;0.040) and HDL cholesterol (r=-0.126, p\u0026thinsp;=\u0026thinsp;0.028). This is consistent with the findings of Yoshitaka Hashimoto et al\u003csup\u003e24\u003c/sup\u003e. These finding indicate that the carbohydrate-to-fiber ratio plays an important role in human health.\u003c/p\u003e \u003cp\u003eIn this study, the risk of central obesity in type 2 diabetic patients was increased (OR\u0026thinsp;\u0026gt;\u0026thinsp;1) at CFR\u0026thinsp;\u0026gt;\u0026thinsp;17.62, which is much greater than the 10:1 CFR value of cereals, which have been shown to be healthier\u003csup\u003e17\u003c/sup\u003e, suggesting that type 2 diabetic centrally obese individuals consume excessive low-quality carbohydrates. A higher CFR increased the odds of central obesity in patients with type 2 diabetes (OR\u0026thinsp;=\u0026thinsp;2.216, 95% CI: 1.217\u0026ndash;4.033). After adjusting for variables, we still found that a higher CFR was associated with central obesity in T2DM patients (OR\u0026thinsp;=\u0026thinsp;2.166, 95% CI: 1.083\u0026ndash;4.334). In addition, after adjusting for the same variables, the association between the CFR and central obesity in T2DM patients was stronger than carbohydrate intake (OR\u0026thinsp;=\u0026thinsp;1.003, 95% CI: 0.998\u0026ndash;1.007) and fiber intake (OR\u0026thinsp;=\u0026thinsp;0.956, 95% CI: 0.918\u0026ndash;0.994) alone. In recent years, a number of studies have shown that carbohydrate quality is more beneficial to human health than quantity\u003csup\u003e25\u0026ndash;27\u003c/sup\u003e. Studies have shown that high-quality carbohydrates reduce weight gain and are the best recipe for weight control in middle-aged adults\u003csup\u003e28\u003c/sup\u003e. In addition, after adjusting for covariates, we found that diabetes distress increased the odds of central obesity in patients with type 2 diabetes (OR\u0026thinsp;=\u0026thinsp;1.034, 95% CI: 1.007\u0026ndash;1.061). Studies have shown that changes in body size and appearance caused by obesity and its somatic complications, in turn, cause negative psychological feelings such as low self-esteem and self-blame, leading to depressive disorders, and further exacerbating patients' overeating behaviors\u003csup\u003e29\u0026ndash;31\u003c/sup\u003e. Prolonged diabetic suffering will aggravate diabetic suffering by causing patients to develop various psychological problems. Psychotherapy can improve the psychological aspects of patients' unhealthy eating habits, leading to better implementation of weight loss dietary programs and behavioral training to achieve weight control and lower BMI and waist circumference.\u003c/p\u003e \u003cp\u003ePrevious studies have shown that the carbohydrate-to-fiber ratio is effective for identifying high-quality carbohydrates or whole grains\u003csup\u003e17\u003c/sup\u003e. Higher ratios reflect poorer carbohydrate quality and are associated with a greater risk of T2DM\u003csup\u003e32\u003c/sup\u003e and coronary heart disease\u003csup\u003e33\u003c/sup\u003e. Taken together, carbohydrate intake and dietary fiber intake alone cannot accurately reflect the physical and mental health of people, CFR as a dietary quality indicator can more sensitively reflect the physical and mental health of people, and dietary CFR as an indicator to assess the quality of carbohydrates is more easily understood and accepted by the public.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eA higher CFR leads to increased central obesity in patients with type 2 diabetes. Diets with a low CFR can be recommended for the dietary management of patients with type 2 diabetes.\u003c/p\u003e\n\u003ch3\u003eStrengths and Limitations\u003c/h3\u003e\n\u003cp\u003eThe strengths of this study are the focus on the association of carbohydrate-to-fiber ratio (CFR), an indicator of carbohydrate quality, with central obesity in patients with type 2 diabetes, and to include psychological indicators (diabetes distress, disease stigma) to conduct an analysis of the impact on central obesity in patients with type 2 diabetes. A higher CFR was found to be associated with central obesity in patients with type 2 diabetes, reflecting the greater impact of a low-quality carbohydrate diet on central obesity in patients with type 2 diabetes. The limitations of this study must be considered; First, this was a cross-sectional study, and causality could not be established. Second, dietary data were collected by recall using a semiquantitative food frequency questionnaire, which may be subject to recall and self-report bias.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eT2DM: Type 2 diabetes mellitus\u003c/p\u003e\n\u003cp\u003eWAT：White adipose tissue\u003c/p\u003e\n\u003cp\u003eBAT：Brown adipose tissue\u003c/p\u003e\n\u003cp\u003eTGs：Triglycerides\u003c/p\u003e\n\u003cp\u003eCFR：Carbohydrate-to-fiber ratio\u003c/p\u003e\n\u003cp\u003eFFQ：Food frequency questionnaire\u003c/p\u003e\n\u003cp\u003eWC：Waist circumference\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFPG：Fasting plasma glucose\u003c/p\u003e\n\u003cp\u003eHbA1c：Glycated hemoglobin\u003c/p\u003e\n\u003cp\u003eSBP：Systolic blood pressure\u003c/p\u003e\n\u003cp\u003eDBP：Diastolic blood pressure\u003c/p\u003e\n\u003cp\u003eTC：Total cholesterol\u003c/p\u003e\n\u003cp\u003eHDL-c：High density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eLDL-c：Low density lipoprotein cholesterol\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data presented in this article are available on request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are very grateful to the people with type 2 diabetes in our community who volunteered to participate in this survey. We are equally thankful to the students and teachers who participated in this survey and whose helpful support enabled us to complete this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the Humanities and Social Sciences Planning Fund of the Ministry of Education (15YJAZH085).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;School of Public Health, Bengbu Medical University, Bengbu, China\u003c/p\u003e\n\u003cp\u003eCui-qi Jing, Hai-meng Zhang, Fan Zhang, Xiao-yu Xu, Jia-jia Ren,\u003c/p\u003e\n\u003cp\u003eSchool of Nursing, Bengbu Medical University, Bengbu, China\u003c/p\u003e\n\u003cp\u003eXiao-mei Ji\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e* Correspondence:[email protected] \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSchool of Public Health, Bengbu Medical University, Bengbu, China\u003c/p\u003e\n\u003cp\u003eHong Xie\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eC.J.: Methodology, Data curation, Formal analysis, and initial draft writing; H.Z.: Data curation, Writing Suggestions; F.Z., X.X., and J.R.: Data curation; X.J.: Data collection and organization; H.X.:\u0026nbsp;Study design, methodology, source, and supervision, Writing-review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was conducted according to the guidelines of the Declaration of Helsinki. The study was approved by the Ethics Committee of Bengbu Medical College [ethical approval number: (2016 )No.015]. All the subjects provided informed consent by signing the informed consent form.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Bengbu Medical College.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed Consent Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all subjects involved in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data in this study involve privacy issues, and the data should not be shared.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHou X, Lu J, Weng J, et al. 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Am J Clin Nutr. 2018;107(2):257\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ajcn/nqx060\u003c/span\u003e\u003cspan address=\"10.1093/ajcn/nqx060\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\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":"dietary carbohydrate-to-fiber ratio, type 2 diabetes, central obesity","lastPublishedDoi":"10.21203/rs.3.rs-4072825/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4072825/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e(1) Background: The carbohydrate-to-fiber ratio (CFR) is an important indicator of dietary carbohydrate quality. However, few studies have focused on obesity in patients with type 2 diabetes. Therefore, the aim of this study was to investigate the association between the CFR and central obesity in type 2 diabetic patients in the community.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(2) Methods: This was a cross-sectional study. A general demographic information questionnaire and a semiquantitative food frequency questionnaire were used to investigate the demographic characteristics and dietary intake information of type 2 diabetic patients in the community, and the daily amounts of carbohydrates and dietary fiber were obtained by calculating the carbohydrate-to-fiber ratio (CFR) using Nutrition Calculator (v2.7.3k) software. Participants' CFR was categorized into Q1, Q2, and Q3 groups from high to low. Central obesity was defined as a waist circumference ≥90 cm for men and ≥85 cm for women.\u003c/p\u003e\n\u003cp\u003e(3) Results: The prevalence of central obesity in community-dwelling type 2 diabetic patients was 66.77%. The CFR was associated with waist circumference (r=0.153, p=0.008), insulin (r=0.118, p=0.040), high-density lipoprotein cholesterol (r=-0.126, p=0.028), and diabetes distress (r=0.197, p=0.001). With Q1 as a reference, the CFR was still significantly associated with central obesity in the Q3 after adjusting for variables (OR=2.166, 95% CI: 1.083-4.334). Carbohydrate intake was not associated with central obesity (OR=1.003, 95% CI: 0.998-1.007). The CFR is a stronger protective factor against central obesity than either fiber or carbohydrate alone.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e(4) Conclusions: A higher CFR leads to increased central obesity in patients with type 2 diabetes. Diets with a low CFR can be recommended for the dietary management of patients with type 2 diabetes.\u003c/p\u003e","manuscriptTitle":"The Carbohydrate-to-fiber ratio (CFR) is a useful marker of central obesity in patients with type 2 diabetes: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-21 18:44:20","doi":"10.21203/rs.3.rs-4072825/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":"609a9c1f-675f-40ad-8f47-a1ec51098d20","owner":[],"postedDate":"March 21st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-11T11:57:17+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-21 18:44:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4072825","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4072825","identity":"rs-4072825","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}