Journal of Obesity & Metabolic Syndrome

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March, 2024 | Vol.33 No.1

J Obes Metab Syndr 2023; 32(1): 55-63

Published online March 30, 2023 https://doi.org/10.7570/jomes22047

Copyright © Korean Society for the Study of Obesity.

Glucose Control in Korean Patients with Type 2 Diabetes Mellitus according to Body Mass Index

Ye-lim Shin1, Heesoh Yoo1, Joo Young Hong1, Jooeun Kim1, Kyung-do Han2, Kyu-Na Lee3, Yang-Hyun Kim4,*

1Department of Medicine, Korea University College of Medicine, Seoul; 2Department of Statistics and Actuarial Science, Soongsil University, Seoul; 3Department of Biomedicine & Health Science, The Catholic University of Korea, Seoul; 4Department of Family Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea

Correspondence to:
Yang-Hyun Kim
https://orcid.org/0000-0003-3548-8758
Department of Family Medicine, Korea University Anam Hospital, Korea University College of Medicine, 73 Goryeodae-ro, Seongbuk-gu, Seoul 02841, Korea
Tel: +82-2-920-5104
Fax: +82-2-928-8083
E-mail: 9754031@korea.ac.kr

Received: August 7, 2022; Reviewed : October 31, 2022; Accepted: March 1, 2023

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Background: The prevalence of type 2 diabetes mellitus has continued to rise. Although many studies have focused on the connection between weight loss and glucose control, only a few studies have investigated the association between body mass index (BMI) and glucose control status. We examined the association between glucose control and obesity.
Methods: We analyzed 3,042 participants with diabetes mellitus who were aged ≥19 years when they participated in the 2014 to 2018 Korean National Health and Nutrition Examination Survey. The participants were divided into four groups according to their BMI (<18.5, 18.5–23, 23–25, and ≥25 kg/m2). We used guidelines from the Korean Diabetes Association to compare the glucose control in those groups, with a cross-sectional design, multivariable logistic regression, and glycosylated hemoglobin <6.5% as the reference.
Results: Overweight males aged ≥60 years had a high odds ratio (OR) for degraded glucose control (OR, 1.706; 95% confidence interval [CI], 1.151 to 2.527). Among obese females, those in the ≥60 years age group showed an increased OR for uncontrolled diabetes (OR, 1.516; 95% CI, 1.025 to 1.892). Moreover, in females, the OR for uncontrolled diabetes tended to increase as the BMI increased (P=0.017).
Conclusion: Obesity is associated with uncontrolled diabetes in female patients with diabetes who are aged ≥60 years. Physicians should closely monitor this group for diabetes control.

Keywords: Obesity, Body mass index, Diabetes mellitus, Glucose control, Glycated hemoglobin

The prevalence of type 2 diabetes mellitus (DM) has increased, making it one of the biggest health issues worldwide. It was estimated in 2015 that one in 11 adults aged 20 to 79 years worldwide had type 2 DM.1 The global prevalence of type 2 DM is expected to increase to 7,079 individuals per 100,000 by 2030, compared with 6,059 individuals per 100,000 in 2017.2

Obesity is an important risk factor of type 2 DM, especially among young people.3,4 Furthermore, weight loss of at least 5% in overweight or obese individuals with type 2 DM improves glucose control, and modest weight loss can improve the cardiovascular risk in obese patients with type 2 DM.5,6 For this reason, the American Diabetes Association recommends weight loss for obese people at high risk for diabetes.7

As such, many studies have examined the association between weight loss or lifestyle modification and glucose control; however, only a few studies have investigated the relationship between body mass index (BMI) and glucose control status in patients being treated for diabetes. Though previous studies have reported that a high BMI is associated with poor diabetes control, none of those studies were performed on Koreans.8,9 Obesity has a more devastating effect on the incidence of diabetes in Asian people than in Western populations.10 Therefore, we investigated the relationship between BMI and glucose control in Korean patients with diabetes.

Data

We used data from the 2014 to 2018 Korean National Health and Nutritional Examination Survey (KNHANES), a cross-sectional population-based investigation performed by the Ministry of Health and Welfare in Korea. KNHANES is based on a complex, stratified, multistage, and probability cluster survey designed to represent the non-institutionalized civilian population of Korea.11 KNHANES data are collected using questionnaires, nutritional investigations, and health examinations. Among the various methods, we used health questionnaire, health examination, and investigation data in this study. KNHANES was reviewed and approved by the ethics committee of the Korean Centers for Disease Control and Prevention (IRB No. 2018-01-03-P-A).

Subjects

The 2014 to 2018 KNHANES included 39,199 participants. For this study, we excluded participants aged <19 years (n=7,889). Among the remaining 31,310 participants, 2,814 participants were excluded due to insufficient fasting status. Among the remaining 28,496 participants, 25,230 participants without DM were excluded, and participants missing key variables (glucose, glycosylated hemoglobin [HbA1c], and BMI, n=17) or other variables (n=207) were also excluded. Thus, 3,042 adult subjects with DM were included in this study. We performed this study according to the ethical principles for medical research involving human subjects, as defined by the Declaration of Helsinki. All KNHANES participants provided written informed consent.

Biochemical measurements

Blood samples were collected from participants after at least 8 hours of fasting. Fasting blood glucose (FBG), total cholesterol, high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), and low-density lipoprotein cholesterol were measured enzymatically using a Hitachi Automatic Analyzer 7600 (Hitachi) at a central testing institute in Seoul, Korea. HbA1c levels were measured using a Tosoh G8 (Tosoh) and a high-performance lipid chromatography method.

Sociodemographic and general health behaviors

The sociodemographic and general health data of the participants were collected from self-reported questionnaires that asked about age, sex, smoking status, alcohol consumption, physical activity, education level, and household income. Current smokers were defined as those who identified as smokers at the time of the survey, and non-smokers were defined as those who had smoked <100 cigarettes in their lifetime, including those who never smoked. In the KNHANES data, heavy drinkers were defined as those having ≥3 glasses of alcohol per day (≥30 g/day), and mild-to-moderate drinkers were defined as those who had <3 glasses of alcohol per day (15 to 30 g/day). We included both categories as alcohol drinkers in our study. Physical activity was evaluated using the International Physical Activity Questionnaire.12 Regular exercise was defined as exercise ≥5 times a week for at least 30 minutes per session or strenuous exercise ≥3 times a week for 20 minutes per session. Education level was categorized as high school graduate (≥13 years) or not, and household income was categorized into quartiles modified by the number of family members.

Definitions of obesity, abdominal obesity, DM, hypertension, and dyslipidemia

In this study, we categorized BMI into four groups (underweight: <18.5 kg/m2; normal weight: 18.5 to 23 kg/m2; overweight: 23 to 25 kg/m2; and obese: ≥25 kg/m2) according to the World Health Organization Western Pacific Region definition of obesity for the Asia-Pacific region.13 Abdominal obesity was defined as a waist circumference (WC) ≥90 cm for males and ≥85 cm for female, as defined in a nationwide study with a Korean population.14

We referred to the American Diabetes Association guidelines to evaluate the glycemic status and glycemic control of the participants.15 We initially categorized the participants into two groups according to their glycemic status: diabetic or normal, and then we further divided the diabetic group based on their glycemic control: well-controlled or uncontrolled. Participants were defined as having DM when they met one of these criteria: FBG ≥126 mg/dL, diagnosis established by a doctor, or a history of antidiabetic medication, including insulin injection. We assessed the degree of glycemic control using the HbA1c percentage, with HbA1c <6.5% reflecting well-controlled diabetes, and HbA1c ≥6.5% reflecting uncontrolled diabetes, according to the guidelines of the Korean Diabetes Association.16

Hypertension was defined as a systolic blood pressure of ≥140 mmHg, diastolic blood pressure of ≥90 mmHg, or the use of antihypertensive medication. Dyslipidemia was defined as a measured fasting total cholesterol level of ≥240 mg/dL or the use of medications to lower blood cholesterol.

Statistical analysis

We examined the general characteristics of participants using an analysis of variance (ANOVA) for categorical variables. All results for continuous and categorical variables are presented as the mean± standard error or percentage (%), respectively.

To analyze the association between BMI and uncontrolled diabetes, we performed a multivariable logistic regression analysis among the four BMI groups (underweight, normal, overweight, and obesity) after adjusting for covariates: age, sex, alcohol consumption, current smoking, exercise, income, education, hypertension, and dyslipidemia. We also performed subgroup analyses according to sex (male and female) and three age groups (20–40, 40–60, and ≥60 years). Similarly, we investigated the associations between abdominal obesity and glucose control using a multivariable logistic regression analysis. All results are presented as odds ratios (ORs) with 95% confidence intervals (CIs), and a P-value for the trend was calculated in each subgroup analysis. The P-value for the trend was obtained through the logistic regression model by analyzing the ORs of the four BMI levels as continuous variables rather than categorial variables.

All statistical analyses ware performed using the SAS software package version 9.2 (SAS Institute). All statistical tests were twotailed, and statistically significant differences were defined as those with a P<0.05.

The general characteristics of the subjects are presented in Table 1. Subjects with a BMI ≥25 kg/m2 were the youngest and had the highest weight, WC, diastolic blood pressure, TG, and rates of hypertension and dyslipidemia and the lowest HDL-C level among the four BMI groups (all P<0.05). The FBG and HbA1c levels did not differ significantly among the four BMI groups (P=0.896 and P=0.694, respectively) (Table 1).

Figure 1 shows the mean HbA1c levels according to the sex and age groups. In males, subjects with a normal weight had the highest mean HbA1c (7.5%), and underweight subjects had the lowest mean HbA1c (6.98%), among the four BMI groups. In females, the mean HbA1c was lower than among males, except for underweight males, and underweight subjects had the highest mean HbA1c (7.27%); however, females subjects with normal weight showed the lowest HbA1c levels (7.12%) (P for trend=0.075 for males and P for trend=0.292 for females) (Figure 1A).

Subjects aged 20 to 39 years had the highest mean HbA1c level, and subjects aged ≥60 years had the lowest mean HbA1c level, except for underweight subjects. Among subjects aged ≥60 years, HbA1c levels were similar in all four BMI groups; however, among subjects aged 20–39 and 40–59 years, the highest HbA1c levels were found among those with normal weight (Figure 1B).

Figure 2 shows the mean HbA1c levels in males and females in the three age groups. Among males, subjects aged 20 to 39 years had the highest mean HbA1c, and subjects aged ≥60 years had the lowest mean HbA1c. Among the four BMI groups, males with a normal weight had the highest mean HbA1c, and underweight males had the lowest mean HbA1c (P for trend=0.596 in males aged 40–59 years and P for trend=0.574 in male aged ≥60 years) (Figure 2A). Among females, the mean HbA1c level increased as the BMI level increased in subjects aged 20 to 39 years, with the lowest level in subjects with a normal weight and the highest level in obese subjects. Among female subjects aged ≥60 years, the highest HbA1c level was found in underweight subjects, and the lowest level was found in subjects with a normal weight; however, among female subjects aged 40 to 59 years, the lowest HbA1c level was seen in underweight subjects, and the highest level was seen in subjects with a normal weight (P for trend=0.897 in females aged 40–59 years and P for trend=0.285 in females aged ≥60 years) (Figure 2B).

The ORs for uncontrolled diabetes in the four BMI groups according to sex and the three age groups are shown in Table 2. After adjusting for all covariates, we found no significant association between BMI and glucose control in males or females. Based on the age groups, overweight and obese subjects aged ≥60 years showed increased rates of uncontrolled diabetes (OR, 1.484 and 1.433, respectively), and the ORs for uncontrolled diabetes tended to increase as BMI increased (P for trend=0.009) (Table 2). We also analyzed the relationship between abdominal obesity and glucose control and found a significant association between abdominal obesity and uncontrolled diabetes in females (OR, 1.335; 95% CI, 1.021 to 1.745) but not in males (OR, 1.009; 95% CI, 0.766 to 1.329) (Supplementary Table 1).

Table 3 shows the ORs for uncontrolled diabetes based on the 4 BMI groups in males and females according to the three age groups. After adjusting for all covariates, overweight males aged ≥60 years showed an increased OR for uncontrolled diabetes (OR, 1.706; 95% CI, 1.151 to 2.527). Obese females aged ≥60 years also showed an increased OR for uncontrolled diabetes (OR, 1.516; 95% CI, 1.025 to 2.244), and the OR for uncontrolled diabetes tended to increase as the BMI increased (P for trend=0.017) (Table 3).

The American Diabetes Association guidelines recommend lifestyle modifications for people at high risk for diabetes who are obese.7 Though a prior study reported that weight loss of ≥5% in overweight or obese individuals with type 2 DM improved glucose control,5 Boulé et al.17 reported that glycemic control could be achieved by lifestyle modification itself, without weight loss. According to that study, glycemic control, such as a decrease in hepatic and muscle insulin resistance, can be achieved by exercise, which is not related to body weight change. The harmful influence of obesity on glycemic control could thus reflect poor lifestyle choices or the effects of obesity itself.18-21 However, studies of the effects of obesity on glycemic control are insufficient. Therefore, we focused on the association between obesity and glucose control in this study.

Obesity is a major risk factor for type 2 DM, and various mechanisms of obesity cause DM. Obesity maintains high plasma-free fatty acid levels with central abdominal fat, which leads to chronic hyperglycemia and damaged insulin sensitivity and eventually chronic low-grade inflammation in the adipose tissue.22 In addition, the proportion and diversity of microbiome composition are defective in obesity, and a decrease in the abundance of Akkermansia muciniphila species enhances gut permeability, allowing lipopolysaccharide into the bloodstream and causing chronic inflammation.23 This sort of chronic inflammation is associated with obesity and insulin resistance.23 Those studies suggest that irrespective of the lifestyle of obese individuals, obesity itself can affect glycemic control.

In this study, we found that glucose was more poorly controlled in obese females aged ≥60 years than in females with a normal weight aged ≥60 years. The first reason is that abdominal obesity is an independent factor for the development of type 2 DM.24 According to the Factsheet of the Korean Society for the Study of Obesity, the prevalence of obesity among females, particularly abdominal obesity, is higher than among males in individuals aged ≥60 years.25 As a supporting finding, WC, a parameter representing abdominal obesity, and glucose control appeared to be related in females in our data (Supplementary Table 1). Therefore, among diabetic patients, abdominal obesity in obese females, especially elderly females, was more common than in obese males, which could explain the poor diabetes control we found in obese females aged ≥60 years. In addition, there is a difference in body composition between males and females, with females having more fat mass, and males having more muscle mass.26 According to previous studies, muscle mass is a protective factor in diabetes.27,28 Therefore, we suggest that a higher BMI, a parameter including not only high adiposity but also low muscle mass, led to poor diabetes control in females but not in males.

As people age, muscle mass decreases and adiposity increases.29,30 Adipogenic potential decreases with age, at least in part through the influence of senescent preadipocytes, which secrete proinflammatory cytokines and thereby induce adipose tissue insulin resistance that eventually increases lipolysis and lowers the lipid storage potential of adipocytes. In postmenopausal females, gluteofemoral adipose tissue is redistributed into the abdominal region, which increases insulin resistance.31 Therefore, obesity in females with type 2 DM aged 60 years or older should be monitored closely for glucose control.

In old age, the risk of hypoglycemia increases because renal function decreases, and that increases the risk of adverse drug events and makes it possible to reduce drug doses.29 Older patients with diabetes can also have altered gustatory perception, underlying disease, masticatory dysfunction, poor gastrointestinal function, lack of ability to prepare their own meals, and memory decline, which can all result in them skipping meals. It is thus challenging for elderly patients to maintain lifestyle habits for diabetes control.32

This study has certain limitations. Because we used KNHANES cross-sectional data, we cannot establish a causal relationship between BMI and diabetes control. In addition, our data could have some biases in analyzing the association between BMI and DM control because we could not consider the effects of weight gain or loss, diabetes medications, or trends of weight change in our participants. Nevertheless, this study also has some strengths. This is the first study to find that uncontrolled diabetes is associated with obesity in Korean females. BMI is a non-invasive indicator that can easily be acquired at home and could thus be a good criterion for educating patients32 because of the many existing studies on nutrition and exercise related to BMI. In addition, it can help in making therapeutic or policy decisions about who should receive particular attention regarding diabetes control by clearly presenting a group of patients who cannot control their diabetes.

In conclusion, obesity is associated with uncontrolled diabetes in elderly Korean females with diabetes. This finding requires a followup study to determine whether treatments such as weight loss are effective in controlling diabetes in elderly females. Furthermore, these findings suggest the need for future research to determine which groups of patients can most effectively improve their diabetes outcomes by losing weight.

Study concept and design: YS, KH, and YHK; acquisition of data: YS, HY, JYH, JK, KH, KNL, and YHK; analysis and interpretation of data: YS, HY, JYH, JK, KH, KNL, and YHK; drafting of the manuscript: YS, HY, JYH, JK, and YHK; critical revision of the manuscript: YS, KH, and KNL; statistical analysis: YS, KH, and KNL; obtained funding: YHK; administrative, technical, or material support: KH and YHK; and study supervision: YHK.

Fig. 1. Mean glycosylated hemoglobin (HbA1c) based on (A) sex and (B) age groups. Data derived from the Korean National Health and Nutrition Examination Survey data set: 2014 to 2018. Body mass index (BMI) was categorized into four groups according to the World Health Organization Western Pacific Region definition of obesity for the Asia-Pacific region: obesity= BMI ≥ 25 kg/m2.
Fig. 2. Mean glycosylated hemoglobin (HbA1c) of (A) males and (B) females according to the three age groups. Data derived from the Korean National Health and Nutrition Examination Survey data set: 2014 to 2018. Body mass index (BMI) was categorized into four groups according to the World Health Organization Western Pacific Region definition of obesity for the Asia-Pacific region: obesity= BMI ≥ 25 kg/m2.

General characteristics of the subjects according to BMI level

Variable BMI (kg/m2) P

< 18.5 (n= 22) 18.5–23 (n= 792) 23–25 (n= 723) ≥ 25 (n= 1,505)
Age (yr) 64.90 ± 1.51 62.16 ± 0.50 61.44 ± 0.54 57.86 ± 0.45 < 0.001
Male sex 59.45 (11.72) 57.22 (2.01) 58.53 (2.24) 56.11 (1.55) 0.802
Weight (kg) 47.42 ± 1.21 56.99 ± 0.32 63.64 ± 0.36 75.39 ± 0.41 < 0.001
Height (cm) 162.63 ± 1.69 162.55 ± 0.41 162.37 ± 0.44 163.12 ± 0.33 0.523
Waist circumference (cm) 70.43 ± 0.92 79.55 ± 0.24 85.65 ± 0.22 94.56 ± 0.24 < 0.001
Smoking (yes, %) 26.42 (10.21) 24.07 (1.95) 19.67 (1.78) 23.23 (1.36) 0.294
Alcohol (yes, %) 3.04 (3.06) 13.63 (1.53) 11.66 (1.52) 11.04 (1) 0.289
Regular exercise (yes, %) 35.55 (11.16) 38.06 (2.07) 43.32 (2.23) 39.75 (1.5) 0.287
Education ≥ 13 years (yes, %) 16.36 (10.78) 17.56 (1.7) 20.56 (1.86) 23.22 (1.41) 0.068
Income Q1 (yes, %) 43.83 (12.04) 31.96 (2.04) 26.15 (1.78) 27.48 (1.41) 0.055
HTN (yes, %) 45.13 (12.37) 48.93 (2.17) 56.65 (2.2) 65.34 (1.5) < 0.001
Dyslipidemia (yes, %) 31.85 (11.19) 34.82 (2.13) 38.89 (2.09) 42.49 (1.55) 0.014
Glucose (mg/dL) 139.93 ± 11.31 145.21 ± 1.86 146.64 ± 1.97 146.34 ± 1.26 0.896
HbA1c (%) 7.1 ± 0.32 7.34 ± 0.07 7.27 ± 0.06 7.25 ± 0.05 0.694
SBP (mmHg) 123.9 ± 3.06 124.67 ± 0.76 124.98 ± 0.73 126.32 ± 0.51 0.210
DBP (mmHg) 74.15 ± 1.92 73.24 ± 0.49 74.22 ± 0.5 78.22 ± 0.35 < 0.001
Total cholesterol (mg/dL) 176.52 ± 7.01 178.98 ± 1.82 179.26 ± 1.78 184.39 ± 1.52 0.053
LDL-C (mg/dL) 101.32 ± 7.57 100.69 ± 1.58 100.48 ± 1.53 102.63 ± 1.27 0.669
HDL-C (mg/dL) 52.97 ± 2.87 48.25 ± 0.5 45.67 ± 0.49 44.14 ± 0.33 < 0.001
TG (mg/dL) 93.0 (69.2–125) 128.0 (121.3–135.2) 149.6 (141.5–158.2) 165.4 (159.5–171.5) < 0.001

Values are presented as mean± standard error as tested by analysis of variance (ANOVA), or percentage (SE). Q1 is the lowest income bracket.

BMI, body mass index; HTN, hypertension; HbA1c, glycosylated hemoglobin; SBP, systolic blood pressure; DBP, diastolic blood pressure; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride.

Multivariable adjusted ORs for glucose control according to sex and age groups

Variable Crude OR (95% CI) P Adjusted OR (95% CI) P P for trend
Total 0.625
Underweight 0.510 (0.190–1.366) 0.119 0.495 (0.178–1.372) 0.120
Normal weight 1 (reference) 1 (reference)
Overweight 1.269 (0.976–1.649) 0.031 1.274 (0.978–1.660) 0.029
Obese 1.073 (0.858–1.343) 0.233 1.063 (0.842–1.343) 0.253
Male 0.324
Underweight 0.558 (0.148–2.096) 0.333 0.584 (0.154–2.217) 0.388
Normal weight 1 (reference) 1 (reference)
Overweight 1.311 (0.920–1.868) 0.068 1.305 (0.907–1.880) 0.072
Obese 0.925 (0.688–1.244) 0.915 0.876 (0.639–1.201) 0.867
Female 0.067
Underweight 0.444 (0.107–1.854) 0.182 0.412 (0.091–1.862) 0.173
Normal weight 1 (reference) 1 (reference)
Overweight 1.211 (0.836–1.755) 0.196 1.214 (0.836–1.765) 0.189
Obese 1.307 (0.950–1.799) 0.069 1.322 (0.953–1.836) 0.066
20–40 years
Underweight - - - - -
Normal weight 1 (reference) 1 (reference)
Overweight 1.007 (0.152–6.683) 0.524 0.840 (0.112–6.288) 0.756
Obese 0.680 (0.141–3.283) 0.462 0.766 (0.131–4.466) 0.882
40–60 years 0.086
Underweight 0.523 (0.075–3.661) 0.551 0.591 (0.082–4.247) 0.663
Normal weight 1 (reference) 1 (reference)
Overweight 1.047 (0.636–1.723) 0.356 1.047 (0.633–1.731) 0.377
Obese 0.780 (0.518–1.176) 0.892 0.717 (0.469–1.094) 0.630
≥ 60 years 0.009
Underweight 0.550 (0.176–1.717) 0.155 0.504 (0.150–1.692) 0.128
Normal weight 1 (reference) 1 (reference)
Overweight 1.424 (1.063–1.909) 0.055 1.484 (1.105–1.993) 0.041
Obese 1.370 (1.051–1.786) 0.061 1.433 (1.082–1.899) 0.042

Values are presented as OR (95% CI) as tested by a multivariable logistic regression analysis. Adjusted for age, sex, alcohol consumption, smoking, regular exercise, income, education, hypertension, and dyslipidemia.

OR, odds ratio; CI, confidence interval.

Multivariable adjusted ORs for glucose control according to sex and age groups

Variable Crude OR (95% CI) P Adjusted OR (95% CI) P P for trend
Male
20–40 years -
Underweight - - - -
Normal weight 1 (reference) 1 (reference)
Overweight - - - -
Obese - - - -
40–60 years 0.070
Underweight 0.433 (0.035–5.342) 0.591 0.449 (0.034–5.969) 0.621
Normal weight 1 (reference) 1 (reference)
Overweight 0.976 (0.494–1.926) 0.408 1.020 (0.504–2.066) 0.372
Obese 0.632 (0.362–1.105) 0.705 0.609 (0.336–1.104) 0.620
≥ 60 years 0.202
Underweight 0.712 (0.155–3.264) 0.442 0.679 (0.154–3.000) 0.392
Normal weight 1 (reference) 1 (reference)
Overweight 1.651 (1.127–2.418) 0.095 1.706 (1.151–2.527) 0.065
Obese 1.315 (0.918–1.883) 0.457 1.297 (0.883–1.905) 0.471
Female
20–40 years -
Underweight - - - -
Normal weight 1 (reference) 1 (reference)
Overweight 5.178 (0.421–63.677) 0.991 7.007 (0.819–59.964) 0.619
Obese 5.235 (0.723–37.924) 0.252 4.466 (0.611–32.619) 0.508
40–60 years 0.982
Underweight 0.736 (0.056–9.652) 0.768 1.269 (0.093–17.418) 0.888
Normal weight 1 (reference) 1 (reference)
Overweight 1.135 (0.554–2.324) 0.703 1.142 (0.560–2.330) 0.932
Obese 1.106 (0.603–2.031) 0.737 1.029 (0.554–1.910) 0.847
≥ 60 years 0.017
Underweight 0.397 (0.076–2.088) 0.188 0.294 (0.046–1.880) 0.127
Normal weight 1 (reference) 1 (reference)
Overweight 1.206 (0.781–1.863) 0.250 1.226 (0.795–1.892) 0.197
Obese 1.396 (0.961–2.028) 0.053 1.516 (1.025–2.244) 0.024

Values are presented as OR (95% CI) as tested by a multivariable logistic regression analysis. Adjusted for age, sex, alcohol consumption, smoking, regular exercise, income, education, hypertension, and dyslipidemia.

OR, odds ratio; CI, confidence interval.

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