Sex- and age-specific body composition indices as predictors of new-onset type 2 diabetes mellitus in Koreans: a nationwide cohort study

性别和年龄特异性身体成分指标作为韩国人新发2型糖尿病的预测因子:一项全国性队列研究

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Abstract

OBJECTIVES: Hormonal and age-related differences in body composition require tailored approaches for predicting new-onset type 2 diabetes (NODM). Previous studies lacked in-depth stratified analyses. We investigate sex- and age-specific body composition indices associated with NODM. DESIGN AND SETTING: A retrospective, nationwide, population-based cohort study. PARTICIPANTS: We analysed 4 058 891 adults who underwent a health examination in the year 2009 and 10-year follow-up data from the National Health Insurance Service. OUTCOME MEASURE: NODM risk stratified by sex and age groups in 20-year intervals according to quartiles or per 1 SD increase in body mass index (BMI), waist circumference (WC), waist-height ratio (WHtR), visceral adiposity index (VAI), a body shape index (ABSI) and weight-adjusted waist index (WWI). RESULTS: Among the total subjects, 625 715 individuals (15.4%) developed NODM during median 10-year follow-up. The fourth quartile of WHtR showed the highest HR for NODM compared with the first quartile among various indices across the entire population (HR 2.54, 95% CI 2.52 to 2.57). In men, WHtR consistently exhibited the strongest association with NODM across all age groups in analysis based on 1 SD increase; ages 20-39 years (HR 1.54, 95% CI 1.53 to 1.55), ages 40-59 years (HR 1.39, 95% CI 1.38 to 1.39), ages 60-79 years (HR 1.23, 95% CI 1.22 to 1.24). In women, the most relevant body composition index for NODM varied by age group; BMI for ages 20-39 years (HR 1.48, 95%CI 1.47 to 1.49), WHtR for ages 40-59 years (HR 1.46, 95% CI 1.45 to 1.47) and WC for ages 60-79 years (HR 1.23, 95%CI 1.22 to 1.24). CONCLUSION: WHtR was the strongest predictor of NODM in men across all ages, while the relevant indices varied by age group in women. These findings highlight the need for sex- and age-specific body composition assessments in predicting NODM risk.

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