The Journal of Practical Medicine ›› 2026, Vol. 42 ›› Issue (10): 1729-1736.doi: 10.3969/j.issn.1006-5725.2026.10.006

• Chronic Disease Control • Previous Articles    

Association and clustering of overweight/obesity with cardiometabolic risks in adults in Guangxi: A cross-sectional study of 100,000 health examination participants

Chaochun WU(),Yu PANG,Fatian LI,Jirong BAO   

  1. Health Management Center,the People's Hospital of Guangxi Zhuang Autonomous Region,Nanning 530021,Guangxi,China
  • Received:2026-02-26 Online:2026-05-25 Published:2026-05-27
  • Contact: Chaochun WU E-mail:n6wcc@126.com

Abstract:

Objective To investigate the prevalence of overweight/obesity and its association with cardiometabolic risk factors among adults in Guangxi and provide evidence for regional weight management and cardiometabolic disease prevention. Methods A cross-sectional study recruited 108,804 adults who underwent health examinations at the People's Hospital of Guangxi Zhuang Autonomous Region from January to December 2024. The participants were classified according to BMI into underweight, normal weight, overweight, and obese groups. Multivariate logistic regression, stratified and interaction analyses, risk factor clustering, and Cochran–Armitage trend tests were carried out. Results The prevalence rates of overweight, obesity, and central obesity were 35.95%, 13.30% (combined 49.25%), and 26.6%, respectively. Overweight/obesity was independently associated with hypertension, hyperglycemia, dyslipidemia, and fatty liver, and the strongest association was observed for fatty liver (obese group: OR = 25.03, 95%CI: 23.66–26.48, adjusted for age and sex). The combined analysis of BMI and central obesity indicated that individuals with both overweight/obesity and central obesity had the highest metabolic risks, with odds ratios (ORs) (95% confidence intervals [CI]) of 3.48 (3.33–3.63) for hypertension, 3.35 (3.17–3.55) for hyperglycemia, 2.76 (2.66–2.86) for dyslipidemia, and 14.18 (13.64–14.74) for fatty liver. Sex-stratified analyses disclosed stronger associations of overweight/obesity with hyperglycemia and fatty liver in women, and with dyslipidemia and hypertension in men (all interaction P < 0.05). Age-stratified analyses demonstrated the strongest associations in the 18–29 age group, and these associations declined with age (interaction P < 0.001). From underweight to obesity, the mean number of risk factors increased from 0.32 to 2.22, and the proportion of individuals with ≥3 risk factors rose from 0.45% to 36.92% (trend χ2 = 27753.48, P < 0.001). Conclusions The prevalence of overweight and obesity is notably high among adults in Guangxi. This high prevalence acts as a crucial driver of cardiometabolic risk factor clustering, and there are significant sex-and age-related differences in these associations. Additionally, the co-occurrence of overweight/obesity and central obesity synergistically exacerbates metabolic risks. Therefore, targeted weight management and comprehensive prevention strategies customized to regional characteristics are necessary.

Key words: Guangxi, overweight, obesity, cardiometabolic risk factors, cross-sectional study

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