Relationship between obesity indicators and hypertension-diabetes comorbidity among adults: a population study from Central China.

OBJECTIVE: To identify the relationship between obesity indicators and hypertension-diabetes comorbidity (HDC) among adults in central China. DESIGN AND SETTING: A cross-sectional study was conducted from 1 June 2015 to 30 September 2018 in 11 districts of Hubei Province, China. PARTICIPANTS: A total of 29 396 participants aged 18 years or above were enrolled in the study. 2083 subjects with missing data were excluded. Eventually, 25 356 participants were available for the present analysis. MAIN OUTCOME MEASURES: Data were subjected to univariable and multivariable logistic regression to examine the association between obesity indicators (body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR)) and HDC prevalence. Crude odds ratio and adjusted OR (AOR) with associated 95% CI were calculated. RESULTS: Overall, 2.8% of the respondents had HDC. The odds of HDC prevalence increased with the BMI of the participants (18.5≤BMI (kg/m2)≤23.9-1; 24≤BMI (kg/m2)≤26.9-AOR: 5.66, 95% CI: 4.25 to 7.55; BMI (kg/m2)≥27-AOR: 7.96, 95% CI: 5.83 to 10.87). The risk of HDC also increased with the WHtR of participants (WHtR≤P25-1; P25≤WHtR≤P50-AOR: 1.73, 95% CI: 1.10 to 2.71; P50 ≤WHtR≤P75-AOR: 2.51, 95% CI: 1.60 to 3.92; WHtR≥P75-AOR: 3.22, 95% CI: 2.01 to 5.16). Stratified analysis by gender showed that high BMI and WHtR were risk factors of HDC in males and females. However, the odds of HDC prevalence increased only when WHtR≥P75 in males, whereas the probability of HDC increased when WHtR≥ P25 in females. CONCLUSION: High BMI and WHtR can increase the risk of HDC among Chinese adults. Reasonable control of BMI and WHtR may be beneficial in preventing HDC. Females should focus on maintaining an optimal WHtR earlier.

Combined Effects of Obesity and Dyslipidaemia on the Prevalence of Diabetes Amongst Adults Aged ≥45 Years: Evidence from a Nationally Representative Cross-Sectional Study.

Objectives: This study aimed to explore the combined effects of different types of obesity and dyslipidaemia on the prevalence of diabetes in middle-aged and elderly residents. Methods: Data were obtained from the 2015 China Health and Retirement Longitudinal Studydatabase, and 5023 valid participants were included after excluding those with missing data. A Chi-square test was used to test the difference in the prevalence of diabetes between the groups. Binary logistic regression was used to analyse the relationship between different types of obesity combined with dyslipidaemia and the prevalence of diabetes. Results: Multivariate logistic regression analysis showed that, compared with those with a body mass index <24/ortholiposis, the subgroup with systemic obesity/dyslipidaemia had 4.37 times the risk of diabetes (OR = 4.37, 95% CI = 2.36−8.10, p < 0.001). In addition, compared with those with a normal waist circumference (WC)/ortholiposis, the subgroup with abdominal obesity/dyslipidaemia had 3.58 times the risk of diabetes (OR = 3.58, 95% CI = 2.49−5.13, p < 0.001). Conclusions: The coexistence of obesity and dyslipidaemia can significantly increase the risk of diabetes, suggesting that the strict control of weight, WC and lipid level is beneficial to the prevention of diabetes.

Impact of Sociodemographic Characteristics, Lifestyle, and Obesity on Coexistence of Diabetes and Hypertension: A Structural Equation Model Analysis amongst Chinese Adults.

BACKGROUND: In general, given the insufficient sample size, considerable literature has been found on single studies of diabetes and hypertension and few studies have been found on the coexistence of diabetes and hypertension (CDH) and its influencing factors with a large range of samples. This study aimed to establish a structural equation model for exploring the direct and indirect relationships amongst sociodemographic characteristics, lifestyle, obesity, and CDH amongst Chinese adults. METHODS: A cross-sectional study was conducted in a representative sample of 25356 adults between June 1, 2015, and September 30, 2018, in Hubei province, China. Confirmatory factor analysis was initially conducted to test the latent variables. A structural equation model was then performed to analyse the association between latent variables and CDH. RESULTS: The total prevalence of CDH was 2.8%. The model paths indicated that sociodemographic characteristics, lifestyle, and obesity were directly associated with CDH, and the effects were 0.187, 0.739, and 0.353, respectively. Sociodemographic characteristics and lifestyle were also indirectly associated with CDH, and the effects were 0.128 and 0.045, respectively. Lifestyle had the strongest effect on CDH (ß = 0.784, P < 0.001), followed by obesity (ß = 0.353, P < 0.001) and sociodemographic characteristics (ß = 0.315, P < 0.001). All paths of the model were significant (P < 0.001). CONCLUSION: CDH was significantly associated with sociodemographic characteristics, lifestyle, and obesity amongst Chinese adults. The dominant predictor of CDH was lifestyle. Targeting these results might develop lifestyle and weight loss intervention to prevent CDH according to the characteristics of the population.