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Disordered eating (DE) is associated with elevated cardiometabolic risk (CMR) factors, yet little is known about this association in non-Western countries. We examined the association between DE characteristics and CMR and tested the potential mediating role of BMI. This cross-sectional study included 2005 Chinese women (aged 18–50 years) from the 2015 China Health and Nutrition Survey. Loss of control, restraint, shape concern and weight concern were assessed using selected questions from the SCOFF questionnaire and the Eating Disorder Examination-Questionnaire. Eight CMR were measured by trained staff. Generalised linear models examined associations between DE characteristics with CMR accounting for dependencies between individuals in the same household. We tested whether BMI potentially mediated significant associations using structural equation modelling. Shape concern was associated with systolic blood pressure (β (95 % CI) 0·06 (0·01, 0·10)), diastolic blood pressure (DBP) (0·07 (95 % CI 0·03, 0·11)) and high-density lipoprotein (HDL)-cholesterol (–0·08 (95 % CI –0·12, −0·04)). Weight concern was associated with DBP (0·06 (95 % CI 0·02, 0·10)), triglyceride (0·06 (95 % CI 0·02, 0·10)) and HDL-cholesterol (–0·10 (95 % CI –0·14, −0·07)). Higher scores on DE characteristics were associated with higher BMI, and higher BMI was further associated with lower HDL-cholesterol and higher other CMR. In summary, we observed significant associations between shape and weight concerns with some CMR in Chinese women, and these associations were potentially partially mediated by BMI. Our findings suggest that prevention and intervention strategies focusing on addressing DE could potentially help reduce the burden of CMR in China, possibly through controlling BMI. [ABSTRACT FROM AUTHOR]

The association of body mass index (BMI) with blood pressure may be stronger in Asian than non-Asian populations, however, longitudinal studies with direct comparisons between ethnicities are lacking. We compared the relationship of BMI with incident hypertension over approximately 9.5 years of follow-up in young (24-39 years) and middle-aged (45-64 years) Chinese Asians (n=5354), American Blacks (n=6076) and American Whites (n=13451). We estimated risk differences using logistic regression models and calculated adjusted incidences and incidence differences. To facilitate comparisons across ethnicities, standardized estimates were calculated using mean covariate values for age, sex, smoking, education and field center, and included the quadratic terms for BMI and age. Weighted least-squares regression models with were constructed to summarize ethnic-specific incidence differences across BMI. Wald statistics and p-values were calculated based on chi-square distributions. The association of BMI with the incidence difference for hypertension was steeper in Chinese (p<0.05) than in American populations during young and middle-adulthood. For example, at a BMI of 25 vs 21 kg/m2 the adjusted incidence differences per 1000 persons (95% CI) in young adults with a BMI of 25 vs those with a BMI of 21 was 83 (36- 130) for Chinese, 50 (26-74) for Blacks and 30 (12-48) for Whites; among middle-aged adults it was 137 (77-198) for Chinese, 49 (9-88) for Blacks and 54 (38-69) for Whites. Whether hypertension carries the same level of risk of stroke or cardiovascular disease across national or ethnic groups remains uncertain.

Age, family history, and body mass index (BMI) influence the prevalence of hypertension, but very little is known about the interplay of these factors in Chinese populations. The authors examined this issue in Chinese adults (n = 4104) in the People's Republic of China Study. In young adults (24-39 years), the prevalence of hypertension/1000 persons (95% confidence interval [CI]) at the referent BMI was greater among subjects with a parental history of hypertension (35; 15-54) compared with those without (7; 3-11). Among middle-aged (40-71 years) adults, the prevalence of hypertension was similar regardless of parental history; however, the effect of BMI was modified by parental history status. For example, at BMI = 25 kg/m(2), the prevalence difference/1000 persons was 375 (95% CI = 245-506) and 97 (95% CI = 51-144) among subjects with and without a parental history, respectively. These large differences call for further investigation of the genetic and environmental factors that could be driving this interaction.

Background: The associations between adiposity and metabolic risk factors have been suggested to vary across ethnicities. Studies in Caucasians have shown that after adjusting for waist circumference and body mass index (BMI), a larger hip circumference may be protective for metabolic risk factors. To our knowledge, these associations have never been examined in a Chinese population., Methods: Baseline (1987-1988) and follow-up (1993-1994) data were from the People's Republic of China Study (n = 1,144 men, n = 1,776 women). Logistic models were stratified by sex and adjusted for age, smoking, center, and education. Incidence differences (ID) comparing the sex specific 85(th) percentile to the 15(th) percentile of hip circumference were computed for elevated blood pressure, blood glucose and triglycerides, low high-density lipoprotein cholesterol (HDL-C), and multiple metabolic abnormalities (three or more of the aforementioned)., Results: In models adjusted for waist circumference and BMI, the ID [95% confidence interval (CI)] per 1,000 persons associated with a 12-cm larger hip were -132 (-237, -26) for low HDL-C; -85 (-138, -31) for elevated triglycerides; and -49 (-83, -4) for multiple metabolic abnormalities. In males, a larger hip circumference was not associated with a reduction of incident risk factors, although the ID tended to be negative., Conclusions: In Chinese women, greater mass in the lower trunk region was inversely associated with incident high triglycerides, low HDL-C, and multiple metabolic abnormalities when adjusted for general and central adiposity. This association was not detected in men. Additional research is needed to better understand the mechanisms by which fat at different depots results in differential risk.