Feiyan Liu

Comparison of body mass index, waist circumference, conicity index, and waist-to-height ratio for predicting incidence of hypertension: the rural Chinese cohort study

This study compared the ability of body mass index (BMI), waist circumference (WC), conicity index, and waist-to-height ratio (WHtR) to predict incident hypertension and to identify the cutoffs of obesity indices for predicting hypertension in rural Chinese adults. This prospective cohort study recruited 9905 participants aged 18–70 years during a median follow-up of 6 years in rural China. Logistic regression and receiver operating characteristic (ROC) curve analyses were used to assess the association, predictive ability, and optimal cutoffs (in terms of hypertension risk factors) of the four obesity indices: BMI, WC, conicity index, and WHtR. The 6-year cumulative incidence of hypertension was 19.89% for men and 18.68% for women, with a significant upward trend of increased incident hypertension with increasing BMI, WC, conicity index, and WHtR (P for trendu2009<u20090.001) for both men and women. BMI and WHtR had the largest area under the ROC curve for identifying hypertension for both genders. The optimal cutoff values for BMI, WC, conicity index, and WHtR for predicting hypertension were 22.65u2009kg/m2, 82.70u2009cm, 1.20, and 0.49, respectively, for men, and 23.80u2009kg/m2, 82.17u2009cm, 1.20, and 0.52, respectively, for women. BMI, WC, conicity index, and WHtR cutoffs may offer a simple and effective way to screen hypertension in rural Chinese adults. BMI and WHtR were superior to WC and conicity index for predicting incident hypertension for both genders.

A J-shaped relation of BMI and stroke: systematic review and dose–response meta-analysis of 4.43 million participants

BACKGROUND AND AIMnMany studies have shown increased risk of stroke with greater adiposity as measured by body mass index (BMI), but questions remain about the shape of the dose-response relation. We conducted a systematic review and meta-analysis of prospective studies to clarify the strength and shape of the dose-response relation between BMI and risk of stroke.nnnMETHODS AND RESULTSnPubMed and Embase databases were searched for articles published up to May 11, 2018. Random-effects generalized least-squares regression models were used to estimate study-specific dose-response association, and restricted cubic splines were used to model the association. We included reports of 44 prospective cohort studies describing 102xa0466 incident cases among 4xa0432xa0475 participants. With a 5-unit increment in BMI, the summary relative risk for stroke incidence was 1.10 (95% confidence interval, 1.06 to 1.13; I2xa0=xa088.0%). The dose-response relation was J-shaped (Pnon-linearity <0.001). The risk was not increased at the low BMI range (<24xa0kg/m2), but was increased within the high BMI range (>25xa0kg/m2).nnnCONCLUSIONnBoth overweight and obesity increase the risk of stroke with a J-shaped dose-response relation, and the nadir of the curve was observed at BMI 23-24xa0kg/m2.

Association of long-term dynamic change in body weight and incident hypertension: The Rural Chinese Cohort Study

OBJECTIVESnThe association of long-term dynamic change in body weight and incident hypertension among general Chinese adults is still unknown. The aim of this study was to evaluate the hypertension risk in a large prospective study of rural Chinese adult using relative weight gain or loss.nnnMETHODSnA total of 10 149 nonhypertensive Chinese adults 18 to 75 y of age completed a questionnaire interview and anthropometric and laboratory measurements at both baseline (2007-2008) and follow-up (2013-2014). Participants were divided into five categories based on relative weight change. Logistic regression analysis was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for hypertension risk by categories of weight change.nnnRESULTSnDuring 6 y of follow-up, about one-third of the participants retained a stable weight (33.3%) or gained >6% (32.7%). Only 7.9% lost >6% weight. For every 1% increase in relative body weight, systolic and diastolic blood pressures increased 0.27 and 0.22u2009mm Hg, respectively. Risk for hypertension was reduced and increased with weight loss >6% (OR, 0.78; 95% CI, 0.61-0.99) and gain >6% (OR, 2.08; 95% CI, 1.79-2.42), respectively, compared with weight loss or gain ≤3%. With baseline prehypertension, compared with maintaining a stable weight, weight loss >6% reduced the risk for hypertension (OR, 0.71; 95% CI, 0.54-0.95). With baseline overweight, compared with maintaining the overweight status during follow-up, changing to normal weight reduced the risk for hypertension (OR, 0.67; 95% CI, 0.49-0.92), but changing to general obesity increased the risk (OR, 1.73; 95% CI, 1.35-2.22).nnnCONCLUSIONSnLong-term excessive weight gain is positively associated with increased risk for incident hypertension. Losing weight by lifestyle modification could be helpful for the primary prevention of hypertension in the general rural Chinese population.

Association of hypertension with parity and with the interaction between parity and body mass index in rural Chinese women

A cross-sectional study was conducted; information for 9247 women living in rural China was collected by questionnaire interview and anthropometric and laboratory measurements during July to August 2013 and July to October 2014. Multiple logistic regression analysis was used to examine the association between parity and hypertension, estimating odds ratios and 95% confidence intervals (CIs). The biological interaction between parity and body mass index was estimated by the relative excess risk due to interaction, attributable proportion due to the interaction, and synergy index. In our study, the prevalence of multiparity and hypertension was 93.10% and 22.90% in premenopausal women and 98.04% and 51.06% in postmenopausal women, respectively. For premenopausal women, parity hypertension was not associated with hypertension. And for postmenopausal women, as compared with para 0-1 status, para 2, 3, 4, andxa0≥xa05 were positively associated with hypertension: adjusted odds ratios (95% CI) was 2.04 (1.24-3.38), 2.25 (1.32-3.82), 2.41 (1.34-4.36), and 2.10 (1.04-4.22), respectively. The interaction effect between multiparity and overweight/obesity on hypertension was additive (relative excess risk due to interaction [95% CI]: 1.59, 0.19-3.00; attributable proportion due to the interaction [95% CI]: 0.34, 0.02-0.67) only in postmenopausal women. Parity was independently related to hypertension, and the interaction effect between multiparity and overweight/obesity on hypertension was additive in rural postmenopausal women.

Body mass index and risk of all-cause mortality with normoglycemia, impaired fasting glucose and prevalent diabetes: results from the Rural Chinese Cohort Study

Background Previous evidence of an association between body mass index (BMI) and mortality in patients with diabetes was inconsistent. The BMI–mortality association with normal fasting glucose (NFG), impaired fasting glucose (IFG) and prevalent diabetes is still unclear in the Chinese population. Methods We analysed data for 17u2009252 adults from the Rural Chinese Cohort Study during 2007–2008 and followed for mortality during 2013–2014. Participants were classified with NFG, IFG and diabetes according to baseline measurement values of fasting glucose and self-reported diabetes. Multivariable Cox proportional hazard models were used to calculate HRs and 95% CIs across BMI categories by glycemic status. Results During the 6-year follow-up, 1109 participants died (563/10 181 with NFG, 349/5572 with IFG and 197/1499 with diabetes). The BMI–mortality association was curvilinear, with low BMI (even in normal range) associated with increased mortality regardless of glycemic status. In adjusted Cox models, risk of mortality showed a decreasing trend with BMI≤18u2009kg/m2, 18<BMI≤20u2009kg/m2 and 20<BMI≤22u2009kg/m2 vs 22<BMI≤24u2009kg/m2: HR 2.83 (95% CI 1.78 to 4.51), 2.05 (1.46 to 2.87) and 1.45 (1.10 to 1.90), respectively, for NFG; 2.53 (1.25 to 5.14), 1.36 (0.86 to 2.14) and 1.09 (0.76 to 1.57), respectively, for IFG; and 4.03 (1.42 to 11.50), 2.00 (1.05 to 3.80) and 1.52 (0.88 to 2.60), respectively, for diabetes. The risk of mortality was lower for patients with diabetes who were overweight or obese versus normal weight. Conclusions Low BMI was associated with increased mortality regardless of glycemic status. Future studies are needed to explain the ‘obesity paradox’ in patients with diabetes.

Dose-response association between the triglycerides: High-density lipoprotein cholesterol ratio and type 2 diabetes mellitus risk: The rural Chinese cohort study and meta-analysis: TG/HDL-C ratio and T2DM

High triglyceride (TG) and low high‐density lipoprotein cholesterol (HDL‐C) levels are traditional risk factors for type 2 diabetes mellitus (T2DM). This study evaluated the dose–response relationship between the TG/HDL‐C ratio and T2DM risk.

Sleep Duration Interacts With Lifestyle Risk Factors and Health Status to Alter Risk of All-Cause Mortality: The Rural Chinese Cohort Study

STUDY OBJECTIVESnMany studies suggest an association of both short and long sleep duration with all-cause mortality, but the effect of co-occurrence of sleep duration and other lifestyle risk factors or health status remains unclear.nnnMETHODSnA total of 17,184 participants aged 18 years or older from rural areas of China were examined at baseline from 2007 to 2008 and followed up from 2013 to 2014. Cox proportional hazard models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI).nnnRESULTSnDuring 6-year follow-up, we identified 1,101 deaths. The multivariable-adjusted mortality risk was significantly higher with short-duration sleepers (< 6.5 hours) (HR = 1.37, 95% CI 1.01-1.86) and long-duration sleepers (≥ 9.5 hours) (HR = 1.35, 95% CI 1.05-1.74) versus 6.5-7.5 hours. The multiplicative interaction of long sleep duration with some lifestyle risk factors and health statuses increased the mortality risk in men (low level of physical activity: HR = 1.03, 95% CI 1.02-1.04; hypertension: HR = 1.06, 95% CI 1.04-1.09; type 2 diabetes mellitus [T2DM]: HR = 1.07, 95% CI 1.04-1.11). Similar results were found in women (low level of physical activity: HR = 1.03, 95% CI 1.02-1.05; T2DM: HR = 1.07, 95% CI 1.05-1.10).nnnCONCLUSIONSnSleep duration could be a predictor of all-cause mortality and its interaction with physical activity, hypertension, and T2DM may increase the risk of mortality.

Chocolate consumption and risk of cardiovascular diseases: a meta-analysis of prospective studies

Objective Studies investigating the impact of chocolate consumption on cardiovascular disease (CVD) have reached inconsistent conclusions. As such, a quantitative assessment of the dose–response association between chocolate consumption and incident CVD has not been reported. We performed a systematic review and meta-analysis of studies assessing the risk of CVD with chocolate consumption. Methods PubMed and EMBASE databases were searched for articles published up to 6 June 2018. Restricted cubic splines were used to model the dose–response association. Results Fourteen publications (23 studies including 405u2009304 participants and 35u2009093 cases of CVD) were included in the meta-analysis. The summary of relative risk (RR) per 20u2009g/week increase in chocolate consumption was 0.982 (95% CI 0.972 to 0.992, I2=50.4%, n=18) for CVD (heart failure: 0.995 (0.981 to 1.010, I2=36.3%, n=5); total stroke: 0.956 (0.932 to 0.980, I2=25.5%, n=7); cerebral infarction: 0.952 (0.917 to 0.988, I2=0.0%, n=4); haemorrhagic stroke: 0.931 (0.871 to 0.994, I2=0.0%, n=4); myocardial infarction: 0.981 (0.964 to 0.997, I2=0.0%, n=3); coronary heart disease: 0.986 (0.973 to 0.999, n=1)). A non-linear dose–response (pnon-linearity=0.001) indicated that the most appropriate dose of chocolate consumption for reducing risk of CVD was 45u2009g/week (RR 0.890;95%CI 0.849 to 0.932). Conclusions Chocolate consumption may be associated with reduced risk of CVD at <100u2009g/week consumption. Higher levels may negate the health benefits and induce adverse effects associated with high sugar consumption.

MFGE8 polymorphisms are significantly associated with metabolism-related indicators rather than metabolic syndrome in Chinese people: A nested case–control study

BACKGROUNDnThe correlation between single nucleotide polymorphisms (SNPs) of milk fat globule-epidermal growth factor 8 (MFGE8) and metabolic syndrome (MetS) and metabolism-related indicators are limited. The present study explored the relation in Chinese adults.nnnMETHODSnWe conducted a nested case-control study based on the Rural Chinese Cohort Study including 408 people with MetS and 408 controls matched by baseline sex, age (±2u202fyears), marital status, and residence village. Four polymorphisms were selected and genotyped by using the SNPscan Genotyping system. Conditional logistic regression was used to estimate the association of MFGE8 polymorphisms with MetS incidence, and linear regression was used to assess the association with metabolism-related indicators in controls.nnnRESULTSnWe found no significant association of MFGE8 SNPs with MetS incidence or systolic blood pressure, or triglycerides level, or fasting plasma glucose (Pu202f>u202f0.05). However, MFGE8 rs4932450 was negatively associated with high-density lipoprotein cholesterol (HDL-C) level under the dominant model (βu202f=u202f-0.0218, Pu202f=u202f0.007) and the additive model (βu202f=u202f-0.0175, Pu202f=u202f0.012) and positively associated with diastolic blood pressure (DBP) under the recessive model (βu202f=u202f4.8848, Pu202f=u202f0.011). The rs3784751 SNP was associated with increased waist circumference (WC) in controls (βu202f=u202f0.0307, Pu202f=u202f0.028).nnnCONCLUSIONSnMFGE8 polymorphisms were not associated with MetS but were related to DBP, HDL-C level, and WC in Chinese adults.

CD36 gene variants is associated with type 2 diabetes mellitus through the interaction of obesity in rural Chinese adults

BACKGROUNDnEvidences show that cluster determinant 36 (CD36) protein plays a role in lipid metabolism and insulin resistance, and the expression of CD36 is inducible in obesity. The present study evaluated the association of CD36 variants and the interaction with obesity on type 2 diabetes mellitus (T2DM) risk.nnnMETHODSnWe performed a case-control study nested in the Rural Chinese Cohort Study. We included 546 incident T2DM cases matched with non-T2DM controls in a 1:1 ratio by sex, age (within 2u202fyears), marital status, and residence village. Four loci in CD36 (rs1194197, rs2151916, rs3211956, and rs7755) were genotyped by SNPscanTM Genotyping system.nnnRESULTSnAfter adjusting for potential confounding, we observed no statistically significant association between the CD36 polymorphisms and T2DM risk. Compared to wild-type homozygous carriers with normal weight, overweight/obesity participants carrying the mutational allele rs7755 showed increased risk of T2DM, by 114% (ORu202f=u202f2.14, 95% CI: 1.33-3.46; Pinteractionu202f=u202f0.007); abdominal obesity participants carrying the mutational allele rs7755 showed increased risk of T2DM, by 133% (ORu202f=u202f2.33, 95% CI: 1.48-3.66; Pinteractionu202f=u202f0.002). Furthermore, rs2151916 polymorphism was associated with triglycerides level (Pu202f=u202f0.019), and the rs1194197 variant was related to systolic blood pressure (Pu202f=u202f0.023) within the group of controls.nnnCONCLUSIONSnCD36 genotypes were not associated with the progression to T2DM independently. However, our results suggested a positive interaction between the CD36 variants and obesity on T2DM susceptibility, which might be through a cardiometabolic disorder.