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Background: To assess the associations of platelet traits and obesity indices with aging biomarkers (telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN))., Methods: A cross-sectional study was performed among 5091 rural Chinese adults. Obesity indices (waist circumference (WC), waist-to-hip ratio (WHR) and waist-to-height ratio (WHtR)) and platelet traits (plateletcrit (PCT), platelet large cell ratio (P-LCR), mean platelet volume (MPV) and platelet distribution width (PDW)) were collected by physical examination. The aging biomarkers were determined by quantitative real-time polymerase chain reaction. Generalized linear regression models and mediation analysis were applied to explore the relationships between platelet traits, obesity indices, and aging biomarkers., Results: The mean age of the participants was 56 years (range: 18-79). Each one-unit increment in WC, WHR and WHtR were related to a 0.316 (95% confidence interval (CI): -0.437, -0.196), 0.323 (95% CI: -0.513, -0.134) and 0.277 (95% CI: -0.400, -0.153) decrease in relative TL; or a 0.102 (95% CI: -0.197, -0.007), 0.109 (95% CI: -0.258, -0.041) and 0.101 (95% CI: -0.199, -0.004) decrease in relative mtDNA-CN. The proportions of obesity indices with aging biomarkers mediated by platelet indices ranged from 2.85% to 10.10%., Conclusions: Increased central obesity indices in relation to shortened relative TL or decreased mtDNA-CN were mediated by platelet traits, indicating that obesity in association with the accelerated aging process may be partially attributable to abnormal platelet activity.

Background and Aims: Janus kinase 2 (JAK2) play an important role in the energy metabolism. Whether there is a causal relationship between JAK2 methylation levels and obesity remains unclear. Based on the instrumental variables of 5 SNP sites, this study was aimed to explore the causal relationship between JAK2 methylation levels and obesity by Mendelian randomization analysis., Methods and Results: A total of 1021 participants (511 cases and 510 controls defined by body mass index (BMI) ≥ 28.0 kg/m 2 ) was conducted from the Henan Rural Cohort study. SNPscan® was performed to test the SNP genotyping and MethylTarget™ was applied to detect the DNA methylation level. The logistic regression model was used to evaluate the associations between SNP or methylation of JAK2 and obesity (according to BMI). Mendelian randomization analysis was used to assess the potential causal association between JAK2 methylation and obesity. According to the logistic regression model, 1 CpG sit in the promotor was related to an increased risk of obesity (P < 0.05). 10 CpG sites in the exon were associated with decreased risk of obesity (P < 0.05). Mendelian randomization analysis showed a causal association between the methylated level of JAK2 and obesity, based on the instrumental variables of 5 SNPs (P < 0.05)., Conclusions: This study supported that the methylation degree of JAK2 has a complex relationship with obesity, which might be related to the region of methylation. A causal relationship exists between the methylated level of JAK2 and obesity., Competing Interests: Declaration of competing interest All authors had declared no conflict of interest., (Copyright © 2021 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Although obesity reflected by BMI can enhance the association of air pollution with increase blood pressures (BP) and prevalent hypertension in susceptible population, there remains lack evidence on interactive effects of different obesity indices and air pollutants on BP and prevalent hypertension in rural adults. 39,259 individuals were recruited from the Henan Rural Cohort. Concentrations of air pollutants (PM 1 , PM 2.5 , PM 10 and NO 2 ) were evaluated by a spatio-temporal model based on satellites data. Independent associations of air pollutants and obesity reflected by BMI, WC, WHR, WHtR, BFP and VFI on BP indicators (SBP, DBP, MAP and PP) and prevalent hypertension were analyzed by linear regression and logistic regression models, respectively. Furthermore, their additive effects were quantified by RERI, AP and S. Six obesity indices enhanced the associations of four air pollutants and BP indicators. Individuals with high PM 1 concentrations plus obesity classified by BMI, WC, WHR, WHtR, BFP and VFI had a 4.18-fold (95% CI: 3.86, 4.53), 3.58-fold (95% CI: 3.34, 3.84), 3.53-fold (95% CI: 3.28, 3.81), 4.02-fold (95% CI: 3.72, 4.35), 3.89-fold (95% CI: 3.59, 4.23), 3.87-fold (95% CI: 3.62, 4.14) increase in prevalent hypertension, respectively, compared to non-obese individuals with low PM 1 concentrations; similar results were observed for combined effect of PM 2.5 , PM 10 or NO 2 and obesity indices on prevalent hypertension. The significant values of RERI, AP and S indicated additive effects of air pollutants and obesity indices on hypertension. Obesity amplified the effects of exposure to high levels of air pollutants on increased BP values and prevalent hypertension, implying that obese individuals may be susceptible to elevate BP and prevalent hypertension in relation to air pollution exposure. CLINICAL TRIAL REGISTRATION: The Henan Rural Cohort study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699, http://www.chictr.org.cn/showproj.aspx?proj=11375)., Competing Interests: Conflicts of interest All authors had declared no conflict of interest., (Copyright © 2021 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.)

Background: Although independent association of socioeconomic status (SES) or physical activity (PA) with obesity has been well-documented in urban settings, their independent and joint associations on obesity measures are limited in rural regions. Methods: Almost 38,000 ( n = 37,922) individuals were included from the Henan Rural Cohort Study. The International Physical Activity Questionnaire (IPAQ) was used to evaluate PA. Obesity was reflected by body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). The independent and interactive effects of SES and PA on obesity were analyzed by logistic regression models and generalized linear regression models, respectively. Results: Compared with high education level, the OR (95%CI) of obesity defined by BMI with low education level was 1.466 (1.337, 1.608), 1.064 (0.924, 1.225), and 1.853 (1.625, 2.114) in total population, men and women, respectively. Besides, the OR (95%CI) of obesity defined by BMI associated with per capita monthly income were 1.089 (1.015, 1.170), 1.192 (1.055, 1.347), 1.038 (0.951, 1.133) in total population, men and women, respectively. Similar results had been observed in other obesity measures. Negative interactive association of low education level and PA on obesity measures were observed only in women (all P < 0.05). Conclusions: This study suggests that women are more susceptible to obesity concerning low SES and that adequate PA may be a potential target for mitigating the negative effect of low SES on obesity in women. Clinical Trial Registration: The Henan Rural Cohort Study has been registered at Chinese Clinical Trial Register (Registration number: ChiCTR-OOC-15006699) http://www.chictr.org.cn/showproj.aspx?proj=11375., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Pan, Tu, Gu, Li, Liu, Chen, Yu, Wang, Mao, Huo, Hou and Wang.)

Background and Aim: The present study was conducted to explore the stratified and joint effects of age at menopause and body mass index (BMI) with the risk of type 2 diabetes mellitus (T2DM) in Chinese rural adults., Methods and Results: A total of 15,406 postmenopausal Chinese women were included in this study. Multivariable logistic regression analysis was used to quantify the stratified and joint effects of age at menopause and BMI on T2DM. Overall, the mean age at menopause and BMI was 48.8 ± 4.7 years and 25.1 ± 3.6 kg/m 2 , respectively. In general, data suggest that: 1) women with BMI ≥ 24 had a higher risk of T2DM, irrespective of age at menopause; 2) in women with BMI < 24, later menopause had a higher risk of T2DM (OR, 1.52; 95% CI, 1.16-2.01); 3) the risk of T2DM was higher only in patients with early or normal age at menopause and BMI ≥ 24, with 0R (95% CI) of (1.58, 1.28-1.94) and (1.48, 1.31-1.67), respectively., Conclusion: Our findings suggest that: 1) women with BMI ≥ 24 had a higher risk of T2DM, irrespective of age at menopause; 2) in women with BMI < 24, a higher risk of T2DM was found only in those with later menopause; 3) women with later menopause had a higher risk of T2DM, irrespective of BMI; 4) in patients with early or normal age at menopause, a higher risk of T2DM was found only in patients with BMI ≥ 24., The Chinese Clinical Trial Registration: ChiCTR-OOC-1500669(URL:http://www.chictr.org.cn/showproj.aspx?proj=11375)., (Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.)

Association between long-term exposure to ambient air pollution and obesity remains inconclusive, and the evidence from rural areas was limited. Thus, this study aimed to assess the association between ambient air pollution and obesity based on different anthropometric indices in Chinese rural adults, and further to compare the effect sizes of different air pollution types. A total of 38,824 participants (aged 18-79 years) were recruited from the Henan Rural Cohort Study. Logistic and multivariable linear regression model were used to examine the association between ambient air pollution exposure (including particulate matter with aerodynamic diameters ≤ 1.0 μm (PM 1 ), ≤2.5 μm (PM 2.5 ), and ≤10 μm (PM 10 ), and nitrogen dioxide (NO 2 )) and obesity as well as obese anthropometric indices (including body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI)). The potential effect modifications were also examined. Positive associations were found between long-term exposure to PM 1 , PM 2.5 , PM 10 and NO 2 and obesity regardless of how obesity was defined (false discovery rate (FDR) < 0.05). Moreover, BMI, WC, WHR, WHtR, BFP, and VFI displayed increased trends with PM 1 , PM 2.5 , PM 10 and NO 2 concentrations increasing (all FDR<0.05). PM 10 had the largest effects on obesity among the four types of air pollution. The elderly, women, individuals with low level of education and income, and those who had high fat diet were more vulnerable to the adverse effects of air pollution. In addition, the results of the sensitivity analysis showed that those associations between ambient air pollution and obesity remained robust. These findings suggest that long-term exposure to ambient air pollutant (particularly PM 10 ) may be positively associated with obesity in Chinese rural adults, especially among the elderly, women, individuals with low education and income, as well as unhealthy lifestyles., Competing Interests: Declaration of competing interest All authors declare no conflict of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: Vitamin D deficiency was associated with obesity. However, the causal relationship remains controversial. We hypothesized that there would be family-based associations in both vitamin D deficient families and obese families for the SNPs associated with vitamin D deficiency, if vitamin D deficiency was a causal factor of obesity. We aimed to investigate the family-based association of SNPs in CYP27B1 with both vitamin D deficiency and obesity., Methods: Four hundred and nineteen pedigrees containing 1505 rural individuals aged from 18 to 79 years in Henan Province of China were included in this study. Family-based associations of rs10877012 and rs4646536 in CYP27B1 with vitamin D deficiency and obesity were investigated. Serum 25(OH)D3 concentration <20 μg/L was defined as vitamin D deficiency. BMI ≥ 28 kg/m 2 was applied for obesity definition. Taqman assays were applied for SNP genotyping. Family-based associations were investigated with FBAT software., Results: It was shown that vitamin D deficiency was a risk factor of obesity (adjusted OR: 1.332, 95% CI: 1.042-1.703, P = 0.022). Furthermore, there were family-based associations for allele T of rs10877012 and allele T of rs4646536 in both vitamin D deficient families and obese families (P < 0.05). Both rs10877012 and rs4646536 were associated with serum 25(OH)D3 levels between siblings (P < 0.05), but not BMI (P > 0.05). In addition, there is linkage disequilibrium between rs10877012 and rs4646536 (D' = 1.0, r 2  = 0.992)., Conclusion: Vitamin D deficiency may be a causal factor of obesity. Maintaining sufficient vitamin D is beneficial to obesity prevention.

Association between vitamin D receptor (VDR) genetic polymorphism and obesity was observed in several case-control studies. This study hypothesized that these associations could be verified in family-based study. We aimed at investigating the associations between VDR SNPs and obesity (BMI ≥ 28 kg/m 2 ) by case-control study with 688 subjects and family-based study with 419 pedigrees. The results of case-control study suggested that rs3847987 (AC vs CC, Adjusted OR: 1.938, 95% CI: 1.359-2.763, P = 0.000405) was associated with obesity. Allele C of rs3847987 was risk factors for obesity (P = 0.006). Furthermore, association of rs3847987 with BMI was verified in family-based study (Z = 2.077, P = 0.037811). In addition, sibling with AC genotype of rs3847987 had significant higher BMI than CC genotype in the same family (P = 0.03). Therefore, it could be concluded that VDR genetic polymorphism (rs3847987) may be associated with obesity.

Aims: We aimed to investigate the association of serum testosterone with impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM) and calculate the proportion explained by obesity status on the relationship., Materials and Methods: A case-control study including 2775 participants was performed. Serum testosterone was quantified by liquid chromatography-tandem mass spectrometry. Conditional logistic regression and multivariable linear regression were performed to estimate the relationships between testosterone and different glucose status. Waist circumference (WC) was used as a mediator to estimate the mediation effect., Results: After adjusting for multiple variables, serum testosterone levels were negatively associated with T2DM in males (per 1 unit natural log-transformed, odd ratio (OR) = 0.73, 95% confidence interval (CI): 0.56, 0.96; Tertile 3 vs Tertile 1, OR = 0.46, 95% CI:0.29, 0.72) while were positively in females (per 1 unit natural log-transformed, OR = 1.56, 95% CI:1.32, 1.84; Tertile 3 vs Tertile 1, OR = 3.55, 95% CI: 2.22, 5.66). In males, a higher testosterone tended to be associated with a lower fasting plasma glucose level and a weaker HOMA2-IR but a stronger HOMA2-β. Opposite findings were observed in females. Furthermore, WC played a full and partial mediating role in the relationship between testosterone and IFG and T2DM both in males and females., Conclusion: Serum testosterone levels had opposite effects on IFG and T2DM in males and females. With higher serum testosterone levels, the dysglycemia progression was decreased among males while increased among females. In addition, WC played a full and partial mediating role in the relationship between testosterone and IFG and T2DM., (© 2019 John Wiley & Sons, Ltd.)

The study aimed to estimate prevalence and influencing factors of overweight, general obesity, and abdominal obesity in rural areas of China. A total of 39034 participants aged 18 to 79 years were enrolled from the Henan Rural Cohort Study for the cross-sectional study. The age-standardized prevalence of overweight, general obesity, and abdominal obesity were 34.97%, 16.82%, and 43.71% in the general Chinese rural adults, respectively. Gender differences were: 36.04%, 18.98%, 35.37% for men, and 34.55%, 15.42%, 49.13% for women, respectively. The subgroup analysis showed the rates of overweight, general obesity, and abdominal obesity existed considerable disparities, but were universally high in all subgroups. Further, the study found that there were statistically significant U-shaped associations between the prevalence of overweight, general obesity, and abdominal obesity and age groups. In addition, the prevalence of participants with both abnormal BMI and WC were even at approximate forty percent. Aging, married/cohabiting, higher per capita monthly income, and unhealthy lifestyle were independent influencing factors of overweight, general obesity and abdominal obesity. In conclusion, overweight and obesity were severe in rural China. There is an increased need for closely monitoring high risk factors and promoting healthy lifestyle to curb the obesity epidemic among rural population.

Background: Few studies are available on the relationship of androstenedione with inflammation and obesity and the effect of androstenedione and inflammation on the association between testosterone and obesity. This study intended to examine the mediation effect of inflammatory markers on the association of testosterone with obesity and the moderation effect of androstenedione on the association of testosterone with inflammation and obesity in Chinese rural men. Materials and methods: This cross‐sectional research enrolled 2536 male rural inhabitants from the Henan Rural Cohort study. The serum concentrations of testosterone and androstenedione were determined by liquid chromatography–tandem mass spectrometry. Linear and logistic regression were used to examine the relationships between testosterone, inflammatory markers, and obesity. Mediation and moderation analyses were carried out to evaluate the potential effects of inflammatory markers on the relationship between testosterone and obesity, as well as androstenedione on the relationships of testosterone with inflammation and obesity. Results: After adjusting for confounding factors, the results showed that testosterone and androstenedione were negatively related to obesity, and inflammatory markers were positively associated with obesity. Besides, testosterone and androstenedione were negatively associated with inflammatory markers. Mediation analysis showed that white blood cell, neutrophil, monocyte, and high‐sensitivity C‐reactive protein had mediating effects on the association between testosterone and obesity. The most vital mediator was high‐sensitivity C‐reactive protein, and its proportion of the effect was 11.02% (defined by waist circumference), 11.15% (defined by waist‐to‐hip ratio), 12.92% (defined by waist‐to‐height ratio), and full mediating effect (defined by body mass index). Moreover, androstenedione played negative moderation effects on the associations of testosterone with inflammation and obesity. Conclusion: Inflammatory markers and androstenedione were first found to have modifying effects on the association of testosterone with obesity. Higher levels of testosterone and androstenedione could reduce the inflammation level and risk of obesity, indicating their potential roles in the prevention and treatment of chronic diseases. [ABSTRACT FROM AUTHOR]

Background: Although the concentrations of progesterone (P4) and 17-hydroxyprogesterone (17-OHP) have been correlated with some characteristics of metabolic syndrome (MetS), the relationships with MetS are inconclusive. Therefore, we investigated the relationship between P4 and 17-OHP with MetS. Methods: In all, the present study includes 4807 participants. Serum P4 and 17-OHP were measured through liquid chromatography-tandem mass spectrometry. Logistic regression and restricted cubic splines were used to assess the independent and combined effects of P4 and 17-OHP on MetS. Results: After adjusting for multiple variables, the positive association of P4 with MetS was observed in postmenopausal women (Third tertiles vs First tertiles: OR = 1.49, 95% CI: 1.20– 1.86) and the negative association of 17-OHP with MetS was observed in men (Third tertiles vs First tertiles: OR = 0.43, 95% CI: 0.32– 0.58). Compared with the combination of low P4 and low 17-OHP, the combination of high P4 and high 17-OHP were significantly related to MetS in postmenopausal women (OR = 1.71, 95% CI: 1.18– 2.48). Moreover, the combination of low P4 and high 17-OHP was negatively associated with MetS in men (OR = 0.41, 95% CI: 0.24– 0.69). Conclusion: The association between P4 and MetS in postmenopausal women was positive, whereas 17-OHP was negatively associated with MetS in men. Additionally, their combination has a synergistic effect on MetS in postmenopausal women and an antagonistic effect on MetS in men. [ABSTRACT FROM AUTHOR]

Although solid-fuel use or smoking is associated with obesity measured by body mass index (BMI), research on their interactive effects on general and central obesity is limited. Data of 20,140 individuals in the Henan Rural Cohort Study was examined the independent and combined associations of solid-fuel use and smoking with prevalent obesity, which was measured by BMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), body fat percentage (BFP), and visceral fat index (VFI). Multiple adjusted logistic regression models showed that the OR (95% CI) of prevalent obesity measured by BMI associated with exposure to solid fuels alone or with smoking was 0.78 (0.70, 0.86) or 0.46 (0.32, 0.66), compared with neither smoking nor solid-fuel exposure. Similar results had been found in other obese anthropometric indices and in the results of linear regression analysis. The results indicated that solid-fuel use and smoking have a synergistic effect on reduction in obesity indices. The effects of household air pollution from solid-fuel use and smoking on obesity should be considered when exploring the influencing factors of obesity. [ABSTRACT FROM AUTHOR]

Purpose: Studies of progesterone with obesity have been lacking, and no prior studies have investigated progesterone and C-reactive protein in rural natural populations. This study aimed to investigate the association of serum progesterone with obesity based on anthropometric parameters in Henan Rural Cohort, then further to explore the potential role of C-reactive protein in this association. Patients and Methods: A total of 4687 participants (2474 men and 2213 postmenopausal women) from the Henan Rural Cohort study were included. Logistic regression analysis, linear regression analysis, and restricted cubic splines were performed to estimate the relationships between progesterone, C-reactive protein, obesity, and obesity-related parameters. Mediation analysis was carried out to assess the intermediary role of C-reactive protein played in the association between progesterone and obesity. Results: After controlling for confounders, the odds ratios of obesity no matter how obesity was defined was associated with progesterone (P trend < 0.05). Moreover, progesterone was related to obesity-related parameters. Also, C-reactive protein increased with the elevation of progesterone, and C-reactive protein was associated with obesity no matter how obesity was defined (P trend < 0.001). Mediation analysis indicated that hsCRP had the mediating effects on the obesity, and the proportion of the effects were 15.35% and full mediating effect (defined by body mass index), 15.46% and 12.24% (defined by waist circumference), 19.14% and 12.12% (defined by waist-to-hip ratio), 23.81% and 15.09% (defined by waist-to-height ratio) for men and postmenopausal women, relatively. Conclusion: In the Chinese rural men and postmenopausal women population, progesterone and C-reactive protein are related to obesity. We firstly found C-reactive protein partly mediates the effect of progesterone on obesity, indicating that systemic inflammation played a critical role in the association. [ABSTRACT FROM AUTHOR]

Objective: Maternal overweight has been associated with increasing offspring birth weight, but epidemiological data on potential biological mechanisms are limited. This study aimed to examine whether steroid hormones mediate the association between maternal prepregnancy BMI (pre-BMI) and birth weight.Methods: This study involving 2,039 participants was conducted from an ongoing cohort study in Wuhan, China. Mediation analysis was used to identify the extent to which steroid hormones mediated associations.Results: Each one-unit increase in pre-BMI was significantly associated with lower log2 -transformed cord blood levels of cortisol and corticosterone. Levels of cortisol and corticosterone were also negatively associated with birth weight. It was estimated that corticosterone mediated 3.48% of the association between pre-BMI and birth weight, and no significant mediation effect was observed in cortisol. After stratification by maternal gestational weight gain (GWG; within or in excess of the Institute of Medicine [IOM] guidelines), the associations of pre-BMI with cortisol and corticosterone levels were significant in the women with GWG > IOM but not in women with GWG ≤ IOM. When the mediation analysis in the women with GWG > IOM was limited, the mediation effects of cord blood cortisol and corticosterone were both significant (P < 0.05).Conclusions: Cord blood cortisol and corticosterone partially mediate the association of increased maternal pre-BMI with higher birth weight. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to explore the independent and combined dose-response association of napping and night sleep duration with type 2 diabetes mellitus (T2DM) among different genders in the rural Chinese population.Methods: For this research, a total of 19,257 participants were enrolled in the Rural Diabetes, Obesity and Lifestyle (RuralDiab) study. Napping and night sleep duration were assessed using the Pittsburgh Sleep Quality Index (PSQI). Restricted cubic splines and logistic regression were used to estimate the relationship between napping and night sleep duration with T2DM.Results: A linear dose-response relationship between napping duration and T2DM as well as a U-shaped relationship between night sleep duration and T2DM were found. Compared with those who reported no napping, participants who had a napping duration of ≥91 min were associated with a 19% increase in prevalence of T2DM. Adjusted odds ratios (ORs) (95% confidence intervals (CIs)) for T2DM were 1.48 (1.03, 2.14) and 1.50 (1.22, 1.85) for shorter (≤5 h) and longer (>9 h) night sleep duration compared with the referential group. Additionally, the combination of longer napping duration (≥91 min) and night sleep duration (>9 h) increased 104% (95% CI: 45%, 128%) prevalence for T2DM. These associations were not found in males but were evident in females.Conclusions: Longer napping duration and extreme night sleep duration increased the prevalence of T2DM. Meanwhile, longer napping and night sleep duration might be jointly associated with a higher prevalence of T2DM. [ABSTRACT FROM AUTHOR]

We aimed to evaluate the effects of serum testosterone, obesity and their interaction on blood pressure (BP) parameters and hypertension among Chinese rural adults. A total of 6199 adults were recruited from the Henan Rural Cohort Study. Serum testosterone was measured by liquid chromatography-tandem mass spectrometry. Logistic regression and linear regression were used to evaluate the association between testosterone, hypertension and BP parameters (including systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure (PP), and mean arterial pressure (MAP)). A generalized linear model was performed to identify the interactive effects of testosterone and obesity on hypertension. High levels of serum testosterone were associated with a lower prevalence of hypertension in males (odds ratio (OR): 0.69, 95% confidence interval (CI): 0.53, 0.89). After stratification by obesity, observed associations were only found in non-obese males. Each one-unit increase in ln-testosterone was associated with a 1.23 mmHg decrease in SBP, 0.97 mmHg decrease in DBP, and 1.05 mmHg decrease in MAP among males. Moreover, interactive effects between testosterone and obesity on hypertension and BP parameters were found, indicating that protective effects of serum testosterone on hypertension and BP parameters were counteracted and accompanied by increased values of obesity-related indicators in males, and additional testosterone increased BP parameters and prevalence of hypertension at high levels of waist-to-hip ratio and waist-to-height ratio in females. Elevated levels of serum testosterone were associated with decreased BP parameters and prevalent hypertension in males, and obesity modifying effects of serum testosterone on BP parameters and hypertension. [Display omitted] • Serum testosterone was negatively associated with hypertension in males. • Obesity modified the effects of testosterone onhypertension in males and females. [ABSTRACT FROM AUTHOR]

Although several single lifestyles have been reported to meliorate serum lipid levels, there is little evidence of the relationship between multiple healthy lifestyles and lipid levels in Chinese adults. Cross-sectional data of 35,150 participants aged 18-79 years without dyslipidemia at baseline in the Henan Rural Cohort were collected from 2015 to 2017, to investigate the associations between individual and combinations of 6 healthy lifestyle factors and lipid levels. In multivariate linear regression analyses, non-current smoking, non-current alcohol consumption, regular physical exercise, healthy diet, lower body mass index, and lower waist-to-hip ratio were significantly associated with lower concentration of total cholesterol (TC), triglyceride (TG), and low-density lipoprotein cholesterol (LDL-C) and higher concentrations of high-density lipoprotein cholesterol (HDL-C) (all P < .001). There were positive quantitative correlations between the number of healthy lifestyle factors and the low levels of lipids (all P for linear trend <0.001). People with 6 healthy lifestyle factors had 0.72-mmol/L (95% confidence interval [CI]: 0.64 to 0.81) lower TC, 1.02-mmol/L (95% CI: 0.93 to 1.11) lower TG, 0.54-mmol/L (95% CI: 0.47 to 0.61) lower LDL-C, and 0.32-mmol/L (95% CI: 0.29 to 0.34) higher HDL-C, than people who had 0-1 healthy lifestyle factors. In this study, we found an association between an increased number of healthy lifestyle factors and better serum lipid profiles. The causality and temporality between maintenance of a healthy lifestyle and optimal lipid levels merit further investigations. [ABSTRACT FROM AUTHOR]

Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries. A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015–2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO 2 , PM 1 , PM 2.5 , and PM 10 were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S). Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO 2 , PM 1 , PM 2.5 and PM 10 were related to a 2.96-fold (2.66–3.29), 2.87-fold (2.58–3.20), 2.98-fold (2.67–3.32) and 3.01-fold (2.70–3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found. The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions. [Display omitted] • Comprehensive assessment of association between obesity and T2DM were conducted. • Joint associations of obesity and air pollutants on T2DM were explored. • Both obesity and exposure to high air pollutants were related to prevalent T2DM. • Obese individuals were more susceptible to prevalent T2DM in highly polluted areas. [ABSTRACT FROM AUTHOR]

Socio-economic status (SES) and air pollutants are thought to play an important role in human obesity. The evidence of interactive effect between SES and long-term exposure to mixture of air pollutants on obesity is limited, thus, this study is aimed to investigate their interactive effects on obesity among a rural Chinese population. A total of 38,817 individuals were selected from the Henan Rural Cohort Study. Structural equation modeling (SEM) was applied to construct the latent variables of low SES (educational level, marital status, family yearly income, and number of family members), air pollution (particulate matter with aerodynamics diameters ≤ 1.0 μm, ≤ 2.5 μm or ≤ 10 μm, and nitrogen dioxide) and obesity (body mass index, waist circumference, waist-to-hip ratio, waist-to-height ratio, body fat percentage and visceral fat index). Generalized linear regression models were used to assess associations between the constructed latent variables. Interaction plots were applied to describe interactive effect of air pollution and low SES on obesity and biological interaction indicators (the relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP) and synergy index (S)) were also calculated. Increased latent variables of low SES and mixture of air pollution were associated with a higher odds of latent variable of obesity (odds ratios (OR) (95% confidence interval (CI)) were 1.055 (1.049, 1.060) and 1.050 (1.045, 1.055)). The association of the mixture of air pollutants on obesity was aggravated by increased values of the latent variable of low SES (P < 0.001). Furthermore, the values of RERI, AP and S were 0.073 (0.051, 0.094), 0.057 (0.040, 0.073) and 1.340 (1.214, 1.479), respectively, indicating an additive effect of estimated latent variable of low SES and air pollution on obesity. These findings suggested that low SES aggravated the negative effect of mixture of air pollutants on obesity, implying that individuals with low SES may be more susceptible to exposure to high levels of mixture of air pollutants related to increased risk of prevalent obesity. • Low socioeconomic status was related to increased risk of obesity in rural adults. • Exposure to mixture of air pollutants was positively related to obesity in rural adults. • Low socioeconomic status aggravated the effect of mixture of air pollution on obesity. [ABSTRACT FROM AUTHOR]