Association Between Night Shift and Hypertension: A Cross-Sectional Study in Chinese Adults.

OBJECTIVE: The purpose of this study was to explore the effect of night-shift work on the risk of hypertension for improving workers' health. METHODS: A total of 10,038 Chinese participants were constituted in the cross-sectional study. Logistic regression and restricted cubic spline were used to estimate the effect of night shift on hypertension. RESULTS: There were higher odds of having hypertension in any night-shift workers (odds ratio [OR], 1.16 [95% confidence interval, 1.03-1.30]) when compared with day workers. Having 5 to 10 night shifts per month were significantly more likely to be hypertensive (OR, 1.19 [95% confidence interval, 1.03-1.38]). The OR for hypertension increased as the number of night shifts increased as the result of the restricted cubic spline. CONCLUSIONS: Our results support the hypothesis that night shift is associated with an elevated risk of hypertension.

Maternal exposure to extreme high-temperature, particulate air pollution and macrosomia in 14 countries of Africa.

BACKGROUND: Macrosomia has increased rapidly worldwide in the past few decades, with a huge impact on health. However, the effect of PM2.5 and extreme high-temperature (EHT) on macrosomia has been ignored. OBJECTIVE: This study aimed to explore the association between maternal exposure to EHT, PM2.5 and macrosomia based on the Seventh Demographic and Health Survey (DHS) in 14 countries of Africa. METHODS: The study included detailed demographic information on 106 382 births and maternal. Satellite inversion models estimated monthly mean PM2.5 and mean surface temperature of 2 m (SMT2m ). Macrosomia was defined as the birth weight ≥ 4000 g. We used a Cox proportional risk regression model to estimate the association between PM2.5 , EHT and macrosomia. We further explored the susceptibility of exposure to EHT and PM2.5 at different pregnancy periods to macrosomia, and plotted the expose-response curve between PM2.5 and macrosomia risk using a restricted cubic spline function. In addition, the Interplot model was used to investigate the interaction between EHT and PM2.5 on macrosomia. Finally, some potential confounding factors were analysed by stratification. RESULTS: There was the positive association between EHT, PM2.5 and macrosomia, and the risk of macrosomia with the increase in concentrations of PM2.5 without clear threshold. Meanwhile, EHT and PM2.5 had a higher effect on macrosomia in middle/later and early/middle stages of pregnancy, respectively. There was a significant interaction between EHT and PM2.5 on macrosomia. CONCLUSIONS: Maternal exposure to EHT, PM2.5 during pregnancy was associated with an increased risk of macrosomia in Africa.

Association of exposure to multiple serum metals with the risk of chronic kidney disease in the elderly: a population-based case-control study.

In the world, chronic kidney disease (CKD) has been recognized as one of the critical public health problems, and the prevalence is higher in the elderly people. However, there are few studies on the association between exposure to multiple serum metal levels and CKD. A case-control study, we established, for elderly people in Anhui Province, China, to explore the effects of different metals and analyze the effect of mixed exposure on CKD. In this study, 287 cases of CKD and 287 controls were selected in the elderly health physical examination project in Tongling City, Anhui Province. Questionnaire survey, physical examination, and blood collection were conducted. Graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES) were used to measure the concentration of serum metals. After selecting by least absolute shrinkage and selection operator (LASSO), 5 metals were brought into the multi-metal model. After adjusting all potential covariates additionally, the concentrations of lead (Pb), cadmium (Cd), cobalt (Co), and manganese (Mn) were significantly associated with CKD risk, whereas Pb, Se, and Cd had significant non-linearity with CKD. Besides, patients with highest quartiles of cobalt (Co), lead (Pb), and manganese (Mn) were 1.64, 1.39, and 0.64 times more possible to have CKD, respectively, as compared with the lowest levels. In the Bayesian kernel machine regression (BKMR) model, cadmium (Cd) had a combined effect with lead (Pb) possibly. This study suggested that the CKD risk was associated with exposure of multiple metals in elderly people. The underlying mechanisms of serum metals and CKD need more experimental and prospective studies to elucidate.

Associations of exposure to multiple metals with the risk of age-related cataract in Anhui, China: a case-control study.

It's well-known that multiple metal elements can lead to the change of oxidative stress response levels in vivo. However, their relationship with age-related cataract (ARC) had not been well studied. We designed a case-control study including 210 individuals with ARC and 210 matched control group. The metal levels in their urine specimens were measured using graphite furnace atomic absorption spectrometry (GFAAS) and inductively coupled plasma optical emission spectrometry (ICP-OES). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select representative metals into the multi-element model and reduce dimension. Multivariate logic analysis and Bayesian kernel machine regression (BKMR) were subsequently used to explore the association of ARC risk with multiple metal elements. We found that magnesium (Mg), chromium (Cr), arsenic (As), manganese (Mn), and selenium (Se) were positively associated with ARC in the single-element model. The multiple exposure model indicated a positive association between Mg and As, in which the OR in their highest quartile were 3.32 (95% CI: 1.24-8.89) and 7.09 (95% CI: 2.56-19.63). The BKMR model also showed the effect of As increased monotonically with its increasing concentration, and high levels of Mg and As had a significant positive effect on ARC risk. In conclusion, we found that exposure to multiple metals was associated with increased ARC risk. Further research is needed to verify these findings in the future.

Individual PM2.5 component exposure model, elevated blood pressure and hypertension in middle-aged and older adults: A nationwide cohort study from 125 cities in China.

Recently, elevated blood pressure (BP) and hypertension (HTN) have caused a huge burden of health loss. Previous studies used ambient air pollutants as a proxy for individual exposure, limiting the assessment of its multiple exposure to health effects. For the first time, this study constructed individual PM2.5 component (SO42-, NO3-, NH4+, OM, and BC) exposure model DAG (Directed Acyclic Graph), DAG-oriented generalized linear model and random forest model, and explored the effects of single and multiple exposures to PM2.5 components on BP at different stages by the generalized linear model (GLM) and Quantile g-Computation (QgC) model based on a large cohort study in China. We defined BP in four stages according to the 2017 ACC/AHA guidelines. After excluding the lack of key information, the cohort analyses ultimately included 9031 participants. Our results showed that the individual PM2.5 component exposure model had good efficacy. Single or multiple exposure to PM2.5 components had significant positive effects on normal BP to elevated BP and elevated BP to stage 1 HTN. In addition, males, the elderly and urban residents were more sensitive to PM2.5 components. This study provided implications for environmental exposure assessment and control of particulate pollution in the future.

Exposure to multiple trace elements and thyroid cancer risk in Chinese adults: A case-control study.

The incidence of thyroid cancer (TC) has increased rapidly in last decades. Multiple trace elements in the external environment have important effects with thyroid function. However, the evidence for these on TC risk were rarely reported. A total of 585 newly diagnosed TC patients and 585 healthy controls were included in this study, and 14 urinary elements were measured to explain the fixed-exposure effect on TC risk. Conditional logistic regressions were used to reflect the multi-element associations, and Bayesian kernel machine regression (BKMR) was applied to show the tendency of mixed effects. Furthermore, the interaction effects were examined by Generalized linear model (GLM). The levels of lithium (Li), cobalt (Co), strontium (Sr), zinc (Zn) and copper (Cu) had negative effects with TC risk, nevertheless lead (Pb), arsenic (As) and chromide (Cr) showed positive effects. The BKMR and GLM models reflected the effect fluctuations of different elements, and there was a slight interaction effects between Li and Cr, Co, Zn and Pb. Further study is required to confirm these results in the future.

Short-term exposure to six air pollutants and cause-specific cardiovascular mortality of nine counties or districts in Anhui Province, China.

Recently, the burden of cardiovascular disease (CVD) has attracted global attention. Meanwhile, CVD has become the leading cause of death in China. Some epidemiological studies have indicated that ambient air pollution may contribute to increased mortality from CVD diseases. Many studies have found a strong association between air pollutants and the risk of CVD deaths in some big cities, but few have focused on the effects of six pollutants in rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on CVD deaths of rural areas in Anhui Province and to further clarify which populations were susceptible to air pollution. First, the generalized additive models were combined with the distributed lag nonlinear models to evaluate the individual effects of air pollution on CVD deaths in each area. Then, random-effects models were used to aggregate the associations between air pollutants and CVD mortality risk in nine regions. Overall, all six pollutants had a statistically significant effect on the risk of CVD deaths on the lag 07 days. The associations between PM2.5, PM10, and SO2 and daily CVD deaths were strongest, with maximum cumulative RR (lag 07) of 1.91 (1.64-2.18), 2.27 (1.50-3.05), and 2.13 (1.44-2.82). In general, we found that six air pollutants were the important risk factors for CVD and specific CVD deaths in Anhui Province. The elderly were susceptible to PM2.5, PM10, and SO2.

Outdoor air pollution enhanced the association between indoor air pollution exposure and hypertension in rural areas of eastern China.

Recently, the high prevalence of hypertension (HTN) has caused serious disease burden. Previous studies mostly focused on the separate association between outdoor or indoor air pollution and HTN, and did not explore their possible interaction with HTN. To explore this issue, this study investigated the relationship between indoor and outdoor air pollution and HTN and their possible interactions among adult residents in 14 rural areas in eastern China. The generalized linear model (GLM) and interplot model were used to evaluate the separate effects and potential interaction of outdoor or indoor air pollutants on HTN. In separate analyses, we found a significant positive association between outdoor and indoor air pollution and HTN, and a significant negative association between range hood use and HTN. In the interaction analysis, outdoor air pollution could significantly enhance the positive effects of indoor air pollution on HTN. In addition, PM2.5 and O3 could significantly reduce the protective effect of range hoods use on HTN. Finally, we found that females were more susceptible to both indoor and outdoor air pollution.

Associations between environmental exposure to polybrominated diphenyl ethers and nodular goiter risk: A case-control study.

Polybrominated diphenyl ethers (PBDEs) are widespread and persistent environmental contaminants, but their association with nodular goiter (NG) remains unknown. The present case-control study of 179 NG cases and 358 matched normal controls aimed to investigate the association between PBDEs and risk of NG. The plasma concentrations of 8 PBDEs congeners (BDE-28, -47, -99, -100, -153, -154, -183, and -209) were determined by gas chromatograph-mass spectrometer. Conditional logistic regression model was used to evaluate the odds ratio (OR) and 95% confidence interval (CI) for the association between each PBDEs congener and NG. Bayesian kernel machine regression (BKMR) was used to evaluate the association between overall levels of 8 PBDEs mixture and NG. The results of logistic model suggested that increased risk of NG was associated with elevated concentrations of all PBDEs congeners, except for BDE-209. In BKMR model, the risk of NG increased with the increase in overall exposure level of 8 PBDEs mixture. Compared to when all PBDEs mixture were at their median value, the risk of exposure-response function for NG increased by 0.34 units when all PBDEs were at their 75th percentile. In women, the results showed similar trends after additional adjustment for age at menarche and menopausal status. These findings provide novel epidemiological evidence for the prevention of NG. However, larger prospective studies are required to address the associations between PBDEs exposure and NG risk.

Multiple environmental exposures and obesity in eastern China: An individual exposure evaluation model.

Obesity has caused a huge burden of disease. Few studies have explored individuals' environmental exposure level and the impact of multiple environmental exposures on obesity. The aim of this study was to explore individual air pollution exposure evaluation, and the association between and multiple environmental factors and obesity among adult residents in rural areas of China. In this study, 8400 residents of 14 districts and counties in eastern of China were selected by multistage stratified cluster sampling, and a total of 8377 residents were included in the final analysis. We adopted BMI (Body Mass Index) > 28 kg/m2 as the definition of obesity. First, an individual air pollution evaluation model was established based on the monitoring data of air pollution stations closest to residential address, different demographic characteristics of residents and daily living habits using generalized linear model and random forest model. Then, we used Bayesian Kernel Machine Regression (BKMR) and Quantile g-Computation (QgC) models to explore multiple environmental exposures on obesity. The results showed that six air pollutants were significantly positively associated with obesity, and green space had a significant protective effect on obesity. The BKMR model showed that the effects of different air pollutants on obesity were significantly enhanced by each other, while green space significantly reduced the positive effect of air pollution on obesity. The QgC model showed a significant positive association with obesity when all environmental factors were exposed as a whole, especially in males, higher household incomes and young people. It suggested that relevant authorities should improve regional air quality and green space to reduce the burden of disease caused by obesity.

The effects of air pollution on the lung cancer mortality in rural areas of eastern China: a multi-region study.

Recently, the burden of lung cancer (LC) has attracted global attention. Meanwhile, LC has become the leading cause of death in China. Many studies found a strong link between air pollutants and the risk of LC mortality in some large cities, but the results have been inconsistent, and most studies have only focused on the daily effects of six pollutants in large cities, ignoring their potential cumulative effects. This study was to investigate the weekly effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on LC mortality in rural areas of eastern China and to further clarify which population groups were susceptible to air pollution and seasonal trends. First, a generalized additive model was combined with a distributed lag nonlinear model to evaluate the individual impact of air pollution on LC deaths in each area. The random-effect model was then used to pool the associations between air pollutants and LC mortality risk in ten counties or districts. The results showed that six air pollutants had a statistically significant effect on the risk of LC mortality at different lag weeks. The effects of NO2, PM10, and CO on weekly LC mortality were strongest at a cumulative lag of 1, 0, and 1 week, respectively, the maximum cumulative risk ratio (RR) of 1.37 (95%CI: 1.23 to 1.52), 1.30 (95%CI: 1.15 to 1.46), and 1.30 (95%CI: 1.17 to 1.43), with interquartile concentrations increasing. In summary, air pollution was an important factor in LC mortality, and the effect was stronger on males, the elderly, and during cold season. It was suggested that relevant departments should formulate air pollution management measures for the elderly, males, and in different seasons in rural areas and reduce the burden of lung cancer caused by air pollution.

Effects of carbon dioxide and green space on sleep quality of the elderly in rural areas of Anhui Province, China.

Sleep quality leads to many healthy problems, which has caused global concern. Most studies have focused on the sleep quality in some large cities, ignoring the elderly in rural areas who may have more serious sleep problems. Therefore, this study aimed to understand the sleep status of the elderly in rural areas of Anhui Province and the influence of environmental factors on it. The data of carbon dioxide (CO2) concentrations for this study were obtained from the Dalhousie University atmospheric composition analysis group. The data of normalized differential vegetation index (NDVI) in 2014 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The 2686 individuals were selected from rural areas of Anhui Province by multi-stage stratified cluster sampling. The Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. The independent, interactive, and mediating effects of CO2 and green space on sleep quality were evaluated by generalized linear model, interaction model, and mediating effect model, respectively. In this study, we found that the prevalence of sleep disturbance in the elderly was 58.40%. In the univariate model, we found that the risk of sleep disturbance increased by 1.6% for each 1 µg/m3 increase in concentrations of CO2, while decreased by 1.5% for every 0.1 increase in NDVI. In the interaction model, the negative correlation between green space and sleep quality decreased with concentrations of CO2 increased. In addition, green space was a mediating factor between CO2 and sleep quality in the mediating effect model.

Associations of combined exposures to ambient temperature, air pollution, and green space with hypertension in rural areas of Anhui Province, China: A cross-sectional study.

Hypertension (HTN) was a major preventable cause of cardiovascular disease (CVD), contributing to a huge disease burden. Ambient temperature, air pollution and green space were important influencing factors of HTN, and few studies have assessed the effects and interactions of ambient temperature, air pollution and green space on HTN in rural areas. In this study, we selected 8400 individuals randomly in rural areas of Anhui Province by a multi-stage stratified cluster sampling. A total of 8383 individuals were included in the final analysis. We collected particulate pollutants and meteorological data from the local air quality monitoring stations and National Center for Meteorological Science from January 1 to December 31, 2020, respectively. The normalized differential vegetation index (NDVI) of Anhui Province in 2020 was produced and processed by remote sensing inversion on the basis of medium resolution satellite images. The average annual mean exposure concentrations of air pollution, meteorological factors, and NDVI were calculated for each individual based on the geocoded residential address. HTN was defined according the Chinese Guidelines for Prevention and Treatment of HTN. The effects and interactions of ambient temperature, air pollution and green space on HTN were evaluated by generalized linear model and interaction model, respectively. In this study, the prevalence of HTN was 24.14%. The adjusted odd ratio of HTN for each 1 µg/m3 increasing in PM2.5 and PM10, 1 °C of ambient temperature, and 0.1 of NDVI were:1.276 (1.013, 1.043), 1.012 (1.006, 1.018), 0.862 (0.862, 0.981) and 0.669 (0.611, 0.733), respectively. The results showed that air pollutants were positively correlated with HTN, while ambient temperature and green space were negatively correlated with HTN. Meanwhile, the negative associations of green space on HTN could decrease with the increasing concentrations of air pollution, but increase with the rising of ambient temperature.

Six air pollutants and cause-specific mortality: a multi-area study in nine counties or districts of Anhui Province, China.

Air pollution and its negative effects on health of people have been a global concern. Many studies had found a strong association between air pollutants and risk of death, but few had focused on the effects of six pollutants and rural areas. Our study aimed to investigate the effects of six air pollutants (CO, NO2, O3, PM2.5, PM10, and SO2) on non-accidental and respiratory deaths in rural areas of Anhui Province by adjusting for confounding factors, and to further clarify which populations were susceptible to death associated with air pollution. In the first phase of the analysis, the generalized additive models were combined with the distributed lag non-linear models to evaluate the individual effects of air pollution on death in each area. In the second stage, random-effects models were used to aggregate the associations between air pollutants and mortality risk in nine areas. Overall, six pollutants had the strongest effects on the risk of death on the lag 07 days. The associations between PM2.5 and NO2 and daily non-accidental deaths were strongest, with maximum RR (lag 07): 1.63 (1.37-1.88) and 1.67 (1.37-1.96). The maximum pooled effects of association between six air pollutants and RD were PM2.5, with RR (lag 07): 1.89 (1.45-2.34). PM2.5 and PM10 had significant differences between the elderly and the non-elderly with respectively, RRR: 1.22 (1.04-1.41) and 1.26 (1.11-1.42). In general, we found that six air pollutants were the important risk factors for deaths (deaths from respiratory disease and non-accidental) in rural areas of Anhui Province. PM10 and PM2.5 had a considerable impact on the elderly.

Body mass index and weight gain after middle adulthood are associated with risk of papillary thyroid cancer: A case-control study.

BACKGROUND: It is unclear whether weight change after middle adulthood influences the risk of thyroid cancer. The aim of this study was to investigate associations between the risk of papillary thyroid cancer (PTC) and body mass index (BMI) and weight change after middle adulthood (age 35). METHODS: A matched case-control study based on three hospitals included 516 pairs of cases newly diagnosed with PTC and controls. Current height and weight after defecation in the morning were measured by trained nurses. During measurement, all subjects were requested to wear lightweight clothing and no shoes. Weight at age 35 was self-reported. BMI and weight change were modeled as continuous and categorical variables. Conditional and unconditional logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (95%CI) for the association between BMI and weight change after middle adulthood and PTC. RESULTS: After adjustment for covariates, measured BMI at the time of current diagnosis was positively associated with PTC (OR 1.16, 95%CI 1.10-1.21). According to WHO BMI guidelines for Asia-Pacific populations, the OR (95%CI) for PTC risk in obesity was 2.99 (1.92-4.67) compared to normal weight (p-trend <0.001). Moreover, PTC was positively associated with BMI at age 35; the OR (95%CI) for PTC risk per unit increase in BMI was 1.06 (1.02-1.11). Compared to stable weight (changed <0.5 kg/year), weight gain ≥1.0 kg/year after middle adulthood was positively associated with PTC (OR 2.57, 95%CI 1.39-4.76, p-trend <0.001). Compared to maintaining non-overweight status, the PTC risk was significantly increased in those individuals who gained weight and became overweight after middle adulthood (OR 3.82, 95%CI 2.50-5.85). CONCLUSION: This study showed that high BMI and obesity were positively associated with increased risk of PTC, and weight gain after middle adulthood also could elevate the PTC risk.

Associations of exposure to multiple trace elements with the risk of goiter: A case-control study.

Goiter is one of common endocrine diseases, and its etiology has not been fully elucidated. The changes in trace elements' levels have an important impact on the thyroid. We designed a case-control study, which involved 383 goiter cases and 383 matched controls. We measured these elements in the urine of participants by inductively coupled plasma optical emission spectrometry (ICP-OES), graphite furnace atomic absorption spectrometry (GFAAS) and As3+-Ce4+ catalytic spectrophotometry. Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to select the elements into multi-element models, conditional logistic regression models were applied to analyze the association between elements and goiter risk. Bayesian kernel machine regression (BKMR) model was used to depict elements' mixtures and evaluate their joint effects. Finally, 7 elements were included in the multi-element model. We found that the concentrations of lithium (Li), strontium (Sr) and barium (Ba) had a negative effect with goiter risk, and lead (Pb) and iodine (I) showed an extreme positive effect. Additionally, compared with the lowest levels, patients with highest quartiles of I and Pb were 6.49 and 1.94 times more likely to have goiter, respectively. On the contrary, in its second and third quartiles, arsenic (As) showed a negative effect (both OR<1). BKMR model showed a certain interaction among Pb, As, Sr and Li on goiter risk. Further large sample studies are needed to confirm these findings in the future.

Thyroid hormones in relation to polybrominated diphenyl ether and metals exposure among rural adult residents along the Yangtze River, China.

Although several studies indicate that exposure to polybrominated diphenyl ethers (PBDEs) and metals may influence thyroid function, the evidence is limited and inconsistent in general population. The current study was conducted to determine the levels of plasma PBDEs and urinary metals and evaluate the associations of co-exposure to both with thyroid hormones (THs) among rural adult residents along the Yangtze River, China. A total of 329 subjects were included in current analyses, and 8 PBDEs congeners and 14 urinary metals were measured to reflect the levels of environmental exposure. Multiple linear regression models were used to evaluate the association between PBDEs, metals and THs levels. Bayesian Kernel Machine Regression (BKMR) was used to examine PBDEs and metals mixtures in relation to THs. The geometric mean (GM) and 95% confidence interval (CI) of total measured PBDEs was 65.10 (59.96, 70.68) ng/g lipid weights (lw). BDE-209 was the most abundant congener, with a GM (95% CI) of 47.91 (42.95, 53.26) ng/g lw, accounting for 73.6% of the total PBDEs. Free thyroxine (FT4) was significantly negatively associated with BDE-28, 47, 99, 100, 154, and 183, and urinary strontium [ß (95% CI): -0.04 (-0.07, -0.02)], but positively associated with selenium [ß (95% CI): 0.04 (0.02, 0.06)]. Free triiodothyronine (FT3) was negatively associated with BDE-28 [ß (95% CI): -0.03 (-0.05, -0.01)] and urinary arsenic [ß (95% CI): -0.01 (-0.02, -0.001)]. The current study did not observe a statistically significant association of thyroid-stimulating hormone (TSH) with PBDEs and urinary metals. BKMR analyses showed similar trends when these chemicals were taken into consideration simultaneously. We found no significant interaction in the association between individual chemical at the 25th versus 75th percentiles and THs estimates, comparing the results when other chemicals were set at their 10th, 50th, and 90th percentile levels. Further study is required to confirm these findings and determine potential mechanisms.

Reproductive and menstrual factors for papillary thyroid cancer risk: A case-control study in Chinese women.

BACKGROUND: Thyroid cancer (TC) is threefold more common in women than men. Reproductive and menstrual factors may be related to the onset of papillary thyroid cancer (PTC). This study aims to determine the association of reproductive and menstrual factors with PTC in Chinese females. METHODS: A total of 335 histologically confirmed cases of PTC were recruited in this case-control study. The controls were matched for age with a deviation of ± 2 years, which conducted from September 2016 to February 2019. Logistic regression models were applied to identify the association of reproductive and menstrual factors with PTC. RESULTS: After adjustment by some variables, early menarche age (OR ≤ 13 years vs. > 13years = 2.40, 95 % CI 1.12-5.13) and shorter lifetime breastfeeding (OR <6 months vs. ≥ 6 months = 1.99, 95 % CI 1.11-3.55) significantly increased the risk of PTC, whereas younger age at first pregnancy had a protective effect against PTC (OR ≤ 24years vs. > 24 years = 0.66, 95 % CI 0.44-0.98). There was a positive correlation between premenopausal and PTC in the lower age group (OR premenopausal vs. Menopause by natural =2.34, 95 %CI 1.03-5.28). CONCLUSIONS: Early menarche age, abortion, shorter breastfeeding duration and premenopausal may be related to the occurrence of PTC. Early age at first pregnancy and larger number of full-time pregnancies were possible to decrease the risk of PTC.

Exposure to 2,4-dichlorophenol, 2,4,6-trichlorophenol, pentachlorophenol and risk of thyroid cancer: a case-control study in China.

Thyroid cancer (TC) has inflicted huge threats to the health of mankind. Chlorophenols (CPs) were persistent organic pollutant and can lead to adverse effects in human health, especially in thyroid. However, epidemiological studies have revealed a rare and inconsistent relationship between internal exposure to CPs and TC risk. The purpose of this study was to investigate the correlation between urinary CPs and TC risk in Chinese population. From June 2017 to September 2019, a total of 297 histologically confirmed TC cases were recruited. Age- and gender-matched controls were enrolled at the same time. Gas chromatography-mass spectrometry (GC-MS) was used to determine the levels of three CPs in urine. Conditional logistic regression models were adopted to assess the potential association. Restricted cubic spline function was used to explore the non-liner association. After adjusting for confounding factors, multivariate analysis showed that, compared with the first quartile, the fourth quartile concentrations of 2,4-dichlorophenol (2,4-DCP), 2,4,6-trichlorophenol (2,4,6-TCP), and pentachlorophenol (PCP) were associated with TC risk (odds ratio (OR)2,4-DCP =2.28, 95% confidence interval (CI): 1.24-4.18; OR2,4,6-TCP =3.09, 95% CI: 1.66-5.77; ORPCP =3.30, 95% CI: 1.71-6.36, respectively), when CPs were included in the multivariate model and restricted cubic spline function as continuous variables, presenting significant dose-response relationships. Meanwhile, whether in the TC group with tumor diameter > 1 cm or metastatic TC, the changes of 2,4,6 TCP and PCP concentrations were positively correlated with the risk of TC. Our study suggests that higher concentrations of urinary CPs are associated with increased TC risks. Moreover, 2,4,6-TCP and PCP have certain effects on the invasiveness of thyroid cancer. Targeted public health policies should be formulated to reduce the CP pollution. These findings need further in-depth studies to confirm and relevant mechanism also needed to be clarified.

Multiple metal exposure and obesity: A prospective cohort study of adults living along the Yangtze River, China.

Association between long-term exposure to multiple metals and obesity remains inconclusive, and prospective evidence on the region along the Yangtze River was limited. Thus, our study aimed to examine the association of multiple metal exposure and obesity. We measured baseline urine levels of 22 metals of 982 adults living along the Yangtze River, incidence of obesity was calculated from body mass index (BMI) and waist circumference (WC) measured at follow-up survey. Cox proportional hazards models were used to examine the hazard ratios (HR) and 95% confidence interval (CI) for the association between urinary metals and obesity, and the mixing effect of metals on obesity was estimated by using quantile g-computation. In multiple-metal models, arsenic was significantly associated with BMI/obesity, with the HR in the highest quartiles of 0.33 (95% CI: 0.16, 0.69; p-trend = 0.004). The HRs for WC/obesity of arsenic and molybdenum were 0.49 (95% CI: 0.32, 0.75 for the fourth vs. first quartile; p-trend = 0.002) and 1.83 (95% CI: 1.25, 2.70; p-trend = 0.001), respectively. Quantile g-computation mixtures approach showed a significantly negative joint effect of multiple metals on WC/obesity, with the HR of 0.26 (95% CI: 0.14, 0.47; p < 0.001) when increasing all seventeen metals by one quartile. Our study suggests that all seventeen metal mixed exposure may be negatively associated with obesity. Further cohort studies are needed to confirm these findings and clarify the underlying biological mechanisms.