Association of long-term exposure to PM2.5 in workplace with fasting plasma glucose among asymptomatic adults: A multicenter study in North China

Associations between maternal periconceptional exposure to PM2.5 and the risk of cryptorchidism: a case-control study of 4274

Currently, there is limited evidence regarding the association between prenatal exposure to environmental fine particulate matter (PM2.5) and the occurrence of cryptorchidism. The objective of this study was to evaluate the potential correlation between prenatal exposure to PM2.5 and the likelihood of cryptorchidism developing in offspring. We performed a 1:1 case-control study, defining the cases as children diagnosed with cryptorchidism at the Children's Hospital Affiliated to Chongqing Medical University from 2013 to 2017, while the control group comprised children born in the corresponding years who did not have any birth defects, chromosomal abnormalities, and had only trauma-related treatments. Between 2012 and 2017, monthly averages of PM2.5, other pollutants (O3, PM10) and temperature were gathered based on the geographical coordinates of patients' residences. The study assessed the correlation between the two using multivariate logistic regression model, and sensitivity analysis was conducted to assess the stability of the model. We included a total of 2137 cases and 2137 matched controls from 2013 to 2017. Our findings revealed that there was a positive association between exposure to PM2.5 during the first 2 months of pregnancy and the occurrence of cryptorchidism. According to this study, the development of cryptorchidism appears to be associated with maternal exposure to PM2.5 during early pregnancy.

Association between exposure to outdoor artificial light at night during pregnancy and glucose homeostasis: A prospective cohort study

BACKGROUND

Outdoor artificial light at night (ALAN) has been linked to an elevated risk of diabetes, but the available literature on the relationships between ALAN and glucose homeostasis in pregnancy is limited.

METHODS

A prospective cohort study of 6730 pregnant women was conducted in Hefei, China. Outdoor ALAN exposure was estimated using satellite data with individual addresses at a spatial resolution of approximately 1 km, and the average ALAN intensity was calculated. Gestational diabetes mellitus (GDM) was diagnosed based on a standard 75-g oral glucose tolerance test. Multivariable linear regression and logistic regression were used to estimate the relationships between ALAN and glucose homeostasis.

RESULTS

Outdoor ALAN was associated with elevated glucose homeostasis markers in the first trimester, but not GDM risk. An increase in the interquartile range of outdoor ALAN values was related to a 0.02 (95% confidence interval [CI]: 0.00, 0.03) mmol/L higher fasting plasma glucose, a 0.42 (95% CI: 0.30, 0.54) μU/mL increase in insulin and a 0.09 (95% CI: 0.07, 0.12) increase in homeostatic model assessment of insulin resistance (HOMA-IR) during the first trimester. Subgroup analyses showed that the associations between outdoor ALAN exposure and fasting plasma glucose, insulin, and HOMA-IR were more pronounced among pregnant women who conceived in summer and autumn.

CONCLUSIONS

The results provided evidence that brighter outdoor ALAN in the first trimester was related to elevated glucose intolerance in pregnancy, especially in pregnant women conceived in summer and autumn, and effective strategies are needed to prevent and manage light pollution.

Long-term exposure to ambient ozone at workplace is positively and non-linearly associated with incident hypertension and blood pressure: longitudinal evidence from the Beijing-Tianjin-Hebei medical examination cohort

BACKGROUND

There is limited longitudinal evidence on the hypertensive effects of long-term exposure to ambient O3. We investigated the association between long-term O3 exposure at workplace and incident hypertension, diastolic blood pressure (DBP), systolic blood pressure (SBP), pulse pressure (PP), and mean arterial pressure (MAP) in general working adults.

METHODS

We conducted a cohort study by recruiting over 30,000 medical examination attendees through multistage stratified cluster sampling. Participants completed a standard questionnaire and comprehensive medical examination. Three-year ambient O3 concentrations at each employed participant's workplace were estimated using a two-stage machine learning model. Mixed-effects Cox proportional hazards models and linear mixed-effects models were used to examine the effect of O3 concentrations on incident hypertension and blood pressure parameters, respectively. Generalized additive mixed models were used to explore non-linear concentration-response relationships.

RESULTS

A total of 16,630 hypertension-free working participants at baseline finished the follow-up. The mean (SD) O3 exposure was 45.26 (2.70) ppb. The cumulative incidence of hypertension was 7.11 (95% CI: 6.76, 7.47) per 100 person-years. Long-term O3 exposure was independently, positively and non-linearly associated with incident hypertension (Hazard ratios (95% CI) for Q2, Q3, and Q4 were 1.77 (1.34, 2.36), 2.06 (1.42, 3.00) and 3.43 (2.46, 4.79), respectively, as compared with the first quartile (Q1)), DBP (β (95% CI) was 0.65 (0.01, 1.30) for Q2, as compared to Q1), SBP (β (95% CI) was 2.88 (2.00, 3.77), 2.49 (1.36, 3.61) and 2.61 (1.64, 3.58) for Q2, Q3, and Q4, respectively), PP (β (95% CI) was 2.12 (1.36, 2.87), 2.03 (1.18, 2.87) and 2.14 (1.38, 2.90) for Q2, Q3, and Q4, respectively), and MAP (β (95% CI) was 1.39 (0.76, 2.02), 1.04 (0.24, 1.84) and 1.12 (0.43, 1.82) for Q2, Q3, and Q4, respectively). The associations were robust across sex, age, BMI, and when considering PM2.5 and NO2.

CONCLUSIONS

To our knowledge, this is the first cohort study in the general population that demonstrates the non-linear hypertensive effects of long-term O3 exposure. The findings are particularly relevant for policymakers and researchers involved in ambient pollution and public health, supporting the integration of reduction of ambient O3 into public health interventions.

The causal relationship between air pollution, obesity, and COVID-19 risk: a large-scale genetic correlation study

OBJECTIVE

Observational evidence reported that air pollution is a significant risk element for numerous health problems, such as obesity and coronavirus disease 2019 (COVID-19), but their causal relationship is currently unknown. Our objective was to probe the causal relationship between air pollution, obesity, and COVID-19 and to explore whether obesity mediates this association.

METHODS

We obtained instrumental variables strongly correlated to air pollutants [PM2.5, nitrogen dioxide (NO2) and nitrogen oxides (NOx)], 9 obesity-related traits (abdominal subcutaneous adipose tissue volume, waist-to-hip ratio, body mass index, hip circumference, waist circumference, obesity class 1-3, visceral adipose tissue volume), and COVID-19 phenotypes (susceptibility, hospitalization, severity) from public genome-wide association studies. We used clinical and genetic data from different public biological databases and performed analysis by two-sample and two-step Mendelian randomization.

RESULTS

PM2.5 genetically correlated with 5 obesity-related traits, which obesity class 1 was most affected (beta = 0.38, 95% CI = 0.11 - 0.65, p = 6.31E-3). NO2 genetically correlated with 3 obesity-related traits, which obesity class 1 was also most affected (beta = 0.33, 95% CI = 0.055 - 0.61, p = 1.90E-2). NOx genetically correlated with 7 obesity-related traits, which obesity class 3 was most affected (beta = 1.16, 95% CI = 0.42-1.90, p = 2.10E-3). Almost all the obesity-related traits genetically increased the risks for COVID-19 phenotypes. Among them, body mass index, waist circumference, hip circumference, waist-to-hip ratio, and obesity class 1 and 2 mediated the effects of air pollutants on COVID-19 risks (p < 0.05). However, no direct causal relationship was observed between air pollution and COVID-19.

CONCLUSION

Our study suggested that exposure to heavy air pollutants causally increased risks for obesity. Besides, obesity causally increased the risks for COVID-19 phenotypes. Attention needs to be paid to weight status for the population who suffer from heavy air pollution, as they are more likely to be susceptible and vulnerable to COVID-19.

Habitual night sleep duration is associated with general obesity and visceral obesity among Chinese women, independent of sleep quality

Purpose

Research on the relationship between sleep duration and obesity defined using multiple anthropometric and bioelectrical indices in women remains scarce. We aimed to explore the association between sleep duration and body mass index (BMI), waist-hip ratio (WHR), body fat percentage (PBF) and visceral fat area (VFA) among females.

Methods

We recruited women for medical examination using multistage cluster sampling. Sleep was assessed using Pittsburgh Sleep Quality Index (PSQI) and sleep duration was categorized into short (<7 h), optimal (7 <9 h) and long sleep (≥ 9 h). Weight and height were measured using a calibrated stadiometer. Waist circumference was manually measured. PBF, and VFA were estimated by bioelectrical impedance analysis. Data on sociodemographic characteristics and lifestyle factors were also collected and included in the logistic regression models to explore the independent association between sleep duration and obesity defined by different indices.

Results

A total of 7,763 women with a mean age of 42.6 ± 13.5 years were included. The percentage of women reporting short and long sleep was 10.3 and 13.4% respectively. The mean BMI, WHR, PBF and VFA were 23.07 ± 3.30 kg/m², 0.78 ± 0.06, 32.23 ± 6.08% and 91.64 ± 35.97cm², respectively. Short sleep was independently associated with 35% (95% CI: 1.05-1.75) increased odds of general obesity (BMI ≥ 28 kg/cm²), and long sleep was associated with 18% (95% CI: 1.01-1.37) increased odds of visceral obesity (VFA > 100 cm²). No association was observed between sleep deprivation or excessive sleep and high WHR or high PBF.

Conclusion

In women, short sleep was associated with an increased odds of general obesity, whereas long sleep was associated with an increased odds of visceral obesity. Longitudinal observations are needed to confirm this cross-sectional relationship.