Long-term exposure to ambient PM2·5, active commuting, and farming activity and cardiovascular disease risk in adults in China: a prospective cohort study

Effect of aerobic exercise and particulate matter exposure duration on the diversity of gut microbiota

Inhalation of ambient particulate matter (PM) can disrupt the gut microbiome, while exercise independently influences the gut microbiome by promoting beneficial bacteria. In this study, we analyzed changes in gut microbial diversity and composition in response to combined interventions of PM exposure and aerobic exercise, extending up to 12 weeks. This investigation was conducted using mice, categorized into five groups: control group (Con), exercise group (EXE), exercise group followed by 3-day exposure to PM (EXE + 3-day PM), particulate matter exposure (PM), and PM exposure with concurrent treadmill exercise (PME). Notably, the PM group exhibited markedly lower alpha diversity and richness compared to the Con group and our analysis of beta diversity revealed significant variations among the intervention groups. Members of the Lachnospiraceae family showed significant enhancement in the exercise intervention groups (EXE and PME) compared to the Con and PM groups. The biomarker Lactobacillus, Coriobacteraceae, and Anaerofustis were enriched in the EXE group, while Desulfovibrionaceae, Mucispirillum schaedleri, Lactococcus and Anaeroplasma were highly enriched in the PM group. Differential abundance analysis revealed that Paraprevotella, Bacteroides, and Blautia were less abundant in the 12-week PM exposure group than in the 3-day PM exposure group. Moreover, both the 3-day and 12-week PM exposure groups exhibited a reduced relative abundance of Bacteroides uniformis, SMB53, and Staphylococcus compared to non-PM exposure groups. These findings will help delineate the possible roles and associations of altered microbiota resulting from the studied interventions, paving the way for future mechanistic research.

Changes in frailty and incident cardiovascular disease in three prospective cohorts

BACKGROUND AND AIMS

Previous studies found that frailty was an important risk factor for cardiovascular disease (CVD). However, previous studies only focused on baseline frailty status, not taking into consideration the changes in frailty status during follow-up. The aim of this study was to investigate the associations of changes in frailty status with incident CVD.

METHODS

This study used data of three prospective cohorts: China Health and Retirement Longitudinal Study (CHARLS), English Longitudinal Study of Ageing (ELSA), and Health and Retirement Study (HRS). Frailty status was evaluated by the Rockwood frailty index and classified as robust, pre-frail, or frail. Changes in frailty status were assessed by frailty status at baseline and the second survey which was two years after the baseline. Cardiovascular disease was ascertained by self-reported physician-diagnosed heart disease (including angina, heart attack, congestive heart failure, and other heart problems) or stroke. Cox proportional hazard models were used to calculate the hazard ratio (HR) and 95% confidence interval (95% CI) after adjusting for potential confounders.

RESULTS

A total of 7116 participants from CHARLS (female: 48.6%, mean age: 57.4 years), 5303 from ELSA (female: 57.7%, mean age: 63.7 years), and 7266 from HRS (female: 64.9%, mean age: 65.1 years) were included according to inclusion and exclusion criteria. The median follow-up periods were 5.0 years in the CHARLS, 10.7 years in the ELSA, and 9.5 years in the HRS. Compared with stable robust participants, robust participants who progressed to pre-frail or frail status had increased risks of incident CVD (CHARLS, HR = 1.84, 95% CI: 1.54-2.21; ELSA, HR = 1.53, 95% CI: 1.25-1.86; HRS, HR = 1.59, 95% CI: 1.31-1.92). In contrast, frail participants who recovered to robust or pre-frail status presented decreased risks of incident CVD (CHARLS, HR = 0.62, 95% CI: 0.47-0.81; ELSA, HR = 0.49, 95% CI: 0.34-0.69; HRS, HR = 0.70, 95% CI: 0.55-0.89) when compared with stable frail participants. These decreased risks of incident CVD were also observed in pre-frail participants who recovered to robust status (CHARLS, HR = 0.66, 95% CI: 0.52-0.83; ELSA, HR = 0.65, 95% CI: 0.49-0.85; HRS, HR = 0.71, 95% CI: 0.56-0.91) when compared with stable pre-frail participants.

CONCLUSIONS

Different changes in frailty status are associated with different risks of incident CVD. Progression of frailty status increases incident CVD risks, while recovery of frailty status decreases incident CVD risks.

Association of ambient air pollution and pregnancy rate among women undergoing assisted reproduction technology in Fujian, China: A retrospective cohort study

BACKGROUND

Previous studies have reported the impact of ambient air pollutants on assisted reproduction. They concentrated on highly polluted environments and individual pollutants. It is unclear whether these effects continue at lower levels and as mixed effects. We aimed to study the influence of lower pollutant concentrations on pregnancy rates and identify vulnerable populations.

METHODS

We conducted a retrospective cohort study involving 9465 patients with infertility who received treatment from a local hospital between 2015 and 2021. Daily average levels of six pollutants (PM2.5, PM10, NO2, CO, SO2, and O3) were collected from air quality monitoring stations. We employed generalized linear regression models (logistic, linear, and lasso), weighted quantile sum (WQS) regression, and Bayesian kernel machine regression (BKMR) to assess the impact of pollutants on pregnancy rates. Additionally, stratified analyses were performed to identify potentially vulnerable populations.

RESULTS

Findings from the generalized linear models revealed a significant negative correlation between interquartile range increment exposure to PM2.5 (OR = 1.17, 95 % CI = 1.09-1.26), PM10 (OR = 1.18, 95 % CI = 1.11-1.26), NO2 (OR = 1.21, 95 % CI = 1.13-1.30), CO (OR = 1.02, 95 % CI = 1.00-1.03), SO2 (OR = 1.11, 95 % CI = 1.05-1.17) and pregnancy rate when considering the effects of individual pollutants. The WQS index exhibited a negative correlation with pregnancy rates and the number of oocytes retrieved (aOR = 1.20, 95 % CI = 1.08-1.34). BKMR analyses indicated an overall significant trend of decreasing pregnancy rates as pollutant concentrations increased across percentiles. Stratified analysis unveiled heightened sensitivity to pollutants among individuals aged ≥35 years.

CONCLUSIONS

By comparing results obtained from diverse models, we observed that exposure to lower levels of air pollutants led to decreased pregnancy rates. Notably, PM10, NO2, SO2, and CO emerged as the four most prominent pollutants in this context. Moreover, stratified analyses highlighted that individuals aged ≥35 years exhibited heightened susceptibility to pollutants.

Multi-scale spatiotemporal trends and corresponding disparities of PM2.5 exposure in China

Despite the effectiveness of targeted measures to mitigate air pollution, China-a developing country with high PM2.5 concentration and dense population, faces a high risk of PM2.5-related mortality. However, existing studies on long-term PM2.5 exposure in China have not reached a consensus as to which year it peaked during the "initially pollution, then mitigation" process. Furthermore, analyses in these studies were rarely undertaken from multi-spatial scales. In this study, a piecewise linear regression model was employed to detect the turning point of population-weighted exposure (PWE) to PM2.5 for the period 2000-2020. Multi-scale spatiotemporal patterns of PM2.5 exposure were evaluated during upward and downward periods at the province, city and county levels, and their corresponding disparities were estimated using the Gini index. The results showed that 2013 was the breakpoint year for PM2.5 PWE across China from 2000 to 2020. Cities and counties where PM2.5 PWE displayed increasing trends during the mitigation stage (2013-2020) basically became the heaviest PM2.5 exposure regions in 2020. High PM2.5 exposure was observed in Beijing-Tianjin-Hebei, Central China, and the Tarim Basin in Xinjiang, whereas lower PM2.5 exposure regions were mainly concentrated in Hainan Province, the Hengduan Mountains, and northern Xinjiang. These cross-provincial patterns might have been overlooked when conducting macro-scale analyses. Province-level PM2.5 exposure inequality was less than the city- and county-levels estimations, and regional inequalities were high in eastern and western China. In this study, multi-scale PM2.5 exposure trends and their disparities over a prolonged period were investigated, and the findings provide a reference for pollution mitigation and regional inequality reduction.

Causal association between air pollution and frailty: a Mendelian randomization study

Backgrounds

Frailty is a significant problem for older persons since it is linked to a number of unfavorable consequences. According to observational researches, air pollution may raise the risk of frailty. We investigated the causal association between frailty and air pollution (including PM2.5, PM2.5-10, PM10, nitrogen dioxide, and nitrogen oxides) using Mendelian randomization approach.

Methods

We conducted MR analysis using extensive publically accessible GWAS (genome-wide association studies) summary data. The inverse variance weighted (IVW) method was employed as the primary analysis method. The weighted median model, MR-Egger, simple model, and weighted model approaches were chosen for quality control. The Cochran's Q test was utilized to evaluate heterogeneity. Pleiotropy is found using the MR-Egger regression test. The MR-PRESSO method was used to recognize outliers. The leave-one-out strategy was used to conduct the sensitivity analysis.

Results

MR results suggested that PM2.5 was statistically significantly associated with frailty [odds ratio (OR) = 1.33; 95%confidence interval (CI) = 1.12-1.58, p = 0.001] in IVW method. We observed no statistical association between PM2.5-10(OR = 1.00, 95% CI = 0.79-1.28, p = 0.979), PM10(OR = 0.91, 95% CI = 0.75-1.11, p = 0.364), nitrogen dioxide (OR = 0.98, 95% CI = 0.85-1.12, p = 0.730), nitrogen oxides (OR = 1.15, 95% CI = 0.98-1.36, p = 0.086) and frailty. There was no pleiotropy in the results. The sensitivity analysis based on the leave-one-out method showed that the individual single nucleotide polymorphisms (SNPs) did not affect the robustness of the results.

Conclusion

The current MR investigation shows a causal association between PM2.5 and frailty. Frailty's detrimental progression may be slowed down with the help of air pollution prevention and control.