Does physical activity attenuate the association between ambient PM2.5 and physical function?

Healthier lifestyles can modify the air pollutants effect on cardiovascular disease among the middle-aged and elderly

There is increasing evidence that air pollutants significantly increase the risk of cardiovascular disease (CVD). Nevertheless, less research has been conducted to date to reveal protective factors. Therefore, this study aims to indicate whether a healthy lifestyle can modify the effects of environmental pollution on CVD. This study screened 3010 participants from the China Health and Retirement Longitudinal Study (CHARLS) Wave 3 (2015). The study aimed to systematically demonstrate the impact of environmental pollution on CVD and elucidate the role of a healthy lifestyle. Air pollutant data were obtained from the China High Air Pollutant (CHAP) datasets. We analyzed the relationship between these pollutants and cardiovascular disease risk using generalized linear mixed models. In addition, healthy lifestyles were categorized as low, medium, and high; stratified analyses were conducted to estimate the effect of healthy lifestyles on the risk of CVD due to air pollutants. 607 had CVD among 3010 participants, and the three-year mean concentrations of the pollutants chloride ion (Cl-), nitrate ion (NO3-), particulate matter with a diameter of 10 micrometers or less (PM10), particulate matter with a diameter of 10 micrometers or less (PM1), particulate matter with a diameter of 10 micrometers or less (PM2.5) were each linked 1.37 (95%CI:1.22,1.54), 1.03 (95%CI:1.00,1.06), 1.02 (95%CI:1.01,1.03), 1.01 (95%CI:1.00,1.01), and 1.01 (95%CI:1.00,1.01) fold risk of CVD, respectively. For the subgroups of low, medium, and high according to the healthy lifestyle score in model 2, the average concentration of Cl- pollutant was each associated with 1.34 (1.12,1.62), 1.34 (1.12,1.61), and 1.32 (1.03,1.71) times risk with CVD, respectively. The NO3 - was each associated with 1.06 (1.02,1.11), 1.01 (0.97,1.05), and 0.98 (0.93,1.04) times risk with CVD, respectively. The PM1 was each associated with 1.03 (1.01,1.05), 1.01 (0.99,1.02), and 1.00 (0.97,1.02) times risk with CVD, respectively. The PM10 was each associated with 1.01 (1.00,1.01), 1.01 (0.99,1.01), and 1.00 (0.99,1.01) times risk with CVD, respectively. PM2.5 was each associated with 1.02 (1.01,1.03), 1.00 (0.99,1.01), and 1.00 (0.99,1.01) times risk with CVD, respectively. Exposure to these pollutants(Cl-, NO3-, PM10, PM1, PM2.5)is associated with higher risk of CVD, and healthier lifestyles can reduce the risk of CVD due to overall air pollutants.

PM2.5 exposure modifies the association of physical activity with depressive symptoms and glaucoma in middle aged and elderly Chinese

It remains unclear that trade-off between the benefits of regular physical activity (PA) and the potentially harmful effects of exposure to PM2.5 (particulate matter with aerodynamic diameter < 2.5 μm) in highly polluted regions. Therefore, we aimed to investigate the modification of PM2.5 on the associations of PA volume and intensity with depressive symptoms and glaucoma in individuals with or without depressive symptoms. Data of this study was obtained from the China Health and Retirement Longitudinal Survey (CHARLS) implemented during 2011 to 2020. PA volume and intensity were measured by a standardized questionnaire; a machine learning prediction model was applied to ascertain the PM2.5 concentrations. Cox proportional hazards regression models were employed to explore associations. A total of 20,930 participants were finally included, with 11,214 analyzed for PA and depressive symptom risk and 16,965 analyzed for PA and glaucoma risk. PA volume or intensity was independent protective factor for incident depressive symptoms, while PM2.5 was independent risk factor for depressive symptoms and glaucoma in participants with or without depressive symptoms. Among participants with low PM2.5 exposure (< 35 micrograms per cubic meter [µg/m3]), PA volume or intensity showed an inverse association with the risk of incident depressive symptoms, but insignificant associations between PA volume or intensity and glaucoma risk were observed in either participants with or without depressive symptoms. Among participants with high PM2.5 exposure (≥ 35 µg/m3), higher PA volume or intensity increased the risks of depressive symptoms and glaucoma. Higher PA level was associated with a reduced risk of depressive symptoms only among participants with low PM2.5 exposure, and higher PA did not decrease the risk of glaucoma regardless of PM2.5 level. Our findings recommend regular PA to prevent depressive symptoms in less polluted regions and reinforce the importance of air quality improvement.

Physical activity trajectories and their determinants in older adults with subjective cognitive decline: Results from a national cohort study

OBJECTIVES

This study aims to investigate the trajectories of physical activity among older adults with subjective cognitive decline and explore the determinants influencing these trajectories within a national cohort.

DESIGN

Cohort study.

METHODS

We used data from a national cohort called the China Health and Retirement Longitudinal Study and included 1063 participants. The short international physical activity questionnaire was used to measure the moderate-to-vigorous physical activity, and group-based trajectory modeling was applied to explore the moderate-to-vigorous physical activity trajectories. The predictors were selected based on the social-ecological model. Multinomial logistic regression was conducted to identify the predictors of physical activity trajectories.

RESULTS

Our findings reveal three trajectories of physical activity among older adults with subjective cognitive decline: the rapid decline group (10.35 %), stable inactive group (80.62 %), and rapid growth group (9.03 %). Several determinants emerged as significant predictors influencing these trajectories, including age, smoking status, body mass index, number of comorbidities, mobility activities of daily life, marital status, family size, frequency of social activities, and residence.

CONCLUSIONS

Our study highlights the predominance of the stable inactive group among older adults with subjective cognitive decline, emphasizing the need for targeted interventions. Addressing some modified determinants, such as smoking status, body mass index, number of comorbidities, mobility activities of daily life, family size, frequency of social activities, and residence is crucial for promoting physical activity in this population.

Gender-specific dual effects of physical activity on depression and mortality: a nine-year cohort study in Chinese adults aged 45 and above

Background

Regular participation in physical activity (PA) reduces all-cause mortality (ACM) in the general population. However, the effects of PA on depressed patients and potential gender-specific responses have not been fully elucidated. In this study, we aimed to investigate the role of PA on new-onset depression and ACM in Chinese adults aged 45 year and older, with particular emphasis on gender differences.

Methods

This was a longitudinal cohort study that took place over a nine-year period and featured 2,264 participants drawn from the China Health and Retirement Longitudinal Study (CHARLS). PA levels were categorized into quartiles using metabolic equivalents (MET; minutes/week), and depression was evaluated according to the 10-item Center for Epidemiologic Studies Depression Scale (CESD-10) scale. Specific relationships between PA, depression, and mortality were then investigated by applying multivariate logistic regression and Cox proportional hazards models.

Results

Highest quantile levels of PA were correlated with a 37% increase in the risk of new-onset depression in middle-aged (45-59 years) and older adults (>60 years). This association was predominantly influenced by a significant increase in the risk of mild depression (a score of 10-14 on the CESD-10) (odds ratio [OR]: 1.76; 95% confidence interval [CI]: 1.29-2.42, p < 0.001), with a more pronounced effect observed in women (OR: 1.83; 95% CI: 1.26-2.66, p = 0.002). A critical threshold for PA was identified at 4536 MET-minutes/week, beyond which the risk of depression increased significantly (p < 0.05). Conversely, higher levels of PA were linked to a 90% reduction in ACM (HR: 0.10; 95% CI: 0.02-0.44, p = 0.002), with the effect being more pronounced in men.

Conclusion

While PA reduces mortality, excessive activity may increase the risk of mild depression, particularly in women. These findings highlight the need for gender-specific PA guidelines that balance physical and mental health outcomes.

Air pollution is linked to cognitive decline independent of hypersensitive C-reactive protein: insights from middle-aged and older Chinese

BACKGROUND

Long-term air pollution exposure and inflammation are considered to be associated with cognitive decline. However, whether air pollution exposure related cognitive decline is dependent on inflammation remains uncertain.

MATERIALS AND METHODS

The present study collected data from China Health and Retirement Longitudinal Study (CHARLS) at baseline in 2011, with a follow up period in 2015. Concentration of air pollutants (particles with diameters ≤ 1.0 μm [PM1], ≤ 2.5 μm [PM2.5], ≤ 10 μm [PM10], nitrogen dioxide [NO2] and ozone [O3]) were obtained from China High Air Pollutants (CHAP) dataset. Hypersensitive C-reactive protein (hs-CRP), a systemic inflammation marker, was measured in blood of subjects and cognitive function was assessed by standardized questionnaire.

RESULTS

A total of 6434 participants were included in the study. Lower exposure to PM2.5, PM1, PM10 and NO2 were associated with mitigated cognitive decline. The odds ratios (ORs) for air pollutants changes and cognitive decline and 95% confidence intervals (CIs) were as follows: PM2.5-0.934(0.925, 0.943), PM1- 0.945 (0.935,0.955), PM10-0.977(0.972,0.982) and NO2-0.962(0.950,0.975), respectively. Hs-CRP showed no significant correlation with cognitive decline or change in levels of air pollution. The interaction regression analyses, both unadjusted and adjusted, did not uncover any significant correlation between hs-CRP and air pollution with respect to cognitive decline. Bootstrap test exhibited no significant mediating effect of hs-CRP on the relationship between any air pollutants and cognitive decline, the indirect effects of hs-CRP in conjunction with exposure to different air pollutants were all found to be non-significant, with the following bootstrap CIs and p-values: PM2.5-1.000([1.000,1.000], P = 0.480),PM1-1.000([1.000,1.000], P = 0.230),PM10-1.000([1.000,1.000], P = 0.650), O3-1.000([1.000,1.000], P = 0.470), ΔNO2-1.000([1.000,1.000], P = 0.830) .

CONCLUSION

Ambient air pollution exposure was linked to cognitive decline independent of hs-CRP level.

Exploring the Interplay Between Climate Change, 24-Hour Movement Behavior, and Health: A Systematic Review

BACKGROUND

Given the emergence of climate change and health risks, this review examined potential relationships between varying indicators of climate change, movement behaviors (ie, physical activity [PA], sedentary behavior, and sleep), and health.

METHODS

Seven databases were searched in March 2020, April 2023, and April 2024. To be included, studies must have examined indicators of climate change and at least one of the movement behaviors as either an exposure or a third variable (ie, mediator/moderator), and a measure of health as outcome. Evidence was summarized by the role (mediator/moderator) that either climate change or movement behavior(s) has with health measures. Relationships and directionality of each association, as well as the strength and certainty of evidence were synthesized.

RESULTS

A total of 79 studies were eligible, representing 6,671,791 participants and 3137 counties from 25 countries (40% low- and middle-income countries). Of 98 observations from 17 studies that examined PA as a mediator, 34.7% indicated that PA mediated the relationship between climate change and health measure such that indicators of adverse climate change were associated with lower PA, and worse health outcome. Of 274 observations made from 46 studies, 28% showed that PA favorably modified the negative association between climate change and health outcome. Evidence was largely lacking and inconclusive for sedentary behavior and sleep, as well as climate change indicators as an intermediatory variable.

CONCLUSIONS

PA may mitigate the adverse impact of climate change on health. Further evidence is needed to integrate PA into climate change mitigation, adaptation, and resilience strategies.

Air pollution exposure in active versus passive travel modes across five continents: A Bayesian random-effects meta-analysis

Epidemiological studies on health effects of air pollution usually estimate exposure at the residential address. However, ignoring daily mobility patterns may lead to biased exposure estimates, as documented in previous exposure studies. To improve the reliable integration of exposure related to mobility patterns into epidemiological studies, we conducted a systematic review of studies across all continents that measured air pollution concentrations in various modes of transport using portable sensors. To compare personal exposure across different transport modes, specifically active versus motorized modes, we estimated pairwise exposure ratios using a Bayesian random-effects meta-analysis. Overall, we included measurements of six air pollutants (black carbon (BC), carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter (PM10, PM2.5) and ultrafine particles (UFP)) for seven modes of transport (i.e., walking, cycling, bus, car, motorcycle, overground, underground) from 52 published studies. Compared to active modes, users of motorized modes were consistently the most exposed to gaseous pollutants (CO and NO2). Cycling and walking were the most exposed to UFP compared to other modes. Active vs passive mode contrasts were mostly inconsistent for other particle metrics. Compared to active modes, bus users were consistently more exposed to PM10 and PM2.5, while car users, on average, were less exposed than pedestrians. Rail modes experienced both some lower exposures (compared to cyclists for PM10 and pedestrians for UFP) and higher exposures (compared to cyclist for PM2.5 and BC). Ratios calculated for motorcycles should be considered carefully due to the small number of studies, mostly conducted in Asia. Computing exposure ratios overcomes the heterogeneity in pollutant levels that may exist between continents and countries. However, formulating ratios on a global scale remains challenging owing to the disparities in available data between countries.

Potential causal links of long-term exposure to PM2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10-year cohort study in South China

There is a lack of evidence from cohort studies on the causal association of long-term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10-year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO4 2-), nitrate (NO3 -), and ammonium (NH4 +) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10-year follow-up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02-1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4 +, OM, NO3 -, and SO4 2- was associated with HRs of 1.36 (95%CI: 1.13-1.65), 1.35 (95%CI: 1.07-1.70), 1.33 (95%CI: 1.11-1.59), 1.32 (95%CI: 1.06-1.64), 1.31 (95%CI: 1.08-1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long-term exposure to PM2.5 and its components and the risk of NPC recurrence.

The mediating effect of TyG-related indicators between long-term exposure to particulate matter and cardiovascular disease: evidence from a national longitudinal cohort study

BACKGROUND

Ambient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association.

METHODS

This cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis.

RESULTS

A total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078-1.195), 1.092 (1.062-1.123), and 1.075 (1.059-1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%.

CONCLUSION

A significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.

Paris air quality monitoring for the 2024 Olympics and Paralympics: focus on air pollutants and pollen

BACKGROUND

Exposure to air pollution can affect the health of individuals with respiratory disease, but may also impede the health and performance of athletes. This is potentially relevant for people travelling to and competing in the Olympic and Paralympic Games (OPG) in Paris. We describe anticipated air quality in Paris based on historical monitoring data and describe the impact of the process on the development of monitoring strategies for future international sporting events.

METHODS

Air pollutant data for July to September 2020-2023 and pollen data for 2015-2022 were provided by Airparif (particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3)) and RNSA stations in the Paris region. Airparif's street-level numerical modelling provided spatial data for the OPG venues.

RESULTS

The maximum daily mean PM2.5 was 11±6 µg/m3 at traffic stations, below the WHO recommended daily air quality threshold (AQT). Daily NO2 concentrations ranged from 5±3 µg/m3 in rural areas to 17±14 µgm3 in urban areas. Near traffic stations, this rose to 40±24 µg/m3 exceeding the WHO AQT. Both peaked around 06:00 and 20:00 UTC (coordinated universal time). The ambient O3 level exceeded the AQT on 20 days per month and peaked at 14:00 UTC. The main allergenic taxa from June to September was Poaceae (ie, grass pollen variety).

CONCLUSION

Air pollutant levels are expected to be within accepted air quality thresholds at the Paris OPG. However, O3 concentrations may be significantly raised in very hot and clear conditions and grass pollen levels will be high, prompting a need to consider and manage this risk in susceptible individuals.

Is subjective life expectancy stronger in older adults with more physical activity? Evidence from China

To explore the relationship between physical activity and subjective life expectancy in an older population. Repeated-measures ANOVA, as well as construction of a cross-lagged model, was conducted with a sample of 4969 older adults from the China Health and Retirement Longitudinal Study data in 2018 and 2020. It was found that T1 subjective life expectancy significantly predicted T2 physical activity (β=0.03, P < 0.01) and T1 physical activity significantly predicted T2 subjective life expectancy (β=0.05, P < 0.05). There was a significant bidirectional predictive relationship between physical activity and subjective life expectancy in older adults, and physical activity is a causal variable for subjective life expectancy.

Health effect of multiple air pollutant mixture on sarcopenia among middle-aged and older adults in China

BACKGROUND

As the global aging process accelerates, the health challenges posed by sarcopenia among middle-aged and older adults are becoming increasingly prominent. However, the available evidence on the adverse effects of air pollution on sarcopenia is limited, particularly in the Western Pacific region. This study aimed to explore relationships of multiple air pollutants with sarcopenia and related biomarkers using the nationally representative database.

METHODS

Totally, 6585 participants aged over 45 years were enrolled from the China Health and Retirement Longitudinal Study (CHARLS) in 2011 and 3443 of them were followed up until 2015. Air pollutants were estimated from high-resolution satellite-based spatial-temporal models. In the cross-sectional analysis, we used generalized linear regression, unconditional logistic regression analytical and restricted cubic spline (RCS) methods to assess the single-exposure and non-linear effects of multiple air pollutants on sarcopenia and related surrogate biomarkers (serum creatinine and cystatin C). Several popular mixture analysis techniques such as Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quantile-based g-computation (Qgcomp) were further used to examinate the combined effects of multiple air pollutants. Logistic regression was used to further analyze the longitudinal association between air pollution and sarcopenia.

RESULTS

Each interquartile range increase in PM2.5, PM10 and NO2 was significantly associated with an increased risk of sarcopenia, with adjusted odds ratios (aORs) of 1.09 [95 % confidence interval (CI): 1.01, 1.20], 1.24 (95 % CI: 1.14, 1.35) and 1.18 (95 % CI: 1.08, 1.28), respectively. Our findings also showed that five air pollutants were significantly associated with the sarcopenia index. In addition, employing a mixture analysis approach, we confirmed significant combined effects of air pollution mixtures on sarcopenia risk and associated biomarkers, with PM10 and PM2.5 identified as major contributors to the combined effect. The results of the exposure-response (E-R) relationships, subgroup analysis, longitudinal analysis and sensitivity analysis all showed the unfavorable impact of air pollution on sarcopenia risk and related vulnerable populations.

CONCLUSIONS

Single-exposure and co-exposure to multiple air pollutants were positively associated with sarcopenia among middle-aged and older adults in China. Our study provided new evidence that air pollution mixture was significantly associated with sarcopenia related biomarkers.

Examining dynamic developmental trends: the interrelationship between age-friendly environments and healthy aging in the Chinese population-evidence from China Health and Retirement Longitudinal Study, 2011-2018

BACKGROUND

The objective of this research is to investigate the dynamic developmental trends between Age-Friendly Environments (AFE) and healthy aging in the Chinese population.

METHODS

This study focused on a sample of 11,770 participants from the CHARLS and utilized the ATHLOS Healthy Aging Index to assess the level of healthy aging among the Chinese population. Linear mixed model (LMM) was used to explore the relationship between AFE and healthy aging. Furthermore, a cross-lagged panel model (CLPM) and a random-intercept cross-lagged panel model (RI-CLPM) were used to examine the dynamic developmental trends of healthy aging, taking into account both Between-Person effects and Within-Person effects.

RESULTS

The results from LMM showed a positive correlation between AFE and healthy aging (β = 0.087, p < 0.001). There was a positive interaction between the geographic distribution and AFE (central region * AFE: β = 0.031, p = 0.038; eastern region * AFE: β = 0.048, p = 0.003). In CLPM and RI-CLPM, the positive effect of healthy aging on AFE is a type of Between-Person effects (β ranges from 0.147 to 0.159, p < 0.001), while the positive effect of AFE on healthy aging is Within-Person effects (β ranges from 0.021 to 0.024, p = 0.004).

CONCLUSION

Firstly, individuals with high levels of healthy aging are more inclined to actively participate in the development of appropriate AFE compared to those with low levels of healthy aging. Furthermore, by encouraging and guiding individuals to engage in activities that contribute to building appropriate AFE, can elevate their AFE levels beyond the previous average level, thereby improving their future healthy aging levels. Lastly, addressing vulnerable groups by reducing disparities and meeting their health needs effectively is crucial for fostering healthy aging in these populations.

Effects of different sizes of ambient particulate matter and household fuel use on physical function: National cohort study in China

BACKGROUND

Impact of outdoor and household air pollution on physical function remains unelucidated. This study examined the influence of various ambient particulate sizes (PM1, PM2.5, and PM10) and household fuel usage on physical function.

METHODS

Data from the China Health and Retirement Longitudinal Study (CHARLS) spanning 2011 and 2015 were utilized. The physical functional score was computed by summing scores from four tests: grip strength, gait speed, chair stand test, and balance. Multivariate linear and linear mixed-effects models were used to explore the separate and combined effects of PM1, PM2.5, PM10 and household fuel use on physical function in the cross-sectional and longitudinal analyses, respectively, and to further observe the effects of fuel cleanup on physical function in the context of air pollution exposure.

RESULTS

Both cross-sectional and longitudinal analyses revealed negative correlations between PM1 (β = -0.044; 95% CI: -0.084, -0.004), PM2.5 (β = -0.024; 95% CI: -0.046, -0.001), PM10 (β = -0.041; 95% CI: -0.054, -0.029), and physical function, with a more pronounced impact observed for fine particulate matter (PM1). Cleaner fuel use was associated with enhanced physical function compared to solid fuels (β = 0.143; 95% CI: 0.070, 0.216). The presence of air pollutants and use of solid fuels had a negative impact on physical function, while cleaner fuel usage mitigated the adverse effects of air pollutants, particularly in areas with high exposure.

CONCLUSION

This study underscores the singular and combined detrimental effects of air pollutants and solid fuel usage on physical function. Addressing fine particulate matter, specifically PM1, and prioritizing efforts to improve household fuel cleanliness in regions with elevated air pollution levels are crucial for preventing physical disability.

Physical activity attenuates the association of long-term exposure to nitrogen dioxide with sleep quality and its dimensions in Chinese rural older adults

BACKGROUND

Joint impacts of air pollution and physical activity (PA) on sleep quality remain unaddressed. We aimed to investigate whether PA attenuates the association of long-term exposure to nitrogen dioxide (NO2) with sleep quality and its dimensions in older adults.

METHODS

This study included 3408 Chinese rural older adults. Annual NO2 was estimated using the Space-Time Extra-Trees model. PA was assessed by International Physical Activity Questionnaire. Sleep quality was evaluated using Pittsburgh Sleep Quality Index (PSQI) scale. Linear regression models were used to assess the associations of long-term NO2 exposure and PA with sleep quality and its dimensions, and interaction plots were used to depict the attenuating effect of PA on associations of NO2 with sleep quality and its dimensions.

RESULTS

Three-year (3-y) average NO2 (per 0.64-μg/m3 increment) was positively associated with global PSQI (β = 0.41, 95 % CI: 0.23, 0.59), sleep duration (β = 0.16, 95 % CI: 0.11, 0.21), and habitual sleep efficiency (β = 0.22, 95 % CI: 0.17, 0.27), while PA was negatively associated with global PSQI (β = -0.33, 95 % CI: -0.46, -0.20) and five domains of PSQI other than sleep duration and sleep disturbances. The associations of NO2 with global PSQI, sleep duration, and habitual sleep efficiency were attenuated with increased PA (Pinteraction were 0.037, 0.020, and 0.079, respectively).

CONCLUSIONS

PA attenuates the adverse impacts of long-term NO2 exposure on sleep quality, especially on sleep duration, and habitual sleep efficiency, in Chinese rural elderly people. Participating in PA should be encouraged in this population, and continued efforts are still needed to reduce air pollution.

Associations of long-term exposure to air pollution and green space with reproductive hormones among women undergoing assisted reproductive technology: A longitudinal study

Studies investigating the association between long-term exposure to air pollution (AP)/green space and female reproductive hormones are still limited. Furthermore, their interactive effects remain unclear. Our study sought to explore the separate and interactive impacts of AP/green space on reproductive hormones among women undergoing assisted reproductive technology. We measured estradiol (E2), progesterone (P), testosterone (T), and follicle-stimulating hormone (FSH) from the longitudinal assisted reproduction cohort in Anhui, China. The annual mean concentrations of air pollutants were calculated at the residential level. Normalized Difference Vegetation Index (NDVI) within 500-m represented green space exposure. To assess the effect of AP/green space on hormones, we employed multivariable linear mixed-effect models. Our results showed that each one-interquartile range (IQR) increment in particulate matter (PM2.5 and PM10) and sulfur dioxide (SO2) was associated with -0.03[-0.05, -0.01], -0.03[-0.05, -0.02], and -0.03[-0.05, -0.01] decrease in P. An IQR increase in PM2.5, PM10, SO2, and carbon monoxide (CO) was associated with a -0.16[-0.17, -0.15], -0.15[-0.16, -0.14], -0.15[-0.16, -0.14], and -0.12[-0.13, -0.11] decrease in T and a -0.31[-0.35, -0.27], -0.30[-0.34, -0.26], -0.26[-0.30, -0.22], and -0.21[-0.25, -0.17] decrease in FSH. Conversely, NDVI500-m was associated with higher levels of P, T, and FSH, with β of 0.05[0.02, 0.08], 0.06[0.04, 0.08], and 0.07[0.00, 0.14]. Moreover, we observed the "U" or "J" exposure-response curves between PM2.5, PM10, and SO2 concentrations and E2 and P levels, as well as "inverted-J" curves between NDVI500-m and T and FSH levels. Furthermore, we found statistically significant interactions of SO2 and NDVI500-m on E2 and P as well as CO and NDVI500-m on E2. These findings indicated that green space might mitigate the negative effects of SO2 on E2 and P, as well as the effect of CO on E2. Future research is needed to determine these findings and underlying mechanisms.

Fine particulate matter and its constituent on ovarian reserve: Identifying susceptible windows of exposure

BACKGROUND

Little is known about the associations of exposure to fine particulate matter (PM2.5) and its constituents with ovarian reserve, and the potential susceptible window of exposure remains unclear.

METHODS

We performed a retrospective cohort study of 5189 women who attended a fertility center in Hubei, China, during 2019-2022, and estimated concentrations of PM2.5 and its major constituents during the development of follicles (4th-6th month [W1], 0-4th month [W2], 0-6th month [W3]) and 1-year before measurement (W4) based on Tracking Air Pollution in China database. We used multivariable linear regression and logistic regression models to examine the associations of PM2.5 and its constituent exposures with anti-Müllerian hormone (AMH), the preferred indicator of ovarian reserve.

RESULTS

We observed significantly decreased AMH levels associated with increasing PM2.5 concentrations, with the percent changes (95 % confidence intervals [CIs]) of 1.99 % (0.24 %-3.71 %) during W1 and 3.99 % (0.74 %-7.15 %) during W4 for per 10 μg/m3 increases in PM2.5.When PM2.5 exposure levels were equal to 50th percentile (32.6-42.3 μg/m3) or more, monotonically decreased AMH levels and increased risks of low AMH were seen with increasing PM2.5 concentrations during W1 and W4 (P < 0.05). Black carbon (BC), ammonium (NH4+), nitrate (NO3-), and organic matter (OM) during W1, and NH4+, NO3-, as well as sulfate (SO42-) during W4 were significantly associated with decreased AMH. Moreover, PM2.5 and SO42- exposures during W4 were positively associated with low AMH. Additionally, the associations were stronger among women aged <35 years, lived in urban regions, or measured AMH in cold-season (P for interaction <0.05).

CONCLUSION

PM2.5 and specific chemical components (particularly NH4+, NO3-, and SO42-) exposure during the secondary to antral follicle stage and 1-year before measurement were associated with diminished ovarian reserve (DOR), indicating the adverse impact of PM2.5 and its constituent exposures on female reproductive potential.