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AbstractObjectiveTo estimate the risks of daily hospital admissions for cause specific major cardiovascular diseases associated with short term exposure to ambient fine particulate matter (aerodynamic diameter ≤2.5 μm; PM2.5) pollution in China.DesignNational time series study.Setting184 major cities in China.Population8 834 533 hospital admissions for cardiovascular causes in 184 Chinese cities recorded by the national database of Urban Employee Basic Medical Insurance from 1 January 2014 to 31 December 2017.Main outcome measuresDaily counts of city specific hospital admissions for primary diagnoses of ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke among different demographic groups were used to estimate the associations between PM2.5 and morbidity. An overdispersed generalised additive model was used to estimate city specific associations between PM2.5 and cardiovascular admissions, and random effects meta-analysis used to combine the city specific estimates.ResultsOver the study period, a mean of 47 hospital admissions per day (standard deviation 74) occurred for cardiovascular disease, 26 (53) for ischaemic heart disease, one (five) for heart failure, two (four) for heart rhythm disturbances, 14 (28) for ischaemic stroke, and two (four) for haemorrhagic stroke. At the national average level, an increase of 10 μg/m3 in PM2.5 was associated with a 0.26% (95% confidence interval 0.17% to 0.35%) increase in hospital admissions on the same day for cardiovascular disease, 0.31% (0.22% to 0.40%) for ischaemic heart disease, 0.27% (0.04% to 0.51%) for heart failure, 0.29% (0.12% to 0.46%) for heart rhythm disturbances, and 0.29% (0.18% to 0.40%) for ischaemic stroke, but not with haemorrhagic stroke (−0.02% (−0.23% to 0.19%)). The national average association of PM2.5 with cardiovascular disease was slightly non-linear, with a sharp slope at PM2.5 levels below 50 μg/m3, a moderate slope at 50-250 μg/m3, and a plateau at concentrations higher than 250 μg/m3. Compared with days with PM2.5 up to 15 μg/m3, days with PM2.5 of 15-25, 25-35, 35-75, and 75 μg/m3 or more were significantly associated with increases in cardiovascular admissions of 1.1% (0 to 2.2%), 1.9% (0.6% to 3.2%), 2.6% (1.3% to 3.9%), and 3.8% (2.1% to 5.5%), respectively.According to projections, achieving the Chinese grade 2 (35 μg/m3), Chinese grade 1 (15 μg/m3), and World Health Organization (10 μg/m3) regulatory limits for annual mean PM2.5 concentrations would reduce the annual number of admissions for cardiovascular disease in China. Assuming causality, which should be done with caution, this reduction would translate into an estimated 36 448 (95% confidence interval 24 441 to 48 471), 85 270 (57 129 to 113 494), and 97 516 (65 320 to 129 820), respectively.ConclusionsThese data suggest that in China, short term exposure to PM2.5 is associated with increased hospital admissions for all major cardiovascular diseases except for haemorrhagic stroke, even for exposure levels not exceeding the current regulatory limits.

To examine the association of baseline body mass index (BMI) and BMI change with cognitive impairment among older adults in China. The study included data from the Chinese Longitudinal Healthy Longevity Study, a national community-based prospective cohort study from 2002 to 2018. Baseline BMI and BMI change were available for 12,027 adults aged older than 65 years. Cognitive impairment was defined as Chinese version of the Mini Mental State Examination score lower than 18. Multivariable Cox proportional hazard model was used. Among 12,027 participants (mean age was 81.23 years old and 47.48% were male), the proportion of underweight, normal, overweight and obese at baseline was 33.87%, 51.39%, 11.39% and 3.34%, respectively. During an average of 5.9 years’ follow-up, 3086 participants (4.35 per 100 person-years) with incident cognitive impairment were identified. Compared with normal weight group, adjusted hazard ratio (AHR) for cognitive impairment was 0.86 (95% CI 0.75–0.99) among overweight group, whereas corresponding AHR was 1.02 (95% CI 0.94–1.10) in underweight and 1.01 (95% CI 0.80–1.28) in obese participants. Large weight loss (< −10%) was significantly associated with an increased risk of cognitive impairment (AHR, 1.42, 95% CI 1.29–1.56), compared to stable weight status group (−5% ~ 5%). In the restricted cubic spline models, BMI change showed a reverse J-shaped association with cognitive impairment. BMI-defined overweight, but not obesity, was associated with a lower risk of cognitive impairment among elderly Chinese adults, while large weight loss was associated with an increased risk. These findings are consistent with weight loss in the prodromal phase of dementia.

Evidence of the short-term effects of ambient air pollution on the risk of ischemic stroke in low- and middle-income countries is limited and inconsistent. We aimed to examine the associations between air pollution and daily hospital admissions for ischemic stroke in China. We identified hospital admissions for ischemic stroke in 2014-2016 from the national database covering up to 0.28 billion people who received Urban Employee Basic Medical Insurance (UEBMI) in China. We examined the associations between air pollution and daily ischemic stroke admission using a two-stage method. Poisson time-series regression models were firstly fitted to estimate the effects of air pollution in each city. Random-effects meta-analyses were then conducted to combine the estimates. Meta-regression models were applied to explore potential effect modifiers. More than 2 million hospital admissions for ischemic stroke were identified in 172 cities in China. In single-pollutant models, increases of 10 μg/m3 in particulate matter with aerodynamic diameter <2.5 μm (PM2.5), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) and 1 mg/m3 in carbon monoxide (CO) concentrations were associated with 0.34% (95% confidence interval [CI], 0.20%-0.48%), 1.37% (1.05%-1.70%), 1.82% (1.45%-2.19%), 0.01% (-0.14%-0.16%), and 3.24% (2.05%-4.43%) increases in hospital admissions for ischemic stroke on the same day, respectively. SO2 and NO2 associations remained significant in two-pollutant models, but not PM2.5 and CO associations. The effect estimates were greater in cities with lower air pollutant levels and higher air temperatures, as well as in elderly subgroups. The main limitation of the present study was the unavailability of data on individual exposure to ambient air pollution. As the first national study in China to systematically examine the associations between short-term exposure to ambient air pollution and ischemic stroke, our findings indicate that transient increase in air pollution levels may increase the risk of ischemic stroke, which may have significant public health implications for the reduction of ischemic stroke burden in China.

Epidemiological studies have provided compelling evidence of associations between ambient temperature and cardiovascular disease. However, evidence of effects of daily temperature variability on cardiovascular disease is scarce and mixed. We aimed to examine short-term associations between temperature variability and hospital admissions for cause-specific cardiovascular disease in urban China. We conducted a national time-series analysis in 184 cities in China between 2014 and 2017. Data on daily hospital admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke were obtained from the database of Urban Employee Basic Medical Insurance (UEBMI) including 0.28 billion enrollees. Temperature data were acquired from the China Meteorological Data Sharing Service Center. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. City-specific associations between temperature variability and cardiovascular disease were examined with overdispersed Poisson models controlling for calendar time, day of the week, public holiday, and daily mean temperature and relative humidity. Random-effects meta-analyses were performed to obtain national and regional average associations. We also plotted exposure-response relationship curve using a natural cubic spline of temperature variability. There were 8.0 million hospital admissions for cardiovascular disease during the study period. At the national-average level, a 1-°C increase in temperature variability at 0-1 days (TV0-1) was associated with a 0.44% (0.32%-0.55%), 0.31% (0.20%-0.43%), 0.48% (0.01%-0.96%), 0.34% (0.01%-0.67%), and 0.82% (0.59%-1.05%) increase in hospital admissions for cardiovascular disease, ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke, respectively. The estimates decreased but remained significant when controlling for ambient fine particulate matter (PM2.5), NO2, and SO2 pollution. The main limitation of the present study was the unavailability of data on individual exposure to temperature variability. Our findings suggested that short-term temperature variability exposure could increase the risk of cardiovascular disease, which may provide new insights into the health effects of climate change.

Dementia constitutes a worldwide concern. To characterize the age- and sex-specific modifiable risk factor profiles of dementia, we included 497,401 UK Biobank participants (mean age = 56.5 years) without dementia at baseline (2006–2010) and followed them until March 2021. Cox proportional hazard models were used to estimate the age- and sex-specific hazard ratios (HRs) of incident dementia associated with socioeconomic (less education and high Townsend deprivation index), lifestyle (non-moderate alcohol intake, current smoking, suboptimal diet, physical inactivity, and unhealthy sleep duration), and health condition factors (hypertension, diabetes, cardiovascular diseases, and depressive symptoms). We also calculated the population attributable fractions (PAFs) of these factors. During follow-up (mean = 11.6 years), we identified 6564 dementia cases. HRs for the risk factors were similar between the sexes, while most factors showed stronger associations among younger participants. For example, the HRs of smoking were 1.74 (95% CI: 1.23, 2.47) for individuals aged < 50 years, and 1.18 (1.05, 1.33) for those aged ≥ 65 years. Overall, 46.8% (37.4%, 55.2%) of dementia cases were attributable to the investigated risk factors. The PAFs of the investigated risk factors also decreased with age, but that for health condition risk factors decreased with lower magnitude than socioeconomic and lifestyle risk factors. The stronger associations and greater PAFs of several modifiable risk factors for dementia among younger adults than older participants underscored the importance of dementia prevention from an earlier stage across the adult life course.

The primary objective of this study was to assess the association between short-term changes in ambient fine particulate matter (PM 2.5 ) and first hospital admissions for ischemic stroke. We identified 63,956 first hospital admissions for ischemic stroke from the Beijing Medical Claim Data for Employees from January 1, 2010, through June 30, 2012. A generalized additive Poisson model was applied to explore the association between PM 2.5 and admissions for ischemic stroke. We also explore the effect modification of risk by age and gender. The exposure–response relationship between PM 2.5 and admissions for ischemic stroke was approximately linear, with a relatively stable response at lower concentrations (<100 μg/m 3 ) and a steeper response at higher concentrations. A 10 μg/m 3 increase in the same-day PM 2.5 concentration was associated with 0.31% (95% CI, 0.17–0.45%, P  < 1.57 × 10 −5 ) increase in the daily admissions for ischemic stroke. The association was also statistically significant at lag 1, 2, 3, 0–2 and 0–4 days. Subgroup analyses showed that the association was not different between patients ≥65 years and <65 years old or between males and females. In conclusion, short-term exposure to PM 2.5 was positively associated with first hospital admissions for ischemic stroke in Beijing, China.

Background Little is known about the effect of ambient fine particulate matter (PM 2.5 ) on chronic obstructive pulmonary disease (COPD) in China. The objective of this study was to explore the short-term effects of PM 2.5 on outpatient and inpatient visits for COPD in Beijing, China. Methods A total of 3,503,313 outpatient visits and 126,982 inpatient visits for COPD between January 1, 2010, and June 30, 2012, were identified from the Beijing Medical Claim Data for Employees. A generalized additive Poisson model was applied to estimate the percentage change with 95% confidence interval (CI) in hospital visits for COPD in relation to an interquartile range (IQR) (90.8 μg/m 3 ) increase in PM 2.5 concentrations. Results Short-term exposure to PM 2.5 was significantly associated with increased use of COPD-related health services. There were clear exposure–response associations of PM 2.5 with COPD outpatient and inpatient visits. An IQR increase in the concurrent day PM 2.5 concentrations was significantly associated with a 2.38% (95% CI, 2.22%–2.53%) and 6.03% (95% CI, 5.19%–6.87%) increase in daily outpatient visits and inpatient visits, respectively. Elderly people were more sensitive to the adverse effects. The estimated risk was higher during the warm season compared to the cool season. Conclusions Short-term exposure to PM 2.5 was associated with increased risk of hospital visits for COPD. Our findings contributed to the limited evidence concerning the effects of ambient PM 2.5 on COPD morbidity in developing countries.

Background Visit-to-visit body weight variability (BWV), pulse rate variability (PRV), and blood pressure variability (BPV) have been respectively linked to multiple health outcomes. The associations of the combination of long-term variability in physiological measures with mortality and epigenetic age acceleration (EAA) remain largely unknown. Methods We constructed a composite score of physiological variability (0-3) of large variability in BWV, PRV, and BPV (the top tertiles) in 2006/2008–2014/2016 in the Health and Retirement Study (HRS) and 2011–2015 in the China Health and Retirement Longitudinal Study (CHARLS). All-cause mortality was documented through 2018. EAA was calculated using thirteen DNA methylation-based epigenetic clocks among 1047 participants in a substudy of the HRS. We assessed the relation of the composite score to the risk of mortality among 6566 participants in the HRS and 6906 participants in the CHARLS by Cox proportional models and then investigated its association with EAA using linear regression models. Results A higher score of variability was associated with higher mortality risk in both cohorts (pooled hazard ratio [HR] per one-point increment, 1.27; 95% confidence interval [CI], 1.18, 1.39; P -heterogeneity = 0.344), after adjustment for multiple confounders and baseline physiological measures. Specifically, each SD increment in BWV, PRV, and BPV was related to 21% (95% CI: 15%, 28%), 6% (0%, 13%), and 12% (4%, 19%) higher hazard of mortality, respectively. The composite score was significantly related to EAA in second-generation clocks trained on health outcomes (e.g., standardized coefficient = 0.126 in the Levine clock, 95% CI: 0.055, 0.196) but not in most first-generation clocks trained on chronological age. Conclusions Larger variability in physiological measures was associated with a higher risk of mortality and faster EAA.

Limited evidence was seen as the association between fine particulate matter (PM2.5) and physician visits for allergic rhinitis (AR), especially in countries with extreme air pollution exposure. This paper addressed the issues about the association between PM2.5 and daily outpatient visits for AR among individuals residing in Beijing, China. Data on daily outpatient visits for AR obtained from Beijing Medical Claim Data for Employees and daily PM2.5 concentrations available from US embassy reports were linked by date from January 1, 2010, to June 30, 2012. A time-series analysis was conducted with a generalized additive Poisson model to assess the association between PM2.5 and AR, adjusting for daily average temperature, relative humidity, day of the week, calendar time, and public holiday. Totally, 229,685 outpatient visits for AR were included in the analysis. The daily mean (SD) concentration of PM2.5 was 99.5 (75.3) μg/m3 during the study period. We found that a 10-μg/m3 increase in PM2.5 content was associated with a 0.47% (95% CI: 0.39% to 0.55%) increase in the number of outpatient visits on the same day. Furthermore, results from subgroup analyses suggested that the association was consistently significant among the groups of different ages (< 65 years and ≥ 65 years) and gender. However, this study failed to find a statistically significant association in the autumn season but found significant positive associations during the spring and summer seasons (P for interaction < 0.001). This study indicated a possible association between PM2.5 and AR outpatients, which may benefit further researches in studying PM2.5 and its influence on diseases in a real and seriously air-polluted context.

Background To evaluate the influence of socioeconomic status (SES) on the associations of moderate to vigorous physical activity (MVPA), light intensity physical activity (LIPA), sedentary behavior, and sleep duration with incident type 2 diabetes (T2D). Methods The analysis included 69,461 participants from the UK Biobank who completed an accelerometer-based physical activity measurement. Individual-level SES was assessed via latent class analysis of household income, employment status, and education qualifications. The area-level SES was determined through the Townsend Deprivation Index. The additive hazard model and Cox proportional hazards model were employed to estimate the risk of T2D. Results After a median follow-up of 6.7 years, 1,252 cases of incident T2D were documented. The associations between physical behaviors and T2D risk differed significantly by SES. Compared with individuals with higher SES, those with lower SES presented greater increases in T2D risk associated with low MVPA (68 vs. 31 cases per 10,000 person-years; p for interaction = 0.030), high sedentary behavior (24 vs. 1 cases per 10,000 person-years; p for interaction < 0.001), and short sleep duration (23 vs. 5 cases per 10,000 person-years; p for interaction = 0.003). Area-level SES also modified the relationship between low MVPA and T2D risk on both additive and multiplicative scales (p for interaction < 0.001), with stronger effects observed in socioeconomically disadvantaged groups. Conclusions Addressing insufficient MVPA, prolonged sedentary behavior, and inadequate sleep among individuals with lower SES could significantly reduce the number of T2D cases, highlighting the importance of targeted public health interventions to mitigate disparities in T2D incidence.