We collected data from Kailuan cohort study from 2006 to 2011 to examine whether short-term effects of ambient temperature on heart rate (HR) and blood pressure (BP) are non-linear or linear, and their potential modifying factors. The HR, BP and individual information, including basic characteristics, life style, socio-economic characteristics and other characteristics, were collected for each participant. Daily mean temperature and relative humidity were collected. A regression model was used to evaluate associations of temperature with HR and BP, with a non-linear function for temperature. We also stratified the analyses in different groups divided by individual characteristics. 47,591 residents were recruited. The relationships of temperature with HR and BP were “V” shaped with thresholds ranging from 22 °C to 28 °C. Both cold and hot effects were observed on HR and BP. The differences of effect estimates were observed among the strata of individual characteristics. The effect estimate of temperature was higher among older people. The cold effect estimate was higher among people with lower Body Mass Index. However, the differences of effect estimates among other groups were inconsistent. These findings suggest both cold and hot temperatures may have short-term impacts on HR and BP. The individual characteristics could modify these relationships.

BACKGROUND: Potential adverse health effects of Asian dust exposure have been reported, but systematic reviews and quantitative syntheses are lacking. OBJECTIVE: We reviewed epidemiologic studies that assessed the risk of mortality, hospital admissions, and symptoms/dysfunction associated with exposure to Asian dust. METHODS: We performed a systematic search of PubMed and Web of Science to identify studies that reported the association between Asian dust exposure and human health outcomes. We conducted separate meta-analyses using a random-effects model for mortality and hospital admissions for a specific health outcome and assessed pooled estimates for each lag when at least three studies were available for a specific lag. RESULTS: We identified 89 studies that met our inclusion criteria for the systematic review, and 21 studies were included in the meta-analysis. The pooled estimates (percentage changes) of mortality from circulatory and respiratory causes for Asian dust days vs. non-Asian dust days were 2.33% [95% confidence interval (CI): 0.76, 3.93] increase at lag 0 and 3.99% (95% CI: 0.08, 8.06) increase at lag 3, respectively. The increased risk for hospital admissions for respiratory disease, asthma, and pneumonia peaked at lag 3 by 8.85% (95% CI: 0.80, 17.55), 14.55% (95% CI: 6.74, 22.94), and 8.51% (95% CI: 2.89, 14.44), respectively. Seven of 12 studies reported reduced peak expiratory flow, and 16 of 21 studies reported increased respiratory symptoms associated with Asian dust exposure. There were substantial variations between the studies in definitions of Asian dust, study designs, model specifications, and confounder controls. DISCUSSION: We found evidence of increased mortality and hospital admissions for circulatory and respiratory events. However, the number of studies included in the meta-analysis was not large and further evidences are merited to strengthen our conclusions. Standardized protocols for epidemiological studies would facilitate interstudy comparisons.

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Highlights Second COVID-19 wave in Malaysia doubled every 3.8 days and decayed after 1 month. Instantaneous reproduction number R t peaked at 3.1 and case fatality rate is 1.9. Movement control measures began 3 days after peaked R t and lasted for 8 weeks. Combining multiple control measures could provide effective exit strategy. Disproportionately impacted subpopulations should be identified and supported.

China is suffering from severe air pollution from fine particulate matter [≤ 2.5 μm in aerodynamic diameter (PM2.5)], especially East China. But its future trends and potential health impacts remain unclear. The study objectives were to project future trends of PM2.5 and its short-term effect on mortality in East China by 2030. First, daily changes in PM2.5 concentrations between 2005 and 2030 were projected under the "current legislation" scenario (CLE) and the "maximum technically feasible reduction" scenario (MFR). Then, they were linked to six population projections, two mortality rate projections, and PM2.5-mortality associations to estimate the changes in PM2.5-related mortality in East China between 2005 and 2030. Under the CLE scenario, the annual mean PM2.5 concentration was projected to decrease by 0.62 μg/m(3) in East China, which could cause up to 124,000 additional deaths, when considering the population growth. Under the MFR scenario, the annual mean PM2.5 concentration was projected to decrease by 20.41 μg/m(3) in East China. At least 230,000 deaths could be avoided by such a large reduction in PM2.5 concentration under MFR scenario, even after accounting for the population growth. Therefore, our results suggest that reducing PM2.5 concentration substantially in East China would benefit the public health. Otherwise, it may still remain as a great health risk in the future, especially when the population keeps growing.

Background Although seasonal variations in mortality have been recognized for millennia, the role of temperature remains unclear. We aimed to assess seasonal variation in mortality and to examine the contribution of temperature. Methods We compiled daily data on all-cause, cardiovascular and respiratory mortality, temperature and indicators on location-specific characteristics from 719 locations in tropical, dry, temperate and continental climate zones. We fitted time-series regression models to estimate the amplitude of seasonal variation in mortality on a daily basis, defined as the peak-to-trough ratio (PTR) of maximum mortality estimates to minimum mortality estimates at day of year. Meta-analysis was used to summarize location-specific estimates for each climate zone. We estimated the PTR with and without temperature adjustment, with the differences representing the seasonal effect attributable to temperature. We also evaluated the effect of location-specific characteristics on the PTR across locations by using meta-regression models. Results Seasonality estimates and responses to temperature adjustment varied across locations. The unadjusted PTR for all-cause mortality was 1.05 [95% confidence interval (CI): 1.00–1.11] in the tropical zone and 1.23 (95% CI: 1.20–1.25) in the temperate zone; adjusting for temperature reduced the estimates to 1.02 (95% CI: 0.95–1.09) and 1.10 (95% CI: 1.07–1.12), respectively. Furthermore, the unadjusted PTR was positively associated with average mean temperature. Conclusions This study suggests that seasonality of mortality is importantly driven by temperature, most evidently in temperate/continental climate zones, and that warmer locations show stronger seasonal variations in mortality, which is related to a stronger effect of temperature.