Jianpeng Xiao

The short-term effect of heat waves on mortality and its modifiers in China: An analysis from 66 communities

BACKGROUND Many studies have reported increased mortality risk associated with heat waves. However, few have assessed the health impacts at a nation scale in a developing country. This study examines the mortality effects of heat waves in China and explores whether the effects are modified by individual-level and community-level characteristics. METHODS Daily mortality and meteorological variables from 66 Chinese communities were collected for the period 2006-2011. Heat waves were defined as ≥2 consecutive days with mean temperature ≥95th percentile of the year-round community-specific distribution. The community-specific mortality effects of heat waves were first estimated using a Distributed Lag Non-linear Model (DLNM), adjusting for potential confounders. To investigate effect modification by individual characteristics (age, gender, cause of death, education level or place of death), separate DLNM models were further fitted. Potential effect modification by community characteristics was examined using a meta-regression analysis. RESULTS A total of 5.0% (95% confidence intervals (CI): 2.9%-7.2%) excess deaths were associated with heat waves in 66 Chinese communities, with the highest excess deaths in north China (6.0%, 95% CI: 1%-11.3%), followed by east China (5.2%, 95% CI: 0.4%-10.2%) and south China (4.5%, 95% CI: 1.4%-7.6%). Our results indicate that individual characteristics significantly modified heat waves effects in China, with greater effects on cardiovascular mortality, cerebrovascular mortality, respiratory mortality, the elderly, females, the population dying outside of a hospital and those with a higher education attainment. Heat wave mortality effects were also more pronounced for those living in urban cities or densely populated communities. CONCLUSION Heat waves significantly increased mortality risk in China with apparent spatial heterogeneity, which was modified by some individual-level and community-level factors. Our findings suggest adaptation plans that target vulnerable populations in susceptible communities during heat wave events should be developed to reduce health risks.

Particle size and chemical constituents of ambient particulate pollution associated with cardiovascular mortality in Guangzhou, China.

Though significant associations between particulate matter (PM) air pollution and cardiovascular diseases have been widely reported, it remains unclear what characteristics, such as particle size and chemical constituents, may be responsible for the effects. A time-series model was applied to examine the cardiovascular effects of particle size (for the period of 2009-2011) and chemical constituents (2007-2010) in Guangzhou, we controlled for potential confounders in the model, such as time trends, day of the week, public holidays, meteorological factors and influenza epidemic. We found significant associations of cardiovascular mortality with PM10, PM2.5 and PM1; the excess risk (ER) was 6.10% (95% CI: 1.76%, 10.64%), 6.11% (95% CI: 1.76%, 10.64%) and 6.48% (95% CI: 2.10%, 11.06%) for per IQR increase in PM10, PM2.5 and PM1 at moving averages for the current day and the previous 3 days (lag03), respectively. We did not find significant effects of PM2.5-10 and PM1-2.5. For PM2.5 constituents, we found that organic carbon, elemental carbon, sulfate, nitrate and ammonium were significantly associated with cardiovascular mortality, the corresponding ER for an IQR concentration increase at lag03 was 1.13% (95% CI: 0.10%, 2.17%), 2.77% (95% CI: 0.72%, 4.86%), 2.21% (95% CI: 1.05%, 3.38%), 1.98% (95% CI: 0.54%, 3.44%), and 3.38% (95% CI: 1.56%, 5.23%), respectively. These results were robust to adjustment of other air pollutants and they remained consistent in various sensitivity analyses by changing model parameters. Our study suggests that PM1 and constituents from combustion and secondary aerosols might be important characteristics of PM pollution associated with cardiovascular mortality in Guangzhou.

Temperature Changes between Neighboring Days and Mortality in Summer: A Distributed Lag Non-Linear Time Series Analysis

Background Many studies have shown that high temperatures or heat waves were associated with mortality and morbidity. However, few studies have examined whether temperature changes between neighboring days have any significant impact on human health. Method A distributed lag non-linear model was employed to investigate the effect of temperature changes on mortality in summer during 2006–2010 in two subtropical Chinese cities. The temperature change was defined as the difference of the current day’s and the previous day’s mean temperature. Results We found non-linear effects of temperature changes between neighboring days in summer on mortality in both cities. Temperature increase was associated with increased mortality from non-accidental diseases and cardiovascular diseases, while temperature decrease had a protective effect on non-accidental mortality and cardiovascular mortality in both cities. Significant association between temperature changes and respiratory mortality was only found in Guangzhou. Conclusion This study suggests that temperature changes between neighboring days might be an alternative temperature indicator for studying temperature-mortality relationship.

The effect of heat waves on mortality and effect modifiers in four communities of Guangdong Province, China

BACKGROUND Heat waves have been reported to be associated with increased mortality; however, fewer studies have examined the effect modification by heat wave characteristics, individual characteristics and community characteristics. METHODS This study investigated the effect of extreme heat on mortality in 2 urban and 2 rural communities in Guangdong Province, China during 2006-2010. The effect of extreme heat was divided into two parts: main effect due to high temperature and added effect due to prolonged heat for several consecutive days. A distributed lag non-linear model was used to calculate the relative risk with consideration of lag days and potential confounding factors. Separate models were further fit by individual characteristics (cause of death, age and gender) and heat wave characteristics (intensity, duration and timing), and potential effect modification of community characteristics was examined using a meta-regression, such as educational levels, percentage of the elderly, Gross Regional Domestic Product (GDP). RESULTS The overall main effects (ER=8.2%, 95% CI: 3.4%, 13.2%) were greater than the added effects (ER=0.0%, 95% CI: -3.8%, 4.0%) on the current day. The main effect peaked at lag0-2, and was higher for the two rural areas compared to the two cities, for respiratory compared to cardiovascular mortality, for those ≥75 years old and for females. The modifying effects of heat wave characteristics and community characteristics on mortality were not statistically significant. CONCLUSION This study suggests the effects of extreme heat were mainly driven by high temperature, which can be modified by some individual characteristics.

Mortality burden of ambient fine particulate air pollution in six Chinese cities: Results from the Pearl River Delta study.

BACKGROUND Epidemiological studies have reported significant association between ambient fine particulate matter air pollution (PM2.5) and mortality, however, few studies have investigated the relationship of mortality with PM2.5 and associated mortality burden in China, especially in a multicity setting. METHODS We investigated the PM2.5-mortality association in six cities of the Pearl River Delta region from 2013 to 2015. We used generalized additive Poisson models incorporating penalized smoothing splines to control for temporal trend, temperature, and relative humidity. We applied meta-analyses using random-effects models to pool the effect estimates in the six cities. We also examined these associations in stratified analyses by sex, age group, education level and location of death. We further estimated the mortality burden (attributable fraction and attributable mortality) due to ambient PM2.5 exposures. RESULTS During the study period, a total of 316,305 deaths were recorded in the study area. The analysis revealed a significant association between PM2.5 and mortality. Specifically, a 10μg/m3 increase in 4-day averaged (lag03) PM2.5 concentration corresponded to a 1.76% (95% confidence interval (CI): 1.47%, 2.06%) increase in total mortality, 2.19% (95% CI: 1.80%, 2.59%) in cardiovascular mortality, and 1.68% (95% CI: 1.00%, 2.37%) in respiratory mortality. The results were generally robust to model specifications and adjustment of gaseous air pollutants. We estimated that 0.56% (95% CI: 0.47%, 0.66%) and 3.79% (95% CI: 3.14%, 4.45%) of all-cause mortalities were attributable to PM2.5 using Chinas and WHOs air quality standards as the reference, corresponding to 1661 (95% CI: 1379, 1946) and 11,176 (95% CI: 9261, 13,120) attributable premature mortalities, respectively. CONCLUSION This analysis adds to the growing body of evidence linking PM2.5 with daily mortality, and mortality burdens, particularly in one Chinese region with high levels of air pollution.

The temperature–mortality relationship in China: An analysis from 66 Chinese communities

BACKGROUND Previous studies examining temperature-mortality associations in China focused on a single city or a small number of cities. A multi-city study covering different climatic zones is necessary to better understand regional differences in temperature risk on mortality in China. METHODS Sixty-six communities from 7 regions across China were included in this study. We first used a Distributed Lag Non-linear Model (DLNM) to estimate community-specific effects of temperature on non-accidental mortality during 2006-2011. A multivariate meta-analysis was then applied to pool the estimates of community-specific effects. RESULTS A U-shaped curve was observed between temperature and mortality at the national level in China, indicating both low and high temperatures were associated with increased mortality risk. The overall threshold was at about the 75th percentile of the pooled temperature distribution. The relative risk was 1.61 (95% CI: 1.48-1.74) for extremely cold temperature (1st percentile of temperature), and 1.21 (95% CI: 1.10-1.34) for extreme hot temperature (99th percentile of temperature) at lag0-21 days. The temperature-mortality relationship is different for different regions. Compared with north China, south China had a higher minimum mortality temperature (MMT), and there was a larger cold effect in the more southern parts of China and a more pronounced hot effect in more northern parts. CONCLUSIONS Both cold and hot temperatures increase mortality risk in China, and the relationship varies geographically. Our findings suggest that public health policies for climate change adaptation should be tailored to the local climate conditions.

Associations of Short-Term and Long-Term Exposure to Ambient Air Pollutants With Hypertension: A Systematic Review and Meta-Analysis

Hypertension is a major disease of burden worldwide. Previous studies have indicated that air pollution might be a risk factor for hypertension, but the results were controversial. To fill this gap, we performed a meta-analysis of epidemiological studies to investigate the associations of short-term and long-term exposure to ambient air pollutants with hypertension. We searched all of the studies published before September 1, 2015, on the associations of ozone (O3), carbon monoxide (CO), nitrogen oxide (NO2 and NOX), sulfur dioxide (SO2), and particulate matter (PM10 and PM2.5) with hypertension in the English electronic databases. A pooled odds ratio (OR) for hypertension in association with each 10 &mgr;g/m3 increase in air pollutant was calculated by a random-effects model (for studies with significant heterogeneity) or a fixed-effect model (for studies without significant heterogeneity). A total of 17 studies examining the effects of short-term (n=6) and long-term exposure (n=11) to air pollutants were identified. Short-term exposure to SO2 (OR=1.046, 95% confidence interval [CI]: 1.012–1.081), PM2.5 (OR=1.069, 95% CI: 1.003–1.141), and PM10 (OR=1.024, 95% CI: 1.016–1.032) were significantly associated with hypertension. Long-term exposure (a 10 &mgr;g/m3 increase) to NO2 (OR=1.034, 95% CI: 1.005–1.063) and PM10 (OR=1.054, 95% CI: 1.036–1.072) had significant associations with hypertension. Exposure to other ambient air pollutants (short-term exposure to NO2, O3, and CO and long-term exposure to NOx, PM2.5, and SO2) also had positive relationships with hypertension, but lacked statistical significance. Our results suggest that short-term or long-term exposure to some air pollutants may increase the risk of hypertension.

Individual-level and community-level effect modifiers of the temperature–mortality relationship in 66 Chinese communities

Objectives To examine the modification of temperature-mortality association by factors at the individual and community levels. Design and methods This study investigated this issue using a national database comprising daily data of 66 Chinese communities for 2006–2011. A ‘threshold-natural cubic spline’ distributed lag non-linear model was utilised to estimate the mortality effects of daily mean temperature, and then examined the modification of the relationship by individual factors (age, sex, education level, place of death and cause of death) using a meta-analysis approach and community-level factors (annual temperature, population density, sex ratio, percentage of older population, health access, household income and latitude) using a meta-regression method. Results We found significant effects of high and low temperatures on mortality in China. The pooled excess mortality risk was 1.04% (95% CI 0.90% to 1.18%) for a 1°C temperature decrease below the minimum mortality temperature (MMT), and 3.44% (95% CI 3.00% to 3.88%) for a 1°C temperature increase above MMT. At the individual level, age and place of death were found to be significant modifiers of cold effect, while age, sex, place of death, cause of death and education level were effect modifiers of heat effect. At the community level, communities with lower socioeconomic status and higher annual temperature were generally more vulnerable to the mortality effects of high and low temperatures. Conclusions This study identifies susceptibility based on both individual-level and community-level effect modifiers; more attention should be given to these vulnerable individuals and communities to reduce adverse health effects of extreme temperatures.

Lagged Effect of Diurnal Temperature Range on Mortality in a Subtropical Megacity of China

Background Many studies have found extreme temperature can increase the risk of mortality. However, it is not clear whether extreme diurnal temperature range (DTR) is associated with daily disease-specific mortality, and how season might modify any association. Objectives To better understand the acute effect of DTR on mortality and identify whether season is a modifier of the DTR effect. Methods The distributed lag nonlinear model (DLNM) was applied to assess the non-linear and delayed effects of DTR on deaths (non-accidental mortality (NAD), cardiovascular disease (CVD), respiratory disease (RD) and cerebrovascular disease (CBD)) in the full year, the cold season and the warm season. Results A non-linear relationship was consistently found between extreme DTR and mortality. Immediate effects of extreme low DTR on all types of mortality were stronger than those of extreme high DTR in the full year. The cumulative effects of extreme DTRs increased with the increment of lag days for all types of mortality in cold season, and they were greater for extreme high DTRs than those of extreme low DTRs. In hot season, the cumulative effects for extreme low DTRs increased with the increment of lag days, but for extreme high DTR they reached maxima at a lag of 13 days for all types of mortality except for CBD(at lag6 days), and then decreased. Conclusions Our findings suggest that extreme DTR is an independent risk factor of daily mortality, and season is a modifier of the association of DTR with daily mortality.

Differentiating the effects of characteristics of PM pollution on mortality from ischemic and hemorrhagic strokes

Though increasing evidence supports significant association between particulate matter (PM) air pollution and stroke, it remains unclear what characteristics, such as particle size and chemical constituents, are responsible for this association. A time-series model with quasi-Poisson function was applied to assess the association of PM pollution with different particle sizes and chemical constituents with mortalities from ischemic and hemorrhagic strokes in Guangzhou, China, we controlled for potential confounding factors in the model, such as temporal trends, day of the week, public holidays, meteorological factors and influenza epidemic. We found significant association between stroke mortality and various PM fractions, such as PM10, PM2.5 and PM1, with generally larger magnitudes for smaller particles. For the PM2.5 chemical constituents, we found that organic carbon (OC), elemental carbon (EC), sulfate, nitrate and ammonium were significantly associated with stroke mortality. The analysis for specific types of stroke suggested that it was hemorrhagic stroke, rather than ischemic stroke, that was significantly associated with PM pollution. Our study shows that various PM pollution fractions are associated with stroke mortality, and constituents primarily from combustion and secondary aerosols might be the harmful components of PM2.5 in Guangzhou, and this study suggests that PM pollution is more relevant to hemorrhagic stroke in the study area, however, more studies are warranted due to the underlying limitations of this study.