Excess deaths and loss of life expectancy attributed to long-term NO2 exposure in the Chinese elderly.

BACKGROUND: Evidence linking nitrogen dioxide (NO2) air pollution to life span of high-vulnerability older adults is extensively scarce in low- and middle-income countries. This study seeks to quantify mortality risk, excess deaths, and loss of life expectancy (LLE) associated with long-term exposure to NO2 among elderly individuals in China. METHODS: A nationwide dynamic cohort of 20352 respondents ≥65 years old were enrolled from the China Longitudinal Health and Longevity Survey during 2005-2018. Residential exposures to NO2 and co-pollutants were assessed by well-validated spatiotemporal prediction models. A Cox regression model with time-dependent covariates was utilized to quantify the association of all-cause mortality with NO2 exposure, controlling for confounders such as demographics, lifestyle, health status, and ambient temperature. NO2-attributable deaths and LLE were evaluated for the years 2010 and 2020 based on the pooled NO2-mortality relation derived from multi-national cohort investigations. Decomposition analyses were conducted to dissociate net shift in NO2-related deaths between 2010 and 2020 into four primary contributing factors. RESULTS: A total of 14313 deaths were recorded during follow-up of approximately 100 hundred person-years (median 3.6 years). We observed an approximately linear relationship (nonlinear P = 0.882) of NO2 exposure with all-cause death across a broad range from 6.6 to 95.7 µg/m3. Every 10-µg/m3 rise in yearly average NO2 concentration was linked to a hazard ratio (HR) of 1.045 (95% confidence interval [CI]: 1.031-1.059). In the updated meta-analysis of this study and 9 existing cohorts, we estimated a pooled HR of 1.043 (95% CI: 1.023-1.063) for each 10-µg/m3 growth in NO2. Reaching a 10-µg/m3 counterfactual target of NO2 concentration in China could avoid 0.33 (95% empirical CI: 0.19-0.49) million premature deaths and an LLE of 0.40 (95% empirical CI: 0.23-0.59) years in 2010, which greatly dropped to 0.24 (95% empirical CI: 0.14-0.36) million deaths and 0.21 (95% empirical CI: 0.12-0.31) years of LLE in 2020. The net fall in NO2-attributable deaths (-26.8%) between 2010 and 2020 was primarily driven by the declines in both NO2 concentration (-41.6%) and mortality rate (-27.1%) under population growth (+41.0%) and age structure transition (+0.9%). CONCLUSIONS: Our findings provide national evidence for increased risk of premature death and loss of life expectancy attributed to later-life NO2 exposure among the elderly in China. In an accelerated aging society, strengthened clean air actions should be formulated to minimize the health burden and regional inequality in NO2-attributable mortality.

Long-term ozone exposure and all-cause mortality: Cohort evidence in China and global heterogeneity by region.

BACKGROUND: Cohort evidence linking long-term ozone (O3) exposure to mortality remained largely mixed worldwide and was extensively deficient in densely-populated Asia. This study aimed to assess the long-term effects of O3 exposure on all-cause mortality among Chinese adults, as well as to examine potential regional heterogeneity across the globe. METHODS: A national dynamic cohort of 42153 adults aged 16+ years were recruited from 25 provinces across Chinese mainland and followed up during 2010-2018. Annual warm-season (April-September) O3 and year-round co-pollutants (i.e., nitrogen dioxide [NO2] and fine particulate matter [PM2.5]) were simulated through validated spatial-temporal prediction models and were assigned to each enrollee in each calendar year. Cox proportional hazards models with time-varying exposures were employed to assess the O3-mortality association. Concentration-response (C-R) curves were fitted by natural cubic spline function to investigate the potential nonlinear association. Both single-pollutant model and co-pollutant models additionally adjusting for PM2.5 and/or NO2 were employed to examine the robustness of the estimated association. The random-effect meta-analysis was adopted to pool effect estimates from the current and prior population-based cohorts (n = 29), and pooled C-R curves were fitted through the meta-smoothing approach by regions. RESULTS: The study population comprised of 42153 participants who contributed 258921.5 person-years at risk (median 6.4 years), of whom 2382 death events occurred during study period. Participants were exposed to an annual average of 51.4 ppb (range: 22.7-74.4 ppb) of warm-season O3 concentration. In the single-pollutant model, a significantly increased hazard ratio (HR) of 1.098 (95% confidence interval [CI]: 1.023-1.179) was associated with a 10-ppb rise in O3 exposure. Associations remained robust to additional adjustments of co-pollutants, with HRs of 1.099 (95% CI: 1.023-1.180) in bi-pollutant model (+PM2.5) and 1.093 (95% CI: 1.018-1.174) in tri-pollutant model (+PM2.5+NO2), respectively. A J-shaped C-R relationship was identified among Chinese general population, suggesting significant excess mortality risk at high ozone exposure only. The combined C-R curves from Asia (n = 4) and North America (n = 17) demonstrated an overall increased risk of all-cause mortality with O3 exposure, with pooled HRs of 1.124 (95% CI: 0.966-1.307) and 1.023 (95% CI: 1.007-1.039) per 10-ppb rise, respectively. Conversely, an opposite association was observed in Europe (n = 8, HR: 0.914 [95% CI: 0.860-0.972]), suggesting significant heterogeneity across regions (P < 0.01). CONCLUSIONS: This study provided national evidence that high O3 exposure may curtail long-term survival of Chinese general population. Great between-region heterogeneity of pooled O3-mortality was identified across North America, Europe, and Asia.

Residential greenness mitigates mortality risk from short-term airborne particulate exposure: An individual-level case-crossover study.

BACKGROUND: Studies suggested that greenness could reduce death risks related to ambient exposure to particulate matter (PM), while the available evidence was mixed across the globe and substantially exiguous in low- and middle-income countries. By conceiving an individual-level case-crossover study in central China, this analysis primarily aimed to quantify PM-mortality associations and examined the modification effect of greenness on the relationship. METHODS: We investigated a total of 177,058 nonaccidental death cases from 12 counties in central China, 2008-2012. Daily residential exposures to PM2.5 (aerodynamic diameter <2.5 µm), PMc (aerodynamic diameter between 2.5 and 10 µm), and PM10 (aerodynamic diameter <10 µm) were assessed at a 1 × 1-km resolution through satellite-derived machine-learning models. Residential surrounding greenness was assessed using satellite-derived enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI) at multiple buffer sizes (250, 500, and 1000 m). To quantify the acute mortality risks associated with short-term exposure to PM2.5, PMc, and PM10, a time-stratified case-crossover design was utilized in conjunction with a conditional logistic regression model in our main analyses. To investigate the effect modification of greenness on PM-mortality associations, we grouped death cases into low, medium, and high greenness levels using cutoffs of 25th and 75th percentiles of NDVI or EVI exposure, and examined potential effect heterogeneity in PM-related mortality risks among these groups. RESULTS: Mean concentrations (standard deviation) on the day of death were 73.8 (33.4) µg/m3 for PM2.5, 43.9 (17.3) µg/m3 for PMc, and 117.5 (44.9) µg/m3 for PM10. Size-fractional PM exposures were consistently exhibited significant associations with elevated risks of nonaccidental and circulatory mortality. For every increase of 10-µg/m3 in PM exposure, percent excess risks of nonaccidental and circulatory mortality were 0.271 (95% confidence interval [CI]: 0.010, 0.533) and 0.487 (95% CI: 0.125, 0.851) for PM2.5 at lag-01 day, 0.731 (95% CI: 0.108, 1.359) and 1.140 (95% CI: 0.267, 2.019) for PMc at lag-02 day, and 0.271 (95% CI: 0.010, 0.533) and 0.386 (95% CI: 0.111, 0.662) for PM10 at lag-01 day, respectively. Compared to participants in the low-level greenness areas, those being exposed to higher greenness were found to be at lower PM-associated risks of nonaccidental and circulatory mortality. Consistent evidence for alleviated risks in medium or high greenness group was observed in subpopulations of female and younger groups (age <75). CONCLUSIONS: Short-term exposure to particulate air pollution was associated with elevated risks of nonaccidental and circulatory death, and individuals residing in higher neighborhood greenness possessed lower risk of PM-related mortality. These findings emphasized the potential public health advantages through incorporating green spaces into urban design and planning.

Long-term exposure to PM2.5 constituents in relation to glucose levels and diabetes in middle-aged and older Chinese.

BACKGROUND: Previous studies have indicated the associations between fine particulate matter (PM2.5) exposure and diabetes or glucose levels. However, evidence linking PM2.5 constituents and diabetes or glucose levels was extensively scarce, particularly in developing countries. This study aimed to investigate the associations of exposure to PM2.5 and its five constituents (black carbon [BC], organic matter [OM], nitrate [NO3-], sulfate [SO42-], and ammonium [NH4+]) with diabetes and glucose levels among the middle-aged and elderly Chinese populations. METHODS: A national cross-sectional sample of participants aged 45+ years was enrolled from 28 provinces across China's mainland. Health examination and questionnaire survey for each respondent were performed during 2011-2012. Diabetes was determined by alternative definitions, and the main definition (MD) was self-report diabetes or antidiabetic medicine use or HbA1c ≥6.5 or fasting glucose ≥7 mmol/L or random glucose ≥11.1 mmol/L. Monthly exposure to PM2.5 mass and its five constituents (BC, OM, NO3-, SO42-, and NH4+) for each participant at residence were estimated using satellite-based spatiotemporal prediction models. Generalized linear models and linear mixed-effects models were used to assess the effects of exposure to PM2.5 and its constituents on diabetes or glucose levels, respectively. Stratification analyses were done by sex and age. RESULTS: We included a total of 17,326 adults over 45 years in this study. The 3-year mean (interquartile range [IQR]) concentrations of PM2.5, BC, OM, NO3-, SO42-, and NH4+ were 47.9 (27.4) µg/m3, 2.9 (2.2) µg/m3, 9.2 (6.6) µg/m3, 10.2 (9.4) µg/m3, 11.0 (5.2) µg/m3, and 7.1 (4.4) µg/m3, respectively. Per IQR rise in exposure to PM2.5 was significantly associated with an increase of 0.133 mmol/L (95% confidence interval, 0.048-0.219) in glucose concentrations. Similar positive associations were observed for BC (0.097 mmol/L [0.012-0.181]), OM (0.160 mmol/L [0.065-0.256]), NO3- (0.145 mmol/L [0.039-0.251]), SO42- (0.111 mmol/L [0.026-0.196]), and NH4+ (0.135 mmol/L [0.041-0.230]). Under different diabetes definitions, PM2.5 mass and selected constituents with the exception of SO42- were all associated with a higher risk of prevalent diabetes. In MD-based analysis, similar positive associations were observed for four constituents, with corresponding odds ratios of 1.180 (1.097-1.270) for PM2.5, 1.154 (1.079-1.235) for BC, 1.170 (1.079-1.270) for OM, 1.200 (1.098-1.312) for NO3-, and 1.123 (1.037-1.215) for NH4+. Stratified analyses showed a significantly higher risk of diabetes in males (1.225 [1.064-1.411]) than females (1.024 [0.923-1.136]) when exposed to PM2.5. Participants under 65 years were generally more vulnerable to diabetes hazards related to PM2.5 constituents exposure. CONCLUSIONS: Exposures to PM2.5 and its constituents (i.e., BC, OM, NO3-, and NH4+) were positively associated with increased risks of prevalent diabetes and elevated glucose levels in middle-aged and older adults.

Developing and validating intracity spatiotemporal air quality health index in eastern China.

BACKGROUND: Recently pilot published city-level air quality health index (AQHI) provides a useful tool for communicating short-term health risks of ambient air pollution, but fails to account for intracity spatial heterogeneity in exposure and associated population health impacts. This study aims to develop the intracity spatiotemporal AQHI (ST-AQHI) via refined air pollution-related health risk assessments. METHODS: A three-stage analysis was conducted through integrating province-wide death surveillance data and high-resolution gridded estimates of air pollution and climate factors spanning 2016-2019 in Jiangsu Province, eastern China. First, an individual-level case-crossover design was employed to quantify the short-term risk of nonaccidental mortality associated with residential exposure to individual pollutant (i.e., PM2.5, NO2, O3, and SO2). Second, we accumulated and scaled the excess risks arising from multiple pollutants to formulate daily gridded ST-AQHI estimates at 0.1° × 0.1°, dividing exposure-related risks into low (0-3), moderate (4-6), high (7-9), and extreme high (10+) levels. Finally, the effectiveness of ST-AQHI as composite risk communication was validated through checking the dose-response associations of individual ST-AQHI exposure with deaths from nonaccidental and major cardiopulmonary causes via repeating case-crossover analyses. RESULTS: We analyzed a total of 1,905,209 nonaccidental death cases, comprising 785,567 from circulatory diseases and 247,336 from respiratory diseases. In the first-stage analysis, for each 10-µg/m3 rise in PM2.5, NO2, O3, and SO2 exposure at lag-01 day, population risk of nonaccidental death was increased by 0.8% (95% confidence interval: 0.7%, 0.9%), 1.9% (1.7%, 2.0%), 0.4% (0.3%, 0.5%), and 4.1% (3.7%, 4.5%), respectively. Spatiotemporal distribution of ST-AQHI exhibited a consistent declining trend throughout the study period (2016-2019), with annual average ST-AQHI decreasing from 5.2 ± 1.3 to 4.0 ± 1.0 and high-risk days dropping from 15.8% (58 days) to 1.6% (6 days). Exposure associated health risks showed great intracity- and between-city heterogeneities. In the validation analysis, ST-AQHI demonstrated approximately linear, threshold-free associations with multiple death events from nonaccidental and major cardiopulmonary causes, suggesting excellent performance in predicting exposure-related health risks. Specifically, each 1-unit rise in ST-AQHI was significantly associated with an excess risk of 2.0% (1.8%, 2.1%) for nonaccidental mortality, 2.3% (2.1%, 2.6%) for overall circulatory mortality, and 2.7% (2.3%, 3.1%) for overall respiratory mortality, as well as 1.7%-3.0% for major cardiopulmonary sub-causes. CONCLUSIONS: ST-AQHI developed in this study performed well in predicting intracity spatiotemporal heterogeneity of death risks related to multiple air pollutants, and may hold significant practical importance in communicating air pollution-related health risks to the public at the community scales.

Sex disparity in cognitive aging related to later-life exposure to ambient air pollution.

BACKGROUND: Sex difference in the association between ambient air pollution and cognitive aging remained unclear. This current study aimed to assess the impacts of long-term exposure to major air pollutants on cognitive performance among Chinese middle-aged and older adults, and explore whether these associations could be modified by sex. METHODS: By deriving longitudinal data from four waves of the China Health and Retirement Longitudinal Study, we included 13,507 participants aged 45+ years who had at least two cognitive tests recorded from 2011 to 2018. We used a standardized questionnaire consisting of five domain-specific functions to measure global cognitive score. Based on well-validated spatiotemporal datasets, annual average concentrations of ambient fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3) were assigned to each enrollee at prefectural city level and at the simulated residential addresses through Monte Carlo simulation approach. Linear mixed-effects models were applied to assess the impacts of major air pollutants on cognitive function with multiple adjustments. Sex-stratified analyses were performed to examine the potential effect modification on these associations. To enhance the interpretability of our results, we also compared the estimated effects of air pollutants with the effect of aging on cognitive function. RESULTS: We evaluated 38,950 records of cognitive function tests, of which 44.0% were from women. An increase of 10-µg/m3 in PM2.5, NO2 and O3 exposure were associated with 0.36 (95% confidence interval: -0.40, -0.31), 0.51 (-0.60, -0.43) and 0.26 (-0.47, -0.06) points decline in global cognitive score, respectively, equivalent to the effect of aging by 2.8-5.0 years. Sex-stratified analyses suggested significantly greater cognitive impairment associated with air pollutants in women than men. We found reversely J-shaped concentration-response relationships between ambient air pollutants and cognitive decline in both sexes. Main findings on sex-specific associations were robust to the adjustments for covariates, inclusion criteria, and co-pollutant analyses, as well as sensitivity analyses based on simulation-based exposure for PM2.5 and NO2. CONCLUSIONS: Later-life exposure to ambient air pollution may accelerate cognitive aging of middle-aged and older adults, suggesting significant sex disparity with higher vulnerability in women.

Secular trends in global burden of diabetes attributable to particulate matter pollution from 1990 to 2019.

Increasing evidence suggests an association between fine particulate matter (PM2.5) exposure and type 2 diabetes mellitus. However, there is still a lack of comparative evaluation regarding diabetes burden due to ambient and indoor PM2.5 pollution at a global scale. This study attempts to provide a systematic and comprehensive profile for PM2.5-attributable burden of diabetes and its spatiotemporal trends, globally and regionally. Comparative estimates of diabetes attributable to ambient PM2.5 and household air pollution (HAP) from solid fuels for 204 countries and territories were derived from the Global Burden of Disease Study 2019. Globally, 292.5 (95% uncertainty interval: 207.1, 373.4) thousand deaths and 13.0 (9.1, 17.2) million disability-adjusted life years (DALYs) from diabetes were attributed to PM2.5 pollution in 2019, wherein more than two-thirds (67.3% deaths and 69.7% DALYs) were contributed by ambient PM2.5. Compared to 1990, age-standardized DALY rate (ASDR) in 2019 attributable to ambient PM2.5 increased by 85.9% (APC: 2.21% [2.15, 2.27]), while HAP-associated ASDR decreased by 37.9% (APC: - 1.66% [- 1.82, - 1.50]). We observed a negative correlation between SDI and APC in ASMR (rs = - 0.5, p < 0.001) and ASDR (rs = -0.4, p < 0.001) among 204 countries and territories. HAP-related diabetes experienced a sharp decline during 1990-2019, while global burden of diabetes attributable to ambient PM2.5 was rising rapidly. The elderly and people in low-SDI countries suffered from the greatest burden of diabetes due to PM2.5 pollution. More targeted interventions should be taken by governments to reduce PM2.5 exposure and related diabetes burden.

Association of diurnal temperature range with daily mortality in England and Wales: A nationwide time-series study.

BACKGROUND: Diurnal temperature range (DTR) reflects within-day temperature variability and is closely associated with climate change. In comparison to temperature extremes, up-to-date DTR-health evidence at the regional and national scales has been still very limited worldwide, especially in Europe. OBJECTIVES: This study aimed to provide nationwide estimates for DTR-associated effects on mortality, and explore whether season and regional-level characteristics modify DTR-mortality relation in United Kingdom. METHODS: Fourteen-year time-series data on weather and mortality were collected from 10 regions in England and Wales during 1993-2006, including 7,573,716 total deaths. A quasi-Poisson regression incorporated with distributed lag non-linear model was first applied to estimate region-specific DTR-mortality relationships. Then, a multivariate meta-analysis was employed to derive the pooled DTR effects at the national level. Also, the modifying effects of some regional characteristics (e.g., geographical and climatological) were examined by conducting multivariate meta-regression. RESULTS: A non-linear DTR-mortality relationship was identified in UK. At the national level, increasing DTR raised the mortality risk observably when DTR exposure was below 25th percentile or above 90th percentile of DTR distribution, with an intermediate risk plateau indicating no associations. Extremely high DTR exhibited greater adverse effect estimates in hot season compared with in cold and transitional season, whereas entirely different association patterns were observed for the season-specific effects of extremely low DTR. In addition to season, regional latitudes, average temperature and humidity were also found to significantly modify DTR-mortality relationship. CONCLUSIONS: Our study added strong evidence that extremely high DTR increased short-term mortality, whereas the effects of extremely low DTR exhibited entirely different seasonal patterns. Also, mortality vulnerability to DTR extremes varied greatly by regional latitudes and climate conditions.

The burden of ambient temperature on years of life lost: A multi-community analysis in Hubei, China.

BACKGROUND: Compared with death rates, years of life lost (YLL) has been widely used as a more informative indicator to quantify the burden of premature death. In the context of global climate change, existing evidence linking ambient temperatures and YLL was very scarce across the globe. METHODS: Daily mortality and meteorological data during 2009-2012 were obtained from 12 communities across Hubei Province in central China. A two-stage approach was used for statistical analysis. At the first stage, a generalized linear regression combined with distributed lag non-linear model was applied to estimate community-specific temperature-YLL associations. A second-stage multivariable meta-analysis was then conducted to pool the community-specific estimates of temperature-related effects on YLL. RESULTS: A pooled J- or U-shaped association was observed between ambient temperature and YLL due to different mortality categories. Heat effects occurred immediately and only persisted for several days, whereas cold effects were delayed and much longer-lasting. At the provincial level, heat effect (per 1°C increase from 75th to 99th percentile of temperature) at lag 0-2days and cold effect (per 1°C decrease from 25th to 1st percentile of temperature) at lag 0-21days was associated with an increase of 1.91% (95% CI: 0.83, 3.00) and 5.09% (2.79, 7.40) in YLL due to non-accidental deaths, respectively. Much greater effect estimates of cold than heat were also observed for other mortality-specific YLLs (except for respiratory mortality). Heat effects on YLL were higher for males and the youth, while cold effects were greater for females and the elderly. Additionally, relatively stronger associations between heat, cold and YLL were consistently observed in low-educated persons. CONCLUSIONS: This multi-community study strengthened the evidence that both cold and hot temperatures were associated with increased years of life lost. Our findings may have important implications for better understanding the burden of premature death related to temperature extremes.

Temporal and seasonal variations of mortality burden associated with hourly temperature variability: A nationwide investigation in England and Wales.

BACKGROUND: Sudden temperature change may elevate short-term mortality and remains an important global health threat in the context of climate change. To date, however, little available temperature-mortality evidence has taken into account both intra- and inter-day temperature variability (TV), thus largely limiting the comprehensive understanding of mortality burden due to unstable weather. Moreover, seasonal and temporal patterns in TV-mortality associations were sparsely discussed, nationally and regionally. OBJECTIVES: We aimed to assess the nationwide association of all-cause mortality with hourly temperature variability (HTV), quantify HTV-attributable mortality, and further explore the temporal and seasonal variations of mortality burden due to HTV in United Kingdom. METHODS: Fourteen-year time-series data on temperature and mortality were collected from 10 regions in England and Wales during 1993-2006, totally including 7,573,716 all-cause deaths. HTV was calculated from the standard deviation of hourly temperature records within two neighboring days. A three-stage analytic approach was adopted to assess HTV-associated mortality burden. We first applied a time-series quasi-Poisson regression to estimate region-specific HTV-mortality associations, then pooled these associations at the national level using a multivariate meta-analysis, and finally estimated the HTV-attributable mortality fraction and illustrated its seasonal and temporal variations by conducting season- and period-specific analyses based on time-varying distributed lag models. RESULTS: We found strong evidence that large HTV exposure elevated short-term mortality risk in England and Wales, with a pooled estimate of 1.13% (95% confidence interval (CI): 0.88, 1.39) associated with a 1-°C increase in HTV. During the whole study period, HTV accounted for a national average attributable fraction of 2.52% (95% empirical confidence interval (eCI): 2.27, 2.76) of the total deaths. This HTV-attributable mortality estimate showed a significant temporal decrease (p < 0.001) from 2.72% (95% eCI: 2.58, 2.87) in 1993-99 to 2.28% (95% eCI: 2.13, 2.43) in 2000-06. Additionally, clear seasonal variations were observed for HTV-attributable mortality burden, with the largest estimate of 3.08% (95% eCI: 2.80, 3.38) in summer, followed by 2.71% (95% eCI: 2.44, 2.98) in spring, 2.40% (95% eCI: 2.16, 2.63) in autumn, and 2.00% (95% eCI: 1.81, 2.20) in winter. CONCLUSIONS: Despite clear evidence observed for the reduction, mortality burden caused by temperature variability remained a great public health threat, especially in warm seasons. It highlighted the importance of specific interventions targeted to unstable weather as well as temperature extremes, so as to reduce climate-related mortality burden.

Burden of mortality and years of life lost due to ambient PM10 pollution in Wuhan, China.

Ambient particulate matter (PM) has been mainly linked with mortality and morbidity when assessing PM-associated health effects. Up-to-date epidemiologic evidence is very sparse regarding the relation between PM and years of life lost (YLL). The present study aimed to estimate the burden of YLL and mortality due to ambient PM pollution. Individual records of all registered deaths and daily data on PM10 and meteorology during 2009-2012 were obtained in Wuhan, central China. Using a time-series study design, we applied generalized additive model to assess the short-term association of 10-µg/m3 increase in PM10 with daily YLL and mortality, adjusting for long-term trend and seasonality, mean temperature, relative humidity, public holiday, and day of the week. A linear-no-threshold dose-response association was observed between daily ambient PM10 and mortality outcomes. PM10 pollution along lag 0-1 days was found to be mostly strongly associated with mortality and YLL. The effects of PM10 on cause-specific mortality and YLL showed generally similar seasonal patterns, with stronger associations consistently occurring in winter and/or autumn. Compared with males and younger persons, females and the elderly suffered more significantly from both increased YLL and mortality due to ambient PM10 pollution. Stratified analyses by education level (0-6 and 7 + years) demonstrated great mortality impact on both subgroups, whereas only low-educated persons were strongly affected by PM10-associated burden of YLL. Our study confirmed that short-term PM10 exposure was linearly associated with significant increases in both mortality incidence and years of life lost. Given the non-threshold adverse effects on mortality burden, the on-going efforts to reduce particulate air pollution would substantially benefit public health in China.

An instrument based on protection motivation theory to predict Chinese adolescents' intention to engage in protective behaviors against schistosomiasis.

BACKGROUND: Further advancement in schistosomiasis prevention requires new tools to assess protective motivation, and promote innovative intervention program. This study aimed to develop and evaluate an instrument developed based on the Protection Motivation Theory (PMT) to predict protective behavior intention against schistosomiasis among adolescents in China. METHODS: We developed the Schistosomiasis PMT Scale based on two appraisal pathways of protective motivation- threat appraisal pathway and coping appraisal pathway. Data from a large sample of middle school students (n = 2238, 51 % male, mean age 13.13 ± 1.10) recruited in Hubei, China was used to evaluated the validity and reliability of the scale. RESULTS: The final scale contains 18 items with seven sub-constructs. Cronbach's Alpha coefficients for the entire instrument was 0.76, and for the seven sub-constructs of severity, vulnerability, intrinsic reward, extrinsic reward, response efficacy, self-efficacy and response cost was 0.56, 0.82, 0.75, 0.80, 0.90, 0.72 and 0.70, respectively. The construct validity analysis revealed that the one level 7 sub-constructs model fitted data well (GFI = 0.98, CFI = 0.98, RMSEA = 0.03, Chi-sq/df = 3.90, p < 0.001). Predictive validity showed that both the PMT instrument score and the 7 sub-construct scores were significantly correlated with the intention engaged in protective behavior against schistosomiasis (p < 0.05). CONCLUSIONS: This study provides a reliable and valid tool to measure protective motivation in schistosomiasis prevention control. Further studies are needed to develop more effective intervention programs for schistosomiasis prevention.