Light at night and cause-specific mortality risk in Mainland China: a nationwide observational study.

BACKGROUND: While epidemiological studies have found correlations between light at night (LAN) and health effects, none has so far investigated the impacts of LAN on population mortality yet. We aimed to estimate the relative risk for mortality from exposure to LAN in Mainland China. METHODS: This time-stratified case-crossover nationwide study used NPP-VIIRS to obtain daily LAN data of Mainland China between 2015 and 2019. The daily mortality data were obtained from the Disease Surveillance Point System in China. Conditional Poisson regression models were applied to examine the relative risk (RR) for mortality along daily LAN in each county, then meta-analysis was performed to combine the county-specific estimates at the national or regional level. RESULTS: A total of 579 counties with an average daily LAN of 4.39 (range: 1.02-35.46) were included in the main analysis. The overall RRs per 100 nW/cm2/sr increases in daily LAN were 1.08 (95%CI: 1.05-1.11) for all-cause mortality and 1.08 (95%CI: 1.05-1.11) for natural-cause mortality. A positive association between LAN and all natural cause-specific mortality was observed, of which the strongest effect was observed on mortality caused by neuron system disease (RR = 1.32, 95%CI: 1.14-1.52). The results were robust in both younger and old, as well as in males and females. The more pronounced effect of LAN was observed in median LAN-level regions. Combined with an exposure-response curve, our study suggests a non-linear association between LAN and mortality in China. CONCLUSIONS: Our study shows LAN is associated with mortality in China, particularly for neuron system disease-related mortality. These findings have important implications for public health policy establishment to minimize the health consequences of light pollution.

Spatial distribution and driving factors of the associations between temperature and influenza-like illness in the United States: a time-stratified case-crossover study.

BACKGROUND: Several previous studies investigated the associations between temperature and influenza in a single city or region without a national picture. The attributable risk of influenza due to temperature and the corresponding driving factors were unclear. This study aimed to evaluate the spatial distribution characteristics of attributable risk of Influenza-like illness (ILI) caused by adverse temperatures and explore the related driving factors in the United States. METHODS: ILI, meteorological factors, and PM2.5 of 48 states in the United States were collected during 2011-2019. The time-stratified case-crossover design with a distributed lag non-linear model was carried out to evaluate the association between temperature and ILI at the state level. The multivariate meta-analysis was performed to obtain the combined effects at the national level. The attributable fraction (AF) was calculated to assess the ILI burden ascribed to adverse temperatures. The ordinary least square model (OLS), spatial lag model (SLM), and spatial error model (SEM) were utilized to identify driving factors. RESULTS: A total of 7,716,115 ILI cases were included in this study. Overall, the temperature was negatively associated with ILI risk, and lower temperature gave rise to a higher risk of ILI. AF ascribed to adverse temperatures differed across states, from 49.44% (95% eCI: 36.47% ~ 58.68%) in Montana to 6.51% (95% eCI: -6.49% ~ 16.46%) in Wisconsin. At the national level, 29.08% (95% eCI: 27.60% ~ 30.24%) of ILI was attributable to cold. Per 10,000 dollars increase in per-capita income was associated with the increment in AF (OLS: ß = -6.110, P = 0.021; SLM: ß = -5.496, P = 0.022; SEM: ß = -6.150, P = 0.022). CONCLUSION: The cold could enhance the risk of ILI and result in a considerable proportion of ILI disease burden. The ILI burden attributed to cold varied across states and was higher in those states with lower economic status. Targeted prevention programs should be considered to lower the burden of influenza.

Acute Effects of Low Temperatures and Cold Waves on Elderly Infectious Pneumonia Mortality - Jinan City, Shandong Province, China, 2014-2022.

What is already known about this topic?: The mortality rate due to pneumonia varies depending on the infectious agents present in a low- temperature environment. What is added by this report?: This study aimed to examine the relationship between low temperatures and cold waves and the risk of mortality from infectious pneumonia in the elderly. The findings indicate a significant increase in the risk of infectious pneumonia, specifically bacterial pneumonia, during periods of low temperatures and cold waves. What are the implications for public health practice?: This study presents compelling evidence that highlights the importance of proactive public responses to infectious pneumonia among the elderly population during periods of cold waves.

The Combined Effects of High Temperatures and Ozone Pollution on Medical Emergency Calls - Jinan City, Shandong Province, China, 2013-2019.

What is already known about this topic?: Studies have extensively documented the separate and independent effects of extreme temperature and ozone on morbidity and mortality associated with respiratory and circulatory diseases. What is added by this report?: The study revealed a significant association between elevated temperature, ozone pollution, and the combined effect of high temperature and ozone pollution with an increased risk of all-cause medical emergency calls (MECs) and MECs specifically related to neurological diseases. What are the implications for public health practice?: Interventional measures should be implemented to mitigate exposure to high temperatures and ozone levels. Specifically, during the warm season, it is crucial for relevant authorities to focus on disseminating scientific information regarding the health impacts of elevated temperatures and ozone pollution. Additionally, timely public health advisories should be issued to alert the public effectively.

Association Between Air Pollutants and Acute Exacerbation of Chronic Obstructive Pulmonary Disease: A Time Stratified Case-Crossover Design With a Distributed Lag Nonlinear Model.

Acute exacerbation of chronic obstruction pulmonary disease (AECOPD) as a respiratory disease, is considered to be related to air pollution by more and more studies. However, the evidence on how air pollution affect the incidence of AECOPD and whether there are population differences is still insufficient. Therefore, we select PM10, PM2.5, SO2, NO2, CO, and O3 as representatives combined with daily AECOPD admission data from 1 January 2015 to 26 June 2016 in the rural areas of Qingyang, northwestern China to explore the associations of air pollution with AECOPD. Based on a time-stratified case-crossover design, we constructed a distributed lag nonlinear model to qualify the single and cumulative lagged effects of air pollution on AECOPD. Stratified related risks by sex and age were also reported. The cumulative exposure-response curves were approximately linear for PM2.5, "V"-shaped for PM10, "U"-shaped for NO2 and inverted-"V" for SO2, CO and O3. Exposure to high-PM2.5 (42 µg/m3), high-PM10 (91 µg/m3), high-SO2 (58 µg/m3), low-NO2 (12 µg/m3), and high-CO (1.55 mg/m3) increased the risk of AECOPD. Females aged 15-64 were more susceptible under extreme concentrations of PM2.5, SO2, CO, and low-PM10 than other subgroups. In addition, adults aged 15-64 were more sensitive to extreme concentrations of NO2 compared with the elderly ≥65 years old, while the latter were more sensitive to high-PM10. High-SO2, high-NO2, and extreme concentrations of PM2.5 had the greatest effects on the day of exposure, while low-SO2 and low-CO had lagged effects on AECOPD. Precautionary measures should be taken with a focus on vulnerable subgroups, to control hospitalization for AECOPD associated with air pollutants.

PM2.5 components and outpatient visits for asthma: A time-stratified case-crossover study in a suburban area.

The effects of fine particles (PM2.5) on asthma have been widely confirmed by epidemiological research studies. However, a limited number of studies have investigated the relationship between exposure to different PM2.5 components and asthma. We characterized the PM2.5 components in a suburban site of central Taiwan and conducted a time-stratified case-crossover study to elaborate the effects of daily concentration of each PM2.5 component on asthma outpatient visits. We retrieved asthma outpatient claims for individuals less than 20 years old with a residential address in the Shalu district, Taiwan, from the National Health Insurance Research Database during 2000-2010. Multiple linear regression models were used to back extrapolate the historic concentration of individual components of PM2.5 from 2000 through to 2010, including black carbon (BC) and eight ions, namely, sulfate, nitrate (NO3-), ammonium, chloride, potassium (K+), magnesium, calcium, sodium. The odds ratio (OR) with a 95% confidence interval (CI) of individual PM2.5 components on asthma was estimated by conditional logistic regression. A total of 887 asthma outpatient visits with individuals who have an average age of 7.96±3.88 years were selected. After adjusting for confounders, we found an interquartile range (IQR) increase in BC level, an IQR increase in NO3- level, and an IQR increase in K+ level that were all associated with the increased risk of asthma outpatient visits from the current day (OR = 1.18, 95% CI: 1.05-1.34; OR = 1.11, 95% CI: 1.01-1.21; and OR = 1.16, 95% CI: 1.04-1.30, respectively). The effects of these components on asthma were stronger in the cold season than in the warm season. However, we did not find any lagging effects. The results suggest that exposure to NO3-, BC, and K+ derived from industry-related combustion or motor vehicles emission sources may increase the risk of asthma outpatient visits, particularly during the cold season.

Ambient Fine Particulate Matter Exposure and Risk of Cardiovascular Mortality: Adjustment of the Meteorological Factors.

Few studies have explicitly explored the impacts of the extensive adjustment (with a lag period of more than one week) of temperature and humidity on the association between ambient fine particulate matter (PM2.5) and cardiovascular mortality. In a time stratified case-crossover study, we used a distributed lag nonlinear model to assess the impacts of extensive adjustments of temperature and humidity for longer lag periods (for 7, 14, 21, 28 and 40 days) on effects of PM2.5 on total cardiovascular mortality and mortality of cerebrovascular and ischemic heart disease and corresponding exposure-response relationships in Beijing, China, between 2008 and 2011. Compared with results only controlled for temperature and humidity for 2 days, the estimated effects of PM2.5 were smaller and magnitudes of exposure-response curves were decreased when longer lag periods of temperature and relative humidity were included for adjustments, but these changes varied across subpopulation, with marked decreases occurring in males and the elderly who are more susceptible to PM2.5-related mortalities. Our findings suggest that the adjustment of meteorological factors using lag periods shorter than one week may lead to overestimated effects of PM2.5. The associations of PM2.5 with cardiovascular mortality in susceptible populations were more sensitive to further adjustments for temperature and relative humidity.