Exposure-response Curves Research Articles

Association between PM2.5 and daily pharmacy visit tendency in China: A time series analysis using mobile phone cellular signaling data

While much is known about the effects of PM2.5 pollution on severe health outcomes, less is known about the heterogeneous impacts of air pollution on less severe health effects experienced by large numbers of people, such as those resulting in pharmacy visits. Based on anonymized daily pharmacy visits extracted from about 136,000 mobile phone station macrocells and 28,170 pharmacy locations, we used the generalized additive model and meta-analysis to investigate the effects of PM2.5 exposure on pharmacy visit tendencies (PVTs), as a proxy variable of health facility utilization, across regions, groups and social contexts. Overall, PVTs increased by 0.338% (95% CI: 0.335%–0.342%) for per 10 μg/m3 increases in PM2.5. The exposure-response curve was nonlinear, having a sharp slope below 60 μg/m3 and then flattening. Sensitivity analyses showed that results were robust to modeling choices and existence of noise in captured PVT data. At pharmacy level, higher percentage increases in PVTs were observed in near-residency pharmacies (0.474%), designated medical insurance pharmacies (0.360%), and pharmacies in urban areas (0.457%) than their counterparts (0.156%, 0.321%, 0.180%). This indicates that social contexts, including inconvenient access to the pharmacy and limited social medical insurance coverage, inhibited residents from utilizing health facilities for the health care needed. Interactions of social contexts led to strong heterogeneity among cities, between rural and urban regions as well as across communities, which call for differentiated health resources allocations to ensure health equity.

Health risk of extreme low temperature on respiratory diseases in western China.

Previous studies have reported that daily average temperature is connected with respiratory diseases (RD), but proof is limited for the influence of the extreme low temperature on RD in Lanzhou, a northwestern China of temperate area. Generalized additive model (GAM) was built in this work to describe the relationship between daily mean temperature and RD in Lanzhou, China from 2012 to 2017. The results indicated that the exposure-response curve was inverse J-shaped, showing the lower the temperature, the larger the relative risk (RR). The RR of daily emergency room (ER) admissions in P5 extreme low temperature (the temperature below the fifth percentile, etc.) was larger than that in P10. The P5 extreme low temperature has the strongest effect at lag 0, and the RRs were 1.043 (95% CI: 1.030, 1.055) for the total, 1.031 (95% CI: 1.015, 1.046) for males and 1.058 (95% CI: 1.039, 1.077) for females. For different age groups, the largest RRs were 1.026 (95% CI: 1.013, 1.039) for the children (age < 16years) at lag 5, 1.057 (95% CI: 1.030, 1.085) for the young adults (aged 16-45years), 1.060 (95% CI: 1.023, 1.099) for the middle-aged (aged 46-60years) and 1.121 (95% CI: 1.077, 1.166) for the elderly group of age > 60years. Meanwhile, females and the elderly were more vulnerable to extreme temperature. The results could strengthen the scientific evidence of effects of extreme low temperature on RD in temperate areas.

Treating children with tuberculosis—Using pharmacometrics to do better

Treating children with tuberculosis—Using pharmacometrics to do better

The use of categorical regression in the assessment of the risks of nutrient deficiency and excess

Exposure-response assessment methods have shifted towards more quantitative approaches, with health risk assessors exploring more statistically driven techniques. These assessments, however, usually rely on one critical health effect from a single key study. Categorical regression addresses this limitation by incorporating data from all relevant studies – including human, animal, and mechanistic studies – thereby including a broad spectrum of health endpoints and exposure levels for exposure-response analysis in an objective manner. Categorical regression requires the establishment of ordered response categories corresponding to increasingly severe adverse health outcomes and the availability of a comprehensive database that summarizes all data on different outcomes from different studies, including the exposure or dose at which these out-comes are observed and their severity. It has found application in the risk assessment of essential nutrients and trace metals. Since adverse effects may arise from either deficient or excess exposure, the exposure-response curve is U-shaped, which provides a basis for determining optimal intake levels that minimize the joint risks of deficiency and excess. This article provides an overview of the use of categorical regression fit exposure-response models incorporating data from multiple evidence streams. An extension of categorical regression that permits the simultaneous analysis of excess and deficiency toxicity data is presented and applied to comprehensive databases on copper and manganese. Future applications of cat-egorical regression will be able to make greater use of diverse data sets developed using new approach methodologies, which can be expected to provide valuable information on toxic responses of varying severity.

Effects of ambient temperatures and extreme weather events on circulatory mortality in a high population density area: Exploring mortality data from Malta

BackgroundTemperature-related circulatory mortality has gained consistent public health importance worldwide due to changes in inter-annual average temperatures and the increased frequency of extreme events over time. This study investigates the association between temperature and circulatory deaths in one of the highest population densities in the world (Malta) with a Mediterranean climate. MethodsDaily deaths relating to circulatory mortality (32,847 deaths) were obtained from January 1992 to December 2017. A distributed lag non-linear model (DLNM) with a Poisson distribution was utilized to estimate effects of ambient temperatures and heatwaves or cold spells (2–4 consecutive days). Effects were also explored for the specific cause of death, different age groups, gender and time periods. ResultsThe study observed a U-shaped cumulative exposure–response curve with a greater mortality risk due to cooler temperatures (8–15°C) after adjusting for harvesting effects (0–27 days). Colder temperatures (<8.9°C) were strongly related to both ischemic heart disease (IHD) (RR, 1.85, 95% CI, 1.24–2.77) and cerebrovascular disease (RR, 3.80,95% CI, 1.57–9.17). While heat effects were short-term (0–5 lag days), the cold effects were long-term (0–27 days) and consistent across different lag days. Cooler temperatures (8.99–12.6°C) were also related to IHD mortality in males (RR, 1.94, 95% CI, 1.05–3.59) and females (RR, 1.95, 95% CI, 1.2–3.59) and cerebrovascular mortality in females (RR, 8.32, 95% CI, 2.58–26.80). Elderly females (over 65 years) had a higher risk of death relating to IHD (RR, 1.33, 95% CI, 1.19–3.18) and cerebrovascular diseases (RR, 8.84, 95% CI, 2.64–29.61). Interestingly, colder temperatures (<8.9°C) were highly related to cerebrovascular deaths in the earliest time period (1992–2000) and IHD deaths in the most recent time period (2000–2017). While the effect of heatwaves was unclear across the time periods, there was some visible cold-spell effects for cerebrovascular mortality (RR, 1.03, 95% CI, 1.01–1.06). ConclusionThis study used a long time series of mortality data from a high population density area to explore the impact of ambient temperature and extreme events on circulatory deaths. The results of the study will help to improve preventive and adaptive strategies to mitigate climatic health impacts.

Residential elevation and its effects on hypertension incidence among older adults living at low altitudes: a prospective cohort study.

BackgroundResearch on the relationship between residential altitude and hypertension incidence has been inconclusive. Evidence at low altitudes (i.e., <1,500 m) is scarce, let alone in older adults, a population segment with the highest hypertension prevalence. Thus, the objective of this study is to determine whether hypertension risk may be affected by altitude in older adults living at low altitudes.MethodsThis prospective cohort study collected data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We selected 6,548 older adults (≥65 years) without hypertension at baseline (2008) and assessed events by the follow-up surveys done in 2011, 2014, and 2018 waves. The mean altitude of 613 residential units (county or district) in which the participants resided was extracted from the Digital Elevation Model (DEM) of the National Aeronautics and Space Administration (NASA) and was accurate to within 30 m. The Cox regression model with penalized splines examined the linear or nonlinear link between altitude and hypertension. A random-effects Cox regression model was used to explore the linear association between altitude and hypertension.ResultsThe overall rate of incident hypertension was 8.6 per 100-person years. The median altitude was 130.0 m (interquartile range [IQR] = 315.5 m). We observed that the exposure–response association between altitude and hypertension incidence was not linear. The shape of the exposure–response curve showed that three change points existed. Hypertension risk increased from the lowest to the first change point (247.1 m) and slightly fluctuated until the last change point (633.9 m). The risk decreased above the last change point. According to the categories stratified by the change points, altitude was only significantly associated with hypertension risk (hazard ratio [HR] = 1.003; 95% confidence interval [CI] = 1.002–1.005) under the first change point (247.1 m) after adjusting for related covariates.ConclusionOur study found that the association between altitude and hypertension risk might not be linear. We hope the further study can be conducted to confirm the generality of our findings.Supplementary informationThe online version contains supplementary material available at https://doi.org/10.1265/ehpm.22-00001.

Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013-2020.

Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/), we characterized the spatiotemporal variations in PM2.5 and O3 exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O3 pollution worsened, with the average April-September O3 exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM2.5 concentration. It is also noticed that with smaller PM2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM2.5-polluted days with the daily average PM2.5 higher than 75 μg/m3 and the considerable increase in O3-polluted days with the daily maximum 8 h average O3 higher than 160 μg/m3, deaths attributable to the short-term O3 exposure were greater than those due to PM2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM2.5 and O3 are urgently needed.

Estimation of the Exposure-Response Relation between Benzene and Acute Myeloid Leukemia by Combining Epidemiologic, Human Biomarker, and Animal Data.

Chemical risk assessment can benefit from integrating data across multiple evidence bases, especially in exposure-response curve (ERC) modeling when data across the exposure range are sparse. We estimated the ERC for benzene and acute myeloid leukemia (AML), by fitting linear and spline-based Bayesian meta-regression models that included summary risk estimates from non-AML and nonhuman studies as prior information. Our complete dataset included six human AML studies, three human leukemia studies, 10 human biomarker studies, and four experimental animal studies. A linear meta-regression model with intercept best predicted AML risks after cross-validation, both for the full dataset and AML studies only. Risk estimates in the low exposure range [<40 parts per million (ppm)-years] from this model were comparable, but more precise when the ERC was derived using all available data than when using AML data only. Allowing for between-study heterogeneity, RRs and 95% prediction intervals (95% PI) at 5 ppm-years were 1.58 (95% PI, 1.01-3.22) and 1.44 (95% PI, 0.85-3.42), respectively. Integrating the available epidemiologic, biomarker, and animal data resulted in more precise risk estimates for benzene exposure and AML, although the large between-study heterogeneity hampers interpretation of these results. The harmonization steps required to fit the Bayesian meta-regression model involve a range of assumptions that need to be critically evaluated, as they seem crucial for successful implementation. By describing a framework for data integration and explicitly describing the necessary data harmonization steps, we hope to enable risk assessors to better understand the advantages and assumptions underlying a data integration approach.See related commentary by Keil, p. 695.

The acute effects of particulate matter air pollution on ambulatory blood pressure: A multicenter analysis at the hourly level.

Epidemiological evidence from ambulatory blood pressure monitoring is needed to clarify the associations of particulate air pollution with blood pressure and potential lag patterns. We examined the associations of fine and coarse particulate matter (PM2.5, PM2.5-10) with ambulatory blood pressure among 7108 non-hypertensive participants from 7 Chinese cities between April 2016 and November 2020. Hourly concentrations of PM2.5 and PM2.5-10 were obtained from the nearest monitoring stations. We measured four blood pressure indicators, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Linear mixed-effect models combined with distributed lag models were applied to analyze the data. Generally, very short-term exposure to PM2.5 was significantly associated with elevated blood pressure. These effects occurred on the same hour of blood pressure measurement, attenuated gradually, and became insignificant approximately at lag 12h. An interquartile range (IQR, 33μg/m3) increase of PM2.5 was significantly associated with cumulative increments of 0.58mmHg for SBP, 0.31mmHg for DBP, 0.38mmHg for MAP, and 0.33mmHg for PP over lag 0 to 12h. The exposure-response relationship curves were almost linear without thresholds, but tended to be flat at very high concentrations. No significant associations were observed for PM2.5-10. Our study provides independent and robust associations between transient PM2.5 exposure and elevated blood pressure within the first 12h, and reinforces the evidence for a linear and non-threshold exposure-response relationship, which may have implications for blood pressure management and hypertension prevention in susceptible population.

The association between ozone and ischemic stroke morbidity among patients with type 2 diabetes in Beijing, China

BackgroundThe association between ozone and ischemic stroke has been widely reported; however, the association among patients with type 2 diabetes (T2D) has remained largely unknown. MethodsThe time series data of daily morbidity and concentrations of ozone from 2014 to 2018 were collected in Beijing, China. A time-stratified case-crossover study combined with a distributed lag nonlinear model was used to estimate the ozone effect on stroke morbidity among T2D patients. Based on principal diagnosis, ischemic stroke cases were identified according to the International Classification of Diseases (I63), and a history of T2D was coded as E12. ResultsA total of 149,757 hospital admissions for ischemic stroke among T2D patients were recorded in Beijing. Approximately U-shaped exposure-response curves were observed for ozone and ischemic stroke morbidity among T2D patients. With a reference at 54.91 μg/m3, extreme-low (5th: 9.59 μg/m3) ozone was significantly associated with a decreased risk for ischemic stroke [RR = 0.88, 95% confidence interval (CI): 0.80–0.98]. Subgroup analysis showed that extremely low-ozone (5th) level only had a significant protective effect in males and elderly population, with a RR value of 0.86 (95% CI: 0.76–0.97) and 0.85 (95% CI: 0.75–0.96), respectively. Extreme-high ozone (99th: 157.06 μg/m3) was significantly associated with an increased risk for ischemic stroke (RR = 1.33, 95% CI: 1.12–1.57). The effect size was 1.34 (95% CI: 1.10–1.63) for males and 1.32 (95% CI: 1.07–1.63) for females, and the difference was not significant (Z = -0.29, P = 0.77). The effect size in younger adults was significantly higher than that in participants aged ≥65 years [1.52 (95% CI: 1.21–1.91) vs. 1.22 (95% CI: 1.01–1.47), Z = -1.62, P < 0.05]. ConclusionsU-shaped associations were observed between ozone and ischemic stroke morbidity in T2D patients. Men and elderly population are vulnerable to low-ozone level, and the younger adults are more susceptible to extremely high-ozone level than the elderly.

Short-term impact of ambient temperature on the incidence of influenza in Wuhan, China.

Few studies have estimated the nonlinear association of ambient temperature with the risk of influenza. We therefore applied a time-series analysis to explore the short-term effect of ambient temperature on the incidence of influenza in Wuhan, China. Daily influenza cases were collected from Hubei Provincial Center for Disease Control and Prevention (Hubei CDC) from January 1, 2014, to December 31, 2017. The meteorological and daily pollutant data was obtained from the Hubei Meteorological Service Center and National Air Quality Monitoring Stations, respectively. We used a generalized additive model (GAM) coupled with the distributed lag nonlinear model (DLNM) to explore the exposure-lag-response relationship between the short-term risk of influenza and daily average ambient temperature. Analyses were also performed to assess the extreme cold and hot temperature effects. We observed that the ambient temperature was statistically significant, and the exposure-response curve is approximately S-shaped, with a peak observed at 23.57 ℃. The single-day lag curve showed that extreme hot and cold temperatures were both significantly associated with influenza. The extreme hot temperature has an acute effect on influenza, with the most significant effect observed at lag 0-1. The extreme cold temperature has a relatively smaller effect but lasts longer, with the effect exerted continuously during a lag of 2-4days. Our study found significant nonlinear and delayed associations between ambient temperature and the incidence of influenza. Our finding contributes to the establishment of an early warning system for airborne infectious diseases.

Time series analysis of short-term effects of particulate matter pollution on the circulatory system disease mortality risk in Lishui District, China.

Epidemiological evidence has shown a significant association between short-term exposure to air pollution and mortality risk for circulatory system diseases (CSD). However, informative insights on the significance and magnitude of its relationship in the process of government interventions on abating air pollution are still lacking, particularly in a burgeoning Chinese city. In this study, we conducted a time series study in Lishui District, Nanjing, to examine the effect of ambient particulate matter (PM), e.g., PM2.5 and PM10, on daily death counts of CSD which included cardiovascular disease (CVD), cerebrovascular disease (CEVD), and arteriosclerotic heart disease (ASHD) mortality from January 1, 2015, to December 31, 2019. The results revealed that each 10μg/m3 increase in PM2.5 and PM10 concentration at lag0 day was associated with an increase of 1.33% (95% confidence interval, 0.08%, 2.60%) and 1.12% (0.43%, 1.82%) in CSD mortality; 2.42% (0.44%, 4.43%) and 1.43% (0.32%, 2.55%) in CVD mortality; 1.20% (- 0.31%, 2.73%) and 1.21% (0.38%, 2.05%) in CEVD mortality; and 2.78% (0.00%, 5.62%) and 1.66% (0.14%, 3.21%) in ASHD mortality, respectively. For cumulative risk, the corresponding increase in daily mortality for the same change in PM2.5 concentration at lag03 day was significantly associated with 1.94% (0.23%, 3.68%), 3.17% (0.58%, 5.84%), 2.38% (0.17%, 4.63%), and 4.92% (1.18%, 8.81%) for CSD, CVD, CEVD, and ASHD, respectively. The exposure-response curves were approximately nonlinear over the entire exposure range of the PM concentrations. We also analyzed the effect modifications by season (warm or cold), age group (0-64years, 65-74years, or ≥ 75years), and sex (male or female). Although not statistically significant, stratified analysis showed greater vulnerability to PM exposure for cold season, population over 65years of age, and female group.

Representative Exposure-Annoyance Relationships Due to Transportation Noises in Japan.

This paper focuses on clarifying the relationship between noise exposure and the prevalence of highly annoyed people due to transportation noise in Japan. The authors accumulated 34 datasets, which were provided by Socio-Acoustic Survey Data Archive and derived from the other surveys conducted in Japan. All the datasets include the following micro-data: demographic factors, exposure, and annoyance data associated with specific noise sources. We performed secondary analyses using micro-data and established the relationships between noise exposure (Lden) and the percentage of highly annoyed people (%HA) for the following noise source: road traffic, conventional railway, Shinkansen railway, civil aircraft, and military aircraft noises. Among the five transportation noises, %HA for the military aircraft noise is the highest, followed by civil aircraft noise and Shinkansen railway noise. The %HA for conventional railway noise was higher than that for road traffic noise. To validate the representativeness of the exposure–response curves, we have discussed factors affecting the difference in annoyance. In addition, comparing the Japanese relationship with that shown in the “Environmental Noise Guidelines for the European Region,” we revealed that Japanese annoyance is higher than the WHO-reported annoyance.

Effects of ambient temperature on outpatient visits for dermatitis in Xinxiang, China: a time-series analysis.

Previous studies have reported regional variations in the relationship between ambient temperature and dermatitis, which therefore remain inconclusive. This study aimed to understand the short-term effects of ambient temperature in outpatients with dermatitis in Xinxiang. Routine data of dermatitis outpatient visits between January 1, 2015, and December 31, 2018 were acquired from the First Affiliated Hospital of Xinxiang Medical University. A distributed lag nonlinear model (DLNM) in combination with a generalized additive model (GAM) was applied to investigate the acute impact of ambient temperature on dermatitis outpatients. Two stratified analyses based on age and sex were conducted to explore their potential modification effects. A total of 18,064 dermatitis outpatient records were retrieved during the study period. The relationship between ambient temperature and dermatitis outpatients was found to be nonlinear; exposure-response curves were approximately "J" shaped. The risk of dermatitis outpatient increased with a corresponding elevation in temperature from 11.5 to 27.5°C. However, the significance was lost when the temperature exceeded the given range. Stratified analysis demonstrated higher sensitivity to temperature in females than in males, and the young groups (<15 years) might be sensitive to heat temperature. This study provides first-hand epidemiological evidence demonstrating a higher risk of dermatitis outpatient visits associated with moderately higher temperatures. The outcomes of this study create awareness among citizens to take the necessary precautions to prevent the adverse effects of moderate heat temperature during early summer and autumn seasons.

Impact of ambient temperature on life loss per death from cardiovascular diseases: a multicenter study in central China

BackgroundIn the context of global climate change, studies have focused on the ambient temperature and mortality of cardiovascular diseases (CVDs). However, little is known about the effect of ambient temperature on year of life lost (YLL), especially the life loss per death caused by ambient temperature. In this study, we aimed to assess the relationship between ambient temperature and life loss and estimate the impact of ambient temperature on life loss per death.MethodsWe collected daily time series of mortality and meteorological data from 70 locations in Hunan province, central China, in periods ranging from Jan. 1, 2013, to Dec. 31, 2017. Crude rates of YLL were calculated per 100,000 people per year (YLL/100,000 population) for each location. A distributed lag nonlinear model and multivariate meta-regression were used to estimate the associations between ambient temperature and YLL rates. Then, the average life loss per death attributable to ambient temperature was calculated.ResultsThere were 711,484 CVD deaths recorded within the study period. The exposure-response curve between ambient temperature and YLL rates was inverted J or U-shaped. Relative to the minimum YLL rate temperature, the life loss risk of extreme cold temperature lasted for 10 to 12 days, whereas the risk of extreme hot temperature appeared immediately and lasted for 3 days. On average, the life loss per death attributable to non-optimum ambient temperatures was 1.89 (95% CI, 1.21-2.56) years. Life loss was mainly caused by cold temperature (1.13, 95% CI, 0.89‑1.37), particularly moderate cold (1.00, 95% CI, 0.78‑1.23). For demographic characteristics, the mean life loss per death was relatively higher for males (2.07, 95% CI, 1.44‑2.68) and younger populations (3.72, 95% CI, 2.06‑5.46) than for females (1.88, 95% CI, 1.21-2.57) and elderly people (1.69, 95% CI, 1.28-2.10), respectively.ConclusionsWe found that both cold and hot temperatures significantly aggravated premature death from CVDs. Our results indicated that the whole range of effects of ambient temperature on CVDs should be given attention.

Long-term nitrogen dioxide exposure and cause-specific mortality in the U.S. Medicare population

BackgroundSince 1971, the annual National Ambient Air Quality Standard (NAAQS) for nitrogen dioxide (NO2) has remained at 53 ppb, the impact of long-term NO2 exposure on mortality is poorly understood. ObjectivesWe examined associations between long-term NO2 exposure (12-month moving average of NO2) below the annual NAAQS and cause-specific mortality among the older adults in the U.S. MethodsCox proportional-hazard models were used to estimate Hazard Ratio (HR) for cause-specific mortality associated with long-term NO2 exposures among about 50 million Medicare beneficiaries living within the conterminous U.S. from 2001 to 2008. ResultsA 10 ppb increase in NO2 was associated with increased mortality from all-cause (HR: 1.06; 95% CI: 1.05–1.06), cardiovascular (HR: 1.10; 95% CI: 1.10–1.11), respiratory disease (HR: 1.09; 95% CI: 1.08–1.11), and cancer (HR: 1.01; 95% CI: 1.00–1.02) adjusting for age, sex, race, ZIP code as strata ZIP code- and state-level socio-economic status (SES) as covariates, and PM2.5 exposure using a 2-stage approach. NO2 was also associated with elevated mortality from ischemic heart disease, cerebrovascular disease, congestive heart failure, chronic obstructive pulmonary disease, pneumonia, and lung cancer. We found no evidence of a threshold, with positive and significant HRs across the range of NO2 exposures for all causes of death examined. Exposure-response curves were linear for all-cause, supra-linear for cardiovascular-, and sub-linear for respiratory-related mortality. HRs were highest consistently among Black beneficiaries. ConclusionsLong-term NO2 exposure is associated with elevated risks of death by multiple causes, without evidence of a threshold response. Our findings raise concerns about the sufficiency of the annual NAAQS for NO2.

Residential greenness and prevalence of chronic kidney disease: Findings from the China National Survey of Chronic Kidney Disease

Green space is associated with many health benefits, but evidence concerning the effects on chronic kidney disease (CKD) has not been investigated. Using the nationwide cross-sectional study of 47,204 adults from the China National Survey of Chronic Kidney Disease dataset and residential greenness assessed by the normalized difference vegetation index (NDVI), this study evaluated the association between residential greenness and CKD prevalence. An interquartile range increase in NDVI1000m (0.26) was associated with decreased odds of CKD for all participants with an odds ratio (OR) of 0.79 (95% confidence interval [CI]: 0.73–0.86). Subgroup analyses demonstrated more apparent inverse associations in younger adults <65 years, male participants, people in higher socio-economic status, as well as people with smoking and alcohol drinking habit. In addition, more apparent inverse associations were found in regions with higher fine particulate matter (PM2.5) concentration levels, with OR of 0.56 (95% CI: 0.49, 0.65) for higher pollution regions, and OR of 0.95 (95% CI: 0.83, 1.09) for lower pollution regions (P for interaction <0.001). The exposure-response curves captured more apparent declines in OR of CKD when in lower NDVI1000m exposure ranges (<0.6), even controlling for the PM2.5 concentration. Our results indicated that residential greenness might be beneficial for the prevention and control of CKD at the population level, suggesting the positive significance of strengthening green space construction, particularly in regions with low greenness.

Acute effect of particulate matter pollution on hospital admissions for cause-specific respiratory diseases among patients with and without type 2 diabetes in Beijing, China, from 2014 to 2020

BackgroundScientific studies have identified various adverse effects of particulate matter (PM) on respiratory disease (RD) and type 2 diabetes (T2D). However, whether short-term exposure to PM triggers the onset of RD with T2D, compared with RD without T2D, has not been elucidated. MethodsA two-stage time-series study was conducted to evaluate the acute adverse effects of PM on admission for RD and for RD with and without T2D in Beijing, China, from 2014 to 2020. District-specific effects of PM2.5 and PM10 were estimated using the over-dispersed Poisson generalized addictive model after adjusting for weather conditions, day of the week, and long-term and seasonal trends. Meta-analyses were applied to pool the overall effects on overall and cause-specific RD, while the exposure-response (E-R) curves were evaluated using a cubic regression spline. ResultsA total of 1550,154 admission records for RD were retrieved during the study period. Meta-analysis suggested that per interquartile range upticks in the concentration of PM2.5 corresponded to 1.91% (95% CI: 1.33–2.49%), 2.16% (95% CI: 1.08–3.25%), and 1.92% (95% CI: 1.46–2.39%) increments in admission for RD, RD with T2D, and RD without T2D, respectively, at lag 0–8 days, lag 8 days, and lag 8 days. The effect size of PM2.5 was statistically significantly higher in the T2D group than in the group without T2D (z = 3.98, P < 0.01). The effect sizes of PM10 were 3.86% (95% CI: 2.48–5.27%), 3.73% (95% CI: 1.72–5.79%), and 3.92% (95% CI: 2.65–5.21%), respectively, at lag 0–13 days, lag 13 days, and lag 13 days, respectively, and no statistically significant difference was observed between T2D groups (z = 0.24, P = 0.81). Significant difference was not observed between T2D groups for the associations of PM and different RD and could be found between three groups for effects of PM10 on RD without T2D. The E-R curves varied by sex, age and T2D condition subgroups for the associations between PM and daily RD admissions. ConclusionsShort-term PM exposure was associated with increased RD admission with and without T2D, and the effect size of PM2.5 was higher in patients with T2D than those without T2D.

Association between air pollution and hospital admissions for hypertension in Lanzhou, China.

Air pollution has been accepted as an important risk factor for hypertension. However, little is known about the association between air pollution and hospitalization for hypertension. In this study, we explored the association between six criteria air pollutants and hypertension hospitalization in Lanzhou, China. An over-dispersed Poisson regression model combined with a distributed lag nonlinear model (DLNM) was used. In addition, we investigated the effect of modification by sex, age, and season. A total of 30,197 hospitalization cases were identified during the study period. A 10μg/m3 increase in PM2.5, PM10, SO2, and NO2 concentrations or 1 mg/m3 increment in CO was significantly associated with relative risks (RRs) of hospital admissions due to hypertension 1.026 [95% confidence interval (CI): 1.010, 1.043], 1.010 (95%CI: 1.005, 1.015), 1.042 (95%CI: 1.001, 1.085), 1.028 (95%CI: 1.003, 1.052), and 1.106 (95%CI: 1.031, 1.186), respectively. No significant influence of O38h was found on hypertension hospital admissions. The associations differed by individual characteristics; the elderly (≥ 65 years) and females were highly vulnerable. The effects of PM2.5, SO2, and CO were more evident in the cool season than in the warm season. From exposure-response curves, we observe a nearly linear relationship for PM2.5, PM10, SO2, NO2, and CO. This study suggests that exposure to PM2.5, PM10, SO2, NO2, and CO is associated with hypertension morbidity.

LPG stove and fuel intervention among pregnant women reduce fine particle air pollution exposures in three countries: Pilot results from the HAPIN trial

The Household Air Pollution Intervention Network trial is a multi-country study on the effects of a liquefied petroleum gas (LPG) stove and fuel distribution intervention on women's and children's health. There is limited data on exposure reductions achieved by switching from solid to clean cooking fuels in rural settings across multiple countries. As formative research in 2017, we recruited pregnant women and characterized the impact of the intervention on personal exposures and kitchen levels of fine particulate matter (PM2.5) in Guatemala, India, and Rwanda. Forty pregnant women were enrolled in each site. We measured cooking area concentrations of and personal exposures to PM2.5 for 24 or 48 h using gravimetric-based PM2.5 samplers at baseline and two follow-ups over two months after delivery of an LPG cookstove and free fuel supply. Mixed models were used to estimate PM2.5 reductions. Median kitchen PM2.5 concentrations were 296 μg/m3 at baseline (interquartile range, IQR: 158–507), 24 μg/m3 at first follow-up (IQR: 18–37), and 23 μg/m3 at second follow-up (IQR: 14–37). Median personal exposures to PM2.5 were 134 μg/m3 at baseline (IQR: 71–224), 35 μg/m3 at first follow-up (IQR: 23–51), and 32 μg/m3 at second follow-up (IQR: 23–47). Overall, the LPG intervention was associated with a 92% (95% confidence interval (CI): 90–94%) reduction in kitchen PM2.5 concentrations and a 74% (95% CI: 70–79%) reduction in personal PM2.5 exposures. Results were similar for each site. ConclusionsThe intervention was associated with substantial reductions in kitchen and personal PM2.5 overall and in all sites. Results suggest LPG interventions in these rural settings may lower exposures to the WHO annual interim target-1 of 35 μg/m3. The range of exposure contrasts falls on steep sections of estimated exposure-response curves for birthweight, blood pressure, and acute lower respiratory infections, implying potentially important health benefits when transitioning from solid fuels to LPG.