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IntroductionWe described how COVID-19 fatality and symptoms varied by dominant variant and vaccination in the US.MethodsUsing the Restricted Access Dataset from the US CDC (1/1/2020–10/20/2022), we conducted a cross-sectional study assessing differences in COVID-19 deaths, severity indicators (hospitalization, ICU, pneumonia, abnormal X-ray, acute respiratory distress syndrome, mechanical ventilation) and 12 mild symptoms by dominant variant/vaccination periods using logistic regression after controlling for confounders.ResultsWe found the highest fatality during the dominant periods of Wild (4.6%) and Delta (3.4%). Most severe symptoms appeared when Delta was dominant (Rate range: 2.0–9.4%). Omicron was associated with higher mild symptoms than other variants. Vaccination showed consistent protection against death and severe symptoms for most variants (Risk Ratio range: 0.41–0.93). Boosters, especially the second, provided additional protection, reducing severe symptoms by over 50%.DiscussionThis dataset may serve as a useful tool to monitor temporospatial changes of fatality and symptom for case management and surveillance.

BackgroundPrevious work reported increased rates of cardiovascular hospitalizations associated with increased source-specific PM2.5 concentrations in New York State, despite decreased PM2.5 concentrations. We also found increased rates of ST elevation myocardial infarction (STEMI) associated with short-term increases in concentrations of ultrafine particles and other traffic-related pollutants in the 2014–2016 period, but not during 2017–2019 in Rochester. Changes in PM2.5 composition and sources resulting from air quality policies (e.g., Tier 3 light-duty vehicles) may explain the differences. Thus, this study aimed to estimate whether rates of STEMI were associated with organic carbon and source-specific PM2.5 concentrations.MethodsUsing STEMI patients treated at the University of Rochester Medical Center, compositional and source-apportioned PM2.5 concentrations measured in Rochester, a time-stratified case-crossover design, and conditional logistic regression models, we estimated the rate of STEMI associated with increases in mean primary organic carbon (POC), secondary organic carbon (SOC), and source-specific PM2.5 concentrations on lag days 0, 0–3, and 0–6 during 2014–2019.ResultsThe associations of an increased rate of STEMI with interquartile range (IQR) increases in spark-ignition emissions (GAS) and diesel (DIE) concentrations in the previous few days were not found from 2014 to 2019. However, IQR increases in GAS concentrations were associated with an increased rate of STEMI on the same day in the 2014–2016 period (Rate ratio [RR] = 1.69; 95% CI = 0.98, 2.94; 1.73 μg/m3). In addition, each IQR increase in mean SOC concentration in the previous 6 days was associated with an increased rate of STEMI, despite imprecision (RR = 1.14; 95% CI = 0.89, 1.45; 0.42 μg/m3).ConclusionIncreased SOC concentrations may be associated with increased rates of STEMI, while there seems to be a declining trend in adverse effects of GAS on triggering of STEMI. These changes could be attributed to changes in PM2.5 composition and sources following the Tier 3 vehicle introduction.

Background: The potential for residential greenness to improve cardiovascular health through both physical and psychological mechanisms is well recognized. However, evidence from rapidly urbanizing developing countries and cohort-based causal inference approaches, remains limited. We aim to examine the effect of residential greenness and time to cardiovascular mortality in South China. Methods: We utilized data from a community-based population survey involving 748,209 participants at baseline from 2009 to 2015, followed up until 2020. Residential greenness exposure was assessed by the annual Normalized Difference Vegetation Index (NDVI) in the 500 m radius of each participant’s residence. We used time-varying proportional hazard Cox models coupled with inverse probability weighting to fit marginal structural models and obtain hazard ratios (HRs) for cardiovascular disease (CVD) mortality after adjusting for confounders. Multiple effect modifiers on both additive and multiplicative scales were further explored. Results: A total of 15,139 CVD-related deaths were identified during a median of 7.9 years of follow-up. A protective effect was found between higher greenness exposure and reduced CVD mortality, with a 9.3 % lower rate of total CVD mortality (HR 0.907, 95 % CI 0.859–0.957) based on a 0.1 increase in annual average NDVI. Demographic (age, marital status) and lifestyle factors (smoking, drinking status) were found to modify the association between residential greenness and CVD mortality (all P interaction values

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1–2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment.A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders.During follow-up, a total of 717 subjects died from T2DM. For every 1 μg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019–1.053). Similarly, for every 1 μg/m3 increase in PM1 and PM1–2.5, the adjusted HRs and 95% CIs were 1.032 (1.003–1.062) and 1.085 (1.054–1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049).The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1–2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

Abstract Background Birthweight is an important indicator of maternal and fetal health globally. The multifactorial origins of birthweight suggest holistic programs that target biological and social risk factors have great potential to improve birthweight. In this study, we examine the dose-response association of exposure to an unconditional cash transfer program before delivery with birthweight and explore the potential mediators of the association. Methods Data for this study come from the Livelihood Empowerment Against Poverty (LEAP) 1000 impact evaluation conducted between 2015 and 2017 among a panel sample of 2,331 pregnant and lactating women living in rural households of Northern Ghana. The LEAP 1000 program provided bi-monthly cash transfers and premium fee waivers to enroll in the National Health Insurance Scheme (NHIS). We used adjusted and unadjusted linear and logistic regression models to estimate the associations of months of LEAP 1000 exposure before delivery with birthweight and low birthweight, respectively. We used covariate-adjusted structural equation models (SEM) to examine mediation of the LEAP 1000 dose-response association with birthweight by household food insecurity and maternal-level (agency, NHIS enrollment, and antenatal care) factors. Results Our study included a sample of 1,439 infants with complete information on birthweight and date of birth. Nine percent of infants (N = 129) were exposed to LEAP 1000 before delivery. A 1-month increase in exposure to LEAP 1000 before delivery was associated with a 9-gram increase in birthweight and 7% reduced odds of low birthweight, on average, in adjusted models. We found no mediation effect by household food insecurity, NHIS enrollment, women’s agency, or antenatal care visits. Conclusions LEAP 1000 cash transfer exposure before delivery was positively associated with birthweight, though we did not find any mediation by household- or maternal-level factors. The results of our mediation analyses may serve to inform program operations and improve targeting and programming to optimize health and well-being among this population. Trial Registration The evaluation is registered in the International Initiative for Impact Evaluation’s (3ie) Registry for International Development Impact Evaluations (RIDIESTUDY- ID-55942496d53af) and in the Pan African Clinical Trial Registry (PACTR202110669615387).

With the continuous development and improvement of digital media technology, its position in dynamic visual design is also increasing. In this paper, we first combine LCEOPaCH algorithm to extract color features from visual images, use local energy pointing mode to get image color transformation information, optimize the dynamic visual measurement method based on dynamic binocular reconstruction, and construct a dynamic visual communication model combined with visual SLAM. Through the empirical data of the visual communication system, the localization accuracy of different methods in dynamic environments is compared based on the root mean square error value of absolute trajectory error in dynamic datasets A, B, and C. The quantization results of this paper’s algorithm under dynamic visual measurement analysis and color feature extraction data comparison in 6 sets of simulated images, the PSNR value is higher than 30, and the average value of PSNR is as high as 38.11 under 24 feature colors. The SSIM value for 8 feature colors is higher than 0.75 in the same quantization. The study demonstrates the advantages of digital media technology in visual communication design and provides practical design ideas.

This meta-analysis investigated the effect of physical exercise (PE) on the levels of oxidative biomarkers in randomized controlled trials (RCTs) involving healthy subjects. We searched five databases for articles until May 1, 2023. A random-effect meta-analysis, subgroup analysis, meta-regressions as well as trim and fill method were conducted using STATA 11.0, involving ten articles. According to the results of the meta-analysis, PE had no significant effect on superoxide dismutase (SOD), glutathione peroxidase, and catalase levels. PE induced significant increase in total antioxidant status (standardized mean difference [SMD] 1.53, 95% CI 0.73–2.32), and PE could significantly reduce the level of malondialdehyde (MDA) (SMD −1.11, 95% CI −2.15 to −0.06). Sensitivity analyses and subgroup analyses showed that male participants, body mass index (BMI)

We evaluated whether demographics and COVID-19 symptoms predicted COVID-19 deaths among healthcare workers (HCWs) in the United States by comparing COVID-19 deaths in HCWs with 3 control groups (HCW nondeaths, non-HCW deaths, and non-HCW nondeaths) using a case–control design. We obtained patient-level data of 33 variables reported during January 1, 2020–October 12, 2021, in all US states. We used logistic regression analysis while controlling for confounders. We found that persons who were >50 years of age, male, Black, or Asian experienced significantly more deaths than matched controls. In addition, HCWs who died had higher risks for the most severe clinical indicators. We also found that the most indicative symptoms were preexisting medical conditions, shortness of breath, fever, cough, and gastrointestinal symptoms. In summary, minority, male, and older HCWs had greater risk for COVID-19 death. Severe clinical indicators and specific symptoms may predict COVID-19–related deaths among HCWs.

Objectives: Low birthweight (LBW) prevalence remains high in African countries and evidence of cash transfer impacts on birthweight, particularly by season of infant birth, is limited. This study examines overall and seasonal cash transfer impacts on LBW in rural Ghana.Methods: Data come from a longitudinal, quasi-experimental impact evaluation of the Livelihood Empowerment Against Poverty (LEAP) 1,000 unconditional cash transfer program for impoverished pregnant or lactating women in rural districts of Northern Ghana. LEAP1000 program impacts on average birthweight and LBW were estimated for a multiply imputed sample of 3,258 and a panel sample of 1,567 infants using differences-in-differences models and triple difference models to assess impacts by season.Results: LEAP1000 decreased LBW prevalence by 3.5 and 4.1 percentage points overall and in the dry season, respectively. LEAP1000 increased average birthweight by 94, 109, and 79 g overall, in the dry season, and in the rainy season, respectively.Conclusion: Our findings of positive LEAP1000 impacts on birthweight across seasons and on LBW in the dry season demonstrate the need to take seasonal vulnerabilities into account when designing and implementing programs for rural populations in Africa.

Background: Little is known regarding whether environmental programs affect student academic performance. We examined if the association between EPA Tools for School (TfS) policies or other environmental programs and student test scores were mediated by student attendance. Methods: The 2015 School Building Condition Survey (BCS) was linked with School Report data provided by the New York State Education Department (NYSED). BCS includes school building information from 2,956 public schools while School Report data provides school attendance and test scores for different subjects in NYS. We conducted causal mediation analysis to investigate direct and indirect effects of TfS or other programs, via improving attendance, on test scores for each course while controlling for school-level socio-demographics. Results: EPA TfS policies were significantly associated with a lower percent of “low total score” for overall math, overall science, and multiple specific subjects (all P

Background: Thermal comfort is essential for human well-being. Consistent exposure to uncomfortable thermal conditions indoors leads to reduced academic performance and adverse health outcomes in schoolchildren. In addition, children are more sensitive to thermal conditions due to physiological differences, yet their exposure to thermal conditions has not been adequately measured.Methods: This cross-sectional study evaluated students' exposure to temperature and relative humidity (RH) using personal air monitors. In this study, we recruited 90 students from 13 classrooms – 60 from 11 NYS primary school classrooms and 30 from two State University of New York at Albany classrooms. Each participant wore an AirBeam air monitor for 48 hours, and their data was transmitted to a cell phone provided by the researchers.Results: Primary school students were routinely exposed to temperatures exceeding ASHRAE standards (winter: 75⁰F, summer: 80.5⁰F), particularly in school in the spring (max=102⁰F, median=82⁰F). At home, temperatures exceeded standards in the evening around dinnertime. However, primary students were routinely exposed to RH below recommended standards in classrooms during all seasons (median=29%). However, the RH was significantly lower in the winter than in any other season (median=17%). Finally, university students were exposed to slightly higher temperatures and significantly lower RH than primary schoolchildren in the spring.Conclusion: These results suggest that students are exposed to uncomfortable thermal conditions, particularly in classrooms when attending class. Teachers should therefore be given more control over classroom ventilation and thermal conditions, while indoor temperature standards should be adjusted for school children.

Background: Although power outage (PO) is one of the most important consequences of increasing weather extremes and the health impact of POs has been reported previously, studies on the neighborhood environment underlying the population vulnerability in such situations are limited. This study aimed to identify dominant neighborhood environmental predictors which modified the impact of POs on multiple health outcomes in New York State. Methods: We applied a two-stage approach. In the first stage, we used time series analysis to determine the impact of POs (versus non-PO periods) on multiple health outcomes in each power operating division in New York State, 2001-2013. In the second stage, we classified divisions as risk-elevated and non-elevated, then developed predictive models for the elevation status based on 36 neighborhood environmental factors using random forest and gradient boosted trees. Results: Consistent across different outcomes, we found predictors representing greater urbanization, particularly, the proportion of residents having access to public transportation (importance ranging from 4.9–15.6%), population density (3.3–16.1%), per capita income (2.3–10.7%), and the density of public infrastructure (0.8–8.5%), were associated with a higher possibility of risk elevation following power outages. Additionally, the percent of minority (-6.3–27.9%) and those with limited English (2.2–8.1%), the percent of sandy soil (6.5–11.8%), and average soil temperature (3.0–15.7%) were also dominant predictors for multiple outcomes. Spatial hotspots of vulnerability generally were located surrounding New York City and in the northwest, the pattern of which was consistent with socioeconomic status. Conclusion: Population vulnerability during power outages was dominated by neighborhood environmental factors representing greater urbanization.

Background and objectives: Diabetes is an increasing public health concern worldwide. The impact of extreme heat exposure on diabetes healthcare utilization such as diabetes-related hospital admissions and emergency department (ED) visits was understudied although extreme temperature exposure was linked with diabetes mortality. In addition, very few systematic reviews have been conducted in this field. This review aims to systematically evaluate the currently available evidence on the association between extreme ambient heat exposure and hospital admissions/ED visits for diabetes and the vulnerable population to heat extremes. Methods: A systematic literature review was conducted by using the keywords/terms “ambient temperature or heatwave or heat wave or extreme temperature or high temperature effect” and “diabetes morbidity or diabetes hospital admissions or diabetes emergency room visits” for available publications until August 2022. The heat exposure was categorized into four groups using difference definitions. The outcomes were diabetes-related hospital admissions/ED visits. A meta-analysis was performed to estimate the pooled effects of relative risk (RR)/odds ratio (OR) and 95% confidence intervals (CI) for each of the associations of interest. Results: Eighteen articles were selected from forty full-text, English written papers based on the inclusion and exclusion criteria. The overall pooled effect of excessive heat on diabetes, across all groups, was 1.045 (95% CI: 1.024-1.066). The pooled effects for each exposure group were significant/borderline significant. Additionally, the pooled effect of the RR/OR was 1.100 (95% CI: 1.067-1.135) among adults aged 65 years or older. The most controlled confounders were air pollutants. The commonly listed limitation in those studies was misclassification of exposure. Conclusions: The body of evidence supports that ambient extreme heat exposure is associated with diabetes-related hospital admissions/ED visits. Additionally, adults 65 years of age or older with diabetes are vulnerable to heat extremes. Future studies should consider controlling for various biases and confounders.

Background: Research is lacking in examining how multiple climate factors affect the incidence of seasonal influenza. We investigated the associations between El Niño Southern Oscillation (ENSO), meteorological factors, and influenza incidence in New York State, United States. Method: We collected emergency department visit data for influenza from the New York State Department of Health. ENSO index was obtained from the National Oceanic and Atmospheric Administration. Meteorological factors, Google Flu Search Index (GFI), and Influenza-like illness (ILI) data in New York State were also collected. Wavelet analysis was used to quantitatively estimate the coherence and phase difference of ENSO, temperature, precipitation, relative humidity, and absolute humidity with emergency department visits of influenza in New York State. Generalized additive models (GAM) were employed to examine the exposure-response relationships between ENSO, weather, and influenza. GFI and ILI data were used to simulate synchronous influenza visits. Results: The influenza epidemic in New York State had multiple periodic and was primarily on the 1-year scale. The incidence of influenza closely followed the low ENSO index by an average of two months, and the lag period of ENSO on influenza was shorter during 2015–2018. Low temperature in the previous 2 weeks and low absolute humidity in the prior week were positively associated with influenza incidence in New York State. We found an l-shaped association between ENSO index and influenza, a parabolic relationship between temperature in the previous two weeks and influenza, and a linear negative association between absolute humidity in the previous week and influenza. The simulation models including GFI and ILI had higher accuracy for influenza visit estimation. Conclusions: Low ENSO index, low temperature, and low absolute humidity may drive the influenza epidemics in New York State. The findings can help us deepen the understanding of the climate-influenza association, and help to develop an influenza forecasting model.

Abstract Background Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO’s role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations. Methods In this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001–2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0–6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM2.5). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations. Results The RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0–6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0–6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations. Conclusions Both major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.

Background: Mental disorders (MDs) are behavioral or mental patterns that cause significant distress or impairment of personal functioning. Previously, temperature has been linked to MDs, but most studies suffered from exposure misclassification due to limited monitoring sites. We aimed to assess whether multiple meteorological factors could jointly trigger MD-related emergency department (ED) visits in warm season, using a highly dense weather monitoring system. Methods: We conducted a time-stratified, case-crossover study. MDs-related ED visits (primary diagnosis) from May-October 2017–2018 were obtained from New York State (NYS) discharge database. We obtained solar radiation (SR), relative humidity (RH), temperature, heat index (HI), and rainfall from Mesonet, a real-time monitoring system spaced about 17 miles (126 stations) across NYS. We used conditional logistic regression to assess the weather-MD associations. Results: For each interquartile range (IQR) increase, both SR (excess risk (ER): 4.9%, 95% CI: 3.2–6.7%) and RH (ER: 4.0%, 95% CI: 2.6–5.4%) showed the largest risk for MD-related ED visits at lag 0–9 days. While temperature presented a short-term risk (highest ER at lag 0–2 days: 3.7%, 95% CI: 2.5–4.9%), HI increased risk over a two-week period (ER range: 3.7–4.5%), and rainfall hours showed an inverse association with MDs (ER: −0.5%, 95% CI: 0.9-(-0.1)%). Additionally, we observed stronger association of SR, RH, temperature, and HI in September and October. Combination of high SR, RH, and temperature displayed the largest increase in MDs (ER: 7.49%, 95% CI: 3.95–11.15%). The weather-MD association was stronger for psychoactive substance usage, mood disorders, adult behavior disorders, males, Hispanics, African Americans, individuals aged 46–65, or Medicare patients. Conclusions: Hot and humid weather, especially the joint effect of high sun radiation, temperature and relative humidity showed the highest risk of MD diseases. We found stronger weather-MD associations in summer transitional months, males, and minority groups. These findings also need further confirmation.

BackgroundThe association between the incidence of hand, foot, and mouth disease (HFMD) and ambient temperature has been well documented. Although the severity of symptoms is an important indicator of disease burden and varies significantly across cases, it usually was ignored in previous studies, potentially leading to biased estimates of the health impact of temperature.MethodsWe estimated the disability-adjusted life year (DALY) by considering the severity of symptoms for each HFMD case reported during 2010-2012 in Guangdong and used distributed lag-nonlinear models to estimate the association between the daily average temperature and daily DALY of HFMD cases at the city-level. We investigated the potential effect modifiers on the pathway between temperature and DALY and pooled city-specific estimates to a provincial association using a meta-regression. The overall impact of temperature was further evaluated by estimates of DALYs that could be attributed to HFMD.ResultsThe overall cumulative effect of daily mean temperature on the DALY of HFMD showed an inverse-U shape, with the maximum effect estimated to be β = 0.0331 (95%CI: 0.0199-0.0463) DALY at 23.8°C. Overall, a total of 6.432 (95%CI: 3.942-8.885) DALYs (attributable fraction = 2.721%, 95%CI: 1.660-3.759%) could be attributed to temperature exposure. All the demographic subgroups had a similar trend as the main analysis, while the magnitude of the peak of the temperature impact tended to be higher among the males, those aged ≥3yrs or from the Pear-River Delta region. Additionally, the impact of temperature on DALY elevated significantly with the increasing population density, per capita GDP, and per capita green space in parks.ConclusionsTemperature exposure was associated with increased burden of HFMD nonlinearly, with certain groups such as boys and those from areas with greater population density being more vulnerable.

Objective: Congenital heart diseases (CHDs) are associated with an extremely heavy global disease burden as the most common category of birth defects. Genetic and environmental factors have been identified as risk factors of CHDs previously. However, high volume clinical indicators have never been considered when predicting CHDs. This study aimed to predict the occurrence of CHDs by considering thousands of variables from self-reported questionnaires and routinely collected clinical laboratory data using machine learning algorithms.Methods: We conducted a birth cohort study at one of the largest cardiac centers in China from 2011 to 2017. All fetuses were screened for CHDs using ultrasound and cases were confirmed by at least two pediatric cardiologists using echocardiogram. A total of 1,127 potential predictors were included to predict CHDs. We used the Explainable Boosting Machine (EBM) for prediction and evaluated the model performance using area under the Receive Operating Characteristics (ROC) curves (AUC). The top predictors were selected according to their contributions and predictive values. Thresholds were calculated for the most significant predictors.Results: Overall, 5,390 mother-child pairs were recruited. Our prediction model achieved an AUC of 76% (69-83%) from out-of-sample predictions. Among the top 35 predictors of CHDs we identified, 34 were from clinical laboratory tests and only one was from the questionnaire (abortion history). Total accuracy, sensitivity, and specificity were 0.65, 0.74, and 0.65, respectively. Maternal serum uric acid (UA), glucose, and coagulation levels were the most consistent and significant predictors of CHDs. According to the thresholds of the predictors identified in our study, which did not reach the current clinical diagnosis criteria, elevated UA (>4.38 mg/dl), shortened activated partial thromboplastin time (

Evidence on the spatial-temporal distribution of tuberculosis (TB) mortality across China and its relationship with long-term particulate matter (PM _2.5 ) exposure is limited. We aimed to address significant gaps in our understanding of the spatial-temporal clustering patterns of TB mortality in China and provide evidence for its causal links with long-term PM _2.5 exposure. Annual pulmonary TB mortality, PM _2.5 concentrations, and socioeconomic factors for provinces in mainland China between 2004 and 2017 were obtained. Turning points in the temporal trend and spatial clustering patterns of pulmonary TB mortality were identified. A difference-in-differences causal inference approach was applied to estimate the long-term effect of PM _2.5 exposure on the mortality. The average annual percent change of pulmonary TB mortality in China was −2.5% (95% CI : −5.6%, 0.7%), with an 11.1% annual increase in the Northwest since 2012 ( P = 0.029). The hot and cold spots, determined by the local Moran’s I index, were all located in northern China, where Xinjiang in the Northwest had the highest mortality across the study period. We found a significant association between long-term PM _2.5 exposure and pulmonary TB mortality, with percent increase risk of mortality ( IR %) being 0.74% (95 CI %, 0.04%, 1.45%) for 1 µ g/m ^3 increase in PM _2.5 concentration. This association varied across multiple socioeconomic groups, with the highest IR % in provinces with lower level of latitude ( IR % = 0.83%, 95% CI : 0.01%, 1.65%), lower quartile of gross domestic product ( IR % = 1.01%, 95% CI: 0.23%, 1.80%) or higher proportion (⩾14%) of people >65 years of age ( IR % = 1.24%, 95% CI: 0.44%, 2.04%). Comprehensive sensitivity analyses showed a robust adverse effect of long-term PM _2.5 exposure on pulmonary TB mortality. Attention needs to be paid to the rising trend of pulmonary TB mortality in Northwest China. Our study provides the stable evidence to date of the causal association between long-term PM _2.5 exposure and the risk of death from pulmonary TB, especially in low-altitude, underdeveloped, and aged provinces.

Background: Accumulating evidence suggests that environmental pollutants may contribute to the occurrence of congenital heart defects (CHDs). However, no previous studies have evaluated the impact of perfluoroalkyl substances (PFAS), persistent environmental pollutants, on CHDs. This exploratory study aimed to generate testable hypotheses of the association between gestational PFAS and the risk of CHDs. Methods: A nested case-control study was conducted in a cohort of 11,578 newborns. Exposure odds ratios were compared between 158 CHD cases and 158 non-malformed controls delivered at the same hospital, individually matched by maternal age (±5 years) and parity. Concentrations of 27 PFAS, including linear and branched isomers, were determined in maternal peripheral blood and cord blood plasma collected before and during delivery using a ultra-performance liquid chromatography coupled to mass spectrometry. Conditional logistic regression was utilized to evaluate associations between individual PFAS and the risk of CHDs, adjusted for confounding variables. Results: Maternal gestational exposure to the highly branched perfluorooctanesulfonate (PFOS) isomer potassium 6-trifluoromethyperfluoroheptanesulfonate [6 m-PFOS, adjusted odds ratio (aOR) (95% CI) = 2.47(1.05,5.83)] and perfluorodecanoic acid [PFDA, aOR (95% CI) = 2.33(1.00,5.45)] were associated with increased odds of septal defects with statistical significance, while linear PFOS [aOR (95% CI) = 3.65(1.09,12.16)] and perfluoro-n-dodecanoic acid [PFDoA, aOR (95% CI) = 6.82(1.75, 26.61)] were associated with conotruncal defects. Effect estimates also suggested associations for higher maternal 6 m-PFOS and PFDA concentrations with ventricular septal defect. However, we did not observe these associations in cord blood. Conclusion: These exploratory findings suggested that gestational exposure to most PFAS, especially linear PFOS, 6 m-PFOS, PFDA, and PFDoA, was associated with greater risks for septal and conotruncal defects. However, a larger, adequately powered study is needed to confirm our findings, and to more comprehensively investigate the potential teratogenic effects of other more recently introduced PFAS, and on associations with individual CHD subtypes.

Background: Evidence of maternal exposure to ambient air pollution on congenital heart defects (CHD) has been mixed and are still relatively limited in developing countries. We aimed to investigate the association between maternal exposure to air pollution and CHD in China. Method: This longitudinal, population-based, case-control study consecutively recruited fetuses with CHD and healthy volunteers from 21 cities, Southern China, between January 2006 and December 2016. Residential address at delivery was linked to random forests models to estimate maternal exposure to particulate matter with an aerodynamic diameter of ≤ 1 µm (PM1), ≤2.5 µm, and ≤10 µm as well as nitrogen dioxides, in three trimesters. The CHD cases were evaluated by obstetrician, pediatrician, or cardiologist, and confirmed by cardia ultrasound. The CHD subtypes were coded using the International Classification Diseases. Adjusted logistic regression models were used to assess the associations between air pollutants and CHD and its subtypes. Results: A total of 7055 isolated CHD and 6423 controls were included in the current analysis. Maternal air pollution exposures were consistently higher among cases than those among controls. Logistic regression analyses showed that maternal exposure to all air pollutants during the first trimester was associated with an increased odds of CHD (e.g., an interquartile range [13.3 µg/m3] increase in PM1 was associated with 1.09-fold ([95% confidence interval, 1.01–1.18]) greater odds of CHD). No significant associations were observed for maternal air pollution exposures during the second trimester and the third trimester. The pattern of the associations between air pollutants and different CHD subtypes was mixed. Conclusions: Maternal exposure to greater levels of air pollutants during the pregnancy, especially the first trimester, is associated with higher odds of CHD in offspring. Further longitudinal well-designed studies are warranted to confirm our findings.

Abstract Background Hand, foot, and mouth disease (HFMD) raises an urgent public health issue in the Asia-Pacific region, especially in China. The associations between weather factors and HFMD have been widely studied but with inconsistent results. Moreover, previous studies utilizing ecological design could not rule out the bias of exposure misclassification and unobserved confounders. Methods We used case-crossover analysis to assess the associations of weather factors on HFMD. Individual HFMD cases from 2009 to 2012 in Guangdong were collected and cases located within 10 km of the meteorological monitoring sites were included. Lag effects were examined through the previous 7 days. In addition, we explored the variability by changing the distance within 20 km and 30 km. Results We observed associations between HFMD and weather factors, including temperature and relative humidity. An approximately U-shaped relationship was observed for the associations of temperature on HFMD across the same day and the previous 7 days, while an approximately exponential-shaped was seen for relative humidity. Statistically significant increases in rates of HFMD were associated with each 10-unit increases in temperature [Excess rate (ER): 7.7%; 95% Confidence Interval (CI): 3.9, 11.7%] and relative humidity (ER: 1.9%; 95% CI: 0.7, 3.0%) on lag days 0–6, when assessing within 10 km of the monitoring sites. Potential thresholds for temperature (30.0 °C) and relative humidity (70.3%) detected showed associations with HFMD. The associations remained robust for 20 km and 30 km. Conclusions Our study found that temperature and relative humidity are significantly associated with the increased rates of HFMD. Thresholds and lag effects were observed between weather factors and HFMD. Our findings are useful for planning on targeted prevention and control of HFMD.

Climate change may bring more frequent and severe floods which will heighten public health problems, including an increased risk of infectious diarrhea in susceptible populations. Affected by heavy rainfall and an El Niño event, a destructive flood occurred in Anhui province, China on 18th June 2016. This study investigates the impact of this severe flood on infectious diarrhea at both city-level and provincial level, and further to identify modifying factor. We obtained information on infectious diarrheal cases during 2013–2017 from the National Disease Surveillance System. An interrupted time-series design was used to estimate effects of the flood event on diarrhea in 16 cities. Then we applied a meta-analysis to estimate the area-level pooled effects of the flood in both flooded areas and non-flooded areas. Finally, a meta-regression was applied to determine whether proximity to flood was a predictor of city-level risks. Stratified analyses by gender and age group were also conducted for flooded areas. A significant increase in infectious diarrhea risk (RR = 1.11, 95% CI: 1.01, 1.23) after the flood event was found in flooded area with variation in risks across cities, while there was no increase in non-flooded areas. Diarrheal risks post-flood was progressively higher in cities with greater proximity to the Yangtze River. Children aged 5–14 were at highest risk of diarrhea post-flood in the flooded areas. Our study provides strong evidence that the 2016 severe flood significantly increased infectious diarrheal risk in exposed populations. Local public health agencies are advised to develop intervention programs to prevent and control infectious diarrhea risk when a major flood occurs, especially in areas close to water bodies and among vulnerable populations. Keywords: Floods, Climate change, Infectious diarrhea, Interrupted time series, China

Background: Previous work reported increased rates of acute cardiovascular hospitalizations associated with increased PM2.5 concentrations in the previous few days across urban centers in New York State from 2005 to 2016. These relative rates were higher after air quality policies and economic changes resulted in decreased PM2.5 concentrations and changes in PM composition (e.g. increased secondary organic carbon), compared to before and during these changes. Changes in PM composition and sources may explain this difference. Objectives: To estimate the rate of acute cardiovascular hospitalizations associated with increases in source specific PM2.5 concentrations. Methods: Using source apportioned PM2.5 concentrations at the same NYS urban sites, a time-stratified case-crossover design, and conditional logistic regression models adjusting for ambient temperature and relative humidity, we estimated the rate of these acute cardiovascular hospitalizations associated with increases in mean source specific PM2.5 concentrations in the previous 1, 4, and 7 days. Results: Interquartile range (IQR) increases in spark-ignition emissions (GAS) concentrations were associated with increased excess rates of cardiac arrhythmia hospitalizations (2.3%; 95% CI = 0.4%, 4.2%; IQR = 2.56 μg/m3) and ischemic stroke hospitalizations (3.7%; 95% CI = 1.1%, 6.4%; 2. 73 μg/m3) over the next day. IQR increases in diesel (DIE) concentrations were associated with increased rates of congestive heart failure hospitalizations (0.7%; 95% CI = 0.2% 1.3%; 0.51 μg/m3) and ischemic heart disease hospitalizations (0.8%; 95% CI = 0.3%, 1.3%; 0.60 μg/m3) over the next day, as hypothesized. However, secondary sulfate PM2.5 (SS) was not. Increased acute cardiovascular hospitalization rates were also associated with IQR increases in concentrations of road dust (RD), residual oil (RO), and secondary nitrate (SN) over the previous 1, 4, and 7 days, but not other sources. Conclusions: These findings suggest a role of several sources of PM2.5 in New York State (i.e. traffic emissions, non-traffic emissions such as brake and tire wear, residual oil, and nitrate that may also reflect traffic emissions) in the triggering of acute cardiovascular events. Keywords: Cardiovascular hospitalizations, Air pollution, Source apportionment, Traffic emissions

Previous investigations on the associations of polyfluoroalkyl substances (PFASs) with overweight/obesity are mixed. Moreover, little information has been reported about the association between isomers of PFASs with body mass index (BMI), waist circumference (WC) or overweight. To address this shortcoming in the literature, we conducted a study involving 1612 Chinese adults (1204 men and 408 women), ages 22–96 years old, from Shenyang, China, to analyze serum isomers of perfluorooctanesulfonate (PFOS), perfluorooctanoate (PFOA), and other PFASs. Height, weight and WC were measured by a standardized protocol of WHO. Results indicated that increased serum concentrations of all (both branched and linear) isomers of PFASs were associated with a higher prevalence of overweight, and these associations were more pronounced in women. The adjusted odds ratios (ORs) from logistic regression analyses among women were 1.45 (95% confidence interval [CI]: 1.06, 1.99) for linear PFOS isomers, 1.33 (95% CI: 1.00, 1.77) for branched PFOS isomers, 1.39 (95% CI: 1.06, 1.81) for 3 + 4 + 5m PFOS, 1.54 (95% CI: 1.08, 2.21) for linear PFOA isomers, and 1.62 (95% CI: 1.05, 2.51) for branched PFOA isomers, respectively. Associations with increased WC were yielded a similar pattern. Linear regression models also showed positive associations between PFASs and BMI or WC. In conclusion, this study suggests that PFASs and their isomers are positively associated with overweight or increased WC, and the associations are stronger in women. Furthermore, PFOA and its isomers displayed the most robust obesogenic associations. Keywords: Perfluoroalkyl substances (PFASs), PFASs isomers, Overweight, Anthropometry, Obesity, Isomers of C8 Health Project

Backgrounds: Evidence on the association between long-term exposure to particulate matter with aerodynamic diameter ≤2.5 μm (PM2.5) and cardiovascular disease (CVD) is scarce in developing countries. Moreover, few studies assessed the role of the PM1 (≤1.0 μm) size fraction and CVD. We investigated the associations between PM1 and PM2.5 and CVD prevalence in Chinese adults. Methods: In 2009, we randomly recruited 24,845 adults at the age of 18–74 years from 33 communities in Northeastern China. CVD status was determined by self-report of doctor-diagnosed CVD. Three-year (2006–08) average concentrations of PM1 and PM2.5 were assigned using a satellite-based exposure. We used spatial Generalized Linear Mixed Models to evaluate the associations between air pollutants and CVD prevalence, adjusting for multiple covariates. Stratified and interaction analyses and sensitivity analyses were also performed. Results: A 10 μg/m3 increase in long-term exposure to ambient PM1 levels was associated a 12% higher odds for having CVD (OR = 1.12; 95% CI = 1.05–1.20). Compared to PM1, association between PM2.5 and CVD was lower (OR = 1.06; 95% CI = 1.01–1.11). No significant association was observed for PM1–2.5 (1–2.5 μm) size fraction (OR = 0.98; 95% CI = 0.85–1.13). Stratified analyses showed greater effect estimates in men and the elder. Conclusions: Long-term PM1 exposure was positively related to CVD, especially in men and the elder. In addition, PM1 may play a greater role than PM2.5 in associations with CVD. Further longitudinal studies are warranted to confirm our findings. Keywords: Particulate matter, Cardiovascular disease, Adults, Chinese, Cross-sectional study

Experimental data suggests that PM1 is more toxic than PM2.5 although the epidemiologic evidence suggests that the health associations are similar. However, few objective exposure data are available to compare the associations of PM1 and PM2.5 with children lung function. Our objectives are a) to evaluate associations between long-term exposure to PM1, PM2.5 and children’s lung function, and b) to compare the associations between PM1 and PM2.5. From 2012 to 2013, we enrolled 6,740 children (7–14 years), randomly recruited from primary and middle schools located in seven cities in northeast China. We measured lung function including forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), peak expiratory flow (PEF), and maximal mid-expiratory flow (MMEF) utilizing two portable electronic spirometers. We dichotomized continuous lung function measures according the expected values for gender and age. The spatial resolution at which PM1 and PM2.5 estimated were estimated using a machine learning method and the temporal average concentrations were averaged from 2009 to 2012. A multilevel regression model was used to estimate the associations of PM1, PM2.5 exposure and lung function measures, adjusted for confounding factors. Associations with lower lung function were consistently larger for PM1 than for PM2.5. Adjusted odds ratios (OR) per interquartile range greater PM1 ranged from 1.53 for MMEF (95% confidence interval [CI]: 1.20–1.96) to 2.14 for FEV1 (95% CI: 1.66–2.76) and ORs for PM2.5 ranged from 1.36 for MMEF (95%CI: 1.12–1.66) to 1.82 for FEV1 (95%CI: 1.49–2.22), respectively. PM1 and PM2.5 had significant associations with FVC and FEV1 in primary school children, and on PEF and MMEF in middle school children. Long-term PM1 and PM2.5 exposure can lead to decreased lung function in children, and the associations of PM1 are stronger than PM2.5. Therefore, PM1 may be more hazardous to children’s respiratory health than PM2.5 exposure.

Background: Proximity to greenness has shown protective effects on coronary heart diseases by limiting exposure to environmental hazards, encouraging physical activity, and reducing mental stress. However, no studies have previously evaluated the impacts of greenness on congenital heart defects (CHDs). We examined the association between maternal residential greenness and the risks of CHDs. Methods: We conducted a case-control study (8042 children with major CHDs and 6887 controls without malformations) in 21 cities in Southern China, 2004 – 2016. CHDs cases were diagnosed and verified by obstetrician, pediatrician, or pediatric cardiologists, within one year. We estimated maternal residential greenness using satellite-derived normalized difference vegetation index (NDVI) in zones of 500 meters (m) and 1000 m surrounding participants’ residences. Logistic regression models were used to assess NDVI-CHD relationships adjusting for confounders. Results: Interquartile range NDVI increases within 500 m or 1000 m were associated with odds ratios (OR) of 0.95 (95% confidence interval (CI): 0.92, 0.98) and 0.94 (95%CI: 0.91, 0.97) for total CHDs respectively. Air pollutants mediated 52.1% of the association. We also identified a protective threshold at 0.21 NDVI on CHD. Similar protective effects from greenness were found in most CHDs subtypes. The protective associations were stronger for fall, urban or permanent residents, higher household income maternal age ≤35 years of age, and high maternal education (ORs: ranged from 0.85 to 0.96). Conclusion: Our findings suggest a beneficial effect of maternal residential greenness on CHDs. Further studies are needed to confirm our findings, which will help to refine preventive health and urban design strategies.

Background Maternal folic acid supplementation (FAS) reduces the risk of neural tube defects in offspring. However, its effect on congenital heart disease (CHDs), especially on the severe ones remains uncertain. This study aimed to assess the individual and joint effect of first‐trimester maternal FAS and multivitamin use on CHDs in offspring. Methods and Results This is a case‐control study including 8379 confirmed CHD cases and 6918 controls from 40 healthcare centers of 21 cities in Guangdong Province, China. Adjusted odds ratios (aORs) of FAS and multivitamin use between CHD cases (overall and specific CHD phenotypes) and controls were calculated by controlling for parental confounders. The multiplicative interaction effect of FAS and multivitamin use on CHDs was estimated. A significantly protective association was detected between first‐trimester maternal FAS and CHDs among offspring (aOR, 0.69; 95% CI, 0.62–0.76), but not for multivitamin use alone (aOR, 1.42; 95% CI, 0.73–2.78). There was no interaction between FAS and multivitamin use on CHDs (P=0.292). Most CHD phenotypes benefited from FAS (aORs ranged from 0.03–0.85), especially the most severe categories (ie, multiple critical CHDs [aOR, 0.16; 95% CI, 0.12–0.22]) and phenotypes (ie, single ventricle [aOR, 0.03; 95% CI, 0.004–0.21]). Conclusions First‐trimester maternal FAS, but not multivitamin use, was substantially associated with lower risk of CHDs, and the association was strongest for the most severe CHD phenotypes. We recommend that women of childbearing age should supplement with folic acid as early as possible, ensuring coverage of the critical window for fetal heart development to prevent CHDs.

Background: Experimental studies show that chlorinated polyfluorinated ether sulfonic acids (Cl-PFESA 6:2 and 8:2), one of perfluoroalkyl substances (PFAS) used as perfluorooctane sulfonate (PFOS) alternatives, are reproductive toxicants in vivo and in vitro. However, the associations between gestational exposure to Cl-PFESAs and birth outcomes are unknown. Objectives: We investigated associations between 6:2 Cl-PFESA and 8:2 Cl-PFESA in maternal serum and birth outcomes. Methods: We measured four PFAS, including 6:2 Cl-PFESA, 8:2 Cl-PFESA, PFOS, and perfluorooctanoic acid (PFOA) in third-trimester maternal serum collected from 372 mother-child dyads participating in the Guangzhou Birth Cohort Study. Characteristics of mothers and infants were gathered from medical records and by interviewer-administered questionnaires. Results: PFOS was the most abundant PFAS in maternal serum (median: 7.15 ng/mL), followed by 6:2 Cl-PFESA (median: 2.41 ng/mL). Greater maternal serum levels of all PFAS alternatives were significantly associated with lower birth weight, adjusted for confounding variables. For example, each ln-ng/mL greater concentration of 6:2 Cl-PFESA and 8:2 Cl-PFESA was associated with a 54.44 g [95% confidence interval (CI): −95.66, −13.22] and 21.15 g (95% CI: −41.44, −0.86) lower birth weight, respectively. Greater continuous maternal serum 6:2 Cl-PFESA (OR: 2.67, 95% CI: 1.73, 4.15) and PFOS (OR: 2.03, 95% CI: 1.24, 3.32) were also associated with higher risks for preterm birth, adjusted for confounders, with a possible threshold effect at the highest quartile of 6:2 Cl-PFESA. Conclusions: For the first time, we report associations between maternal serum 6:2 Cl-PFESA and 8:2 Cl-PFESA concentrations and adverse birth outcomes. Our findings suggest that PFOS alternatives may be reproductive toxicants in human populations and should be considered with caution before widespread use. Given the preliminary nature of our results, additional epidemiological and toxicological investigations are needed to more definitively assess the risks. Keywords: Perfluorooctane sulfonate (PFOS) alternatives, 6:2 Cl-PFESA, 8:2 Cl-PFESA, Preterm birth, Birth weight

Background: Residing in greener areas has several health benefits, but no study to date has examined the effects of greenness on metabolic syndrome (MetS). We aimed to assess associations between residential greenness and MetS prevalence in China, and to explore whether air pollution and physical activity mediated any observed associations. Methods: We analyzed data from 15,477 adults who participated in the 33 Communities Chinese Health Study during 2009. We defined MetS according to standard guidelines for Chinese populations. Residential greenness was estimated using the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), and the Vegetation Continuous Field (VCF). We used generalized linear mixed models to assess the associations between greenness and MetS, and mediation analyses to explore potential mechanisms underlying the associations. Results: Higher greenness levels were associated with lower odds of MetS [e.g., for every interquartile range increase of NDVI500-m, SAVI500-m, and VCF500-m, the adjusted odds ratio of MetS was 0.81 (95% confidence interval: 0.70–0.93), 0.80 (95% confidence interval: 0.69–0.93), and 0.91 (95% confidence interval: 0.83–1.00), respectively]. The direction and the magnitude of the associations persisted in several sensitivity analyses. Stratified analyses showed that age and household income modified the associations, with greater effect estimates observed in participants younger than 65 years old or those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide, and ozone mediated 2.1–20.3% of the associations between greenness and MetS; no evidence of mediation was observed for physical activity. Conclusions: Our findings suggest a beneficial association for residential greenness and MetS in Chinese urban dwellers, especially for participants younger than 65 years old and those with higher household income. Particulate matter with an aerodynamic diameter ≤10 μm, nitrogen dioxide and ozone, but not physical activity, may only partially mediate the association. Keywords: Greenness, Metabolic syndrome, Mediation, Chinese adults, Cross-sectional study