quasi-Poisson Model Research Articles

Prescription Drug Monitoring and Child Maltreatment in the United States, 2004-2018

To test whether a policy approach aimed at decreasing prescription drug misuse, specifically, state monitoring of controlled substance prescriptions-prescription drug monitoring programs (PDMPs)-were associated with changes in Child Protective Services-reported maltreatment prevalence. Using a difference-in-differences design and maltreatment data (2004-2018) from 50 states and the District of Columbia, we compared the prevalence of total maltreatment incidents and total victims, in states with and without PDMPs, before and after implementation. Exploratory analyses further examined models disaggregated by maltreatment type (neglect, physical abuse, sexual abuse, psychological abuse) and among different racial/ethnic groups. Quasi-Poisson models included state-level covariates, state- and year-fixed effects, and cluster-robust standard errors. Difference-in-differences models identified greater relative reductions in PDMP states relative to controls (total prevalence ratio, 0.87; 95% CI, 0.80, 0.940; victimization prevalence ratio, 0.92; 95% CI, 0.85-0.98) over the observation period. Decreases seemed to be driven by changes in neglect (prevalence ratio, 0.87; 95% CI, 0.80-0.93) and physical abuse (prevalence ratio, 0.78; 95% CI, 0.71-0.87) incidents, and may have been especially salient for American Indian/Alaskan Native children (prevalence ratio, 0.78; 95% CI, 0.65-0.94). We found evidence supporting an association between prescription drug monitoring and reduced maltreatment prevalence at the state level. Policies aimed at restricting the prescribing and dispensing of controlled substances may have indirect implications for child welfare.

Excess mortality in England during the COVID-19 pandemic

IntroductionExcess mortality monitoring is not dependent on completeness or consistency of coding of causes of death and captures deaths caused directly and indirectly by COVID-19. It takes account of existing inequalities in the baseline rates and shows the additional impact of COVID-19. We report weekly on excess mortality by age, gender, geographical area, deprivation, and ethnicity.MethodsA quasi-Poisson model was fitted to deaths data for 2015-2019 to estimate expected mortality in population sub-groups each week during the COVID-19 pandemic. This was compared with observed mortality reported each week. Information on deaths registered was obtained from death certificates. Ethnicity was obtained from hospital records linked to deaths data.ResultsEarly in the pandemic, excess deaths exceeded official reported COVID-19 deaths every week. Throughout the pandemic there were stark inequalities in excess death rates. Based on data from 21 March 2020 to 9 April 2021, people living in the most deprived areas in England experienced more excess (1.21 times; 95% CI 1.21-1.22) compared with people living in the least deprived areas (1.17; 1.16-1.18). Black (1.56; 1.53-1.58) and Asian groups (1.55; 1.53-1.56) experienced more excess than the White group (1.16; 1.16-1.17). There was wide variation between English regions.ConclusionsReporting overall excess mortality early in the pandemic is important to inform policy makers and public about the true scale of the death toll when coding is inconsistent and developing. This approach has highlighted the large increases in already established inequalities in mortality. It provides rapid surveillance of developing disparities for national and local decision makers. It has been used to inform policy around reducing disparities and to revise messaging to encourage hospital attendance for non- COVID-19 health problems.Key messages Excess deaths from all causes is a robust measure of overall impact, unaffected by coding consistency.COVID-19 has dramatically worsened established inequalities between ethnic groups and deprivation groups.

Multi-pollutant urban study on acute respiratory hospitalization and mortality attributable to ambient air pollution in Canada for 2001–2012

Humans inhale a mixture of various air pollutants, and there is ambiguity whether these pollutants act independently or in an additive, synergistic, or antagonistic manner. We aimed to examine differences in adverse health effects of short-term exposure to air pollution through single-versus multi-pollutant models. We collected daily ambient air pollutants (O3, NO2 and PM2.5) concentrations from 24 Canadian urban centers from 2001 to 2012. We examined between-pollutant correlations and estimated their associations with respiratory hospitalization and mortality. We applied a generalized quasi-Poisson model to each city adjusting for one and/or two pollutants. Then we employed a Bayesian hierarchical model to pool the city-specific estimates for national estimates. We also examined 0- to 6-day air pollutant lagged effects by season. Overall, we found more frequently significant effects from single-pollutant models (vs. multi-pollutant models), for hospitalization (vs. mortality), for O3 (vs. NO2, PM2.5), for warm (vs. cold) season, and for lags ≤2 days (vs. 3–6 days). The most consistent effects appeared on respiratory hospitalization for 1-day lagged O3 and PM2.5, but not NO2. This study found little additive or antagonistic risk of respiratory health outcomes from multi-pollutant models due to low-to-medium correlations among the specified air pollutants.

Can Adherence to and Persistence with Inhaled Long-acting Bronchodilators Improve the Quality of Life in Patients with Chronic Obstructive Pulmonary Disease? Results from a German Disease Management Program.

Included ILAB users were aged ≥18years, continuously insured with AOK Bavaria and enrolled in the DMP for COPD. Adherence to ILAB [proportion of days covered (PDC); PDC ≥80%], and persistence (days of uninterrupted ILAB therapy) were assessed in the year preceding the study's HRQoL questionnaire. In a cross-sectional design we applied quasi-Poisson models with log link function and subgroup analyses. The robustness of results was analyzed with comprehensive sensitivity analyses. Patients with PDC≥ 80% had 2.96% higher VAS scores than patients with lower PDCs. From all analyses, patients with GOLD stage III had the highest effects from PDC ≥ 80% (5.33% increased VAS). Patients without heart failure profited significantly more from PDC ≥ 80% (+ 4.34% vs - 2.88%) and from an additional persistent day (+0.01% vs - 0.01%) than patients with heart failure. Overall, ILAB users significantly profited from PDC≥ 80%, but not from continuous PDC or persistent days. In secondary subgroup analyses, patients with GOLD stage III and patients without heart failure particularly profited from PDC≥ 80%. Only patients without heart failure particularly profited from more persistent days. Because identified effects were small and often not robust, advancing adherence and persistence alone may not improve the German DMP for COPD substantially.

Impact of Exposure to Ambient Fine Particulate Matter Pollution on Adults with Knee Osteoarthritis.

The impact of exposure to fine particulate matter (PM2.5) on the incidence of knee osteoarthritis is unclear, especially in Beijing which is a highly polluted city. We conducted a time-series study to examine the correlation between PM2.5 exposure and outpatient visits for knee osteoarthritis in Beijing. Changes (in percentage) in the number of outpatient visits corresponding to every 10-μg/m3 increase in the PM2.5 concentration were determined using a generalized additive quasi-Poisson model. There were records of 9,797,446 outpatient visits for knee osteoarthritis in the study period from 1 January 2010 to 31 December 2017. The daily concentration of PM2.5 was 86.8 (74.3) μg/m3 over this period. A 10-μg/m3 increase in PM2.5 concentrations on lag days 0–3 was associated with a 1.41% (95% confidence interval: 1.40–1.41%) increase in outpatient visits for knee osteoarthritis. Females and patients aged above 65 years were more sensitive to the adverse effects of PM2.5 exposure. The present findings demonstrate that short-term exposure to PM2.5 resulted in an increase in the number of outpatient visits for knee osteoarthritis in Beijing. The findings shed light on the effects of air pollution on knee osteoarthritis and could guide risk-mitigating strategies in cities such as Beijing.

Heat-related cardiovascular morbidity and mortality in Switzerland: a clinical perspective.

Previous studies found increased cardiovascular mortality during hot days, while emergency hospital admissions were decreasing. We explored potential underlying reasons by analysing clinically similar cardiovascular disease groups taking into account primary, underlying and immediate causes of death. We assessed associations of daytime maximum temperature in relation to cardiovascular deaths and emergency hospital admissions between 1998 and 2016 in Switzerland. We applied conditional quasi-Poisson models with non-linear distributed lag functions to estimate relative risks (RRs) of daily cardiovascular mortality and morbidity for temperature increases from the median (22°C) to the 98th percentile (32°C) of the warm season temperature distribution with 10 days of lag. Cardiovascular mortality (n = 163,856) increased for total cardiovascular disease (RR 1.13, 95% confidence interval [CI] 1.08-1.19) and the disease groups hypertension (1.18, 1.02-1.38), arrhythmia (1.29, 1.08-1.55), heart failure (1.22, 1.05-1.43) and stroke of unknown origin (1.20, 1.02-1.4). In contrast, emergency hospital admissions (n = 447,577) decreased for total cardiovascular disease (0.91, 0.88-0.94), hypertension (0.72, 0.64-0.81), heart failure (0.83, 0.76-0.9) and myocardial infarction (0.88, 0.82-0.95). Opposing heat effects were most pronounced for disease groups associated with diuretic and antihypertensive drug use, with the age group ≥75 years at highest risk. Volume depletion and vasodilation from heat stress plausibly explain the risk reduction of heat-related emergency hospital admissions for hypertension and heart failure. Since primary cause of death mostly refers to the underlying chronic disease, the seemingly paradoxical heat-related mortality increase can plausibly be explained by an exacerbation of heat effects by antihypertensive and diuretic drugs. Clinical guidelines should consider recommending strict therapy monitoring of such medication during heatwaves, particularly in the elderly.

Mortality risk attributable to wildfire-related PM2·5 pollution: a global time series study in 749 locations

Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m3 increase in the 3-day moving average (lag 0-2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016-1·022) for all-cause mortality, 1·017 (1·012-1·021) for cardiovascular mortality, and 1·019 (1·013-1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48-0·75) of all-cause deaths, 0·55% (0·43-0·67) of cardiovascular deaths, and 0·64% (0·50-0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period. Short-term exposure to wildfire-related PM2·5 was associated with increased risk of mortality. Urgent action is needed to reduce health risks from the increasing wildfires. Australian Research Council, Australian National Health & Medical Research Council.

Exposure to Industrial Hog Operations and Gastrointestinal Illness in North Carolina, USA

BACKGROUND AND AIM: With 9 million hogs, North Carolina (NC) is the second leading hog producer in the United States. Most hogs are housed at concentrated animal feeding operations (CAFOs), where millions of tons of hog waste can pollute the air and water with fecal pathogens that can cause diarrhea, vomiting, and/or nausea (known as acute gastrointestinal illness (AGI)). METHODS: We used NC’s ZIP code-level syndromic surveillance system to calculate rates of AGI emergency department (ED) visits during 2016-2019 and swine permit data to estimate hog exposure. Exposure was estimated as the inverse distances from each hog CAFO to census block centroids, weighting with Gaussian decay and by hogs per CAFO, then aggregated to ZIP codes using population weights. We compared ZIP codes in the upper quartile of hog exposure to those without hog exposure. Using inverse probability of treatment weighting, we created a control with similar demographics to the high hog exposed population and calculated rate ratios (RR) using quasi-Poisson models. We examined effect measure modification of rurality and race using adjusted models. RESULTS:Among the 111 high hog exposed ZIP codes, the median number of hogs per ZIP code was 50,022. In high hog exposed areas compared to areas without hog exposure, we observed a 17% increase in AGI rate (95% CI: 1.08, 1.26) and a 24% increase in rural areas (95% CI: 1.04, 1.48). The association was stronger during the weeks after heavy rain (RR=1.54, 95% CI: 1.25, 1.83). When restricted to rural areas, we found an increased AGI rate among American Indian (RR=5.26, 95% CI: 4.60, 5.91) and Black (RR=1.47, 95% CI: 1.04, 1.89) patients. CONCLUSIONS:Residing near hog CAFOs may increase rates of AGI ED visits. Hog CAFOs are disproportionally built near rural Black and American Indian communities in NC and are associated most strongly with increased AGI in these populations. KEYWORDS: Concentrated animal feeding operation (CAFO), animal production, swine, environmental pollution, gastrointestinal illness, waterborne pathogens

Association between exposure to PM2.5 components and disease aggravation in amyotrophic lateral sclerosis: an analysis in New York State

BACKGROUND AND AIM: In a previous study we found that long-term exposure to fine particle matter (PM2.5) may contribute to disease aggravation in amyotrophic lateral sclerosis (ALS). However, PM2.5 is a heterogeneous mixture of particles whose composition changes over time and space. In this study, we examined the association between ALS disease aggravation and long-term exposure to specific PM2.5 components. Our study brings insight into whether PM2.5 composition influences its toxicity and shed light into potentially relevant pollution sources. METHODS: We used data from the New York Department of Health Statewide Planning and Research Cooperative System (2000–2014) to construct annual county counts of first hospitalizations with an ALS diagnosis. We used well-validated prediction models at 1km2 resolution to estimate county-level population-weighted annual concentrations of six PM2.5 components: black carbon, organic matter, nitrate, sulfate, sea salt, and soil. Exposure was assigned based on county of residence. We used mixed quasi-Poisson models with county-specific random intercepts to estimate rate ratios (RRs) and 95% confidence intervals (CI) for a 1-year exposure to each PM2.5 component. We allowed for nonlinear exposure–outcome relationships using penalized splines and accounted for potential geospatial and temporal confounders. RESULTS:On average, nitrate and organic matter constituted most of the total PM2.5 mass, 35 and 31% respectively. Sulfate had the strongest correlation with PM2.5 with a Spearman correlation coefficient of 0.88. We found a linear positive association between one-year exposure to organic matter and disease aggravation in ALS (RR=1.20, 95%CI: 1.13, 1.27 per one standard deviation increase). We found no association between the outcome and nitrate, sulfate, sea salt, or soil exposure. CONCLUSIONS:Our results suggest that PM2.5 adverse effects on ALS may vary by particle composition, and we identified organic matter as a potentially relevant PM2.5 component. KEYWORDS: Neurodegenerative diseases, air pollution, particle components, long-term exposures, disease aggravation, ALS

Association between exposure to PM2.5 components and disease aggravation in Parkinson’s disease: an analysis in New York State

BACKGROUND AND AIM: Studies suggests that long-term fine particle matter (PM2.5) exposure may contribute to aggravation of Parkinson’s disease (PD), but overall results have been inconsistent. Among other factors, the differences may arise from variations in PM2.5 composition. In a previous study in New York State, we found a nonlinear PM2.5–PD association. To further characterize this association, here we evaluated long-term exposure to specific PM2.5 components in the same cohort. METHODS: We used data from the New York Department of Health Statewide Planning and Research Cooperative System (2000–2014) to construct annual county counts of first hospitalizations with a PD diagnosis. We used well-validated prediction models at 1km2 resolution to calculate county-level population-weighted annual concentrations of six PM2.5 components: black carbon, organic matter, nitrate, sulfate, sea salt, and soil. Exposure was assigned based on county of residence. We used mixed quasi-Poisson models with county-specific random intercepts to estimate rate ratios (RRs) and 95% confidence intervals (CI) for a 1-year exposure to each PM2.5 component. We allowed for nonlinear exposure–outcome relationships using penalized splines and accounted for potential geospatial and temporal confounders. RESULTS:We estimated a linear positive association between organic matter and disease aggravation in PD (RR=1.06, 95%CI: 1.04, 1.09 per one standard deviation (SD) increase) and a positive linear association with nitrate (RR=1.06, 95%CI: 1.03, 1.10 per one SD increase). We found no association with sulfate, sea salt, or soil exposure. CONCLUSIONS:Our results support that particle composition of PM2.5 may influence its adverse effects on PD. Specifically, we identified organic matter and nitrate as potentially important components in the PD–PM2.5 association. KEYWORDS: Air pollution, particle composition, Parkinson's disease, long-term exposures, disease aggravation

Short-term joint effects of multiple air pollutants on cardio-respiratory disease hospital admissions in Cape Town, 2011 – 2016

BACKGROUND AND AIM: There is limited understanding on the short-term association between hospital admissions and ambient air pollution in sub-Sahara African countries. Therefore, this study investigated the short-term association of air pollution with daily counts of hospital admissions due to respiratory and cardiovascular diseases in Cape Town, South Africa. METHODS: Generalized additive quasi-Poisson models were used within a distributed lag linear modelling framework to estimate the cumulative effects of PM10, NO2 and SO2 up to a lag of 14 days. We further conducted multi-pollutant models and stratified our analysis by age group, sex and season. RESULTS:The relative risk (95% confidence interval (CI)) for PM10, NO2 and SO2 for all ages, both sexes, and seasons, at lag 0 – 1 for hospital admissions due to respiratory disease (RD) were 3.5% (1.8 – 5.2%), 3.2% (1.0 – 5.5%), 1.8% (0 – 3.6%), respectively. In cardiovascular disease (CVD), 2.2% (0.3% - 4%), 1.8% (-0.6% - 4.3%) and -0.5% (-2.3% - 1.3%), respectively, per inter-quartile range increase of 12 ug/m3 for PM10, 7.3 ug/m3 for NO2 and 3.6 ug/m3 for SO2. In multi-pollutant models, PM10 for associations RD remained significant despite some attenuation. The overall cumulative risk per IQR increase in PM10 for females of all ages was 2.7% (-0.2% - 5.6%), 2.9% (0.1% - 5.9%) for males and 6.8% (2.6% - 11.2%) for aged ≥ 65. However, in CVD the association were not significant for all the pollutants, the overall effect estimate for all ages and sexes were 1.4% (-0.8% – 3.7%), 1.4% (-1.4% - 4.3%) and -1% (-2.9% - 1%) for PM10, NO2 and SO2 in three-pollutant models. CONCLUSIONS:We found robust associations of daily respiratory disease hospital admissions with daily PM10 concentrations. Associations were strongest during the warm season and people aged ≥ 65. KEYWORDS: cardiovascular disease, respiratory disease, multi pollutant, short-term association, DLNM, South Africa

Tropical cyclones and mortality in the United States

BACKGROUND AND AIM: In the US, tropical cyclones, such as hurricanes and tropical storms, have a devastating impact on society and are an important public health concern. Previous work has comprehensively examined the association of tropical cyclones with hospitalizations within the week of exposure, and case studies have quantified storm impacts on some causes of death for particular powerful hurricanes. But a comprehensive assessment of multiple causes of mortality across multiple years of study is currently missing. METHODS: In the present study, we used data from over 85 million deaths from the National Center for Health Statistics and a comprehensive record of tropical cyclone occurrence in the US over 30 years (1988 – 2017). We formulated a Bayesian conditional quasi-Poisson model to examine how monthly tropical cyclone exposure—defined as number of days in a month with a sustained maximal wind speed of greater than 34 knots—by county affects monthly death rates up to six months after exposure using unconstrained distributed lag terms. We will also examine how changes in storm-related mortality vary by age and sex, as well as how less powerful but more common winds also impact mortality. RESULTS:There was a total of 4,624 tropical cyclone exposure days (of which 202 were hurricane-level) in 1,174 counties distributed throughout 31 states during our study period. We found that each additional hurricane exposure day was associated with average increases in death rate for cardiovascular diseases only in the month following exposure (3.3%; 95% credible interval [CrI]:0.2, 6.3%); and for respiratory diseases (5.3%; 95%CrI:1.1, 9.7%) in the month of exposure with a positive association remaining until three months afterwards. CONCLUSIONS:Our findings demonstrate the need for targeted interventions and additional preparedness for key causes of death before, during, and after tropical cyclones, especially as they are likely to increase in strength with global climate change. KEYWORDS: Tropical Cyclones, Hurricanes, Climate Change, Natural Disasters, Mortality, Weather

Estimation of all-cause excess mortality by age-specific mortality patterns for countries with incomplete vital statistics: a population-based study of the case of Peru during the first wave of the COVID-19 pandemic

SummaryBackgroundAll-cause excess mortality is a comprehensive measure of the combined direct and indirect effects of COVID-19 on mortality. Estimates are usually derived from Civil Registration and Vital Statistics (CRVS) systems, but these do not include non-registered deaths, which may be affected by changes in vital registration coverage over time.MethodsOur analytical framework and empirical strategy account for registered mortality and under-registration. This provides a better estimate of the actual mortality impact of the first wave of the COVID-19 pandemic in Peru. We use population and crude mortality rate projections from Peru's National Institute of Statistics and Information (INEI, in Spanish), individual-level registered COVID-19 deaths from the Ministry of Health (MoH), and individual-level registered deaths by region and age since 2017 from the National Electronic Deaths Register (SINADEF, in Spanish).We develop a novel framework combining different estimates and using quasi-Poisson models to estimate total excess mortality across regions and age groups. Also, we use logistic mixed-effects models to estimate the coverage of the new SINADEF system.FindingsWe estimate that registered mortality underestimates national mortality by 37•1% (95% CI 23% - 48•5%) across 26 regions and nine age groups. We estimate total all-cause excess mortality during the period of analysis at 173,099 (95% CI 153,669 - 187,488) of which 108,943 (95% CI 96,507 - 118,261) were captured by the vital registration system. Deaths at age 60 and over accounted for 74•1% (95% CI 73•9% - 74•7%) of total excess deaths, and there were fewer deaths than expected in younger age groups. Lima region, on the Pacific coast and including the national capital, accounts for the highest share of excess deaths, 87,781 (95% CI 82,294 - 92,504), while in the opposite side regions of Apurimac and Huancavelica account for less than 300 excess deaths.InterpretationEstimating excess mortality in low- and middle-income countries (LMICs) such as Peru must take under-registration of mortality into account. Combining demographic trends with data from administrative registries reduces uncertainty and measurement errors. In countries like Peru, this is likely to produce significantly higher estimates of excess mortality than studies that do not take these effects into account.FundingNone.

Temporal variation in association between short-term exposure to fine particulate matter and hospitalisations in older adults in the USA: a long-term time-series analysis of the US Medicare dataset

Short-term exposure to fine particulate matter (PM2·5) is associated with increased risk of hospital admissions and mortality, and health risks differ by the chemical composition of PM2·5. Policies to control PM2·5 could change its chemical composition and total mass concentration, leading to change in the subsequent health impact. However, there is little ence on whether associations between PM2·5 and health exhibit temporal variation. We investigated whether risks of hospitalisations from short-term exposure to PM2·5 varied over time in the USA. We did a time-series analysis using a national dataset comprising daily circulatory and respiratory hospitalisation rates of Medicare beneficiaries (age ≥65 years) and PM2·5 in 173 US counties from 1999 to 2016. We fitted modified quasi-Poisson models to estimate temporal trends of associations within a county, and pooled county-level estimates using Bayesian hierarchical modelling to generate an overall estimate. The study included 10 559 654 circulatory and 3 027 281 respiratory hospitalisations. We identified changes in the national average association between previous-day PM2·5 and respiratory hospitalisation over time, with a U-shape that is robust under stratification, linear, and non-linear models. The change in risk of respiratory hospitalisation per 10 μg/m3 increase in previous-day PM2·5 decreased from 0·75% (95% posterior credible interval 0·05 to 1·46) in 1999 to -0·28% (-0·79 to 0·23) in 2008, and then increased to 1·44% (0·00 to 2·91) in 2016. No statistically significant temporal change was observed for associations between same-day PM2·5 and circulatory hospitalisation. Hospitalisation risk from PM2·5 changes over time and has increased over the past 7 years in study, especially in northeastern USA. The temporal trend differs by cause of hospitalisation. This study emphasises the necessity of evaluating temporal heterogeneity in health impacts of PM2·5 and suggests caution in applying association estimates to a different time period. US Environmental Protection Agency and Yale Institute for Biospheric Studies.

Prenatal and Postnatal Household Air Pollution Exposures and Pneumonia Risk: Evidence From the Ghana Randomized Air Pollution and Health Study

Nearly 40%of the world's population is exposed daily to household air pollution. The relative impact of prenatal and postnatal household air pollution exposure on early childhood pneumonia, a leading cause of mortality, is unknown. Are prenatal or postnatal household air pollution, or both, associated with pneumonia risk in the first year of life? The Ghana Randomized Air Pollution and Health Study enrolled 1,414 nonsmoking, pregnant women before 24weeks' gestation with prospective follow-up to the child's age of 1 year. We measured 72-h personal household air pollution exposures, indexed by carbon monoxide (CO), four times prenatally and three times postnatally. Weekly fieldworker surveillance identified ill-appearing children for physician pneumonia assessment. We used quasi-Poisson models to examine associations between prenatal and postnatal CO and physician-diagnosed pneumonia and severe pneumonia. Sex-specific effects were examined. Of the 1,306 live births, 1,141 infants were followed up with 55,605 child-weeks of fieldworker surveillance. The estimated risk for pneumonia and severe pneumonia in the first year of life increased by 10%(relative risk [RR], 1.10; 95%CI, 1.04-1.16) and 15%(RR, 1.15; 95%CI, 1.03-1.28), respectively, per 1-part per million (ppm) increase in average prenatal CO exposure and by 6%(RR, 1.06; 95%CI, 0.99-1.13) per 1-ppm increase in average postnatal CO exposure. Sex-stratified analyses suggest that in girls, higher prenatal CO exposure was associated with pneumonia risk, while no association was seen in boys. Prenatal household air pollution exposure increased risk of pneumonia and severe pneumonia in the first year of life. Clean-burning interventions may be most effective when begun prenatally. ClinicalTrials.gov; No.: NCT01335490; URL: www.clinicaltrials.gov.

Trends in 30-day readmissions following hospitalisation for heart failure by sex, socioeconomic status and ethnicity.

BackgroundReducing the high patient and economic burden of early readmissions after hospitalisation for heart failure (HF) has become a health policy priority of recent years.MethodsAn observational study linking Hospital Episode Statistics to socioeconomic and death data in England (2002-2018). All first hospitalisations with a primary discharge code for HF were identified. Quasi-poisson models were used to investigate trends in 30-day readmissions by age, sex, socioeconomic status and ethnicity.FindingsThere were 698,983 HF admissions, median age 81 years [IQR 14].In-hospital deaths reduced by 0.7% per annum (pa), whilst additional deaths at 30-days remained stable at 5%. Age adjusted 30-day readmissions (21% overall), increased by 1.4% pa (95% CI 1.3-1.5). Readmissions for HF (6%) and ‘other cardiovascular disease (CVD)’ (3%) remained stable, but readmissions for non-CVD causes (12%) increased at a rate of 2.6% (2.4-2.7) pa. Proportions were similar by sex but trends diverged by ethnicity. Black groups experienced an increase in readmissions for HF (1.8% pa, interaction-p 0.03) and South Asian groups had more rapidly increasing readmission rates for non-CVD causes (interaction-p 0.04). Non-CVD readmissions were also more prominent in the least (15%; 15-15) compared to the most affluent group (12%; 12-12). Strongest predictors for HF readmission were Black ethnicity and chronic kidney disease, whilst cardiac procedures were protective. For non-CVD readmissions, strongest predictors were non-CVD comorbidities, whilst cardiologist care was protective.InterpretationIn HF, despite readmission reduction policies, 30-day readmissions have increased, impacting the least affluent and ethnic minority groups the most.FundingNIHR.

Parkinson’s disease aggravation in association with fine particle components in New York State

BackgroundLong-term exposure to fine particulate matter (PM2.5) has been associated with neurodegenerative diseases, including disease aggravation in Parkinson's disease (PD), but associations with specific PM2.5 components have not been evaluated. ObjectiveTo characterize the association between specific PM2.5 components and PD first hospitalization, a surrogate for disease aggravation. MethodsWe obtained data on hospitalizations from the New York Department of Health Statewide Planning and Research Cooperative System (2000–2014) to calculate annual first PD hospitalization counts in New York State per county. We used well-validated prediction models at 1 km2 resolution to estimate county level population-weighted annual black carbon (BC), organic matter (OM), nitrate, sulfate, sea salt (SS), and soil particle concentrations. We then used a multi-pollutant mixed quasi-Poisson model with county-specific random intercepts to estimate rate ratios (RR) of one-year exposure to each PM2.5 component and PD disease aggravation. We evaluated potential nonlinear exposure–outcome relationships using penalized splines and accounted for potential confounders. ResultsWe observed a total of 197,545 PD first hospitalizations in NYS from 2000 to 2014. The annual average count per county was 212 first hospitalizations. The RR (95% confidence interval) for PD aggravation was 1.06 (1.03, 1.10) per one standard deviation (SD) increase in nitrate concentrations and 1.06 (1.04, 1.09) for the corresponding increase in OM concentrations. We also found a nonlinear inverse association between PD aggravation and BC at concentrations above the 96th percentile. We found a marginal association with SS and no association with sulfate or soil exposure. ConclusionIn this study, we detected associations between the PM2.5 components OM and nitrate with PD disease aggravation. Our findings support that PM2.5 adverse effects on PD may vary by particle composition.

Sociodemographic determinants of intraurban variations in COVID-19 incidence: the case of Barcelona

BackgroundIntraurban sociodemographic risk factors for COVID-19 have yet to be fully understood. We investigated the relationship between COVID-19 incidence and sociodemographic factors in Barcelona at a fine-grained geography.MethodsThis cross-sectional ecological...

Gestational exposure to fatal police violence and pregnancy loss in US core based statistical areas, 2013-2015.

BackgroundFatal police violence in the United States disproportionately affects Black, Native American, and Hispanic people, and for these groups it is a racially oppressive population-level stressor that we hypothesize increases the risk of pregnancy loss. Focusing on core based statical areas (CBSAs) surrounding small and large urban centers, we accordingly tested whether gestational exposure to fatal police violence decreased the number of live births, which is reflective of a rise in lost pregnancies.MethodsOur observational study linked microdata for all births (N = 7,709,300) in 520 CBSAs with at least one incident of fatal police violence in 2013–2015 to Fatal Encounters, a database that prospectively identified 2594 police-related fatalities using online media reports and public records. We estimated the association between month-to-month fatal police violence and conceptions resulting in live births using distributed lag quasi-Poisson models with CBSA-level fixed effects, adjusted for seasonality and stratified by maternal race/ethnicity.FindingsFor each additional police-related fatality that occurred in the first through sixth months of gestation, we observed a 0.14% decrease (95% confidence interval: 0.05%, 0.23%) in the total number of live births within CBSAs, and a 0.29% decrease in births to Black women (95% CI: 0.11%, 0.48%). The association was null for births to White women.InterpretationOur findings suggest fatal police violence may have population-level consequences for pregnancy loss and adds to the evidence regarding the importance of preventing these fatalities.

Assessing mortality risk attributable to high ambient temperatures in Ahmedabad, 1987 to 2017

BackgroundStudies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection. MethodsWe collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987–2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987–2002 and 2003–2017 to evaluate temporal heterogeneity. FindingsThe model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003–2017 to 1987–2002. InterpretationThe analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.