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Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

ABSTRACT: Objective: To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM_2.5) for 214 mutually exclusive disease groups.

Design: Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.

Setting: Medicare inpatient hospital claims in the United States, 2000-12 (n=95?277?169).

Participants: All Medicare fee-for-service beneficiaries aged 65 or older admitted to hospital.

Main outcome measures: Risk of hospital admission, number of admissions, days in hospital, inpatient and post-acute care costs, and value of statistical life (that is, the economic value used to measure the cost of avoiding a death) due to the lives lost at discharge for 214 disease groups.

Results: Positive associations between short term exposure to PM_2.5 and risk of hospital admission were found for several prevalent but rarely studied diseases, such as septicemia, fluid and electrolyte disorders, and acute and unspecified renal failure. Positive associations were also found between risk of hospital admission and cardiovascular and respiratory diseases, Parkinson's disease, diabetes, phlebitis, thrombophlebitis, and thromboembolism, confirming previously published results. These associations remained consistent when restricted to days with a daily PM_2.5 concentration below the WHO air quality guideline for the 24 hour average exposure to PM_2.5. For the rarely studied diseases, each 1 µg/m³ increase in short term PM_2.5 was associated with an annual increase of 2050 hospital admissions (95% confidence interval 1914 to 2187 admissions), 12?216 days in hospital (11?358 to 13?075), US$31m (£24m, €28m; $29m to $34m) in inpatient and post-acute care costs, and $2.5bn ($2.0bn to $2.9bn) in value of statistical life. For diseases with a previously known association, each 1 µg/m³ increase in short term exposure to PM_2.5 was associated with an annual increase of 3642 hospital admissions (3434 to 3851), 20?098 days in hospital (18?950 to 21?247), $69m ($65m to $73m) in inpatient and post-acute care costs, and $4.1bn ($3.5bn to $4.7bn) in value of statistical life.

Conclusions: New causes and previously identified causes of hospital admission associated with short term exposure to PM_2.5 were found. These associations remained even at a daily PM_2.5 concentration below the WHO 24 hour guideline. Substantial economic costs were linked to a small increase in short term PM_2.5.

SUBMITTER: Wei Y

PROVIDER: S-EPMC6880251 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

Wei Yaguang Y Wang Yan Y Di Qian Q Choirat Christine C Wang Yun Y Koutrakis Petros P Zanobetti Antonella A Dominici Francesca F Schwartz Joel D JD

BMJ (Clinical research ed.) 20191127

<h4>Objective</h4>To assess risks and costs of hospital admission associated with short term exposure to fine particulate matter with diameter less than 2.5 µm (PM<sub>2.5</sub>) for 214 mutually exclusive disease groups.<h4>Design</h4>Time stratified, case crossover analyses with conditional logistic regressions adjusted for non-linear confounding effects of meteorological variables.<h4>Setting</h4>Medicare inpatient hospital claims in the United States, 2000-12 (n=95 277 169).<h4>Participants< ...[more]

PMID: 31776122

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Project description:Background: Exposure to fine particulate matter (PM2.5) during wildfire seasons has been associated with adverse health outcomes. Previous studies have focused on daily exposure, but PM2.5 levels in smoke events can vary considerably within 1 d.Objectives: We aimed to assess the immediate and lagged relationship between sub-daily exposure to PM2.5 and acute health outcomes during wildfire seasons in British Columbia.Methods: We used a time-stratified case-crossover study design to evaluate the association between modeled hourly PM2.5 and ambulance dispatches during wildfire seasons from 2010 to 2015. Distributed lag nonlinear models were used to estimate the lag-specific and cumulative odds ratios (ORs) at lags from 1 to 48 h. We examined the relationship for all dispatches and dispatches related to respiratory, circulatory, and diabetic conditions, identified by codes for ambulance dispatch (AD), paramedic assessment (PA) or hospital diagnosis (HD).Results: Increased respiratory health outcomes were observed within 1 h of exposure to a 10-?g/m3 increase in PM2.5. The 48-h cumulative OR [95% confidence interval (CI)] was 1.038 (1.009, 1.067) for the AD code Breathing Problems and 1.098 (1.013, 1.189) for PA code Asthma/COPD. The point estimates were elevated within 1 h for the PA code for Myocardial Infarction and HD codes for Ischemic Heart Disease, which had 24-h cumulative ORs of 1.104 (0.915, 1.331) and 1.069 (0.983, 1.162), respectively. The odds of Diabetic AD and PA codes increased over time to a cumulative 24-h OR of 1.075 (1.001, 1.153) and 1.104 (1.015, 1.202) respectively.Conclusions: We found increased PM2.5 during wildfire seasons was associated with some respiratory and cardiovascular outcomes within 1 h following exposure, and its association with diabetic outcomes increased over time. Cumulative effects were consistent with those reported elsewhere in the literature. These results warrant further investigation and may have implications for the appropriate time scale of public health actions. https://doi.org/10.1289/EHP5792.

Dataset Information

Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

Publications

Short term exposure to fine particulate matter and hospital admission risks and costs in the Medicare population: time stratified, case crossover study.

Similar Datasets

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