The Impact of Power Outages on Cardiovascular Hospitalizations Among Medicare Fee-for-service Enrollees in New York State, 2017-2018
Power outages are common. They can result in exposure to extreme temperatures by shutting off temperature-controlling devices, and thereby also cause stress. Consequently, outages may precipitate cardiovascular disease (CVD)-related hospitalizations. We assessed this relationship among older adults....
Saved in:
| Published in: | Epidemiology (Cambridge, Mass.) Vol. 36; no. 4; p. 458 |
|---|---|
| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
United States
01.07.2025
|
| Subjects: | |
| ISSN: | 1531-5487, 1531-5487 |
| Online Access: | Get more information |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Power outages are common. They can result in exposure to extreme temperatures by shutting off temperature-controlling devices, and thereby also cause stress. Consequently, outages may precipitate cardiovascular disease (CVD)-related hospitalizations. We assessed this relationship among older adults.
We leveraged 2017-2018 data from 245,452 New York State Medicare Fee-for-Service beneficiaries (65+ years) with 390,530 CVD hospitalizations. Using NY Department of Public Services data, we calculated total hours without power 1 day, 1-2 days, and 1-3 days before case and control periods, with an outage ZIP Code Tabulation Area (ZCTA)-hour defined based on ≥10% of customers in a ZCTA-hour without power in primary analyses. We used a case-crossover study design and ran conditional logistic regression to assess associations separately within each urbanicity level: New York City (NYC), non-NYC urban, and rural areas. We additionally stratified models by warm versus cool season, individual-level age and sex, and ZCTA-level socioeconomic factors. Secondarily, we considered emergency (n = 298,910) and nonemergency hospitalizations separately.
We generally observed null associations between power outages and all CVD hospitalizations across New York State and within subgroups. For example, in NYC, we observed a rate ratio of 1.05 (95% confidence interval: 0.85, 1.30) for each additional power outage hour 1 day prior.
The case-crossover design we used eliminated time-fixed confounding, but there were a limited number of exposed cases, limiting statistical power. Future studies should investigate co-occurring severe weather, span additional years, and evaluate other and broader geographic areas. |
|---|---|
| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1531-5487 1531-5487 |
| DOI: | 10.1097/EDE.0000000000001853 |