Modeling and comparing central and room air conditioning ownership and cold-season in-home thermal comfort using the American Housing Survey

Household-level information on central air conditioning (cenAC) and room air conditioning (rmAC) air conditioning and cold-weather thermal comfort are often missing from publicly available housing databases hindering research and action on climate adaptation and air pollution exposure reduction. We...

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Bibliographic Details
Published in:Journal of exposure science & environmental epidemiology 2020-09, Vol.30 (5), p.814-823
Main Authors: Gronlund, Carina J., Berrocal, Veronica J.
Format: Article
Language:English
Subjects:
Air Conditioning
Air pollution
Air quality management
Alternation learning
Climate action
Climate adaptation
Cold
Epidemiology
Health aspects
Health risks
Housing
Humans
Medicine
Medicine & Public Health
Ownership
Polls & surveys
Pollution control
Regression analysis
Regression models
Seasons
Sensitivity
Statistical analysis
Surveys
Surveys and Questionnaires
Thermal comfort
United States
Weather
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Summary:Household-level information on central air conditioning (cenAC) and room air conditioning (rmAC) air conditioning and cold-weather thermal comfort are often missing from publicly available housing databases hindering research and action on climate adaptation and air pollution exposure reduction. We modeled these using information from the American Housing Survey for 2003–2013 and 140 US core-based statistical areas employing variables that would be present in publicly available parcel records. We present random-intercept logistic regression models with either cenAC, rmAC or “home was uncomfortably cold for 24 h or more” (tooCold) as outcome variables and housing value, rented vs. owned, age, and multi- vs. single-family, each interacted with cooling- or heating-degree days as predictors. The out-of-sample predicted probabilities for years 2015–2017 were compared with corresponding American Housing Survey values (0 or 1). Using a 0.5 probability threshold, the model had 63% specificity (true negative rate), and 91% sensitivity (true positive rate) for cenAC, while specificity and sensitivity for rmAC were 94% and 34%, respectively. Area-specific sensitivities and specificities varied widely. For tooCold, the overall sensitivity was effectively 0%. Future epidemiologic studies, heat vulnerability maps, and intervention screenings may reliably use these or similar AC models with parcel-level data to improve understanding of health risk and the spatial patterning of homes without AC.
ISSN:1559-0631
1559-064X
DOI:10.1038/s41370-020-0220-8