ArticleScientific data2025
A Comprehensive Dataset of Residential Air Conditioning Prevalence in the Continental United States.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Summer Heat, Physical Activity, and Sedentary Behavior of Children Outdoors and Indoors in an Urban Setting.Journal of urban health : bulletin of the New York Academy of Medicine · 2026Article
- Assessing disparities in air conditioning operation across Southern California.Research square · 2026Article
- A Comprehensive Dataset of Residential Air Conditioning Prevalence in the Continental United States.Scientific data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
This dataset presents the most comprehensive estimate of residential air conditioning (AC) prevalence across the continental United States. Using property-level data for over 103 million housing units from the Dewey database, we imputed and classified four AC types: central, other, evaporative cooler, and none, using XGBoost models optimized for performance. Housing characteristics, socioeconomic indicators, and environmental conditions, such as Cooling Degree Days and elevation, informed predictions. The final product offers national coverage with spatial resolution at the census tract, ZIP code, and metropolitan levels. Model validation was conducted using American Housing Survey data, with strong alignment observed for the central and no air conditioning (AC) categories. This dataset addresses longstanding gaps in understanding the geographic and demographic disparities in AC access, critical for public health, climate adaptation, and energy equity research. Users may integrate these data into epidemiological modeling, resilience planning, and policy analysis to support heat vulnerability assessments and infrastructure interventions.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.