ArticlePloS one2025
Population, demographic and socioeconomic characteristics associated with state preemption laws in the United States, 2009-2018.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveIn the United States, preemption laws enacted by state governments can remove local government authority to enact policy and undermine community self-determination and local democracy. No study to date has evaluated the population, demographic, and socioeconomic characteristics associated with state preemption of public health policies. Our study identifies state characteristics associated with preemption of local paid sick leave, food and nutrition, tobacco control, and firearm safety policies.
methodsWe conducted a Classification and Regression Tree (CART) analysis using state-level demographic, socioeconomic, and population health indicators from 2009 to 2018 to predict state ceiling preemption of local paid sick leave, food and nutrition, tobacco control, and firearm safety policies.
resultsSeveral demographic, economic, political, and health factors best distinguish states with and without preemption in each of the four domains. Total state population was an important characteristic in all four trees and the non-Hispanic Black population was important in three trees. All other age- and race/ethnicity-related demographic variables included were important characteristics in at least one tree. Additionally, adult obesity and flu vaccination were relevant in the paid sick leave tree and firearm-deaths, suicide-deaths, and the unemployment rate were relevant in the firearm safety tree. The relationship between specific factors and preemption in each of the four domains varied depending on the location of the factor within the trees. CONCLUSIONS AND RELEVANCE: Specific population, demographic and economic characteristics in a state are associated with the adoption of ceiling preemption of paid sick, food and nutrition, tobacco, and firearm safety laws, but these characteristics vary by domain. Our study identified which populations within groups of states may be affected by preemption. The findings can inform whether preemption laws considered or adopted in a state may also require protective measures for population groups that could be adversely affected by these laws.
Indexed as
Identifiers
What OpenQuestion holds
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.