Observational studyBMJ open2019
Decomposition of the US black/white inequality in premature mortality, 2010-2015: an observational study.
Observational study in BMJ open, 2019. 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
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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.
- Impacts of census differential privacy for small-area disease mapping to monitor health inequities.Science advances · 2023Article
- A longitudinal analysis of the relationship between housing insecurity and physical health among midlife and aging adults in the United States.SSM - population health · 2022Article
- "We're, Like, the Most Unhealthy People in the Country": Using an Equity Lens to Reduce Barriers to Healthy Food Access in Rural Appalachia.Preventing chronic disease · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
objectiveDecompose the US black/white inequality in premature mortality into shared and group-specific risks to better inform health policy.
settingAll 50 US states and the District of Columbia, 2010 to 2015.
participantsA total of 2.85 million non-Hispanic white and 762 639 non-Hispanic black US-resident decedents. PRIMARY AND SECONDARY OUTCOME MEASURES: The race-specific county-level relative risks for US blacks and whites, separately, and the risk ratio between groups.
resultsThere is substantial geographic variation in premature mortality for both groups and the risk ratio between groups. After adjusting for median household income, county-level relative risks ranged from 0.46 to 2.04 (median: 1.03) for whites and from 0.31 to 3.28 (median: 1.15) for blacks. County-level risk ratios (black/white) ranged from 0.33 to 4.56 (median: 1.09). Half of the geographic variation in white premature mortality was shared with blacks, while only 15% of the geographic variation in black premature mortality was shared with whites. Non-Hispanic blacks experience substantial geographic variation in premature mortality that is not shared with whites. Moreover, black-specific geographic variation was not accounted for by median household income.
conclusionUnderstanding geographic variation in mortality is crucial to informing health policy; however, estimating mortality is difficult at small spatial scales or for small subpopulations. Bayesian joint spatial models ameliorate many of these issues and can provide a nuanced decomposition of risk. Using premature mortality as an example application, we show that Bayesian joint spatial models are a powerful tool as researchers grapple with disentangling neighbourhood contextual effects and sociodemographic compositional effects of an area when evaluating health outcomes. Further research is necessary in fully understanding when and how these models can be applied in an epidemiological setting.
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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.