Evidence map›Paper›PMID 38715565›Full record

ArticleJournal of clinical and translational science2024

Measuring concordance and discordance between selected individual characteristics and corresponding neighborhood-level social determinants of health.

Ka Ming Ngai, Andrew Maroko, Saadiyah Bilal, Marcee Wilder, Lauren Gordon, Lynne D Richardson

Abstract read
In one paragraph

Article in Journal of clinical and translational science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ka Ming NgaiInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.ORCID https://orcid.org/0000-0003-2650-6651
Andrew MarokoInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Saadiyah BilalInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Marcee WilderInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lauren GordonInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Lynne D RichardsonInstitute for Health Equity Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Individuals reside within communities influenced by various social determinants impacting health, which may harmonize or conflict at individual and neighborhood levels. While some experience concordant circumstances, discordance is prevalent, yet poorly understood due to the lack of a universally accepted method for quantifying it. This paper proposes a methodology to address this gap. Methods: We propose a systematic approach to operationalize concordance and discordance between individual and neighborhood social determinants, using household income (HHI) (continuous) and race/ethnicity (categorical) as examples for individual social determinants. We demonstrated our method with a small dataset that combines self-reported individual data with geocoded neighborhood level. We anticipate that the risk profiles created by either self-reported individual data or neighborhood-level data alone will differ from patterns demonstrated by typologies based on concordance and discordance. Results: In our cohort, it was revealed that 20% of patients experienced discordance between their HHIs and neighborhood characteristics. Additionally, 38% reside in racially/ethnically concordant neighborhoods, 23% in discordant ones, and 39% in neutral ones. Conclusion: Our study introduces an innovative approach to defining and quantifying the notions of concordance and discordance in individual attributes concerning neighborhood-level social determinants. It equips researchers with a valuable tool to conduct more comprehensive investigations into the intricate interplay between individuals and their environments. Ultimately, this methodology facilitates a more accurate modeling of the true impacts of social determinants on health, contributing to a deeper understanding of this complex relationship.

Indexed as

Health disparitiesindividual risk factorsneighborhood risk factorssocial determinants of health (SDoH)

Identifiers

PMID38715565
PMCPMC11075104

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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.