Evidence map›Paper›PMID 40814044›Full record

ArticleBMC public health2025

Social determinant of health patterns and mortality outcomes in US adults.

Fangyuan Chen, Ryan D Nipp, Xuesong Han, Zhiyuan Zheng, Tianci Wang, K Robin Yabroff, Changchuan Jiang

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PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

7 authors.

Fangyuan ChenSchool of Medicine, Tsinghua University, Beijing, China.
Ryan D NippOU Health Stephenson Cancer Center, University of Oklahoma College of Medicine, Oklahoma City, OK, USA.
Xuesong HanSurveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA.
Zhiyuan ZhengSurveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA.
Tianci WangBurnett School of Medicine, Texas Christian University, Fort Worth, TX, USA.
K Robin YabroffSurveillance and Health Equity Science, American Cancer Society, Atlanta, GA, USA.
Changchuan JiangDivision of Medical Oncology and Hematology, Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA. Changchuan.jiang@utsouthwestern.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial Determinants of Health (SDOH) influences healthcare access, especially in patients with chronic diseases. However, SDOHs were often investigated as single variables. Combination patterns and joint effects of multiple SDOHs are much understudied. This study seeks to identify SDOH patterns in the US general population and their influence in all-cause and specific mortality.

methodsThis study included US adults aged 18 to 79 from 2002 to 2018 National Health Interview Survey (NHIS) and NHIS Linked Mortality Files. 12 SDOHs from 5 domains (healthcare access, education and literacy, economic stability, social isolation, neighborhood cohesion) were selected and binarized from the NHIS, including: material, psychological, and behavioral medical financial hardship, delayed care due to transportation and due to non-transportation factors, education, employment, food security, income, housing security, marital status, and neighborhood cohesion. Key outcomes, including all-cause, cancer-specific mortality, and cardiovascular disease-specific death were identified at quarter and year of death.

resultsFrom the 105,824 younger adults (18–64 years), and the 23,825 older adults (65–79 years), five distinct SDOH patterns were identified: pattern 1 (31%, few barriers); 2 (20%, unmarried); 3 (17%, unemployed); 4 (15%, both unmarried and unemployed); and 5 (16%, with relatively high rate of non-married status, housing insecurity, and material, psychological, or behavioral medical financial hardships). Compared to pattern 1, pattern 4 and 5 had worse prognosis in all mortality outcomes in both age groups, including all-cause mortality, cancer-specific mortality, and cardiovascular disease-specific mortality in both age groups.

conclusionsIn this study, we found that SDOHs could be clustered into five distinct patterns. Patients who were unmarried and unemployed (pattern 4) or with multiple concurrent adverse SDOHs (pattern 5) had poorest key health outcomes. These findings support comprehensive screening for SDOH profiles to understand cumulative influences of SDOHs on quality of life and clinical outcomes of patients with chronic medical conditions.

Indexed as

MortalitySocial Determinants of HealthAdolescentAdultAgedCause of DeathFemaleHealth Services AccessibilityHealth SurveysHumansMaleMiddle AgedSocioeconomic Disparities in HealthUnited StatesYoung AdultCancer-specific mortalityHealthcare accessMortality outcomesNational health interview surveySocial determinants of health

Identifiers

PMID40814044
PMCPMC12351764

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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.