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Observational Study
. 2020 Nov 5;15(11):e0241868.
doi: 10.1371/journal.pone.0241868. eCollection 2020.

Quantifying the collective influence of social determinants of health using conditional and cluster modeling

Zachary D Rethorn  1 , Alessandra N Garcia  2 , Chad E Cook  1   3 , Oren N Gottfried  4
Affiliations
Observational Study

Quantifying the collective influence of social determinants of health using conditional and cluster modeling

Zachary D Rethorn et al. PLoS One. .

Abstract

Objectives: Our objective was to analyze the collective effect of social determinants of health (SDoH) on lumbar spine surgery outcomes utilizing two different statistical methods of combining variables.

Methods: This observational study analyzed data from the Quality Outcomes Database, a nationwide United States spine registry. Race/ethnicity, educational attainment, employment status, insurance payer, and gender were predictors of interest. We built two models to assess the collective influence of SDoH on outcomes following lumbar spine surgery-a stepwise model using each number of SDoH conditions present (0 of 5, 1 of 5, 2 of 5, etc) and a clustered subgroup model. Logistic regression analyses adjusted for age, multimorbidity, surgical indication, type of lumbar spine surgery, and surgical approach were performed to identify the odds of failing to demonstrate clinically meaningful improvements in disability, back pain, leg pain, quality of life, and patient satisfaction at 3- and 12-months following lumbar spine surgery.

Results: Stepwise modeling outperformed individual SDoH when 4 of 5 SDoH were present. Cluster modeling revealed 4 distinct subgroups. Disparities between the younger, minority, lower socioeconomic status and the younger, white, higher socioeconomic status subgroups were substantially wider compared to individual SDoH.

Discussion: Collective and cluster modeling of SDoH better predicted failure to demonstrate clinically meaningful improvements than individual SDoH in this cohort. Viewing social factors in aggregate rather than individually may offer more precise estimates of the impact of SDoH on outcomes.

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Conflict of interest statement

I have read the journal’s policy and the authors of this manuscript have the following competing interests: ONG reports personal fees from RTI pioneer and Medtronic, outside the submitted work. ZDR, ANG, and CEC certify that they have no affiliations with or financial involvement in any organization or entity with a direct financial interest in the subject matter or materials discussed in the article. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Cohort selection process.
Fig 2
Fig 2. Probability of 100 persons from the younger, minority, low socioeconomic status (YML) subgroup compared to the younger, white, high socioeconomic status (YWH) subgroup achieving success on each outcome at 3 months.
Fig 3
Fig 3. Probability of 100 persons from the younger, minority, low socioeconomic status (YML) subgroup compared to the younger, white, high socioeconomic status (YWH) subgroup achieving success on each outcome at 12 months.
Fig 4
Fig 4. Infographic of quantifying the collective influence of social determinants of health.
See this image and copyright information in PMC

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