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Individual and neighborhood characteristics as predictors of depression symptom response
Author(s) -
Panaite Vanessa,
Bowersox Nicholas W.,
Zivin Kara,
Ganoczy Dara,
Kim Hyungjin Myra,
Pfeiffer Paul N.
Publication year - 2019
Publication title -
health services research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.706
H-Index - 121
eISSN - 1475-6773
pISSN - 0017-9124
DOI - 10.1111/1475-6773.13127
Subject(s) - depression (economics) , medicine , patient health questionnaire , logistic regression , propensity score matching , retrospective cohort study , cohort , depressive symptoms , demography , psychiatry , anxiety , economics , macroeconomics , sociology
Objective Assess whether neighborhood characteristics predict patient‐reported outcomes for depression. Data Sources VA electronic medical record data and U.S. census data. Study Design Retrospective longitudinal cohort. Data Extraction Methods Neighborhood and individual characteristics of patients (N = 4,269) with a unipolar depressive disorder diagnosis and an initial Patient Health Questionnaire (PHQ‐9) score ≥10 were used to predict 50 percent improvement in 4‐8‐month PHQ‐9 scores. Principal Findings The proportion of a patient's neighborhood living in poverty (OR = 0.98; 95% CI: 0.97‐.1.00; P = 0.03) was associated with lower likelihood of depression symptom improvement in addition to whether the patient was black (OR = 0.76; 95% CI:0.61‐0.96; P = 0.02) had PTSD (OR = 0.59; 95% CI:0.50‐0.69; P < 0.001) or had any service‐connected disability (OR = 0.73; 95% CI:0.61‐0.87; P < 0.001). Conclusions Neighborhood poverty should be considered along with patient characteristics when determining likelihood of depression improvement.