TY - JOUR
T1 - Social Determinants of Health Phenotypes and Cardiometabolic Condition Prevalence Among Patients in a Large Academic Health System
T2 - Latent Class Analysis
AU - Howell, Carrie R
AU - Zhang, Li
AU - Clay, Olivio J
AU - Dutton, Gareth
AU - Horton, Trudi
AU - Mugavero, Michael J
AU - Cherrington, Andrea L
N1 - © Carrie R Howell, Li Zhang, Olivio J Clay, Gareth Dutton, Trudi Horton, Michael J Mugavero, Andrea L Cherrington. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org).
PY - 2024/8/7
Y1 - 2024/8/7
N2 - BACKGROUND: Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor.OBJECTIVE: This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status.METHODS: Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs).RESULTS: Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79).CONCLUSIONS: Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.
AB - BACKGROUND: Adverse social determinants of health (SDoH) have been associated with cardiometabolic disease; however, disparities in cardiometabolic outcomes are rarely the result of a single risk factor.OBJECTIVE: This study aimed to identify and characterize SDoH phenotypes based on patient-reported and neighborhood-level data from the institutional electronic medical record and evaluate the prevalence of diabetes, obesity, and other cardiometabolic diseases by phenotype status.METHODS: Patient-reported SDoH were collected (January to December 2020) and neighborhood-level social vulnerability, neighborhood socioeconomic status, and rurality were linked via census tract to geocoded patient addresses. Diabetes status was coded in the electronic medical record using International Classification of Diseases codes; obesity was defined using measured BMI ≥30 kg/m2. Latent class analysis was used to identify clusters of SDoH (eg, phenotypes); we then examined differences in the prevalence of cardiometabolic conditions based on phenotype status using prevalence ratios (PRs).RESULTS: Complete data were available for analysis for 2380 patients (mean age 53, SD 16 years; n=1405, 59% female; n=1198, 50% non-White). Roughly 8% (n=179) reported housing insecurity, 30% (n=710) reported resource needs (food, health care, or utilities), and 49% (n=1158) lived in a high-vulnerability census tract. We identified 3 patient SDoH phenotypes: (1) high social risk, defined largely by self-reported SDoH (n=217, 9%); (2) adverse neighborhood SDoH (n=1353, 56%), defined largely by adverse neighborhood-level measures; and (3) low social risk (n=810, 34%), defined as low individual- and neighborhood-level risks. Patients with an adverse neighborhood SDoH phenotype had higher prevalence of diagnosed type 2 diabetes (PR 1.19, 95% CI 1.06-1.33), hypertension (PR 1.14, 95% CI 1.02-1.27), peripheral vascular disease (PR 1.46, 95% CI 1.09-1.97), and heart failure (PR 1.46, 95% CI 1.20-1.79).CONCLUSIONS: Patients with the adverse neighborhood SDoH phenotype had higher prevalence of poor cardiometabolic conditions compared to phenotypes determined by individual-level characteristics, suggesting that neighborhood environment plays a role, even if individual measures of socioeconomic status are not suboptimal.
KW - Humans
KW - Social Determinants of Health
KW - Female
KW - Male
KW - Middle Aged
KW - Phenotype
KW - Latent Class Analysis
KW - Prevalence
KW - Adult
KW - Aged
KW - Cardiovascular Diseases/epidemiology
KW - Academic Medical Centers/statistics & numerical data
KW - Risk Factors
KW - electronic medical record
KW - latent class analysis
KW - cardiometabolic
KW - EHR
KW - obese
KW - social determinants
KW - obesity
KW - cardiovascular disease
KW - risk factors
KW - social determinants of health
KW - social determinant
KW - EMR
KW - risk factor
KW - phenotypes
KW - cardiometabolic disease
KW - diabetes
KW - electronic health record
UR - http://www.scopus.com/inward/record.url?scp=85200939318&partnerID=8YFLogxK
U2 - 10.2196/53371
DO - 10.2196/53371
M3 - Article
C2 - 39113389
SN - 2369-2960
VL - 10
SP - e53371
JO - JMIR Public Health and Surveillance
JF - JMIR Public Health and Surveillance
M1 - e53371
ER -