Development of PRAPARE Social Determinants of Health Clusters and Correlation with Diabetes and Hypertension Outcomes

Abstract

Introduction: PRAPARE is a leading social risk screening tool. No studies yet have simplified the 22 PRAPARE social determinants of health (SDoH) into clusters to analyze associations with chronic disease outcomes.Methods: A federally qualified health center conducted cross-sectional PRAPARE screening on its general adult population. Exploratory and confirmatory factor analyses were used to identify SDoH clusters and construct cluster scores and SDoH total risk scores. Logistic regression assessed relationships between cluster scores and uncontrolled diabetes and/or hypertension.Results: Of the 11,773 adults who answered the survey, 716 had diabetes only, 2,388 had hypertension only, 1,477 had both, and 7,192 had neither. We found 3 composite SDoH clusters (social background, social insecurities, insurance/employment) and 3 standalone clusters (housing status, social isolation, poverty). Among patients with diabetes, those at risk in social background, social insecurities, and insurance/employment were more likely to have uncontrolled diabetes. Among patients with hypertension, those at more risk in social insecurities were more likely to have uncontrolled hypertension.Conclusions: We simplified the 22 PRAPARE SDoH into 3 composite clusters and 3 individual clusters and demonstrated the reliability and validity of PRAPARE. The 3 composite clusters were positively associated with uncontrolled diabetes and/or hypertension.

Analyzing Multiple Social Determinants of Health Using Different Clustering Methods

“…This finding provides insights into the potential underlying structure of the data, and informing how future scales might be able to group concepts to describe specific domains, such as housing or food insecurity [34]. This result aligns with the study of Wan et al [9], who identified three composite clusters among the 22 PRAPARE SDoH factors.…”

“…We also used 3 measures of area-level SDoH by census-tract of participant's residence at time of assessment for these analyses: the Social Vulnerability Index overall score, rural urban commuting code, and the Yost SES Index [21]. Demographic variables such as age, sex, and gender were used to describe our results but were not included in factor analysis or latent class analysis [9].…”

“…Despite the widespread use of PRAPARE, study is limited regarding which SDoH measures matter most [8], and which groupings of SDoH measures have the greatest impact on specific chronic disease outcomes [9] or social risk of specific group of patients [10]. Utilizing advanced statistical methods that group SDoH may help extract meaningful insights from the data and identify patterns and relationships among the variables.…”

Health related social needs and whole person health: Relationship between unmet social needs, health outcomes, and healthcare spending among commercially insured adults

“…The following health conditions were assessed: anxiety/depression, hypertension, and type 2 diabetes (ICD 10 codes included in supplemental Table 2 ). These three conditions were selected based on their widespread prevalence in the U.S. population and their demonstrated associations with HRSNs in other study populations ( Heller et al, 2021 , Wan et al, 2022 ).…”

Expert panel identified health-related social needs and methodological considerations for a polysocial risk score

“…For example, numerous HRSNs screening questionnaires exist, but most have no scoring guidelines 9 . HRSNs are often co-occurring 10 , but organizations often collect information on only select HRSNs [11][12][13] . Overall, HRSNs are not view holistically.…”