The Sexual and Reproductive Health Burden Index: Development, Validity, and Community-Level Analyses of a Composite Spatial Measure.

The Sexual and Reproductive Health Burden Index (SRHBI) was developed to provide a composite spatial measure of sexual and reproductive health (SRH) indicators that can be widely adopted by urban public health departments for the planning of SRH services. The index was constructed using eight indicators: teen births, low birthweight, infant mortality, new HIV diagnoses, people living with HIV, and incidences of gonorrhea, chlamydia, and syphilis. Chicago Department of Public Health data (2014-2017) were used to calculate index scores for Chicago community areas; scores were mapped to provide geovisualization and global Moran's I was calculated to assess spatial autocorrelation. Cronbach's alpha was calculated to assess internal reliability of the SRHBI. Pearson correlations were conducted to assess concurrent validity and correlation with community-level factors. Linear regression was conducted to assess community-level predictors of the SRHBI. Application of the SRHBI in Chicago demonstrates substantial variation in SRH burden across Chicago's urban landscape with significant spatial autocorrelation of scores (I = .580, p = .001). Internal reliability of the measure was excellent with α = .937. The SRHBI was significantly correlated with other indicators of SRH including rate of prenatal care initiation in the first trimester, rate of preterm births, reported sexual assault incidence, cervical cancer incidence, prostate cancer incidence, and rate of smoking during pregnancy. This suggests good concurrent validity of the measure. Linear regression revealed that the percent of Black residents, percent of household couples that are same-sex, community violence, economic hardship, and population density were significant predictors of the SRHBI. The SRHBI provides a valid, useful, and replicable measure to assess and communicate community-level SRH burden in urban environments. The SRHBI may be scaled through a multi-city public data dashboard and utilized by urban public health departments to optimally target and tailor SRH interventions to communities.