A Bayesian shared components modeling approach to develop small area indicators of social determinants of health with measures of uncertainty.

ABSTRACT:

Objectives

Existing Canadian social determinants of health (SDOH) indicators do not quantify uncertainty to identify priority areas. The objectives of this methodologic study were: (1) to estimate and map small area (dissemination area) shared and variable-specific SDOH indicators with measures of uncertainty using a Bayesian model that accounts for spatial dependence; (2) to quantify geographic variation in the SDOH indicators and their contribution to a shared indicator; and (3) to assess the SDOH indicators' associations with behavioural risk factors and their consistency with the Ontario Marginalization Index (ON-Marg).

Methods

Lower education-, income-, unemployment-, living alone- and visible minority-related variables used in existing Canadian SDOH indices were fit as

SUBMITTER: Norwood TA 

PROVIDER: S-EPMC7352027 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature