Table 2.

Standardized direct, indirect, and total effects for the relationship between historic redlining and diabetes prevalence

	Direct effects	Indirect effects	Total effects
Diabetes prevalence
Incarceration	0.06***	—	0.06***
Poverty	−0.10***	—	−0.10***
Discrimination	0.14***	—	0.14***
Substance abuse: drinking	−0.65***	—	−0.65***
Substance abuse: smoking	0.36***	—	0.36***
Housing instability	−0.07***	—	−0.07***
Education	0.06***	—	0.06***
Employment	−0.17***	—	−0.17***
Food access	0.14***	—	0.14***
Historic redlining	0.01**	0.28***	0.29***
Incarceration
Historic redlining	0.27***	—	0.27***
Poverty
Historic redlining	0.35***	—	0.35***
Discrimination
Historic redlining	0.30***	—	0.30***
Substance abuse: drinking
Historic redlining	−0.09***	—	−0.09***
Substance abuse: smoking
Historic redlining	0.28***	—	0.28***
Housing instability
Historic redlining	0.28***	—	0.28***
Education
Historic redlining	0.26***	—	0.26***
Employment
Historic redlining	−0.35***	—	−0.35***
Food access
Historic redlining	0.27***	—	0.27***

Structural equation modeling with standardized estimates were used to investigate relationships. Significant direct effects indicate direct association between variables. For example, higher levels of historic redlining are associated with higher diabetes prevalence. Significant indirect effects indicate pathways through which variables influence outcomes. For example, increased historic redlining is associated with diabetes prevalence through discrimination.

**P < 0.01

***P < 0.001. Dash indicates no path hypothesized.