Table 3.

Age-and-sex adjusted prevalence and incidence rates^* of type 2 diabetes mellitus (T2DM) by tertiles of neighborhood environments.

	Age-and sex-adjusted prevalence rates (%)*
Neighborhood environments	Low	Medium	High	§P for trend
†Survey-based social environments
Social cohesion	22.4	21.6	18.9	0.017
Violence	19.1	20.0	23.8	0.002
Problems	18.6	20.8	23.4	0.001
‡GIS-based physical environments
Favorable food stores	19.4	21.6	22.9	0.011
Unfavorable food stores	17.9	23.0	21.9	0.010
Physical activity resources	19.3	21.9	21.8	0.089
	Age-and-sex-adjusted incidence rates per 1000 Person Years *
Neighborhood environments	Low	Medium	High	§P for trend
†Survey-based social environments
Social cohesion	27. 5	24.8	20.8	0.010
Violence	21.6	26.4	25.0	0.187
Problems	23.1	23.1	26.6	0.190
‡GIS-based physical environments
Favorable food stores	21.7	24.5	28.2	0.008
Unfavorable food stores	21.1	23.8	28.4	0.007
Physical activity resources	21.6	25.2	26.0	0.086

Abbreviation: GIS: geographic information systems.

^*Logistic regression was used to estimate age-and sex-adjusted prevalence rates of T2DM and Poisson regression was used to estimate age-and sex-adjusted incidence rates of T2DM (sum of events/person-years) according to neighborhood scores; person-years were approximated by using midpoints between clinic visits.

^†Survey-based neighborhood environments were collected from JHS participants and aggregated to census tracts using empirical Bayes estimation. Item responses had a possible range of 1 to 4; higher scores indicate better social cohesion, and higher violence and problems.

^‡GIS-based densities of favorable and unfavorable food stores and physical activity resources were derived using standard industrial classification codes from commercial listings of establishments obtained from National Establishment Time-Series database from Walls & Associates. The densities were calculated for a 1-mile buffer around each of JHS participant’s residential address.

^§P for trend for neighborhood scores entered as ordinal variables in logistic regression or Poisson model.