Fig 1.
a. Study flow chart of NWAS statistical methods b. Overview of study findings by methodological phase.
a Logit(p) = α+βi0xage+ βi1xyear of diagnosis + βi2xneighborhood variable (i, j) + εij;
where i = individual cancer cases; j = census tracts (Phase 1)
b Logit(p) = α+βi0xage+βi1xyear of diagnosis+β2xneighborhood variable (i, j) +V(j) +U(j)
where i = individual prostate cancer cases; j = county, V(j) are independent non-spatial random effects and U(j) are spatially structured random effects (Phase 2).
*These 17 components explain 90% of the variance
Fig 2.
Phase 3-Principal components and fine mapping analysis to identify top hits.
Dots represent single neighborhood variables from Phase 2 (n = 217 total dots). Open dots are color-coded to their respective component (from Phase 3-Principal Components analysis). Closed-colored dots represent the most significant variable within each component (Phase 3-Fine Mapping) and corresponding statistics are provided by component number in Fig 3. *Top hit based on statistical significance from Phase 2 data. a Statistical significance determined by Bonferroni-corrected confidence intervals from the Phase 2 Bayesian model, i.e. smaller credible interval length indicates greater statistical significance.
Fig 3.
Summary of neighborhood variable “top hits” associated with aggressive prostate cancer by phase.
aStandard deviation (sd); bConfidence or Credible Interval (CI).