Racial and Geographic Disparities in Late-Stage Prostate Cancer Diagnosis in Florida

Abstract

Disparities in prostate cancer diagnosis among racial/ethnic groups and across Florida were mapped for the period 1996–2002 and their relationship with putative factors (individual, census tract and county level) was investigated using multilevel modeling and contingency analysis. More counties had higher rates of late-stage diagnosis for Black men than for White men and the location of these racial disparities changed with time. An important finding was the substantially larger correlation between county-level rates for Black and White men in 2002 relatively to 1996, which suggests a convergence in their spatial patterns. Major significant factors for late-stage diagnosis included lack of insurance, low household income, smoking, not being married and presence of farm house. These findings should help the design of intervention programs to target counties with the greatest racial disparities in health outcomes. Additional analysis is needed to disentangle the observed racial/ethnic and geographic differences.

Research on neighborhood effects on health in the United States: A systematic review of study characteristics

“…Only one-tenth of studies analyzed neighborhood effects using three level models, and just two papers (0.8% of our sample) conducted analyses beyond three levels. For three-level analyses, counties were most often chosen as the third level (Major et al, 2012; Major et al, 2014; Markossian et al, 2014; Robert & Ruel, 2006; Xiao et al, 2007; Xiao et al, 2011), while census tracts (Subramanian et al, 2005) and states (Subramanian et al, 2008) were less commonly used. One study investigating the relationship among neighborhood stressors, stress-buffering mechanisms, and likelihood of alcohol, drug, and mental health disorder analyzed four-levels (level-1 individuals, level-2 households, level-3 census tracts, and level-4 county) (Stockdale et al, 2007).…”

Analysis of geographical disparities in temporal trends of health outcomes using space–time joinpoint regression

“…These results warrant further exploration of how the introduction of new screening procedures and pace of urbanization impacted the stage of prostate cancer diagnosis and indirectly survival. Individual-level data available for the same time period are currently analyzed to explore the impact of race, individual characteristics, area-level census measures of education, income, and environmental exposure on prostate cancer mortality, incidence and stage at diagnosis (Xiao et al, 2011). These data will help test hypothesis on the potential influence of urbanization and the introduction of PSA test that were formulated on the basis of results of the current county-level analysis.…”

Factors Associated with Overall Survival Prostate Cancer in Florida: A Multilevel Analysis

“…28 Advanced diagnostic techniques and the emergence of new therapies may explain the increased survival among men diagnosed with PCa in recent years. 29,30 Long-term survival depends, in part, on risks posed by existing comorbidity because patients with significant comorbidities are not likely to derive expected benefits from treatment. This is based on the fact that those patients may not be treated aggressively, due to lower life expectancy and side effects associated with concurrent treatments.…”