Principal-components common factor analysis indicated that the first common factor explained 43.5% of the total variance (). Eight census variables, including percentage of unemployed males aged 20 years or more, percentage of unemployed females aged 20 years or more, percentage of female-headed households with dependent children, percentage of households on public assistance, percentage of households without a car, percentage of households with low income, percentage of the population below the federal poverty line, and percentage of the population non-Hispanic black, had substantially higher factor loadings on this first factor (). These 8 census variables indicated a high internal consistency (Cronbach's α = 0.92) and were standardized and comprised the census tract-level socioeconomic deprivation score, which was calculated by weighting factor scoring coefficients.
shows that higher percentages of females; nonwhites; less educated persons; persons who were unmarried, widowed, or living alone; persons with distant CRC; obese persons; persons with diabetes, heart disease, or stroke; persons with lower physical activity levels; current smokers; persons with lower Mediterranean dietary scores; and persons with poorer self-rated health resided in more socioeconomically deprived census tracts.
Among 7,024 primary CRC cases, 2,468 deaths (1,440 from CRC and 1,028 from other causes) were observed during the study period. Kaplan-Meier analysis () indicated that 11-year overall survival rates for the deprivation quartiles were statistically different (log-rank test, P = 0.001), with survival for the least deprived quartile (60.9%) being higher than that for the more deprived quartiles (53.4%, 54.0%, and 52.4%). The 10-year CRC-specific survival rates for the deprivation quartiles also were statistically different, although differences were relatively small (76.1% for the least deprived quartile and 73.5%, 73.2%, and 74.1%, respectively, for the more deprived quartiles; log-rank test, P = 0.008).
Figure 1. Kaplan-Meier survival curves for colorectal cancer (CRC) patients in the NIH-AARP Diet and Health Study, 1995–2005/2006. Neighborhood socioeconomic deprivation score was categorized into 4 quartiles (least deprived (quartile 1) to most deprived (more ...)
Model 1 in shows that CRC patients who lived in census tracts characterized by deprivation quartiles 2–4 were more likely to die from any cause than patients in the least deprived census tracts after adjustment for age and sex. For example, persons who lived in census tracts with the most deprivation were 1.2 times (95% confidence interval (CI): 1.1, 1.4) more likely to die from any cause than persons in the least deprived census tracts. A similar association was found for CRC-specific risk of death. Model 1 also shows that overall risk of death (variance = 0.2) and CRC-specific survival (variance = 0.3) varied geographically. The MHR indicated that the overall risk of death was 1.5 times (95% CI: 1.3, 1.6) higher and the risk of CRC-specific death was 1.6 times (95% CI: 1.4, 1.9) higher, on average, when comparing a CRC patient who lived in a more deprived census tract with another CRC patient with the same individual characteristics (age and sex, in this model) who lived in a less deprived census tract. The IqHR in model 1 indicates that the overall risk of death is 2.5 times (95% CI: 1.9, 3.1) higher and the risk of CRC-specific death is 3.3 times (95% CI: 2.2, 4.4) higher when comparing the 25% of all CRC patients who lived in census tracts with the highest mortality risk to the 25% of CRC patients who lived in census tracts with the lowest mortality risk.
Table 3. Geographic Variation in Neighborhood Socioeconomic Deprivation and Association of Neighborhood Socioeconomic Deprivation With All-Cause and Colorectal Cancer Mortality Among Colorectal Cancer Patients, NIH-AARP Diet and Health Study, 1995–2005/2006 (more ...)
Next, we added various blocks of individual-level characteristics to model 1 (). Results showed that the association between census-tract deprivation and the risk of death was attenuated when models were adjusted for the individual-level characteristics (models 2–7), suggesting that the 6 groups of individual-level factors partially explained the effect of census-tract deprivation on overall risk of death. Similar results were found for CRC-specific risk of death. For both overall and CRC-specific risks of death, the significance of geographic variations was not altered, as evidenced by the stability of the MHR and the IqHR across the 7 models.
All of the 80% IHR ranges contained the value of 1 (data not shown). This indicates that census-tract-level socioeconomic deprivation did not account for a significant amount of census-tract heterogeneity in all-cause and CRC-specific survival.
Sensitivity analysis indicated that adding type of CRC treatment to the models did not alter the findings regarding the geographic variation in and the effect of census tract deprivation on all-cause or CRC-specific survival (data not shown). Participants who were aged ≥70 years or had poorer self-rated health were more likely to be without treatment data (χ2 test, P < 0.001). Additionally, missing treatment data partly resulted from unavailability of information from Michigan.