Geocoding and Monitoring of US Socioeconomic Inequalities in Mortality and Cancer Incidence: Does the Choice of Area-Based Measure and Geographic Level Matter?

Geocoding and Monitoring of US Socioeconomic Inequalities in Mortality and Cancer Incidence: Does the Choice of Area-based Measure and Geographic Level Matter?

The Public Health Disparities Geocoding Project

Nancy Krieger, Jarvis T. Chen, Pamela D. Waterman, Mah-Jabeen Soobader, S. V. Subramanian, and Rosa Carson

From the Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA.

Received for publication October 18, 2001; accepted for publication May 7, 2002.

Despite the promise of geocoding and use of area-based socioeconomic measures to overcome the paucity of socioeconomic data in US public health surveillance systems, no consensus exists as to which measures should be used or at which level of geography. The authors generated diverse single-variable and composite area-based socioeconomic measures at the census tract, block group, and zip code level for Massachusetts (1990 population: 6,016,425) and Rhode Island (1990 population: 1,003,464) to investigate their associations with mortality rates (1989–1991: 156,366 resident deaths in Massachusetts and 27,291 in Rhode Island) and incidence of primary invasive cancer (1988–1992: 140,610 resident cases in Massachusetts; 1989–1992: 19,808 resident cases in Rhode Island). Analyses of all-cause and cause-specific mortality rates and all-cause and site- specific cancer incidence rates indicated that: 1) block group and tract socioeconomic measures performed comparably within and across both states, but zip code measures for several outcomes detected no gradients or gradients contrary to those observed with tract and block group measures; 2) similar gradients were detected with categories generated by quintiles and by a priori categorical cutpoints; and 3) measures including data on economic poverty were most robust and detected gradients that were unobserved using measures of only education and wealth. Am J Epidemiol 2002;156:471–82.

censuses; geographic information system; geostatistics; mortality; neoplasms; population surveillance; poverty; socioeconomic factors

Abbreviations: IRR, incidence rate ratio; RII, relative index of inequality; SEP, socioeconomic position.

Despite growing recognition of the magnitude and persis- of socioeconomic position (SEP) (5). This lack of data tence of socioeconomic inequalities in health and the need to hampers meaningful monitoring of socioeconomic inequali- address them (1–4), few or no socioeconomic data exist in ties in public health databases. most US public health surveillance databases (5, 6). Only in Reflecting the limitations of available data, the US 1989 did collection of educational data on birth and death National Center for Health Statistics’ first-ever national certificates become routine (7)—60 years after the last chartbook on “Socioeconomic Status and Health,” issued in attempt, in 1930, to generate vital statistics stratified by 1998 (1), presented data based solely on birth and death occupational class (8, 9). Even so, in 1997, only 7 percent, 4 records plus data from the National Health Interview Survey, percent, and 0 percent of US state registries for cancer, tuber- but it could not include data on cancer incidence or survival, culosis, and acquired immunodeficiency syndrome included tuberculosis, human immunodeficiency virus/acquired data on education—and neither they nor birth and death immunodeficiency syndrome, and other health outcomes not databases included data on poverty, income, or other aspects assessed in the National Health Interview Survey. Relatedly,

Correspondence to Dr. Nancy Krieger, Department of Health and Social Behavior, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115 (e-mail: [email protected]).

471 472 Krieger et al.

FIGURE 1. Geographic relations in the US Census. The solid lines (—) indicate connections between entities in the basic census hierarchy (from the nation to blocks) and other geographic areas; the dotted lines (– – –) indicate geographic areas that have boundaries coterminous with census blocks (85).

70 percent of the 467 US public health objectives for the year variety of outcomes, spanning from birth to death (27–38), 2010 lack quantitative targets for reducing socioeconomic have employed markedly different single-variable and disparities in health, given a lack of baseline data (10, 11). composite area-based measures, variously derived from One possible solution to these gaps is to combine data three different geographic levels (figure 1): the census tract from public health surveillance systems with socioeconomic (average population = 4,000); the census block group, a data derived from the US Census. The basic approach is to subdivision of the census tract (average population = 1,000); classify people in public health databases and in the total and the US Postal Service zip code (average population = population by the socioeconomic characteristics of their resi- 30,000) (25). By contrast, in the United Kingdom, several dential neighborhood, thereby permitting calculation of well-established, theoretically conceived, and validated population-based rates stratified by area-based SEP (6, 12). area-based deprivation measures, such as the Townsend These area-based geosocial measures—conceptualized as index, permit meaningful comparisons and monitoring of meaningful indicators of socioeconomic context in their own national, regional, and local socioeconomic gradients in right and not merely “proxies” for individual-level data— health over time (14, 39–42). can be validly applied to all persons, regardless of age, Accordingly, we designed the Public Health Disparities gender, and employment status (6, 12–15). First employed in Geocoding Project to determine which area-based socioeco- US health studies in the 1930s (16–22), the use of such nomic measures, at which level of geography, would be most geosocial measures—by which we mean empirically observ- able social and physical characteristics of areas whose appropriate for US public health surveillance systems and spatial distribution is patterned by human activity—has been research. Considerations pertained to 1) external validity (do greatly facilitated by the past decade’s rapid development of the measures find gradients in the direction reported in the geographic information systems technology (23–25). literature, i.e., positive, negative, or none, and across the full Indeed, National Objective 23-3 of Healthy People 2010 sets range of the distribution?); 2) robustness (do the measures the goal of geocoding, by the year 2010, 90 percent of “all detect expected gradients across a wide range of outcomes?); major national, state, and local health data systems… to 3) completeness (is the measure relatively unaffected by promote nationwide use of geographic information systems missing data?); and 4) user-friendliness (how easy is the (GIS) at all levels” (10). measure to understand and explain?). Guided by an ecosocial Obstacles to the use of area-based socioeconomic framework (43), we deliberately included data from multiple measures are not only technical, however. They are also public health surveillance systems to maximize our ability to conceptual. To date, there exists no consensus in the United assess associations and geosocial health disparities observed States regarding which area-based measures should be used, for diverse health outcomes manifested at different ages. In at which level of geography, to measure or monitor socio- this paper, we report our results for mortality rates and cancer economic inequalities in health (6, 26). Instead, studies on a incidence.

Am J Epidemiol Vol. 156, No. 5, 2002 Geographic Information Systems and Health Inequalities 473

TABLE 1. People and areas included in a study of geocoding and health disparities, Massachusetts and Rhode Island, 1988–1992

Massachusetts Rhode Island

Study base Population size Population size No. No. Mean Range Mean Range Population 1990 population 6,016,425 1,003,464 Mortality data* (1989– 1991) 156,366 27,291 Cancer data* (primary invasive neoplasm) (1988–1992)† 140,610 19,808

Areas Block groups 5,603 1,085.4 (665.2)‡ 5–10,096 897 1,137.7 (670.8) 7–5,652 Census tracts 1,331 4,571.8 (2,080.0) 18–15,411 235 4,325.3 (1,810.9) 26–9,822 Zip codes 474 12,719.7 (12,244.1) 14–65,001 70 14,335.2 (13,234.8) 63–53,763

* In-state residents only. † Massachusetts data were from 1988–1992; Rhode Island data were from 1989–1992 (data from 1988 were not available for Rhode Island because of the recency of the registry). ‡ Numbers in parentheses, standard deviation.

MATERIALS AND METHODS be relatively homogeneous with respect to population characteristics, economic status, and living conditions” (25, pp. Data sources G-10, G-11); its subdivision, the block group, is the smallest The study base comprised populations and areas in Massa- geographic census unit for which census socioeconomic data chusetts and Rhode Island enumerated at or within 2 years of are tabulated (25, p. G-6). By contrast, zip codes are “admin- the 1990 US Census (44, 45). Mortality data and cancer inci- istrative units established by the United States Postal dence data (table 1) were provided by the Massachusetts Service… for the most efficient delivery of mail, and there- Department of Public Health and the Rhode Island Depart- fore generally do not respect political or census statistical ment of Health. Use of these data was approved by all rele- area boundaries” (48, p. A-13). Spanning from large areas vant institutional review boards/human subjects committees cutting across states to a single building or company with a at the Harvard School of Public Health, the Massachusetts high volume of mail, “carrier routes for one zip code may Department of Public Health, and the Rhode Island Depart- intertwine with those of one or more zip codes” such that ment of Health. Cause of death was categorized according to “this area is more conceptual than geographic” (49, p. 22). the International Classification of Diseases, Ninth Revision, To geocode data to the census tract, block group, and zip Clinical Modification (46), cancer type according to the code levels, we submitted residential addresses from the standard site/histology definitions of the Surveillance, mortality and cancer databases to a commercial geocoding Epidemiology, and End Results Program (47), and gender firm selected for its accuracy (50). and race/ethnicity (plus educational level, death only) as Two criteria central to formulating apt area-based reported by next of kin, and/or as recorded by the funeral measures of SEP are that they 1) meaningfully summarize director (for death data) or abstracted by registry staff from important aspects of the specified area’s socioeconomic medical records (for cancer data). Mortality outcomes conditions and 2) employ socioeconomic data that can legit- analyzed included all-cause mortality and the top five causes imately be compared over time and across regions (6, 11, 14, of death in each state by race/ethnicity, yielding nine specific 26, 39–42). On the basis of a priori conceptual definitions of causes of death: heart disease, malignant neoplasm, cere- SEP and social class (6) and evidence from both the United brovascular disease, pneumonia and influenza, chronic States and the United Kingdom emphasizing the detrimental obstructive pulmonary disease, unintentional injury, effects of material deprivation on health (1–4, 51), we devel- diabetes mellitus, human immunodeficiency virus, and oped area-based socioeconomic measures for six domains of homicide and legal intervention. Incidence of cancer was SEP—occupational class, income, poverty, wealth, educa- analyzed for all cancers combined and for five leading sites: tion, and crowding—premised on the understanding that the breast, cervix, colon, lung, and prostate (27, 47). social class, as a social relationship, fundamentally drives We obtained 1990 Census data for census tracts and block the distribution of these manifest aspects of SEP (6). groups from US Bureau of the Census Summary Tape File Table 2 provides information on the 11 single-variable 3A and zip code data from Summary Tape File 3B (48). The measures and eight composite measures we generated for Census Bureau defines a census tract as a “small, relatively each state at each level of geography. Among the composite permanent statistical subdivision of a county… designed to variables, two were US analogs of the United Kingdom

Am J Epidemiol Vol. 156, No. 5, 2002 474 Krieger et al.

TABLE 2. Constructs and operational definitions for area-based socioeconomic measures,* Massachusetts and Rhode Island, 1988– 1992

Construct Operational definition Census variable Occupational class Working class (6) Percentage of persons employed in predominantly working-class occupations, i.e., as nonsupervisory P78 employees. Operationalized as percentage of persons employed in the following eight of 13 census-based occupational groups: administrative support; sales; private household service; other service (except protective); precision production, craft, and repair; machine operators, assemblers, and inspectors; transportation and material moving; handlers, equipment cleaners, and laborers. Unemployment Percentage of persons aged 16 years or older in the labor force who are unemployed (and actively seeking P71 work).

Income Median household income Median household income in the year prior to the decennial census ($30,056 for the United States in 1989). P80A Low income (67) Percentage of households with an income <50% of the US median household income (i.e., <$15,000 in 1989). P80 High income Percentage of households with an income ≥400% of the US median household income (i.e., ≥$150,000 in P80 1989). Gini coefficient A measure of income inequality regarding the share of income distribution across the population. Calculated P80, P80A, using the standard algorithm employed by the US Bureau of the Census to extrapolate the lower and upper P81 ends of the income distribution (86, 87).

Poverty Below US poverty line Percentage of persons below the federally defined poverty line, a threshold that varies by the size and age P117 composition of the household; on average, it equaled $12,647 for a family of four in 1989 (48).

Wealth Expensive homes Percentage of owner-occupied homes worth ≥$300,000 (400% of the median value of owned homes in 1989). H61

Educational level Low: less than high school Percentage of persons aged ≥25 years with less than a 12th-grade education. P57 High: ≥4 years of college Percentage of persons aged ≥25 years with at least 4 years of college. P57

Crowding Crowded households Percentage of households containing more than one person per room. H69, H49

Composite measures Townsend index (39–41) A United Kingdom deprivation measure consisting of a standardized z score combining data on percentage of H69, H49, crowding, percentage of unemployment, percentage of no car ownership, and percentage of renters. H40, H8 Carstairs index (14, 40–42) A United Kingdom deprivation measure consisting of a standardized z score combining data on percentage of H69, H49, crowding, percentage of male unemployment, percentage of no car ownership, and percentage of low social H40, P78 class (equivalent to the following US census categories: transportation and material moving; handlers, equipment cleaners, and laborers; and household service). Index of Local Economic A “summary index” based on “white-collar employment, unemployment, and family income” (52). P78, P71, Resources (52) P107A SEP1 A composite categorical variable based on percentage below the US poverty line, working class, and P117, P78, expensive homes. H61 SEP2 A composite categorical variable based on percentage below the US poverty line, working class, and high P117, P78, income. P80 Factor 1† A factor pertaining to economic resources. Highly correlated with poverty, median household income, home —† ownership, and car ownership. Factor 2† A factor pertaining to occupation and education. Highly correlated with percentage working class, low —† education (less than high school), and high education (≥4 years of college). SEP index A summary deprivation measure consisting of a standardized z score combining data on percentage working P78, P71, class, unemployment, percentage below the US poverty line, low education (less than high school), expensive P117, P57, homes, and median household income‡. P80

* Created using data from the 1990 US Census (40). † Variables employed in the factor analysis: percentage working class, unemployment, percentage below poverty line, home ownership, car ownership, no telephone, expensive homes, low education (less than high school), high education (≥4 years of college), household crowding, households with only one room, no kitchen, no private plumbing, median household income, and proportion of total income in the area derived from interest, dividends, and net rent. ‡ Values for “expensive homes” and “median household income” were reversed before the z score was computed so that a higher score on the SEP index would correspond to a higher degree of deprivation.

Am J Epidemiol Vol. 156, No. 5, 2002 Geographic Information Systems and Health Inequalities 475

Townsend (39–41) and Carstairs (14, 42) deprivation socioeconomic stratum, we also calculated the relative index indices, one used the algorithm for the US Centers for of inequality (RII), a measure of effect that consequently Disease Control and Prevention’s Index of Local Economic permits meaningful comparison of gradients across different Resources (52), and five were created exclusively for our socioeconomic measures (62–64). In step 4, we further study. To mirror the skewed population distribution of socio- restricted analyses to persons geocoded to all three levels of economic resources, we created the variables “SEP1” and geography. In step 5, we summarized findings across socio- “SEP2” to combine simultaneously categorical data on economic measures and geographic levels, in relation to our poverty, working class, and either wealth or high income. a priori considerations regarding external validity, robust- We generated “factor 1” and “factor 2” by factor analysis ness, and completeness of each measure. As a further check with a maximum likelihood approach (53, 54) applied to on internal validity, we also analyzed mortality using indi- inputs listed in table 2 (see second footnote in table), using vidual-level educational data. All analyses were conducted rank values of the census data, rather than impose arbitrary in SAS (65). transformations to normalize their often considerably skewed distributions; tied values were assigned an average RESULTS rank. We selected the two-factor model as the most appropriate description of the underlying factor structure. Correla- Fully 92.8 percent of the 370,196 mortality and cancer tions between the factors ranged from 0.420 to 0.564 after records for Massachusetts and Rhode Island were success- oblique rotation. Finally, we generated the “SEP index,” a fully geocoded to the census block group level, and 99.6 standardized z score akin to the Townsend index, using percent were geocoded to both the census tract level and the inputs identified by the factor analysis. zip code level. These results were independent of gender, age, race/ethnicity, and, for the mortality data, educational Data analysis level (table 3). The proportion of areas without the specified socioeconomic measures was also low (typically <1 Our analytical plan involved five steps. Step 1 was to percent), considering all measures across all levels of geog- assess the distribution and missingness of data. Step 2 was to raphy in both states (data not shown; available upon request). calculate age-standardized average annual mortality rates Among the total 368,530 records geocoded to the zip code and cancer incidence rates stratified by the area-based socio- level, 23,350 (6.3 percent) could not be linked to 1990 economic measures at each level of geography for each state Census data because their zip codes either were for nonresi- (55, p. 54; 56, p. 263). We standardized for age using the dential areas (e.g., government agencies, businesses with a year 2000 standard million (57) and age-specific rates gener- high mail volume, or post offices and post office boxes) or ated for 11 age groups (<1, 1–4, 5–14, 15–24, …, 75–84, and were created or changed after the 1990 Census. ≥85 years). The numerators and denominators of these rates Table 4 (the full version is available on the World Wide consisted of persons residing in areas identified at the speci- Web at http://www.aje.oupjournals.org) presents results of fied geographic level for which data on the specified area- selected analyses generating and comparing all-cause and based socioeconomic measure were available. Following cause-specific mortality rates and cancer incidence rates, standard practice for rates centered around a census (58, 59), stratified by each area-based socioeconomic measure at each we set the total number of person-years in the denominator level of geography, for each state. Given the similar findings, equal to the population in that socioeconomic stratum we present data for the categorical version of the poverty enumerated in the 1990 Census multiplied by the relevant variable but not the quintile version, for SEP1 but not SEP2, number of years of observation. Cutpoints for categorical for the SEP index but not factor 1 or factor 2, and for death area-based socioeconomic measures (see Appendix at http:// due to diabetes but not death due to unintentional injury www.aje.oupjournals.org) were based on both their percen- (data not shown; available upon request). Patterns of associ- tile distributions (e.g., quintiles) and a priori considerations ation were equivalent for analyses restricted to persons (e.g., the federal definition of “poverty areas” as regions geocoded to all three levels of geography (data not shown; where ≥20 percent of the population lives below the US available upon request). poverty line (60, 61)). As table 4, section a, illustrates, depending on the type of In step 3, we visually inspected and quantified socioeco- mortality and the area-based socioeconomic measure nomic gradients for each outcome using each area-based chosen, estimates of effect comparing Massachusetts socioeconomic measure at each geographic level, excluding mortality rates for persons living in areas with the least persons who were geocoded to areas with no population resources versus persons living in areas with the most (e.g., geocoded to a zip code not included in the 1990 resources ranged from no effect to a substantial effect; Census). Based on clear evidence of linear trends (data not similar patterns were observed at each level of geography. shown; available upon request), we followed standard US For example, across levels of geography, the median value reporting practices (1) and computed the mortality rate ratio, of both the IRR and the RII for all-cause mortality was 1.3– incidence rate ratio (IRR), and incidence rate difference, 1.4, with most measures performing similarly in detecting comparing rates for people living in areas with the least (as expected) associations between higher mortality and resources with rates for people living in areas with the most fewer economic resources (1); the exception was the Gini resources; given similar patterns, we report only the IRR. To coefficient, a measure of income inequality (no gradient take into account both the population distribution of the detected). Similar patterns were evident for Massachusetts exposure and the magnitude of the rate ratio detected in each mortality due to heart disease, malignant neoplasm (albeit

Am J Epidemiol Vol. 156, No. 5, 2002 476 Krieger et al.

TABLE 3. Percentages of deaths and cancer cases geocoded to the census block group, census tract, and zip code levels, Massachusetts and Rhode Island, 1988–1992*

Percent geocoded No. Block group Census tract Zip code Not geocoded

MA† RI† MA RI MA RI MA RI MA RI

Mortality Total 156,366 27,291 93.8 91.1 99.8 95.3 99.9 94.7 0.1 4.7

Gender Men 75,051 13,279 93.9 92.3 99.8 95.9 99.9 95.4 0.1 4.1 Women 81,315 14,012 93.7 90.0 99.8 94.6 99.9 94.1 0.1 5.3

Age (years) <15 1,904 466 92.9 93.6 98.9 96.1 99.3 95.9 0.7 3.9 15–44 9,702 1,490 94.7 93.0 99.5 96.2 99.6 95.9 0.4 3.8 45–64 23,949 4,032 94.4 93.5 99.7 96.5 99.8 96.3 0.2 3.5 ≥65 120,209 21,299 93.6 90.5 99.9 94.9 99.9 94.3 0.1 5.0

Race/ethnicity White, non-Hispanic 147,946 25,883 93.7 91.0 99.8 95.2 99.9 94.6 0.1 4.8 Black, non-Hispanic 5,572 853 96.1 94.1 99.7 97.1 99.7 96.6 0.3 2.9 Other, non-Hispanic‡ 939 152 93.6 93.4 97.8 96.1 97.9 95.4 2.1 3.9 Hispanic 1,908 246 95.3 96.3 98.8 97.2 99.1 97.2 0.9 2.8

Education (among persons aged ≥25 years) 0–11 years 36,285 —§ 93.2 — 99.9 — 99.9 — 0.1 — 12 years 77,454 — 94.3 — 99.9 — 99.9 — 0.1 — ≥13 years 29,935 — 93.1 — 99.7 — 99.8 — 0.2 —

Cancer incidence Total 140,610 19,809 92.4 91.5 100.0 99.8 100.0 99.8 0 0.2

Gender Men 69,334 9,725 92.2 91.6 100.0 99.8 100.0 99.8 0 0.2 Women 71,276 10,084 92.5 91.4 100.0 99.8 100.0 99.8 0 0.2

Age (years) <15 904 90 94.9 90.0 100.0 100.0 100.0 100.0 0 0.0 15–44 12,687 1,599 93.1 92.1 100.0 99.7 100.0 99.7 0 0.3 45–64 41,260 5,227 93.5 92.4 100.0 99.7 100.0 99.7 0 0.3 ≥65 85,759 12,882 91.7 91.1 100.0 99.8 100.0 99.8 0 0.2

Race/ethnicity White, non-Hispanic 131,176 18,789 92.3 91.6 100.0 99.8 100.0 99.8 0 0.2 Black, non-Hispanic 3,716 392 94.0 94.6 100.0 100.0 100.0 100.0 0 0.0 Other, non-Hispanic‡ 1,040 88 95.1 95.5 100.0 100.0 100.0 100.0 0 0.0 Hispanic 842 129 96.3 93.0 100.0 99.2 100.0 99.2 0 0.8

* For both Massachusetts and Rhode Island, mortality data were from 1989–1991; cancer data for Massachusetts were from 1988–1992 and data for Rhode Island were from 1989–1992. † MA, Massachusetts; RI, Rhode Island. ‡ Includes “Asian and Pacific Islander,” “American Indian and Alaska Native,” and groups classified in the US Census as “other.” These ethnic groups together constituted less than 3 percent of the Massachusetts and Rhode Island populations in 1990. § Data not available.

Am J Epidemiol Vol. 156, No. 5, 2002 Geographic Information Systems and Health Inequalities 477

TABLE 4. Rates of all-cause mortality according to area-based socioeconomic measures* (census block group, census tract, and zip code) for persons residing in areas with the least and the most socioeconomic resources, Massachusetts, 1989–1991

Rate for areas with the least Rate for areas with the most Incidence rate ratio for least versus most resources resources Area-based socioeconomic measure BG CT ZC

BG‡ CT‡ ZC‡ BG CT ZC IRR‡ 95% CI‡ IRR 95% CI IRR 95% CI Working class (categories) 929.7 966.6 900.3 718.9 749.8 647.1 1.29 1.23, 1.36 1.29 1.22, 1.36 1.39 1.30, 1.49 Median household income 954.9 1,006.7 927.0 747.9 781.1 698.9 1.28 1.22, 1.34 1.29 1.23, 1.35 1.33 1.26, 1.39 (quintiles) Poverty (categories) 1,030.7 1,060.4 1,070.5 763.3 800.1 766.8 1.35 1.29, 1.42 1.33 1.26, 1.39 1.40 1.32, 1.47 Gini coefficient (quintiles) 865.5 937.1 884.3 840.2 854.9 822.7 1.03 0.98, 1.08 1.10 1.04, 1.15 1.07 1.01, 1.14 Wealth (categories) 834.3 886.1 880.5 703.7 751.1 665.9 1.19 1.13, 1.24 1.18 1.13, 1.23 1.32 1.26, 1.39 Crowding (categories) 1,119.4 1,024.6 944.7 782.7 837.6 803.5 1.43 1.23, 1.67 1.22 1.00, 1.5 1.18 0.69, 2.00 Low education (categories) 962.4 986.6 960.8 752.3 780.4 734.9 1.28 1.22, 1.34 1.26 1.20, 1.33 1.31 1.23, 1.39 Townsend index (quintiles) 1,001.9 1,049.9 938.2 743.2 777.8 733.3 1.35 1.28, 1.42 1.35 1.28, 1.42 1.28 1.21, 1.35 Index of Local Economic 952.5 1,005.9 953.3 726.7 769.8 681.5 1.31 1.25, 1.37 1.31 1.25, 1.37 1.40 1.34, 1.46 Resources (quintiles) SEP1‡ (categories) 1,025.6 1,036.3 1,043.9 687.4 741.7 646.2 1.49 1.38, 1.61 1.40 1.30, 1.51 1.62 1.43, 1.82 SEP index (quintiles) 934.8 1,004.2 934.4 712.1 754.5 672.1 1.31 1.25, 1.38 1.33 1.27, 1.4 1.39 1.33, 1.46 Median value 954.9 1,005.9 938.2 743.2 777.8 698.9 1.31 1.29 1.33

* Average annual age-standardized† rates (per 100,000) and age-adjusted incidence rate ratios. Cutpoints for the measures shown are provided in the Appendix (aje.oupjournals.org). † Age-standardized to the year 2000 standard million (57). ‡ BG, block group; CT, census tract; ZC, zip code; IRR, incidence rate ratio; CI, confidence interval; SEP, socioeconomic position. with a weaker gradient), and diabetes (with a stronger zip code data were in the direction opposite that observed gradient). By contrast, for mortality due to human immuno- using block group and tract socioeconomic data for colon deficiency virus and to homicide and legal intervention, cancer (IRR and RII) and for all sites combined (RII only). measures intended to reflect poverty detected notably larger Visually summarizing key results, figure 2 depicts socio- gradients. For human immunodeficiency virus, estimates economic gradients in all-cause mortality for Massachusetts ranged from no effect (wealth) to a >20-fold effect (RII for by employing the three block group measures that most poverty, Townsend index, and crowding), with a median consistently detected socioeconomic gradients in health IRR between 3 and 4 and a median RII between 5 and 7. For while differently delimiting the population at risk: poverty homicide and legal intervention, estimates ranged from a (single-variable, categorical), SEP1 (composite, categor- twofold effect (IRR for wealth) to a >30-fold effect (RII for ical), and the Townsend index (composite, quintile). poverty, crowding, and Townsend index), with a median IRR between 9 and 11 and a median RII between 22 and 24. DISCUSSION For all outcomes, the precision of the effect estimates was greater for the RII than for the IRR. Findings Analysis of the Rhode Island mortality data (table 4, This study—which to our knowledge was the first system- section c) yielded similar patterns, except that somewhat atic US investigation of area-based socioeconomic measures stronger socioeconomic gradients were apparent both for suitable for monitoring population health and the first that median household income and for all outcomes except homi- simultaneously compared diverse area-based socioeconomic cide and legal intervention. For both states, analyses of measures within and across levels of geography—provided mortality and individual-level education data comparing empirical evidence that both choice of measure and level of persons with a high school education or less with persons geography matter. Specifically, examining mortality and with more than a high school education showed gradients cancer incidence for two New England states during the pointing in the same direction (data not shown; available period around 1990 in conjunction with 1990 US Census upon request). data, we obtained three findings. First, measures designed to Alternatively, for cancer incidence, level of geography detect economic deprivation were most robust, consistently mattered for several of the sites but not all (table 4, sections detecting socioeconomic gradients not only for the leading b and d). For example, census block and tract-level measures causes of death and cancer, as did the other measures, but detected expected socioeconomic gradients (27, 28, 66) for also for deaths due to human immunodeficiency virus and three cancer sites not captured by zip code measures (breast homicide and legal intervention, whose gradients were and prostate cancer in Massachusetts and lung cancer in detected less well or missed by measures of education and Rhode Island). In Massachusetts, gradients detected using wealth. Second, census block group and census tract

Am J Epidemiol Vol. 156, No. 5, 2002 478 Krieger et al.

FIGURE 2. Age-adjusted all-cause mortality rates per 100,000 person-years (y-axes) and incidence rate ratios for mortality (x-axis above each section) according to three socioeconomic measures (top, percent below US poverty line; middle, SEP1; bottom, Townsend index) at the US Census block group level, Massachusetts, 1989–1991. For detailed definitions of measures, see table 2. The width of the bars is proportional to the percentage of the population they contain. IRR, incidence rate ratio; CI, confidence interval; SEP, socioeconomic position. Am J Epidemiol Vol. 156, No. 5, 2002 Geographic Information Systems and Health Inequalities 479 measures performed similarly for virtually all outcomes; zip socioeconomic measures can be meaningfully compared code measures, however, in some cases failed to detect across decennial censuses, a necessary attribute for moni- gradients or detected gradients contrary to those observed toring socioeconomic trends over time (67). with the block group and tract measures. Third, categories Analyses conducted for this first phase of our project did based on quintiles and a priori cutpoints detected similar not take into account either spatial correlation of geographic socioeconomic gradients, but only the latter could be areas (e.g., nesting of block groups within tracts) or issues of uniformly applied across levels of geography within and adjacency (e.g., effects of living in a poor block group adja- across states. cent to chiefly poor block groups versus more affluent block groups). Although use of multilevel models to take into Study limitations account geographic nesting would have improved the precision of our effect estimates, existing literature suggests that Several sources of error and bias could have affected our it would not have substantially changed the estimates them- findings. If, for example, underregistration or misclassifica- selves or the patterns of associations we observed (68–70). tion of cases were either nondifferential with respect to Had the analyses taken into account issues of adjacency, poverty or increased with respect to poverty (66), the net however, different and additional effect estimates might effect would be to underestimate socioeconomic gradients in have been obtained (68–70). The type of aggregation bias the specified outcomes. A conservative bias would also have typically referred to in epidemiologic literature as the occurred if persons subject to socioeconomic deprivation “ecologic fallacy” (71–75) is not germane to the present were less likely to have a geocodable address (12); table 3 study design, since individuals constituted the unit of obser- suggests that our results were unlikely to have been affected vation for both the dependent variables (health outcomes) by this problem. Were such biases operative, however, they and the independent variables (living in an area with certain would have equally affected analyses at each geographic sociodemographic characteristics). Instead, the validity of level and thus would not invalidate comparisons of socioeco- using area-based socioeconomic measures depends on the nomic gradients across socioeconomic measures and across extent to which areas constitute meaningful geographic units levels of geography. Adding further credence to our find- (12, 76)—a different question from whether they are ings, the proportion of areas without data on the area-based “proxies” for individual-level socioeconomic data. socioeconomic measures was so low as to render negligible the impact of these missing data, and we minimized Interpretation and implications geocoding error by using a commercial firm whose accuracy we validated with records from the study’s death and birth The patterning of socioeconomic gradients in health databases (50). detected by the selected area-based socioeconomic measures Additional concerns pertain to the construction of the area- employed in this study, within and across levels of geog- based socioeconomic measures. One controversy centers on raphy and across health outcomes, is likely to reflect both the the benefits and drawbacks of using single-variable different meanings of the areas investigated and the different indicators versus composite indicators—a topic as relevant pathways by which diverse aspects of SEP influence health to individual-level socioeconomic data as to area-based (6, 39, 40, 77). It is notable that almost all measures detected socioeconomic measures (6, 26, 39–42). A related contro- gradients across the full socioeconomic spectrum in the versy pertains to establishing categorical cutpoints for socio- direction expected on the basis of extant literature (1, 3, 66). economic data (6, 26, 39–42). To address these issues The fact that patterns at the block group and tract levels were empirically, we employed a variety of single-variable and largely similar for Massachusetts and Rhode Island but composite socioeconomic measures, using cutpoints based patterns at the zip code level differed within and across these on both percentile distributions and a priori considerations. It states is perhaps not surprising, given that census tract and is notable that several of the single-variable measures, espe- block groups would, by design, be expected to contain more cially those intended to measure poverty, detected the same homogenous populations than zip codes (6, 25). Epidemio- magnitude of socioeconomic inequality in health as the logic studies that have investigated the use of individual- composite measures, and categorical variables based on a based socioeconomic measures versus area-based measures priori cutpoints and quintiles detected gradients of the same have reported similar performance for the block group and magnitude. However, while the a priori cutpoints could be tract measures (or their equivalents) (12, 13, 32, 35, 38, 78– uniformly applied to each level of geography in each state, 83) and inconsistent results for zip code data (32, 35). the data-dependent cutpoints differed by level within and Together, these results underscore the conclusion that addi- across states, rendering comparison of findings across tional effort expended to geocode health data to the tract and regions and geographic levels more problematic. block group level is likely to offset the greater ease of Other caveats pertain to temporal and spatial scale. From obtaining potentially less informative zip code data. an etiologic perspective, misclassification of SEP may occur However, the novel finding that results based on zip codes if SEP at the time of disease diagnosis or death differs from versus tracts and block groups differed chiefly for cancer that at the time of exposure to conditions causing the incidence, not mortality, cannot simply be attributed to level outcome (6, 11). From a monitoring standpoint, however, of geography per se. One speculative explanation is that use of temporally congruent socioeconomic data is appro- exclusion of persons geocoded to zip codes not included in priate for delimiting population distributions of the specified the 1990 Census introduced more of a selection bias in rela- outcomes. It is also notable that all of our study’s area-based tion to SEP for cancer incidence (9.4 percent) than for

Am J Epidemiol Vol. 156, No. 5, 2002 480 Krieger et al. mortality (3.2 percent). The consistent lack of association REFERENCES between the health outcomes and the area-based Gini coeffi- 1. National Center for Health Statistics. Health, United States, cient, in turn, is probably due to the relatively small size of 1998 with socioeconomic status and health chartbook. Hyatts- the geographic areas studied, since, given the realities of ville, MD: National Center for Health Statistics, 1998. (DHHS economic residential segregation in the United States, mean- publication no. (PHS) 98-1232). ingful measurement of income inequality requires analysis 2. Evans T, Whitehead M, Diderichsen F, et al. Challenging ineq- of larger regions (61, 70). Perhaps most importantly, the uities in health: from ethics to action. New York, NY: Oxford University Press, 2001. finding that the single-variable and composite measures 3. Leon D, Walt G, eds. Poverty, inequality, and health: an inter- explicitly capturing aspects of economic impoverishment national perspective. New York, NY: Oxford University Press, consistently detected the sharpest socioeconomic gradients 2001. in health across different specific causes of death and types 4. Berkman L, Kawachi I, eds. Social epidemiology. New York, of cancer underscores the profound impact of material depri- NY: Oxford University Press, 2000. vation on health and the fundamental necessity of evaluating 5. Krieger N, Chen JT, Ebel G. Can we monitor socioeconomic area-based socioeconomic measures across more than just inequalities in health? A survey of U.S. health departments’ data collection and reporting practices. Public Health Rep one or two outcomes. 1997;112:481–91. In conclusion, drawing on our a priori criteria pertaining to 6. Krieger N, Williams D, Moss N. Measuring social class in US external validity, robustness, completeness, and user-friend- public health research: concepts, methodologies and guidelines. liness, along with Rossi and Gilmartin’s (85) criteria for Annu Rev Public Health 1997;18:341–78. valid and useful social indicators—that they be 1) conceptu- 7. Tolson GC, Barnes JM, Gay GA, et al. The 1989 revision of the U.S. standard certificates and reports. Hyattsville, MD: ally based; 2) constructed from valid, reliable, and accessible National Center for Health Statistics, 1991. (Vital and health data using appropriate statistical techniques; 3) comparable statistics, series 1, no. 28) (DHHS publication no. PHS 91- over time and across population groups; and 4) readily 1465). understandable, with normative value relevant to timely 8. Whitney JS, ed. Death rates by occupation based on data of the policy making—we offer a tentative recommendation, U.S. Census Bureau 1930. New York, NY: National Tuberculo- pending our analyses of additional data from public health sis Association, 1934. 9. Krieger N, Fee E. Measuring social inequalities in health in the surveillance systems. Specifically, our findings suggest that United States: an historical review, 1900–1950. Int J Health efforts to monitor US socioeconomic inequalities in health Serv 1996;26:391–418. using area-based socioeconomic measures will be best 10. Public Health Service, US Department of Health and Human served by those tract or block group measures that are Services. Healthy People 2010 (conference edition, in two vol- 1) most attuned to capturing economic deprivation, 2) mean- umes). Washington, DC: US GPO, 2000. (http:// ingful across regions and over time, and 3) easily under- www.health.gov/healthypeople). [Last accessed June 10, 2001]. stood, and hence based on readily interpretable variables 11. Krieger N, Zierler S, Hogan JW, et al. Geocoding and measure- with a priori categorical cutpoints. One likely candidate ment of neighborhood socioeconomic position. In: Kawachi I, meeting all of these criteria is the measure “percentage of Berkman LF, eds. Neighborhoods and health. New York, NY: persons living below the US poverty line.” Oxford University Press (in press). 12. Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health 1992;82:703–10. ACKNOWLEDGMENTS 13. Krieger N. Women and social class: a methodological study comparing individual, household, and census measures as pre- This work was funded by grant 1 R01 HD36865-01 from dictors of black/white differences in reproductive history. J the National Institute of Child Health and Human Develop- Epidemiol Community Health 1991;45:35–42. 14. Carstairs V, Morris R. Deprivation and mortality: an alternative ment (Principal Investigator, Dr. Nancy Krieger). to social class? Community Med 1989;11:210–19. The authors thank Drs. Daniel Friedman (Bureau of Health 15. Sorensen A. Women, family, and class. Annu Rev Sociol 1994; Statistics, Research and Evaluation, Massachusetts Depart- 20:27–47. ment of Health) and Jay Buechner (Office of Health Statis- 16. Watkins RJ. Introduction. In: Watkins RJ, Swift AL Jr, Green tics, Rhode Island Department of Health) for facilitating the HW, et al. Golden anniversary of census tracts, 1956. Washing- use of health department data in the conduct of this study and ton, DC: American Statistical Association, 1956:1–2. 17. Nathan WB. Health conditions in North Harlem 1923–1927. for their helpful comments. The authors likewise thank the New York, NY: National Tuberculosis Association, 1932. following health department staff for supplying mortality 18. Green HW. Tuberculosis and economic strata, Cleveland’s and cancer registry data: Massachusetts Department of Five-City Area, 1928–1931. Cleveland, OH: Anti-Tuberculosis Public Health—Alice Mroszczyk; Cancer Registry: Dr. League, 1932. Susan Gershman, Mary Mroszczyk, and Ann R. MacMillan; 19. Green HW. Infant mortality and economic status, Cleveland Registry of Vital Records and Statistics: Elaine Trudeau and Five-City Area. Cleveland, OH: Cleveland Health Council, 1939. Charlene Zion; Rhode Island Department of Health—Vital 20. Terris M. Relation of economic status to tuberculosis mortality Statistics: Roberta Chevoya; Division of Disease Prevention by age and sex. Am J Public Health 1948;38:1061–70. and Control: Dr. John Fulton. 21. Cohart EM. Socioeconomic distribution of stomach cancer in

Am J Epidemiol Vol. 156, No. 5, 2002 Geographic Information Systems and Health Inequalities 481

New Haven. Cancer 1954;8:455–61. and validation. J Epidemiol Community Health 1995;49(suppl 22. Sheps C, Watkins JH. Mortality in the socio-economic districts 2):S39–44. of New Haven. Yale J Biol Med 1947-48;20:51–80. 41. Townsend P, Phillimore P, Beattie A. Health and deprivation: 23. Richards TB, Croner CM, Rushton G, et al. Geographic infor- inequality and the North. London, United Kingdom: Croom mation systems and public health: mapping the future. Public Helm, 1988. Health Rep 1999;114:359–73. 42. Carstairs V. Deprivation indices: their interpretation and use in 24. Moore DA, Carpenter TE. Spatial analytical methods and geo- relation to health. J Epidemiol Community Health 1995; graphic information systems: use in health research and epide- 49(suppl 2):S3–8. miology. Epidemiol Rev 1999;21:143–61. 43. Krieger N. Theories for social epidemiology for the 21st cen- 25. Bureau of the Census, US Department of Commerce. Geo- tury: an ecosocial perspective. Int J Epidemiol 2001;30:668–77. graphical areas reference manual. Washington, DC: Bureau of 44. Bureau of the Census, US Department of Commerce. American the Census, 1994. (http://www.census.gov/geo/www/ fact finder. Massachusetts. Washington, DC: Bureau of the garm.html). [Last accessed June 28, 2001]. Census, 2001. (http://factfinder.census.gov/bf/_lang=en_vt_ 26. Lynch J, Kaplan G. Socioeconomic position. In: Berkman L, name=DEC_2000_SF1_U_DP1_geo_id=04000US25.html). Kawachi I, eds. Social epidemiology. New York, NY: Oxford [Last accessed August 30, 2001]. University Press, 2000:13–35. 45. Bureau of the Census, US Department of Commerce. American 27. Krieger N, Quesenberry C Jr, Peng T, et al. Social class, race/ fact finder. Rhode Island. Washington, DC: Bureau of the Cen- ethnicity, and incidence of breast, cervix, colon, lung, and pros- sus, 2001. (http://factfinder.census.gov/servlet/BasicFactsTable?_ tate cancer among Asian, black, Hispanic, and white residents lang=enand_vt_name=DEC_1990_STF1_DP1and_geo_ of the San Francisco Bay Area, 1988–1992 (USA). Cancer id=04000US44). [Last accessed August 30, 2001]. Causes Control 1999;10:525–37. 46. Health Care Financing Administration, US Department of 28. Liu L, Deapen D, Bernstein L. Socioeconomic status and can- Health and Human Services. International classification of dis- cers of the female breast and reproductive organs: a comparison eases, ninth revision, clinical modification (ICD-9-CM). (Com- across racial/ethnic populations in Los Angeles County, Cali- puter file). 6th ed. Washington, DC: Health Care Financing fornia (United States). Cancer Causes Control 1998;9:369–80. Administration, 2000. 29. Ellen JM, Kohn RP, Bolan GA, et al. Socioeconomic differ- 47. National Cancer Institute. SEER cancer statistics review, 1973– ences in sexually transmitted disease rates among black and 1999. Bethesda, MD: National Cancer Institute, 2001. (http:// white adolescents, San Francisco, 1990 to 1992. Am J Public www.seer.cancer.gov/csr/1973_1999). [Last accessed July 11, Health 1995;85:1546–8. 2001]. 30. Chen FM, Breiman RF, Farley M, et al. Geocoding and linking 48. Bureau of the Census, US Department of Commerce. Census of data from population-based surveillance and the US Census to population and housing, 1990. Summary Tape File 3 technical evaluate the impact of median household income on the epide- documentation. (http://www.census.gov/td/stf3/contents/html). miology of invasive Streptococcus pneumoniae infections. Am Washington, DC: Bureau of the Census, 1991. J Epidemiol 1998;148:1212–18. 49. Bureau of the Census, US Department of Commerce. Geo- 31. Wissow LS, Gittelsohn AM, Szklo M, et al. Poverty, race, and graphic changes for Census 2000 + glossary. Washington, DC: hospitalization for childhood asthma. Am J Public Health 1988; Bureau of the Census, 2001. (http://www.census.gov/geo/ 78:777–82. www/tiger/glossary.html). [Last accessed July 3, 2001]. 32. Geronimus AT, Bound J. Use of census-based aggregate vari- 50. Krieger N, Waterman P, Lemieux K, et al. On the wrong side of ables to proxy for socioeconomic group: evidence from the tracts? Evaluating accuracy of geocoding for public health national samples. Am J Epidemiol 1998;48:475–86. research. Am J Public Health 2001;91:1114–16. 33. Smith GD, Neaton JD, Wentworth D, et al. Socioeconomic dif- 51. Council of Economic Advisors for the President’s Initiative on ferentials in mortality among men screened for the Multiple Race. Changing America: indicators of social and economic Risk Factor Intervention Trial: I. white men. Am J Public well-being by race and Hispanic origin. Washington, DC: US Health 1996;86:486–96. GPO, 1998. (http://www.access.gpo.gov/eop/ca/index.html). 34. Smith GD, Wentworth D, Neaton JD, et al. Socioeconomic dif- [Last accessed May 15, 2000]. ferentials among men screened for the Multiple Risk Factor 52. Casper ML, Barnett E, Halverson JA, et al. Women and heart Intervention Trial: II. black men. Am J Public Health 1996;86: disease: an atlas of racial and ethnic disparities in mortality. 497–504. Morgantown, WV: Office for Social Environment and Health 35. Geronimus AT, Bound J, Neidert LJ. On the validity of using Research, West Virginia University, 1999. census geocode data to proxy individual socioeconomic charac- 53. Lawley DN, Maxwell AE. Factor analysis as a statistical teristics. J Am Stat Assoc 1996;91:529–37. method. New York, NY: Macmillan Publishing Company, 36. Roberts EM. Neighborhood social environments and the distri- 1971. bution of low birthweight in Chicago. Am J Public Health 54. Bartholomew DJ. Latent variable models and factor analysis. 1997;87:597–603. London, United Kingdom: Charles Griffin and Company, 1987. 37. Diez-Roux AV, Merkin SS, Arnett D, et al. Neighborhood of 55. Breslow NE, Day NE, eds. Statistical methods in cancer residence and incidence of coronary heart disease. N Engl J research. Vol 2. The design and analysis of cohort studies. Med 2001;345:99–106. (IARC Scientific Publication no. 82). Lyon, France: Interna- 38. Cherkin DC, Grothaus L, Wagner EH. Is magnitude of co-pay- tional Agency for Research on Cancer, 1987. ment effect related to income? Using census data for health ser- 56. Rothman KJ, Greenland S. Modern epidemiology. 2nd ed. Phil- vices research. Soc Sci Med 1992;34:33–41. adelphia, PA: Lippincott-Raven, 1998. 39. Lee P, Murie A, Gordon D. Area measures of deprivation: a 57. Anderson RN, Rosenberg HM. Age standardization of death study of current methods and best practices in the identification rates: implementation of the year 2000 standard. Hyattsville, of poor areas in Great Britain. Birmingham, United Kingdom: MD: National Center for Health Statistics, 1998. (National vital Centre for Urban and Regional Studies, University of Birming- statistics reports, vol 37, no. 3). ham, 1995. 58. Breslow NE, Day NE. Statistical methods in cancer research. 40. Gordon D. Census based deprivation indices: their weighting Vol 1. The analysis of case-control studies. (IARC Scientific

Am J Epidemiol Vol. 156, No. 5, 2002 482 Krieger et al.

Publication no. 32). Lyon, France: International Agency for 74. Robinson WS. Ecological correlations and the behavior of indi- Research on Cancer, 1980:47. viduals. Am Sociol Rev 1950;15:351–7. 59. Boyle P, Parkin DM. Statistical methods for registries. In: 75. Langbein LI, Lichtman AJ. Ecological inference. Beverly Hills, Jensen OM, Parkin DM, MacLennan R, et al, eds. Cancer reg- CA: Sage Publications, 1978:27–8. istration: principles and methods. (IARC Scientific Publication 76. Oppenshaw S, Taylor PJ. The modifiable areal unit problem. no. 95). Lyon, France: International Agency for Research on In: Wrigley N, Bennett RJ, eds. Quantitative geography. Lon- Cancer, 1991:126–58. don, United Kingdom: Routledge and Kegan Paul, 1981:60–9. 60. Bureau of the Census, US Department of Commerce. Poverty 77. Smith GD, Whitley E, Dorling D, et al. Area based measures of areas. Washington, DC: Bureau of the Census, 2001. (http:// social and economic circumstances: cause specific mortality www.census.gov/population/socdemo/statbriefs/povarea.html). patterns depend on the choice of index. J Epidemiol Commu- [Last accessed October 8, 2001]. nity Health 2001;55:149–50. 61. Jargowsky PA. Poverty and place: ghettos, barrios, and the 78. Greenwald JP, Polissar NL, Borgatta EF, et al. Detecting sur- American city. New York, NY: Russell Sage Foundation, 1997. vival effects of socioeconomic status: problems in the use of 62. Pamuk ER. Social class inequality in mortality from 1921 to aggregate data. J Clin Epidemiol 1994;47:903–9. 1972 in England and Wales. Popul Stud 1985;39:17–31. 79. Carr-Hill R, Rice N. Is enumeration district level an improve- 63. Wagstaff A, Paci P, van Doorslaer E. On the measurement of ment on ward level analysis in studies of deprivation and inequalities in health. Soc Sci Med 1991;33:545–57. health? J Epidemiol Community Health 1995;49(suppl 2): 64. Davey Smith G, Hart C, Hole D, et al. Education and occupa- S28–9. tional social class: which is the more important indicator of 80. Mustard CA, Derksen S, Berthelot JM, et al. Assessing eco- mortality risk? J Epidemiol Community Health 1998;52:153– logic proxies for household income: a comparison of household 60. and neighbourhood level income measures in the study of pop- 65. SAS Institute, Inc. SAS/STAT user’s guide, version 6. 4th ed. ulation health status. Health Place 1999;5:157–71. Vol 1. Cary, NC: SAS Institute, Inc, 1989. 81. Reijneveld SA, Verheij RA, de Bakker DH. The impact of area 66. Kogevinas M, Pearce N, Susser M, et al, eds. Social inequalities deprivation on differences in health: does the choice of the geo- in cancer. Lyon, France: International Agency for Research on graphical classification matter? J Epidemiol Community Health Cancer, 1997. (IARC Scientific Publication no. 136). 2000;54:306–13. 67. Gordon D, Spicker P, eds. The international glossary of poverty. (CROP International Series on Poverty). London, United 82. Hyndman JC, D’Arcy D, Holman J, et al. Misclassification of Kingdom: Zed Books, 1999. social disadvantage based on geographical areas: comparison of 68. Subramanian SV, Duncan C, Jones K. Multilevel perspectives postcode and collector’s districts analyses. Int J Epidemiol on modeling census data. Environment and Planning A 2001; 1995;24:165–76. 33:399–417. 83. Diez-Roux AV, Kiefe CI, Jacobs DR Jr, et al. Area characteris- 69. Duncan C, Jones K, Moon G. Context, composition and hetero- tics and individual-level socioeconomic position indicators in geneity: using multilevel models in health research. Soc Sci three population-based epidemiologic studies. Ann Epidemiol Med 1998;46:97–117. 2001;11:395–405. 70. Soobader M, LeClere FB. Aggregation and the measurement of 84. Rossi RJ, Gilmartin KJ. The handbook of social indicators: income inequality, effects on morbidity. Soc Sci Med 1999;48: sources, characteristics, and analysis. New York, NY: Garland 733–44. STPM Press, 1980. 71. Alker HR Jr. A typology of ecologic fallacies. In: Doggan M, 85. Bureau of the Census, US Department of Commerce. Cen- Rokkan S, eds. Social ecology. Cambridge, MA: MIT Press, sus geography. Washington, DC: Bureau of the Census, 1969:69–86. 2001. (http://factfinder.census.gov/home/en/epss/census_ 72. Diez-Roux AV. Bringing context back into epidemiology: vari- geography.html). [Last accessed May 29, 2001]. ables and fallacies in multilevel analysis. Am J Public Health 86. Kennedy BP, Kawachi I, Prothrow-Stith D. Income distribution 1998;88:216–22. and mortality: cross sectional ecological study of the Robin 73. Macintyre S, Ellaway A. Ecological approaches: rediscovering Hood index in the United States. BMJ 1996;312:1004–7. the role of the physical and social environment. In: Berkman L, 87. Cowell FA. Measuring inequality. 2nd ed. (LSE Handbooks in Kawachi I, eds. Social epidemiology. New York, NY: Oxford Economics series). London, United Kingdom: Prentice Hall, University Press, 2000:332–48. 1995.

Am J Epidemiol Vol. 156, No. 5, 2002 Geocoding and Monitoring of US Socioeconomic Inequalities in Mortality and Cancer Incidence: Does the Choice of Area-based Measure and Geographic Level Matter? The Public Health Disparities Geocoding Project Nancy Krieger, Jarvis T. Chen, Pamela D. Waterman, Mah-Jabeen Soobader, S. V. Subramanian, and Rosa Carson

From the Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA.

TABLE 4. Mortality and cancer incidence rates stratified according to area-based socioeconomic measures* (census block group, census tract, and zip code) for persons residing in areas with the least and the most socioeconomic resources, Massachusetts and Rhode Island, 1988-1992†,‡

Section a: Massachusetts mortality (1989-1991)

Rate for areas with the least Rate for areas with the most Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Mortality Area-based socioeconomic resources resources interval) interval) outcome measure BG§ CT§ ZC§ BG CT ZC BG CT ZC BG CT ZC All causes Working class (categories) 929.7 966.6 900.3 718.9 749.8 647.1 1.29 (1.23, 1.36) 1.29 (1.22, 1.36) 1.39 (1.30, 1.49) 1.33 (1.31, 1.36) 1.29 (1.27, 1.32) 1.43 (1.40, 1.46)

Median household income (quintiles) 954.9 1,006.7 927.0 747.9 781.1 698.9 1.28 (1.22, 1.34) 1.29 (1.23, 1.35) 1.33 (1.26, 1.39) 1.28 (1.25, 1.30) 1.34 (1.31, 1.36) 1.39 (1.36, 1.41)

Poverty (categories) 1,030.7 1,060.4 1,070.5 763.3 800.1 766.8 1.35 (1.29, 1.42) 1.33 (1.26, 1.39) 1.40 (1.32, 1.47) 1.39 (1.36, 1.41) 1.37 (1.35, 1.40) 1.40 (1.38, 1.43) Gini coefficient (quintiles) 865.5 937.1 884.3 840.2 854.9 822.7 1.03 (0.98, 1.08) 1.10 (1.04, 1.15) 1.07 (1.01, 1.14) 1.03 (1.01, 1.04) 1.13 (1.11, 1.15) 1.14 (1.12, 1.16) Wealth (categories) 834.3 886.1 880.5 703.7 751.1 665.9 1.19 (1.13, 1.24) 1.18 (1.13, 1.23) 1.32 (1.26, 1.39) 1.33 (1.30, 1.37) 1.26 (1.23, 1.28) 1.45 (1.42, 1.48) Crowding (categories)‡ 1,119.4 1,024.6 944.7 782.7 837.6 803.5 1.43 (1.23, 1.67) 1.22 (1.00, 1.50) 1.18 (0.69, 2.00) 1.64 (1.60, 1.69) 1.63 (1.59, 1.68) 1.67 (1.63, 1.72) Low education (categories) 962.4 986.6 960.8 752.3 780.4 734.9 1.28 (1.22, 1.34) 1.26 (1.20, 1.33) 1.31 (1.23, 1.39) 1.33 (1.30, 1.35) 1.36 (1.34, 1.39) 1.41 (1.39, 1.44) Townsend index (quintiles) 1,001.9 1,049. 9 938.2 743.2 777.8 733.3 1.35 (1.28, 1.42) 1.35 (1.28, 1.42) 1.28 (1.21, 1.35) 1.45 (1.42, 1.47) 1.40 (1.38, 1.42) 1.40 (1.37, 1.42) Index of Local Economic Resources 952.5 1,005.9 953.3 726.7 769.8 681.5 1.31 (1.25, 1.37) 1.31 (1.25, 1.37) 1.40 (1.34, 1.46) 1.33 (1.31, 1.36) 1.35 (1.33, 1.38) 1.46 (1.43, 1.48) (quintiles) SEP1§ (categories) 1,025.6 1,036.3 1,043.9 687.4 741.7 646.2 1.49 (1.38, 1.61) 1.40 (1.30, 1.51) 1.62 (1.43, 1.82) 1.45 (1.42, 1.48) 1.38 (1.36, 1.41) 1.52 (1.49, 1.55) SEP index (quintiles) 934.8 1,004.2 934.4 712.1 754.5 672.1 1.31 (1.25, 1.38) 1.33 (1.27, 1.40) 1.39 (1.33, 1.46) 1.36 (1.34, 1.39) 1.36 (1.34, 1.38) 1.45 (1.42, 1.48) Median value 1,005.9 938.2 743.2 777.8 698.9 1.31 1.29 1.33 1.33 1.36 1.43 Working class (categories) 315.0 332.9 314.1 226.7 235.6 202.7 1.39 (1.28, 1.51) 1.41 (1.28, 1.56) 1.55 (1.37, 1.75) 1.43 (1.39, 1.48) 1.39 (1.35, 1.44) 1.52 (1.47, 1.57)

Median household income (quintiles) 309.8 326.3 304.0 242.2 251.7 226.9 1.28 (1.18, 1.39) 1.30 (1.19, 1.41) 1.34 (1.23, 1.46) 1.28 (1.24, 1.32) 1.35 (1.31, 1.39) 1.37 (1.33, 1.42)

Poverty (categories) 334.2 346.3 335.1 250.7 264.2 253.8 1.33 (1.23, 1.45) 1.31 (1.20, 1.43) 1.32 (1.20, 1.45) 1.38 (1.34, 1.43) 1.36 (1.32, 1.40) 1.35 (1.31, 1.40) Gini coefficient (quintiles) 278.3 296.4 283.7 282.1 290.7 282.6 0.99 (0.90, 1.08) 1.02 (0.94, 1.11) 1.00 (0.90, 1.12) 0.97 (0.94, 1.00) 1.06 (1.02, 1.09) 1.05 (1.01, 1.08) Wealth (categories) 280.3 297.6 296.1 218.8 231.3 208.5 1.28 (1.18, 1.39) 1.29 (1.19, 1.40) 1.42 (1.31, 1.54) 1.52 (1.46, 1.58) 1.42 (1.37, 1.48) 1.62 (1.56, 1.69) Crowding (categories)‡ 340.7 263.7 239.2 260.1 277.9 267.1 1.31 (0.99, 1.74) 0.95 (0.63, 1.42) 0.90 (0.31, 2.57) 1.52 (1.45, 1.59) 0.65 (0.62, 0.68) 0.64 (0.61, 0.67) Heart disease Low education (categories) 318.6 333.4 320.4 245.1 251.7 238.0 1.30 (1.19, 1.42) 1.32 (1.21, 1.45) 1.35 (1.21, 1.49) 1.37 (1.32, 1.41) 1.46 (1.41, 1.50) 1.50 (1.45, 1.55) Townsend index (quintiles) 322.6 338.2 306.2 248.1 256.7 239.9 1.30 (1.19, 1.42) 1.32 (1.21, 1.44) 1.28 (1.16, 1.40) 1.40 (1.36, 1.45) 1.37 (1.33, 1.41) 1.37 (1.32, 1.41)

Index of Local Economic Resources 311.7 331.9 313.2 235.3 248.0 217.6 1.32 (1.22, 1.44) 1.34 (1.23, 1.46) 1.44 (1.33, 1.56) 1.37 (1.33, 1.41) 1.40 (1.36, 1.45) 1.50 (1.45, 1.54) (quintiles) SEP1 (categories) 344.1 352.4 365.7 214.4 230.4 202.9 1.60 (1.40, 1.84) 1.53 (1.34, 1.74) 1.80 (1.47, 2.21) 1.58 (1.53, 1.63) 1.52 (1.47, 1.57) 1.59 (1.54, 1.65) SEP index (quintiles) 313.1 335.4 310.6 228.3 238.3 213.9 1.37 (1.26, 1.49) 1.41 (1.29, 1.53) 1.45 (1.34, 1.58) 1.43 (1.39, 1.48) 1.44 (1.40, 1.49) 1.50 (1.46, 1.55) Median value 315.0 332.9 310.6 242.2 251.7 226.9 1.31 1.32 1.35 1.40 1.39 1.50 Malignant neoplasm Working class (categories) 224.0 230.7 216.8 193.9 204.0 178.5 1.16 (1.05, 1.27) 1.13 (1.01, 1.26) 1.21 (1.06, 1.40) 1.18 (1.14, 1.23) 1.14 (1.10, 1.19) 1.26 (1.21, 1.30)

Median household income (quintiles) 227.7 235.0 219.3 200.8 210.5 189.9 1.13 (1.03, 1.25) 1.12 (1.01, 1.23) 1.16 (1.05, 1.27) 1.11 (1.07, 1.15) 1.15 (1.11, 1.19) 1.19 (1.15, 1.23)

Poverty (categories) 236.4 239.6 238.9 203.5 212.5 205.1 1.16 (1.05, 1.28) 1.13 (1.02, 1.25) 1.17 (1.04, 1.30) 1.17 (1.13, 1.21) 1.16 (1.12, 1.20) 1.17 (1.13, 1.22) Gini coefficient (quintiles) 215.3 227.7 217.5 218.5 218.8 214.2 0.99 (0.89, 1.09) 1.04 (0.94, 1.15) 1.02 (0.90, 1.14) 0.99 (0.96, 1.03) 1.05 (1.02, 1.09) 1.05 (1.02, 1.09) Wealth (categories) 211.4 223.3 221.5 192.9 206.5 180.8 1.10 (1.00, 1.20) 1.08 (0.99, 1.18) 1.22 (1.12, 1.34) 1.16 (1.11, 1.21) 1.12 (1.07, 1.17) 1.30 (1.25, 1.36) Crowding (categories)‡ 252.0 256.0 253.9 204.1 217.6 209.0 1.23 (0.89, 1.71) 1.18 (0.78, 1.78) 1.21 (0.42, 3.49) 1.36 (1.29, 1.44) 1.25 (1.18, 1.32) 1.32 (1.25, 1.39) Low education (categories) 219.7 226.9 220.7 202.1 208.8 194.9 1.09 (0.98, 1.20) 1.09 (0.97, 1.21) 1.13 (1. 00, 1.28) 1.13 (1.09, 1.17) 1.15 (1.11, 1.20) 1.22 (1.18, 1.27) Townsend index (quintiles) 236.0 243.2 229.3 194.9 203.6 197.9 1.21 (1.10, 1.34) 1.19 (1.08, 1.32) 1.16 (1.04, 1.29) 1.28 (1.24, 1.33) 1.22 (1.18, 1.26) 1.22 (1.18, 1.27) Index of Local Economic Resources 228.4 231.8 225.0 196.5 207.7 186.5 1.16 (1.06, 1.28) 1.12 (1.01, 1.23) 1.21 (1.10, 1.32) 1.16 (1.12, 1.20) 1.15 (1.11, 1.19) 1.24 (1.20, 1.29) (quintiles) SEP1 (categories) 226.7 235.9 222.4 191.7 204.1 178.5 1.18 (1.01, 1.39) 1.16 (0.99, 1.35) 1.25 (0.96, 1.61) 1.22 (1.18, 1.27) 1.15 (1.11, 1.19) 1.29 (1.23, 1.34) SEP index (quintiles) 222.6 230.9 223.7 195.1 206.3 185.1 1.14 (1.04, 1.26) 1.12 (1.01, 1.24) 1.21 (1.10, 1.32) 1.17 (1.13, 1.22) 1.15 (1.11, 1.19) 1.24 (1.20, 1.28) Median value 226.7 231.8 222.4 196.5 207.7 189.9 1.16 1.12 1.21 1.17 1.15 1.24

Section a (continued)

Rate for areas with the Rate for areas with the Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Mortality Area-based least resources most resources interval) interval) outcome socioeconomic measure BG CT ZC BG CT ZC BG CT ZC BG CT ZC Working class (categories) 24.1 26.6 24.2 15.3 15.4 12.5 1.57 (1.14, 2.17) 1.73 (1.21, 2.49) 1.94 (1.24, 3.06) 1.71 (1.51, 1.93) 1.71 (1.52, 1.92) 1.84 (1.63, 2.08)

Median household income (quintiles) 23.7 25.1 23.6 15.6 16.3 14.4 1.52 (1.10, 2.10) 1.53 (1.11, 2.11) 1.64 (1.19, 2.26) 1.63 (1.45, 1.84) 1.64 (1.46, 1.83) 1.73 (1.54, 1.94)

Poverty (categories) 26.2 26.6 25.0 17.1 18.7 16.9 1.54 (1.13, 2.08) 1.42 (1.04, 1.94) 1.48 (1.03, 2.12) 1.73 (1.53, 1.95) 1.52 (1.36, 1.71) 1.65 (1.46, 1.86) Gini coefficient (quint iles) 20.6 21.7 20.2 19.8 20.9 20.6 1.04 (0.75, 1.44) 1.03 (0.75, 1.42) 0.98 (0.66, 1.46) 1.04 (0.93, 1.17) 1.01 (0.90, 1.14) 0.93 (0.83, 1.04) Wealth (categories) 20.6 22.1 22.0 14.0 15.0 12.6 1.48 (1.06, 2.05) 1.47 (1.07, 2.02) 1.74 (1.25, 2.44) 1.77 (1.51, 2.08) 1.64 (1.42, 1.89) 1.99 (1.73, 2.30) Crowding (categories)‡ 34.1 21.2 22.2 18.5 19.9 19.3 1.84 (0.76, 4.46) 1.07 (0.28, 4.12) 1.15 (0.04, 34.56) 2.06 (1.74, 2.43) 1.97 (1.66, 2.34) 1.64 (1.38, 1.95) Diabetes Low education (categories) 26.4 26.9 27.9 16.8 17.5 16.7 1.57 (1.15, 2.13) 1.54 (1.11, 2.14) 1.67 (1.16, 2.40) 1.65 (1.47, 1.87) 1.64 (1.45, 1.84) 1.63 (1.44, 1.83) Townsend index (quintiles) 25.3 27.4 23.2 17.0 17.1 15.1 1.49 (1.08, 2.05) 1.60 (1.16, 2.20) 1.54 (1.06, 2.24) 1.65 (1.47, 1.85) 1.64 (1.46, 1.83) 1.64 (1.46, 1.85)

Index of Local Economic Resources 24.2 26.3 24.2 15.2 16.0 13.8 1.59 (1.17, 2.17) 1.65 (1.20, 2.25) 1.75 (1.29, 2.37) 1.67 (1.48, 1.87) 1.69 (1.51, 1.90) 1.78 (1.59, 2.00) (quintiles)

SEP1 (categories) 27.5 28.9 28.2 13.2 14.6 12.2 2.09 (1.26, 3.48) 1.98 (1.22, 3.19) 2.31 (1.10, 4.84) 1.92 (1.69, 2.18) 1.88 (1.65, 2.13) 2.00 (1.75, 2.29) SEP index (quintiles) 23.3 25.9 23.5 14.3 15.7 13.4 1.63 (1.17, 2.27) 1.65 (1.20, 2.28) 1.76 (1.27, 2.43) 1.75 (1.55, 1.97) 1.71 (1.52, 1.92) 1.81 (1.61, 2.04) Median value 24.2 26.3 23.6 15.6 16.3 14.4 1.57 1.54 1.67 1.71 1.64 1.73 Human Working class (categories) 10.7 12.3 9.8 7.4 8.4 6.4 1.44 (0.89, 2.34) 1.46 (0.87, 2.46) 1.51 (0.74, 3.11) 1.55 (1.28, 1.88) 1.48 (1.22, 1.79) 1.89 (1.55, 2.30) immunodeficiency virus Median household income (quintiles) 18.7 21.4 17.6 3.2 3.6 2.3 5.85 (3.37, 10.15) 5.98 (3.55, 10.08) 7.61 (3.93, 14.73) 9.02 (7.37, 11.05) 11.41 (9.33, 13.96) 14.01 (11.29, 17.39)

Poverty (categories) 23.9 27.8 32.8 3.7 3.5 2.9 6.43 (4.23, 9.76) 8.02 (5.21, 12.35) 11.41 (7.07, 18.42) 15.70 (12.75, 19.32) 22.03 (17.82, 27.22) 31.51 (25.16, 39.48) Gini coefficient (quintiles) 15.9 21.8 17.9 3.5 3.4 2.8 4.57 (2.57, 8.09) 6.37 (3.76, 10.79) 6.40 (2.94, 13.93) 6.48 (5.30, 7.92) 13.44 (10.91, 16.56) 16.66 (13.30, 20.88) Wealth (categories) 7.0 7.3 7.6 8.9 11.3 11.8 0.78 (0.51, 1.20) 0.65 (0.44, 0.95) 0.64 (0.44, 0.94) 0.97 (0.76, 1.24) 0.67 (0.54, 0.84) 0.74 (0.60, 0.91) Crowding (categories)‡ 15.6 23.0 36.3 5.5 5.8 5.2 2.83 (0.98, 8.20) 3.96 (1.21, 13.04) 6.95 (4.05, 11.91) 15.89 (12.88, 19.60) 19.89 (16.17, 24.47) 26.32 (21.45, 32.30) Low education (categories) 15.9 14.8 17.2 5.0 5.4 4.6 3.19 (2.00, 5.07) 2.75 (1.66, 4.56) 3.73 (2.14, 6.51) 4.39 (3.62, 5.34) 3.94 (3.26, 4.76) 5.66 (4.65, 6.89) Townsend index (quintiles) 24.8 28.3 16.9 2.9 2.7 2.2 8.70 (4.74, 15.96) 10.38 (5.79, 18.61) 7.84 (3.22, 19.10) 30.61 (24.23, 38.66) 28.76 (23.00, 35.97) 23.03 (18.00, 29.46)

Index of Local Economic Resources (quintiles) 15.6 18.4 16.7 5.2 5.6 4.6 3.02 (1.89, 4.81) 3.25 (2.07, 5.12) 3.62 (2.26, 5.79) 4.59 (3.78, 5.58) 5.05 (4.18, 6.11) 6.59 (5.40, 8.04) SEP1 (categories) 17.6 18.0 16.7 6.9 8.4 6.7 2.54 (1.31, 4.90) 2.13 (1.15, 3.92) 2.49 (0.91, 6.84) 2.88 (2.33, 3.56) 2.68 (2.17, 3.30) 2.55 (2.05, 3.16) SEP index (quintiles) 15.2 18.2 14.9 5.0 6.0 4.9 3.05 (1.86, 5.00) 3.06 (1.93, 4.84) 3.02 (1.84, 4.95) 5.18 (4.21, 6.37) 4.49 (3.70, 5.45) 6.20 (5.07, 7.60) Median value 15.9 18.4 16.9 5.0 5.6 4.6 3.05 3.25 3.73 5.18 5.05 6.59 Working class (categories) 8.2 9.3 5.7 1.6 1.4 1.2 5.23 (2.25, 12.14) 6.48 (2.53, 16.62) 4.92 (1.44, 16.78) 8.96 (6.63, 12.11) 10.64 (7.88, 14.37) 9.60 (7.09, 13.00)

Median household incom e (quintiles) 9.6 10.5 8.3 0.9 1.0 0.8 10.90 (3.95, 30.08) 10.30 (4.03, 26.34) 10.30 (3.33, 31.82) 19.77 (14.25, 27.43) 23.55 (16.95, 32.71) 22.91 (16.25, 32.31)

Poverty (categories) 12.8 13.9 15.2 1.4 1.1 1.1 8.86 (4.81, 16.32) 12.92 (6.37, 26.23) 13.36 (6.41, 27.83) 25.77 (18.54, 35.82) 42.62 (30.07, 60.42) 35.10 (24.79, 49.69) Gini coefficient (quintiles) 7.4 9.3 7.7 1.9 1.6 0.7 3.94 (1.78, 8.74) 5.96 (2.67, 13.30) 10.86 (2.43, 48.65) 7.22 (5.37, 9.70) 12.09 (8.90, 16.42) 16.33 (11.69, 22.83) Wealth (categories) 4.0 4.2 4.7 2.1 1.9 1.8 1.87 (0.82, 4.26) 2.24 (0.95, 5.24) 2.63 (1.12, 6.19) 4.47 (2.87, 6.97) 3.20 (2.18, 4.68) 5.53 (3.76, 8.14) Crowding (categories)‡ 21.2 30.1 20.1 2.3 2.2 2.0 9.26 (3.91, 21.91) 13.63 (4.68, 39.70) 10.09 (0.38, 270.49) 27.85 (20.57, 37.72) 46.32 (34.32, 62.51) 52.47 (38.71, 71.13) Homicide and legal intervention Low education (categories) 11.7 11.9 10.7 1.3 1.2 1.1 9.32 (4.71, 18.46) 9.70 (4.65, 20.25) 9.55 (4.12, 22.14) 22.35 (16.21, 30.81) 23.48 (17.03, 32.36) 23.05 (16.64, 31.91) Townsend index (quintiles) 11.3 13.7 7.7 1.1 1.0 1.0 10.54 (3.89, 28.58) 13.99 (5.35, 36.59) 8.13 (2.02, 32.70) 45.19 (31.13, 65.60) 54.67 (37.70, 79.27) 33.72 (22.73, 50.01) Index of Local Economic Resources 10.7 12.9 9.8 1.1 1.1 1.0 10.17 (4.13, 25.06) 12.24 (5.12, 29.30) 10.25 (3.92, 26.80) 28.55 (20.29, 40.15) 34.58 (24.59, 48.65) 29.30 (20.69, 41.50) (quintiles) SEP1 (categories) 12.9 14.6 9.1 1.2 1.3 1.3 10.88 (3.21, 36.94) 11.34 (3.79, 33.95) 7.27 (1.68, 31.44) 15.90 (11.36, 22.25) 19.46 (14.00, 27.04) 17.83 (12.75, 24.93) SEP index (quintiles) 10.1 12.3 8.4 1.2 1.2 1.0 8.64 (3.44, 21.68) 10.63 (4.36, 25.93) 8.69 (3.03, 24.87) 25.25 (17.64, 36.12) 32.52 (22.92, 46.14) 24.46 (17.14, 34.91) Median value 10.7 12.3 8.4 1.3 1.2 1.1 9.26 10.63 9.55 22.35 23.55 23.05

Section b: Massachusetts cancer incidence (1988-1992)

Rate for areas with Rate for areas with Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence interval) Cancer site Area-based socioeconomic measure the least resources the most resources interval) BG CT ZC BG CT ZC BG CT ZC BG CT ZC Working class (categories) 429.2 440.2 410.2 452.2 483.4 283.2 0.95 (0.90, 1.00) 0.91 (0.86, 0.97) 1.45 (1.34, 1.57) 0.95 (0.93, 0.97) 0.90 (0.88, 0.92) 1.32 (1.29, 1.34)

Median household income (quintiles) 429.7 450.8 423.3 457.9 485.3 370.7 0.94 (0.89, 0.99) 0.93 (0.88, 0.98) 1.14 (1.08, 1.20) 0.90 (0.88, 0.92) 0.92 (0.90, 0.94) 1.17 (1.15, 1.20)

Poverty (categories) 435.0 454.2 453.3 432.6 467.7 412.7 1.01 (0.95, 1.06) 0.97 (0.92, 1.03) 1.10 (1.03, 1.17) 1.00 (0.98, 1.02) 0.98 (0.96, 1.00) 1.07 (1.05, 1.09) Gini coefficient (quintiles) 432.8 473.6 397.1 448.8 462.1 456.0 0.96 (0.91, 1.02) 1.02 (0.97, 1.08) 0.87 (0.82, 0.93) 0.95 (0.93, 0.97) 1.02 (1.00, 1.04) 0.88 (0.86, 0.90) Wealth (categories) 424.0 455.7 440.1 451.4 499.3 332.0 0.94 (0.90, 0.98) 0.91 (0.87, 0.95) 1.33 (1.26, 1.40) 0.92 (0.90, 0.95) 0.89 (0.87, 0.91) 1.43 (1.39, 1.46) Crowding (categories)‡ 421.8 369.1 610.1 426.6 464.8 410.2 0.99 (0.82, 1.20) 0.79 (0.61, 1.03) 1.49 (0.91, 2.43) 0.92 (0.90, 0.95) 0.98 (0.95, 1.01) 1.26 (1.22, 1.29) All sites Low education (categories) 406.4 420.4 436.3 442.3 476.1 393.5 0.92 (0.87, 0.97) 0.88 (0.83, 0.94) 1.11 (1.03, 1.19) 0.91 (0.89, 0.93) 0.91 (0.90, 0.93) 1.13 (1.11, 1.16) Townsend index (quintiles) 447.9 462.0 418.1 434.4 466.9 391.1 1.03 (0.98, 1.09) 0.99 (0.94, 1.04) 1.07 (1.01, 1.13) 1.06 (1.04, 1.08) 0.99 (0.97, 1.01) 1.03 (1.01, 1.05)

Index of Local Economic Resources (quintiles) 422.4 441.0 432.3 451.4 480.6 338.2 0.94 (0.89, 0.98) 0.92 (0.87, 0.97) 1.28 (1.22, 1.35) 0.91 (0.89, 0.92) 0.92 (0.90, 0.94) 1.27 (1.24, 1.29)

SEP1 (categories) 428.5 437.6 431.2 462.2 490.9 291.8 0.93 (0.85, 1.01) 0.89 (0.82, 0.97) 1.48 (1.28, 1.71) 0.96 (0.94, 0.98) 0.89 (0.87, 0.91) 1.37 (1.34, 1.40) SEP index (quintiles) 419.3 439.8 423.2 458.2 487.5 350.1 0.92 (0.87, 0.96) 0.90 (0.86, 0.95) 1.21 (1.15, 1.27) 0.91 (0.89, 0.93) 0.91 (0.89, 0.92) 1.21 (1.19, 1.23) Median value 428.5 441.0 431.2 451.4 480.6 370.7 0.94 0.91 1.21 0.92 0.92 1.21 Working class (categories) 71.1 75.2 65.9 51.7 54.8 33.7 1.38 (1.20, 1.59) 1.37 (1.17, 1.61) 1.95 (1.58, 2.42) 1.45 (1.37, 1.52) 1.36 (1.29, 1.43) 1.66 (1.57, 1.75)

Median household income (quintiles) 73.6 75.0 66.0 54.8 58.8 46.4 1.34 (1.17, 1.54) 1.28 (1.11, 1.46) 1.42 (1.24, 1.64) 1.37 (1.30, 1.44) 1.31 (1.25, 1.38) 1.44 (1.37, 1.52)

Poverty (categories) 73.9 75.7 70.8 57.8 62.1 56.8 1.28 (1.11, 1.47) 1.22 (1.06, 1.41) 1.25 (1.06, 1.47) 1.38 (1.31, 1.45) 1.32 (1.26, 1.39) 1.30 (1.23, 1.37) Gini coefficient (quintiles) 65.9 72.1 60.3 61.7 66.3 67.4 1.07 (0.93, 1.23) 1.09 (0.95, 1.24) 0.89 (0.76, 1.05) 1.07 (1.01, 1.12) 1.07 (1.02, 1.12) 0.93 (0.88, 0.98) Wealth (categories) 64.6 69.2 66.7 49.5 57.7 40.2 1.31 (1.14, 1.50) 1.20 (1.06, 1.36) 1.66 (1.43, 1.93) 1.45 (1.36, 1.55) 1.29 (1.21, 1.37) 1.43 (1.35, 1.51) Crowding (categories)‡ 73.4 64.0 89.0 60.3 66.0 59.7 1.22 (0.77, 1.93) 0.97 (0.51, 1.84) 1.49 (0.45, 4.94) 1.54 (1.43, 1.66) 0.78 (0.72, 0.85) 1.39 (1.28, 1.50) Lung Low education (categories) 68.5 71.3 69.0 56.7 60.1 51.6 1.21 (1.04, 1.40) 1.19 (1.02, 1.39) 1.34 (1.12, 1.60) 1.34 (1.27, 1.42) 1.33 (1.27, 1.40) 1.45 (1.38, 1.53) Townsend index (quintiles) 76.6 76.1 65.7 53.0 57.3 50.0 1.44 (1.26, 1.66) 1.33 (1.15, 1.53) 1.31 (1.12, 1.54) 1.57 (1.49, 1.65) 1.39 (1.33, 1.46) 1.30 (1.23, 1.37)

Index of Local Economic Resources (quintiles) 71.5 75.1 68.2 53.5 57.6 41.6 1.34 (1.17, 1.53) 1.30 (1.13, 1.50) 1.64 (1.43, 1.88) 1.39 (1.32, 1.47) 1.36 (1.29, 1.43) 1.63 (1.55, 1.72)

SEP1 (categories) 74.1 77.7 75.3 50.4 54.8 34.7 1.47 (1.17, 1.84) 1.42 (1.14, 1.76) 2.17 (1.52, 3.10) 1.52 (1.43, 1.60) 1.37 (1.30, 1.45) 1.74 (1.64, 1.85) SEP index (quintiles) 70.1 74.6 66.5 51.3 57.1 41.6 1.37 (1.19, 1.57) 1.31 (1.14, 1.50) 1.60 (1.38, 1.84) 1.47 (1.40, 1.55) 1.36 (1.30, 1.43) 1.58 (1.50, 1.66) Median value 71.5 75.0 66.7 53.5 57.7 46.4 1.34 1.28 1.49 1.45 1.33 1.44 Breast Working class (categories) 114.6 112.0 105.6 148.5 153.8 91.7 0.77 (0.68, 0.88) 0.73 (0.62, 0.85) 1.15 (0.93, 1.42) 0.76 (0.72, 0.80) 0.72 (0.69, 0.76) 1.10 (1.05, 1.16)

Median household income (quintiles) 113.7 117.3 115.4 148.2 152.8 119.2 0.77 (0.67, 0.87) 0.77 (0.67, 0.88) 0.97 (0.85, 1.10) 0.72 (0.68, 0.75) 0.74 (0.70, 0.77) 0.96 (0.91, 1.01)

Poverty (categories) 110.9 111.0 113.6 136.0 146.1 130.0 0.82 (0.70, 0.95) 0.76 (0.65, 0.88) 0.87 (0.74, 1.03) 0.79 (0.75, 0.83) 0.76 (0.72, 0.80) 0.84 (0.79, 0.88) Gini coefficient (quintiles) 123.9 129.4 109.2 138.2 142.9 145.5 0.90 (0.78, 1.02) 0.91 (0.79, 1.03) 0.75 (0.64, 0.87) 0.87 (0.83, 0.91) 0.90 (0.86, 0.94) 0.76 (0.72, 0.80)

Wealth (categories) 125.4 132.9 128.7 147.7 156.4 104.2 0.85 (0.76, 0.95) 0.85 (0.76, 0.95) 1.24 (1.09, 1.40) 0.79 (0.74, 0.84) 0.79 (0.75, 0.83) 1.28 (1.21, 1.36) Crowding (categories)‡ 84.2 70.0 145.8 131.6 140.6 124.7 0.64 (0.36, 1.13) 0.50 (0.22, 1.13) 1.17 (0.25, 5.41) 0.69 (0.64, 0.76) 0.64 (0.58, 0.70) 1.17 (1.07, 1.27) Low education (categories) 101.2 103.3 109.9 141.2 150.6 124.8 0.72 (0.61, 0.84) 0.69 (0.58, 0.81) 0.88 (0.73, 1.06) 0.70 (0.67, 0.74) 0.71 (0.67, 0.74) 0.91 (0.86, 0.95) Townsend index (quintiles) 113.7 113.8 113.7 142.4 149.2 122.7 0.80 (0.70, 0.91) 0.76 (0.66, 0.88) 0.93 (0.80, 1.07) 0.80 (0.76, 0.84) 0.76 (0.73, 0.80) 0.82 (0.78, 0.86)

Index of Local Economic Resources (quintiles) 111.5 111.5 114.6 146.7 153.4 109.7 0.76 (0.67, 0.87) 0.73 (0.63, 0.84) 1.05 (0.92, 1.19) 1.00 (1.32, 1.45) 0.73 (0.70, 0.77) 1.01 (0.96, 1.06)

SEP1 (categories) 109.2 106.9 103.0 153.5 156.0 94.5 0.71 (0.57, 0.89) 0.69 (0.55, 0.86) 1.09 (0.73, 1.62) 0.75 (0.71, 0.79) 0.70 (0.67, 0.74) 1.13 (1.07, 1.20) SEP index (quintiles) 111.4 111.1 114.6 150.6 153.9 113.2 0.74 (0.65, 0.84) 0.72 (0.63, 0.83) 1.01 (0.89, 1.15) 0.72 (0.68, 0.75) 0.72 (0.69, 0.76) 1.02 (0.97, 1.08) Median value 111.5 111.5 113.7 146.7 152.8 119.2 0.77 0.73 1.01 0.76 0.73 1.01

Section b (continued)

Rate for areas with Rate for areas with Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence interval) Cancer site Area-based socioeconomic measure the least resources the most resources interval) BG CT ZC BG CT ZC BG CT ZC BG CT ZC Working class (categories) 13.1 14.4 11.7 6.3 6.9 4.2 2.10 (1.25, 3.52) 2.09 (1.19, 3.67) 2.78 (1.26, 6.13) 2.56 (2.12, 3.10) 2.35 (1.95, 2.82) 2.71 (2.23, 3.31)

Median household income (quintiles) 13.8 14.2 11.8 6.4 7.1 5.7 2.15 (1.31, 3.53) 1.99 (1.22, 3.26) 2.06 (1.23, 3.44) 2.43 (2.02, 2.93) 2.26 (1.89, 2.70) 2.40 (1.99, 2.90)

Poverty (categories) 15.9 15.6 14.0 7.3 7.9 7.3 2.19 (1.40, 3.41) 1.98 (1.25, 3.13) 1.93 (1.15, 3.25) 2.67 (2.21, 3.22) 2.32 (1.94, 2.78) 2.17 (1.79, 2.62) Gini coefficient (quintiles) 11.0 12.4 9.7 7.7 8.8 8.5 1.43 (0.86, 2.38) 1.40 (0.88, 2.25) 1.14 (0.64, 2.04) 1.52 (1.26, 1.83) 1.51 (1.27, 1.81) 1.30 (1.08, 1.57) Wealth (categories) 10.0 10.6 10.3 5.7 6.8 5.0 1.75 (1.02, 2.99) 1.56 (0.95, 2.55) 2.06 (1.17, 3.64) 2.33 (1.80, 3.02) 2.43 (2.02, 2.93) 2.66 (2.10, 3.39) Crowding (categories)‡ 17.0 10.0 21.8 8.3 9.1 8.2 2.05 (0.61, 6.86) 1.10 (0.12, 9.77) 2.66 (0.04, 171.54) 3.50 (2.75, 4.45) 3.09 (2.40, 3.97) 3.02 (2.34, 3.90) Cervix Low education (categories) 15.0 14.0 11.9 7.0 7.8 6.4 2.15 (1.32, 3.48) 1.80 (1.06, 3.04) 1.85 (0.97, 3.51) 2.53 (2.09, 3.05) 2.27 (1.89, 2.72) 2.43 (2.01, 2.95) Townsend index (quintiles) 14.3 15.1 11.3 6.1 7.5 6.6 2.35 (1.40, 3.93) 2.02 (1.24, 3.27) 1.70 (0.95, 3.03) 2.75 (2.29, 3.32) 2.42 (2.02, 2.89) 2.06 (1.70, 2.50)

Index of Local Economic Resources (quintiles) 14.8 15.5 12.9 6.5 7.0 5.5 2.29 (1.43, 3.66) 2.21 (1.38, 3.56) 2.35 (1.44, 3.84) 2.68 (2.23, 3.23) 2.51 (2.10, 3.00) 2.85 (2.36, 3.45)

SEP1 (categories) 17.6 15.1 13.8 6.3 6.7 4.3 2.79 (1.35, 5.77) 2.25 (1.07, 4.70) 3.19 (0.98, 10.41) 2.96 (2.42, 3.62) 2.65 (2.17, 3.24) 2.86 (2.30, 3.56) SEP index (quintiles) 14.5 15.2 12.3 6.2 6.9 5.4 2.36 (1.43, 3.90) 2.20 (1.35, 3.59) 2.28 (1.35, 3.86) 2.99 (2.47, 3.62) 2.57 (2.14, 3.08) 2.74 (2.26, 3.32) Median value 14.5 14.4 11.9 6.4 7.1 5.7 2.15 1.99 2.06 2.56 2.42 2.66 Prostate Working class (categories) 116.1 114.2 116.6 172.8 189.9 103.4 0.67 (0.58, 0.78) 0.60 (0.50, 0.72) 1.13 (0.89, 1.43) 0.62 (0.59, 0.65) 0.58 (0.55, 0.61) 1.03 (0.97, 1.09) Median household income (quintiles) 114.8 119.2 115.2 175.4 182.7 127.5 0.65 (0.56, 0.76) 0.65 (0.56, 0.76) 0.90 (0.78, 1.05) 0.57 (0.54, 0.59) 0.60 (0.57, 0.63) 0.88 (0.84, 0.93)

Poverty (categories) 111.7 121.1 130.3 145.3 159.9 135.6 0.77 (0.64, 0.92) 0.76 (0.63, 0.90) 0.96 (0.79, 1.16) 0.71 (0.68, 0.75) 0.70 (0.67, 0.74) 0.84 (0.79, 0.88) Gini coefficient (quintiles) 132.6 148.4 116.8 140.2 144.7 138.4 0.95 (0.81, 1.11) 1.03 (0.88, 1.19) 0.84 (0.69, 1.03) 0.91 (0.86, 0.95) 1.02 (0.97, 1.07) 0.83 (0.79, 0.88) Wealth (categories) 123.2 130.9 125.6 182.0 198.4 121.5 0.68 (0.60, 0.76) 0.66 (0.59, 0.74) 1.03 (0.90, 1.19) 0.56 (0.53, 0.60) 0.54 (0.51, 0.57) 1.03 (0.97, 1.09) Crowding (categories)‡ 109.1 110.1 155.7 135.1 146.8 125.5 0.81 (0.44, 1.47) 0.75 (0.35, 1.62) 1.24 (0.27, 5.80) 0.88 (0.81, 0.95) 0.81 (0.74, 0.88) 1.18 (1.08, 1.28) Low education (categories) 103.7 110.4 114.1 157.6 174.1 136.5 0.66 (0.55, 0.79) 0.63 (0.52, 0.77) 0.84 (0.67, 1.04) 0.57 (0.54, 0.60) 0.56 (0.54, 0.59) 0.80 (0.76, 0.84) Townsend index (quintiles ) 120.5 123.3 116.9 150.4 166.3 135.0 0.80 (0.69, 0.94) 0.74 (0.63, 0.87) 0.87 (0.73, 1.02) 0.79 (0.75, 0.83) 0.70 (0.67, 0.74) 0.79 (0.75, 0.83)

Index of Local Economic Resources (quintiles) 109.5 114.8 118.5 172.2 179.8 120.0 0.64 (0.55, 0.74) 0.64 (0.54, 0.75) 0.99 (0.85, 1.14) 0.57 (0.54, 0.60) 0.59 (0.56, 0.62) 0.93 (0.88, 0.98)

SEP1 (categories) 105.0 108.1 110.9 187.2 198.8 107.2 0.56 (0.42, 0.74) 0.54 (0.42, 0.71) 1.03 (0.65, 1.65) 0.59 (0.56, 0.62) 0.54 (0.52, 0.57) 1.03 (0.97, 1.09) SEP index (quintiles) 110.3 113.7 113.1 179.3 190.6 127.3 0.61 (0.53, 0.72) 0.60 (0.51, 0.70) 0.89 (0.77, 1.03) 0.55 (0.52, 0.58) 0.55 (0.53, 0.58) 0.83 (0.78, 0.87) Median value 111.7 114.8 116.8 172.2 179.8 127.3 0.67 0.65 0.96 0.59 0.58 0.88 Working class (categories) 41.3 42.5 41.1 45.8 48.3 27.9 0.90 (0.77, 1.06) 0.88 (0.73, 1.06) 1.47 (1.14, 1.90) 0.89 (0.84, 0.95) 0.85 (0.80, 0.90) 1.28 (1.20, 1.36)

Median household income (quintiles) 41.0 42.5 42.3 46.3 48.9 37.2 0.89 (0.75, 1.04) 0.87 (0.74, 1.03) 1.14 (0.97, 1.34) 0.87 (0.82, 0.93) 0.88 (0.83, 0.93) 1.19 (1.12, 1.27)

Poverty (categories) 41.7 45.6 44.8 43.9 47.4 41.6 0.95 (0.80, 1.13) 0.96 (0.81, 1.15) 1.08 (0.88, 1.32) 0.94 (0.88, 1.00) 0.95 (0.89, 1.01) 1.06 (0.99, 1.13) Gini coefficient (quintiles) 42.4 46.1 39.9 46.3 47.3 44.6 0.92 (0.77, 1.08) 0.97 (0.83, 1.15) 0.89 (0.73, 1.10) 0.88 (0.83, 0.94) 0.97 (0.91, 1.03) 0.88 (0.83, 0.94) Wealth (categories) 42.8 46.5 44.9 43.7 48.6 31.7 0.98 (0.84, 1.14) 0.96 (0.83, 1.10) 1.42 (1.20, 1.67) 0.97 (0.90, 1.05) 0.95 (0.89, 1.02) 1.53 (1.43, 1.65) Crowding (categories)‡ 45.4 35.3 106.5 42.6 47.0 41.4 1.07 (0.59, 1.92) 0.75 (0.32, 1.76) 2.57 (0.78, 8.49) 1.08 (0.98, 1.19) 0.90 (0.81, 1.00) 1.26 (1.14, 1.39) Colon Low education (categories ) 39.5 40.8 43.8 45.2 48.0 39.3 0.87 (0.73, 1.05) 0.85 (0.70, 1.03) 1.11 (0.90, 1.38) 0.84 (0.79, 0.90) 0.90 (0.85, 0.96) 1.15 (1.08, 1.22) Townsend index (quintiles) 43.9 46.1 42.0 44.9 47.6 39.6 0.98 (0.83, 1.16) 0.97 (0.82, 1.15) 1.06 (0.88, 1.28) 0.97 (0.92, 1.04) 0.96 (0.91, 1.02) 1.01 (0.95, 1.07)

Index of Local Economic Resources (quintiles) 40.3 42.6 43.1 45.4 48.7 33.6 0.89 (0.76, 1.04) 0.87 (0.74, 1.03) 1.28 (1.09, 1.50) 0.86 (0.81, 0.91) 0.88 (0.83, 0.94) 1.27 (1.19, 1.35)

SEP1 (categories) 41.6 42.5 44.3 45.4 48.2 28.8 0.92 (0.70, 1.21) 0.88 (0.67, 1.16) 1.54 (0.99, 2.40) 0.91 (0.85, 0.97) 0.91 (0.85, 0.97) 1.43 (1.33, 1.53) SEP index (quintiles) 40.2 42.5 42.7 46.5 48.4 34.8 0.86 (0.73, 1.02) 0.88 (0.74, 1.04) 1.23 (1.04, 1.45) 0.86 (0.81, 0.91) 0.88 (0.83, 0.94) 1.24 (1.16, 1.32) Median value 41.6 42.5 43.1 45.4 48.2 37.2 0.92 0.88 1.23 0.89 0.90 1.24 Section c: Rhode Island mortality (1989-1991)

Rate for areas with the least Rate for areas with the most Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Mortality Area-based socioeconomic resources resources interval) interval) outcome measure BG CT ZC BG CT ZC BG CT ZC BG CT ZC Working class (categories) 898.8 982.5 1,026.3 714.9 762.1 769.9 1.26 (1.10, 1.44) 1.29 (1.10, 1.52) 1.33 (1.08, 1.64) 1.47 (1.40, 1.54) 1.45 (1.38, 1.52) 1.56 (1.49, 1.63)

Median household income (quintiles) 949.5 1,032.3 926.2 635.6 723.1 659.9 1.49 (1.33, 1.68) 1.43 (1.27, 1.61) 1.40 (1.2, 1.64) 1.56 (1.49, 1.63) 1.49 (1.43, 1.56) 1.48 (1.42, 1.55)

Poverty (categories) 1,000.8 1,063.1 1,061.5 724.1 753.5 705.8 1.38 (1.24, 1.54) 1.41 (1.26, 1.58) 1.50 (1.31, 1.73) 1.43 (1.37, 1.50) 1.45 (1.39, 1.52) 1.50 (1.43, 1.57) Gini coefficient (quintiles) 835.3 877.6 880.3 775.9 727.1 668.5 1.08 (0.95, 1.22) 1.21 (1.07, 1.36) 1.32 (1.05, 1.65) 1.11 (1.06, 1.16) 1.21 (1.16, 1.26) 1.23 (1.18, 1.29) Wealth (categories) 788.7 829.9 826.9 587.7 744.9 722.1 1.34 (1.11, 1.62) 1.11 (0.93, 1.33) 1.15 (0.97, 1.35) 1.34 (1.25, 1.44) 1.25 (1.18, 1.33) 1.39 (1.32, 1.47) Crowding (categories)‡ 1,301.8 1,138.5 1,238.7 734.2 776.6 760.8 1.77 (1.19, 2.64) 1.47 (0.83, 2.60) 1.63 (1.30, 2.04) 2.24 (2.10, 2.39) 2.02 (1.89, 2.17) 2.02 (1.88, 2.18) All causes Low educ ation (categories) 929.2 987.6 968.9 722.6 717.5 719.2 1.29 (1.15, 1.44) 1.38 (1.21, 1.57) 1.35 (1.19, 1.53) 1.38 (1.31, 1.44) 1.40 (1.34, 1.46) 1.42 (1.35, 1.49) Townsend index (quintiles) 994.3 1,060.8 889.4 711.1 725.7 644.4 1.40 (1.24, 1.58) 1.46 (1.30, 1.64) 1.38 (1.11, 1.71) 1.55 (1.48, 1.62) 1.54 (1.48, 1.61) 1.47 (1.41, 1.54)

Index of Local Economic Resources 1,012.6 1,058.3 945.0 693.0 745.7 730.3 1.46 (1.30, 1.64) 1.42 (1.27, 1.58) 1.29 (1.17, 1.43) 1.49 (1.42, 1.56) 1.49 (1.42, 1.56) 1.43 (1.36, 1.49) (quintiles) SEP1 (categories) 1,060.8 1,150.4 1112.0 752.0 733.2 765.7 1.41 (1.16, 1.71) 1.57 (1.25, 1.97) 1.45 (1.16, 1.82) 1.51 (1.44, 1.59) 1.58 (1.51, 1.66) 1.66 (1.57, 1.75) SEP index (quintiles) 976.5 1,049.9 924.7 681.2 732.6 699.4 1.43 (1.27, 1.62) 1.43 (1.28, 1.61) 1.32 (1.16, 1.51) 1.51 (1.44, 1.58) 1.50 (1.43, 1.57) 1.46 (1.40, 1.53) Median value 976.5 1,049.9 945.0 714.9 733.2 719.2 1.40 1.42 1.35 1.49 1.49 1.47 Heart disease Working class (categories) 310.4 342.4 343.5 237.1 264.1 261.7 1.31 (1.04, 1.64) 1.30 (0.99, 1.70) 1.31 (0.92, 1.87) 1.48 (1.36, 1.60) 1.45 (1.34, 1.56) 1.48 (1.37, 1.61)

Median household income (quintiles) 318.4 355.8 317.2 218.8 254.7 237.7 1.45 (1.19, 1.78) 1.40 (1.15, 1.70) 1.33 (1.02, 1.74) 1.49 (1.38, 1.61) 1.43 (1.32, 1.54) 1.36 (1.26, 1.47)

Poverty (categories) 332.6 358.2 344.7 257.1 270.6 259.4 1.29 (1.08, 1.55) 1.32 (1.09, 1.60) 1.33 (1.04, 1.69) 1.33 (1.23, 1.44) 1.34 (1.24, 1.45) 1.37 (1.26, 1.48) Gini coefficient (quintiles) 289.5 306.3 298.7 273.5 263.5 231.8 1.06 (0.86, 1.31) 1.16 (0.95, 1.42) 1.29 (0.87, 1.90) 1.09 (1.01, 1.18) 1.17 (1.08, 1.26) 1.18 (1.09, 1.27) Wealth (categories) 277.4 289.6 289.3 194.8 255.7 253.5 1.42 (1.02, 1.98) 1.13 (0.84, 1.53) 1.14 (0.86, 1.51) 1.07 (0.87, 1.30) 1.23 (1.11, 1.37) 1.37 (1.24, 1.50) Crowding (categories)‡ 395.3 379.8 403.9 257.1 274.1 269.7 1.54 (0.71, 3.34) 1.39 (0.50, 3.86) 1.50 (1.00, 2.23) 2.18 (1.95, 2.43) 1.80 (1.60, 2.03) 1.69 (1.49, 1.92) Low education (categories) 314.8 338.4 334.1 254.0 244.0 251.3 1.24 (1.02, 1.51) 1.39 (1.11, 1.74) 1.33 (1.08, 1.64) 1.31 (1.21, 1.42) 1.42 (1.31, 1.53) 1.39 (1.29, 1.51) Townsend index (quintiles) 341.6 363.6 302.0 248.0 253.3 213.9 1.38 (1.12, 1.69) 1.44 (1.18, 1.74) 1.41 (0.97, 2.06) 1.48 (1.37, 1.60) 1.50 (1.39, 1.62) 1.36 (1.25, 1.47)

Index of Local Economic Resources 345.1 365.8 321.3 243.3 256.4 259.8 1.42 (1.16, 1.73) 1.43 (1.19, 1.72) 1.24 (1.04, 1.47) 1.46 (1.35, 1.58) 1.47 (1.36, 1.58) 1.33 (1.23, 1.44) (quintiles) SEP1 (categories) 346.8 400.4 363.8 247.5 262.1 259.9 1.40 (1.00, 1.96) 1.53 (1.04, 2.24) 1.40 (0.95, 2.06) 1.50 (1.39, 1.63) 1.57 (1.44, 1.70) 1.49 (1.36, 1.63) SEP index (quintiles) 330.4 354.7 316.5 237.4 252.9 247.9 1.39 (1.14, 1.71) 1.40 (1.15, 1.71) 1.28 (1.02, 1.60) 1.46 (1.35, 1.57) 1.46 (1.35, 1.57) 1.40 (1.29, 1.51) Median value 330.4 355.8 321.3 247.5 256.4 253.5 1.39 1.39 1.33 1.46 1.45 1.37 Working class (categories) 218.8 231.6 233.7 189.9 197.4 195.5 1.15 (0.89, 1.50) 1.17 (0.85, 1.63) 1.20 (0.78, 1.84) 1.25 (1.14, 1.37) 1.25 (1.14, 1.36) 1.35 (1.23, 1.48)

Median household income (quintiles) 221.0 234.5 223.1 176.6 193.3 173.6 1.25 (0.99, 1.58) 1.21 (0.96, 1.54) 1.29 (0.95, 1.74) 1.28 (1.17, 1.40) 1.28 (1.17, 1.39) 1.28 (1.17, 1.41)

Poverty (categories) 226.5 229.6 234.2 195.3 201.2 184.4 1.16 (0.93, 1.45) 1.14 (0.90, 1.45) 1.27 (0.95, 1.70) 1.17 (1.07, 1.29) 1.21 (1.11, 1.32) 1.28 (1.16, 1.40) Gini coefficient (quintiles) 210.2 207.8 216.2 214.1 191.4 182.5 0.98 (0.77, 1.25) 1.09 (0.86, 1.38) 1.18 (0.77, 1.82) 0.99 (0.91, 1.08) 1.09 (1.00, 1.19) 1.08 (0.99, 1.18) Wealth (categories) 204.3 212.4 212.8 171.8 186.3 181.7 1.19 (0.85, 1.67) 1.14 (0.81, 1.61) 1.17 (0.83, 1.65) 1.27 (1.11, 1.45) 1.28 (1.13, 1.44) 1.42 (1.27, 1.59) Crowding (categories)‡ 329.7 229.8 252.7 194.5 203.6 198.5 1.70 (0.79, 3.66) 1.13 (0.29, 4.34) 1.27 (0.76, 2.13) 1.65 (1.44, 1.89) 1.40 (1.21, 1.62) 1.52 (1.31, 1.77) Malignant neoplasm Low education (categories) 220.2 229.5 227.5 192.8 183.2 189.8 1.14 (0.91, 1.43) 1.25 (0.96, 1.63) 1.20 (0.94, 1.54) 1.20 (1.10, 1.32) 1.23 (1.13, 1.35) 1.23 (1.12, 1.35) Townsend index (quintiles) 230.8 234.1 215.2 193.8 196.7 181.7 1.19 (0.94, 1.51) 1.19 (0.94, 1.50) 1.18 (0.80, 1.76) 1.28 (1.17, 1.40) 1.26 (1.16, 1.38) 1.25 (1.14, 1.37)

Index of Local Economic Resources 233.7 234.9 225.3 188.7 199.6 195.0 1.24 (0.98, 1.56) 1.18 (0.94, 1.47) 1.16 (0.94, 1.42) 1.26 (1.15, 1.38) 1.25 (1.14, 1.36) 1.22 (1.11, 1.33) (quintiles) SEP1 (categories) 244.2 242.6 245.9 198.1 189.2 195.1 1.23 (0.84, 1.81) 1.28 (0.81, 2.02) 1.26 (0.79, 2.02) 1.30 (1.18, 1.42) 1.28 (1.16, 1.40) 1.36 (1.22, 1.51) SEP index (quintiles) 229.8 238.8 223.0 184.1 192.9 181.6 1.25 (0.98, 1.58) 1.24 (0.98, 1.56) 1.23 (0.94, 1.60) 1.31 (1.20, 1.44) 1.29 (1.18, 1.41) 1.29 (1.17, 1.41) Median value 226.5 231.6 225.3 192.8 193.3 184.4 1.19 1.18 1.20 1.27 1.26 1.28

Section c (continued)

Rate for areas with the Rate for areas with the Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Mortality Area-based socioeconomic least resources most resources interval) interval) outcome measure BG CT ZC BG CT ZC BG CT ZC BG CT ZC Diabetes Working class (categories) 22.6 24.9 25.0 13.3 17.0 21.0 1.71 (0.67, 4.34) 1.46 (0.50, 4.29) 1.19 (0.33, 4.32) 1.82 (1.34, 2.47) 1.63 (1.20, 2.20) 1.91 (1.40, 2.61)

Median household income (quintiles) 23.7 25.4 22.8 13.7 15.0 11.7 1.74 (0.79, 3.84) 1.69 (0.76, 3.75) 1.95 (0.63, 6.08) 1.98 (1.47, 2.67) 1.86 (1.39, 2.49) 1.93 (1.43, 2.62)

Poverty (categories) 24.7 26.2 24.4 14.7 16.4 13.8 1.68 (0.81, 3.45) 1.60 (0.76, 3.36) 1.77 (0.66, 4.72) 1.96 (1.45, 2.65) 1.72 (1.28, 2.31) 1.81 (1.33, 2.46) Gini coefficient (quintiles) 22.2 22.5 21.1 15.9 16.0 10.3 1.39 (0.60, 3.23) 1.41 (0.65, 3.05) 2.05 (0.34, 12.17) 1.55 (1.15, 2.09) 1.47 (1.10, 1.97) 1.34 (1.00, 1.82) Wealth (categories) 18.4 19.5 19.4 12.0 17.5 20.3 1.53 (0.42, 5.59) 1.11 (0.35, 3.56) 0.95 (0.35, 2.62) 1.34 (0.85, 2.11) 1.35 (0.90, 2.02) 0.68 (0.47, 0.99) Crowding (categories)‡ 29.0 36.2 36.1 17.1 17.8 17.7 1.70 (0.12, 24.55) 2.03 (0.07, 55.44) 2.04 (0.52, 7.91) 2.31 (1.52, 3.52) 2.54 (1.64, 3.93) 2.29 (1.44, 3.64) Low education (categories) 23.5 26.2 24.0 16.3 17.2 13.4 1.44 (0.68, 3.07) 1.52 (0.66, 3.52) 1.79 (0.74, 4.32) 1.62 (1.20, 2.20) 1.67 (1.24, 2.24) 1.84 (1.36, 2.51) Townsend index (quintiles) 25.4 25.6 22.4 16.3 16.7 10.5 1.56 (0.72, 3.36) 1.54 (0.73, 3.24) 2.13 (0.43, 10.55) 2.00 (1.49, 2.70) 1.91 (1.43, 2.56) 2.19 (1.60, 2.99) Index of Local Economic Resources 25.8 26.7 22.9 14.7 17.1 14.6 1.75 (0.81, 3.76) 1.56 (0.77, 3.17) 1.57 (0.78, 3.17) 1.78 (1.32, 2.40) 1.60 (1.20, 2.14) 1.93 (1.42, 2.61) (quintiles) SEP1 (categories) 25.6 28.5 25.9 16.5 16.8 21.0 1.55 (0.43, 5.64) 1.70 (0.37, 7.76) 1.23 (0.30, 5.11) 1.72 (1.25, 2.35) 1.88 (1.37, 2.59) 1.94 (1.36, 2.77) SEP index (quintiles) 24.2 27.3 22.8 13.7 15.0 14.4 1.77 (0.78, 3.98) 1.82 (0.84, 3.96) 1.58 (0.63, 3.94) 1.80 (1.33, 2.43) 1.88 (1.40, 2.51) 1.84 (1.36, 2.50) Median value 24.2 26.2 22.98 14.7 16.8 14.4 1.68 1.56 1.77 1.80 1.72 1.91 Working class (categories) 9.3 10.3 13.7 3.9 5.6 7.4 2.39 (0.38, 14.88) 1.83 (0.27, 12.51) 1.85 (0.21, 16.75) 3.32 (1.94, 5.66) 3.34 (1.97, 5.65) 5.39 (3.12, 9.33)

Median household income (quintiles) 14.5 16.7 12.2 1.7 2.6 1.6 8.31 (1.39, 49.82) 6.51 (1.41, 30.10) 7.71 (0.58, 102.43) 9.88 (5.68, 17.18) 12.17 (6.93, 21.35) 11.56 (6.40, 20.88)

Poverty (categories) 17.3 21.1 22.0 4.2 3.2 1.9 4.13 (1.44, 11.84) 6.52 (2.02, 20.99) 11.82 (1.90, 73.45) 7.35 (4.30, 12.58) 11.83 (6.80, 20.56) 12.51 (7.10, 22.05)

Gini coefficient (quintiles) 10.2 14.0 12.9 3.6 1.8 3.5 2.85 (0.64, 12.66) 7.96 (1.25, 50.86) 3.66 (0.81 16.53) (1.90, 73.45) 6.37) 7.36 (4.28, 12.65) 7.50 (4.27, 13.18) Wealth (categories) 6.4 6.7 6.7 3.7 4.5 5.5 1.71 (0.16, 18.04) 1.50 (0.17, 13.41) 1.23 (0.17, 8.76) 2.07 (0.88, 4.83) 1.07 (0.87, 1.30) 1.62 (0.85, 3.08) Crowding (categories)‡ 28.8 8.8 29.7 4.8 4.8 5.2 5.96 (0.78, 45.30) 1.84 (0.03, 102.43) 5.77 (1.54, 21.65) 11.95 (6.65, 21.47) 19.01 (10.68, 33.84) 11.49 (6.14, 21.50) Human immunodeficiency virus Low education (categories) 12.1 12.4 10.7 2.8 2.4 3.1 4.31 (0.98, 18.88) 5.05 (0.79, 32.42) 3.45 (0.67, 17.89) 6.78 (3.90, 11.78) 6.16 (3.58, 10.61) 4.72 (2.74, 8.12) Townsend index (quintiles) 15.8 16.6 11.4 3.5 4.0 2.4 4.55 (1.10, 18.93) 4.14 (1.12, 15.25) 4.80 (0.27, 84.42) 9.47 (5.42, 16.54) 8.92 (5.18, 15.36) 9.87 (5.38, 18.10) Index of Local Economic Resources 11.5 14.3 12.1 3.6 4.0 3.7 3.20 (0.79, 13.00) 3.58 (0.98, 13.11) 3.24 (0.91, 11.52) 4.62 (2.73, 7.83) 5.00 (2.97, 8.44) 5.83 (3.38, 10.05) (quintiles) SEP1 (categories) 14.7 14.4 17.7 4.3 5.5 7.4 3.42 (0.34, 34.76) 2.62 (0.25, 27.13) 2.40 (0.25, 23.08) 4.54 (2.62, 7.86) 7.73 (4.50, 13.27) 11.25 (6.33, 19.98) SEP index (quintiles) 13.3 15.9 12.2 2.9 2.9 3.3 4.58 (1.00, 21.06) 5.52 (1.23, 24.78) 3.65 (0.64, 20.76) 7.09 (4.06, 12.39) 7.91 (4.60, 13.59) 7.67 (4.35, 13.51) Median value 13.3 14.3 12.2 3.6 4.0 3.3 4.13 4.14 3.65 6.78 7.73 7.67 Homicide and legal Working class (categories) 7.6 8.9 10.4 1.0 1.4 2.0 7.36 (0.26, 206.19) 6.46 (0.22, 187.77) 5.25 (0.18, 151.07) 7.53 (3.75, 15.12) 6.37 (3.28, 12.37) 6.46 (3.30, 12.63) intervention Median household income (quintiles) 11.7 13.7 9.0 2.5 1.6 1.5 4.75 (0.95, 23.62) 8.40 (1.23, 57.58) 5.90 (0.33, 106.51) 14.17 (6.91, 29.05) 12.91 (6.44, 25.91) 11.17 (5.42, 23.01)

Poverty (categories) 12.1 14.6 17.1 1.9 2.4 2.3 6.23 (1.51, 25.74) 5.97 (1.56, 22.87) 7.54 (1.25, 45.39) 11.09 (5.51, 22.32) 10.22 (5.17, 20.21) 14.45 (7.14, 29.21) Gini coefficient (quintiles) 5.6 8.5 8.9 3.1 2.9 3.8 1.81 (0.34, 9.47) 2.89 (0.58, 14.44) 2.37 (0.17, 33.03) 2.36 (1.26, 4.43) 3.78 (2.01, 7.11) 10.67 (5.21, 21.86) Wealth (categories) 4.5 5.0 5.3 0.6 1.4 2.3 7.18 (0.02, 2068.8) 3.61 (0.06, 211.70) 2.26 (0.11, 44.75) 4.54 (1.35, 15.21) 3.82 (1.42, 10.28) 4.12 (1.70, 9.98) Crowding (categories)‡ 26.3 25.0 25.9 2.9 2.9 3.2 9.19 (1.47, 57.23) 8.58 (0.38, 193.33) 8.20 (1.98, 33.97) 21.35 (10.61, 42.98) 31.81 (16.03, 63.13) 24.11 (11.91, 48.83) Low education (categories) 9.9 10.1 8.6 1.9 1.9 2.0 5.13 (0.88, 29.79) 5.34 (0.60, 47.40) 4.28 (0.54, 33.76) 10.36 (5.13, 20.92) 7.37 (3.79, 14.35) 6.81 (3.49, 13.30) Townsend index (quintiles) 11.2 13.3 7.8 2.7 1.6 2.9 4.09 (0.80, 20.85) 8.33 (1.21, 57.53) 2.70 (0.15, 48.66) 12.67 (6.17, 26.05) 14.63 (7.18, 29.84) 11.32 (5.28, 24.28) Index of Local Economic Resources 11.5 13.2 9.4 1.6 2.3 1.5 6.98 (1.06, 45.85) 5.87 (1.19, 28.95) 6.43 (0.94, 43.99) 14.30 (7.02, 29.15) 11.02 (5.57, 21.78) 11.24 (5.53, 22.82) (quintiles) SEP1 (categories) 15.6 17.3 16.8 1.2 0.7 2.0 12.97 (0.22, 772.52) 23.90 (0.08, 7116.86) 8.46 (0.29, 248.89) 11.75 (5.77, 23.94) 13.42 (6.82, 26.40) 13.04 (6.42, 26.50) SEP index (quintiles) 11.4 13.7 9.0 1.9 1.7 2.2 6.14 (0.95, 39.86) 7.96 (1.16, 54.75) 4.07 (0.43, 38.34) 13.74 (6.59, 28.65) 11.74 (5.90, 23.36) 9.45 (4.67, 19.13) Median value 11.4 13.3 9.0 1.9 1.7 2.2 6.23 6.46 5.25 11.75 11.02 11.17

Section d: Rhode Island cancer incidence (1989-1992)

Rate for areas with the Rate for areas with the Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Area-based socioeconomic Cancer site least resources most resources interval) interval) measure BG CT ZC BG CT ZC BG CT ZC BG CT ZC Working class (categories) 433.0 455.7 468.5 440.6 478.2 479.9 0.98 (0.84, 1.15) 0.95 (0.79, 1.15) 0.98 (0.76, 1.25) 0.94 (0.89, 0.99) 0.96 (0.91, 1.01) 1.00 (0.95, 1.05)

Median household income (quintiles) 432.4 451.0 455.5 414.6 478.5 453.1 1.04 (0.91, 1.20) 0.94 (0.82, 1.08) 1.01 (0.85, 1.18) 1.07 (1.02, 1.13) 0.95 (0.90, 0.99) 1.03 (0.98, 1.08)

Poverty (categories) 437.3 445.5 446.9 427.1 460.5 445.8 1.02 (0.89, 1.18) 0.97 (0.83, 1.12) 1.00 (0.84, 1.20) 1.02 (0.96, 1.08) 0.99 (0.94, 1.05) 1.00 (0.95, 1.06) Gini coefficient (quintiles) 426.9 457.2 452.5 465.5 431.2 446.8 0.92 (0.79, 1.06) 1.06 (0.92, 1.22) 1.01 (0.80, 1.29) 0.96 (0.91, 1.01) 1.17 (1.11, 1.23) 1.02 (0.97, 1.08) Wealth (categories) 423.3 451.2 456.7 436.5 648.8 462.8 0.97 (0.80, 1.17) 0.70 (0.59, 0.82) 0.99 (0.82, 1.19) 0.99 (0.92, 1.07) 0.78 (0.73, 0.83) 0.99 (0.93, 1.05) Crowding (categories)‡ 437.1 344.3 453.3 418.0 459.2 456.2 1.05 (0.61, 1.80) 0.75 (0.31, 1.83) 0.99 (0.84, 1.17) 1.17 (1.07, 1.27) 0.97 (0.89, 1.06) 0.99 (0.90, 1.09) All sites Low education (categories) 425.5 437.1 453.2 451.8 526.7 470.1 0.94 (0.82, 1.08) 0.83 (0.72, 0.96) 0.96 (0.84, 1.11) 0.95 (0.90, 1.01) 0.85 (0.81, 0.89) 0.95 (0.90, 1.00) Townsend index (quintiles ) 431.4 449.5 458.8 415.9 435.0 431.2 1.04 (0.90, 1.20) 1.03 (0.90, 1.19) 1.06 (0.86, 1.32) 1.08 (1.03, 1.14) 1.01 (0.96, 1.06) 1.05 (1.00, 1.11)

Index of Local Economic Resources 431.2 451.1 452.4 421.3 478.6 445.8 1.02 (0.89, 1.18) 0.94 (0.82, 1.08) 1.01 (0.90, 1.15) 1.05 (1.00, 1.11) 0.95 (0.90, 1.00) 1.00 (0.95, 1.06) (quintiles) SEP1 (categories) 428.9 451.3 449.5 474.4 499.3 477.6 0.90 (0.72, 1.14) 0.90 (0.70, 1.17) 0.94 (0.71, 1.24) 0.96 (0.91, 1.01) 0.84 (0.79, 0.89) 0.99 (0.93, 1.06) SEP index (quintiles) 423.4 454.0 454.6 428.6 494.1 453.1 0.99 (0.85, 1.14) 0.92 (0.80, 1.06) 1.00 (0.87, 1.16) 0.96 (0.91, 1.01) 0.93 (0.89, 0.98) 1.00 (0.95, 1.06) Median value 431.2 451.1 453.2 428.6 478.5 453.1 0.99 0.94 1.00 0.99 0.95 1.00 Lung Working class (categories) 78.3 80.0 79.4 54.0 56.8 61.6 1.45 (0.96, 2.20) 1.41 (0.83, 2.39) 1.29 (0.65, 2.54) 1.62 (1.41, 1.87) 1.41 (1.23, 1.61) 1.28 (1.12, 1.47)

Median household income (quintiles) 82.8 87.3 74.9 50.8 65.7 63.8 1.63 (1.14, 2.34) 1.33 (0.94, 1.88) 1.17 (0.76, 1.80) 1.70 (1.48, 1.95) 1.41 (1.24, 1.61) 1.22 (1.07, 1.39)

Poverty (categories) 86.1 88.7 86.4 58.4 66.3 64.7 1.48 (1.06, 2.05) 1.34 (0.95, 1.89) 1.34 (0.87, 2.04) 1.62 (1.41, 1.86) 1.42 (1.24, 1.62) 1.21 (1.05, 1.38) Gini coefficient (quintiles) 72.8 75.8 71.3 65.9 67.2 71.0 1.11 (0.77, 1.59) 1.13 (0.80, 1.59) 1.00 (0.55, 1.83) 1.17 (1.02, 1.34) 1.22 (1.07, 1.39) 1.01 (0.88, 1.15) Wealth (categories) 67.4 71.8 71.9 51.8 83.0 66.8 1.30 (0.77, 2.21) 0.86 (0.55, 1.36) 1.08 (0.66, 1.77) 1.57 (1.27, 1.94) 0.91 (0.77, 1.09) 1.20 (1.02, 1.41) Crowding (categories)‡ 45.5 57.1 79.8 62.6 68.7 68.8 0.73 (0.14, 3.68) 0.83 (0.10, 6.95) 1.16 (0.52, 2.57) 0.59 (0.48, 0.72) 0.64 (0.52, 0.80) 1.41 (1.12, 1.77) Low education (categories) 78.1 79.5 76.0 57.8 73.3 66.7 1.35 (0.96, 1.91) 1.08 (0.75, 1.57) 1.14 (0.79, 1.65) 1.55 (1.35, 1.77) 1.21 (1.06, 1.38) 1.12 (0.98, 1.28) Townsend index (quintiles) 81.2 87.4 74.3 54.2 61.0 60.7 1.50 (1.04, 2.15) 1.43 (1.01, 2.03) 1.22 (0.69, 2.17) 1.67 (1.46, 1.91) 1.45 (1.27, 1.65) 1.24 (1.09, 1.42) Index of Local Economic Resources 79.6 84.4 74.9 53.4 64.5 63.4 1.49 (1.04, 2.14) 1.31 (0.93, 1.83) 1.18 (0.87, 1.61) 1.68 (1.47, 1.92) 1.50 (1.31, 1.70) 1.21 (1.06, 1.38) (quintiles) SEP1 (categories) 84.8 89.7 84.4 57.3 62.0 61.6 1.48 (0.81, 2.70) 1.45 (0.73, 2.86) 1.37 (0.66, 2.85) 1.81 (1.57, 2.09) 1.34 (1.16, 1.55) 1.34 (1.15, 1.58) SEP index (quintiles) 82.1 88.1 74.8 54.6 66.3 64.9 1.50 (1.04, 2.16) 1.33 (0.94, 1.87) 1.15 (0.79, 1.69) 1.71 (1.49, 1.96) 1.43 (1.25, 1.63) 1.22 (1.07, 1.40) Median value 79.6 84.4 74.9 54.6 66.3 64.7 1.48 1.33 1.17 1.62 1.41 1.22 Working class (categories) 103.6 115.0 115.5 137.1 152.5 149.8 0.76 (0.51, 1.12) 0.75 (0.47, 1.20) 0.77 (0.41, 1.44) 0.80 (0.69, 0.92) 0.79 (0.68, 0.90) 0.83 (0.72, 0.95)

Median household income (quintiles) 111.4 118.2 120.5 122.2 136.7 137.3 0.91 (0.62, 1.33) 0.86 (0.60, 1.25) 0.88 (0.58, 1.32) 0.92 (0.80, 1.06) 0.80 (0.70, 0.91) 0.94 (0.82, 1.07)

Poverty (categories) 112.8 111.0 110.3 119.7 128.1 125.6 0.94 (0.65, 1.37) 0.87 (0.58, 1.30) 0.88 (0.54, 1.43) 0.93 (0.81, 1.08) 0.89 (0.77, 1.02) 0.97 (0.84, 1.12) Gini coefficient (quintiles) 120.5 133.6 126.7 127.7 116.4 123.7 0.94 (0.65, 1.37) 1.15 (0.80, 1.65) 1.02 (0.56, 1.88) 0.97 (0.85, 1.12) 1.20 (1.04, 1.37) 1.14 (0.99, 1.31) Wealth (categories) 115.2 121.9 124.7 142.5 203.6 152.8 0.81 (0.52, 1.27) 0.60 (0.40, 0.89) 0.82 (0.52, 1.28) 0.84 (0.69, 1.03) 1.49 (1.25, 1.76) 0.92 (0.78, 1.08) Crowding (categories)‡ 115.4 61.7 115.2 117.4 127.7 127.0 0.98 (0.25, 3.85) 0.48 (0.04, 6.29) 0.91 (0.39, 2.13) 0.91 (0.72, 1.15) 0.81 (0.63, 1.04) 0.77 (0.59, 1.00) Breast Low education (categories) 111.0 115.9 118.4 130.0 150.0 139.7 0.85 (0.60, 1.22) 0.77 (0.53, 1.13) 0.85 (0.59, 1.23) 0.82 (0.71, 0.95) 0.75 (0.66, 0.86) 0.85 (0.74, 0.98) Townsend index (quintiles) 113.7 117.3 121.3 125.2 127.4 129.4 0.91 (0.62, 1.32) 0.92 (0.63, 1.34) 0.94 (0.55, 1.60) 0.90 (0.78, 1.03) 0.84 (0.73, 0.96) 0.94 (0.82, 1.08)

Index of Local Econom ic Resources 111.6 115.6 118.5 124.1 136.4 130.6 0.90 (0.61, 1.32) 0.85 (0.59, 1.23) 0.91 (0.66, 1.24) 0.89 (0.77, 1.02) 0.78 (0.69, 0.90) 0.86 (0.75, 0.99) (quintiles) SEP1 (categories) 105.3 117.3 110.3 154.9 168.6 150.1 0.68 (0.38, 1.22) 0.70 (0.37, 1.30) 0.73 (0.36, 1.49) 0.75 (0.64, 0.87) 0.67 (0.57, 0.78) 0.81 (0.69, 0.96) SEP index (quintiles) 107.5 115.2 120.3 125.8 139.6 140.3 0.85 (0.58, 1.26) 0.83 (0.57, 1.20) 0.86 (0.59, 1.24) 0.85 (0.74, 0.98) 0.79 (0.69, 0.90) 0.88 (0.77, 1.01) Median value 111.6 115.9 118.5 125.8 136.7 137.3 0.90 0.83 0.88 0.89 0.80 0.88

Section d (continued)

Rate for areas with the least Rate for areas with the most Incidence rate ratio for least vs. most (95% confidence Relative index of inequality (95% confidence Cancer Area-based socioeconomic resources resources interval) interval) site measure BG CT ZC BG CT ZC BG CT ZC BG CT ZC Cervix Working class (categories) 13.3 12.9 13.7 4.6 8.9 6.1 2.87 (0.42, 19.72) 1.44 (0.22, 9.37) 2.25 (0.11, 45.21) 2.70 (1.64, 4.45) 1.84 (1.13, 2.99) 2.18 (1.33, 3.59)

Median household income (quintiles) 15.3 15.0 13.6 6.3 8.8 8.8 2.43 (0.62, 9.49) 1.70 (0.48, 5.98) 1.54 (0.35, 6.82) 2.41 (1.49, 3.91) 1.92 (1.20, 3.07) 1.83 (1.13, 2.95)

Poverty (categories) 14.9 16.3 14.7 7.9 9.0 9.0 1.88 (0.59, 5.96) 1.81 (0.55, 5.98) 1.64 (0.35, 7.78) 2.31 (1.42, 3.75) 1.91 (1.19, 3.07) 1.78 (1.09, 2.90) Gini coefficient (quintiles) 9.5 11.2 12.9 9.2 9.9 12.3 1.04 (0.26, 4.16) 1.13 (0.31, 4.09) 1.05 (0.15, 7.24) 1.46 (0.90, 2.36) 1.25 (0.78, 1.99) 1.20 (0.74, 1.93) Wealth (categories) 10.7 11.1 11.2 6.1 11.2 8.4 1.77 (0.20, 15.69) 0.99 (0.18, 5.38) 1.34 (0.19, 9.35) 2.43 (1.07, 5.53) 0.63 (0.32, 1.23) 1.74 (0.94, 3.22) Crowding (categories)‡ 57.1 36.2 23.5 9.3 9.8 9.9 6.11 (0.91, 41.24) 3.69 (0.14, 98.29) 2.36 (0.37, 15.20) 3.51 (1.86, 6.62) 3.37 (1.72, 6.59) 2.43 (1.17, 5.07)

Low education (categories) 15.1 13.5 12.5 6.9 9.5 8.1 2.19 (0.61, 7.90) 1.42 (0.37, 5.40) 1.55 (0.39, 6.18) 2.14 (1.31, 3.50) 1.67 (1.03, 2.69) 1.45 (0.89, 2.36) Townsend index (quintiles) 15.5 16.4 12.8 5.8 7.2 12.8 2.69 (0.65, 11.08) 2.28 (0.63, 8.34) 1.00 (0.18, 5.45) 2.93 (1.81, 4.76) 2.33 (1.46, 3.72) 1.82 (1.12, 2.98) Index of Local Economic Resources 14.3 15.7 14.0 6.8 7.8 7.9 2.11 (0.55, 8.06) 2.01 (0.58, 6.95) 1.78 (0.55, 5.69) 2.68 (1.65, 4.35) 2.05 (1.28, 3.28) 2.14 (1.32, 3.48) (quintiles) SEP1 (categories) 17.6 17.9 14.7 5.1 8.0 6.1 3.47 (0.27, 44.30) 2.25 (0.20, 24.76) 2.41 (0.10, 55.8) 2.67 (1.60, 4.43) 1.68 (1.01, 2.80) 1.80 (1.02, 3.17) SEP index (quintiles) 16.3 15.1 13.7 5.9 8.3 8.2 2.75 (0.69, 10.95) 1.83 (0.52, 6.44) 1.67 (0.40, 6.97) 3.17 (1.94, 5.19) 2.15 (1.34, 3.44) 1.84 (1.14, 2.97) Median value 15.1 15.1 13.6 6.3 8.9 8.4 2.43 1.81 1.64 2.67 1.91 1.82 Working class (categories) 101.6 102.5 101.3 140.6 167.5 168.3 0.72 (0.46, 1.14) 0.61 (0.35, 1.06) 0.60 (0.29, 1.23) 0.70 (0.60, 0.82) 0.60 (0.51, 0.69) 0.59 (0.50, 0.68)

Median household income (quintiles) 92.5 90.2 100.9 136.5 148.1 160.5 0.68 (0.43, 1.06) 0.61 (0.38, 0.98) 0.63 (0.39, 1.02) 0.71 (0.61, 0.82) 0.60 (0.52, 0.69) 0.61 (0.53, 0.70)

Poverty (categories) 93.3 96.6 92.8 124.0 129.3 138.2 0.75 (0.47, 1.20) 0.75 (0.45, 1.23) 0.67 (0.37, 1.23) 0.71 (0.61, 0.83) 0.77 (0.67, 0.89) 0.65 (0.56, 0.76) Gini coefficient (quintiles) 110.6 116.5 109.1 136.2 117.1 145.0 0.81 (0.52, 1.28) 0.99 (0.64, 1.54) 0.75 (0.37, 1.54) 0.87 (0.75, 1.01) 0.90 (0.78, 1.04) 0.80 (0.70, 0.93) Wealth (categories) 107.7 113.4 111.3 160.2 236.4 137.2 0.67 (0.40, 1.14) 0.48 (0.30, 0.76) 0.81 (0.46, 1.43) 0.56 (0.46, 0.68) 0.43 (0.36, 0.51) 0.53 (0.45, 0.62) Crowding (categories)‡ 40.6 80.7 109.4 113.8 126.2 125.6 0.36 (0.02, 6.29) 0.64 (0.04, 11.39) 0.87 (0.28, 2.71) 0.85 (0.66, 1.09) 0.73 (0.56, 0.96) 0.64 (0.48, 0.86) Prostate Low education (categories) 85.9 90.6 102.4 158.1 182.3 155.9 0.54 (0.35, 0.83) 0.50 (0.31, 0.79) 0.66 (0.42, 1.03) 0.50 (0.43, 0.58) 0.48 (0.42, 0.56) 0.55 (0.47, 0.63) Townsend index (quintiles) 96.0 93.3 111.5 126.0 122.1 136.6 0.76 (0.48, 1.21) 0.76 (0.47, 1.24) 0.82 (0.43, 1.54) 0.77 (0.66, 0.89) 0.69 (0.60, 0.80) 0.74 (0.64, 0.86) Index of Local Economic Resources 92.4 92.1 103.6 135.5 144.3 141.6 0.68 (0.42, 1.09) 0.64 (0.40, 1.01) 0.73 (0.50, 1.07) 0.67 (0.58, 0.78) 0.63 (0.55, 0.73) 0.68 (0.59, 0.78) (quintiles) SEP1 (categories) 87.2 89.0 95.0 161.6 171.3 162.5 0.54 (0.26, 1.12) 0.52 (0.23, 1.17) 0.58 (0.25, 1.38) 0.43 (0.08, 0.27) 0.44 (0.38, 0.52) 0.57 (0.48, 0.68) SEP index (quintiles) 84.6 92.6 100.1 146.6 162.7 147.4 0.58 (0.36, 0.92) 0.57 (0.36, 0.89) 0.68 (0.43, 1.07) 0.58 (0.50, 0.67) 0.55 (0.48, 0.64) 0.57 (0.49, 0.66) Median value 92.5 92.6 102.4 136.5 148.1 145.0 0.68 0.61 0.68 0.70 0.60 0.61 Colon Working class (categories) 47.9 48.7 50.6 44.5 44.6 43.4 1.08 (0.68, 1.72) 1.09 (0.60, 1.99) 1.17 (0.53, 2.58) 1.12 (0.95, 1.32) 1.02 (0.87, 1.20) 1.12 (0.95, 1.32)

Median household income (quintiles) 40.8 40.7 48.6 42.4 53.1 48.8 0.96 (0.62, 1.49) 0.77 (0.50, 1.18) 1.00 (0.60, 1.65) 1.00 (0.85, 1.18) 0.86 (0.74, 1.00) 1.05 (0.90, 1.23)

Poverty (categories) 37.4 36.8 43.1 46.3 50.8 47.6 0.81 (0.52, 1.26) 0.72 (0.45, 1.17) 0.90 (0.52, 1.57) 0.88 (0.75, 1.04) 0.88 (0.75, 1.03) 0.93 (0.79, 1.10) Gini coefficient (quintiles) 40.6 41.2 45.9 56.2 47.7 52.5 0.72 (0.47, 1.10) 0.86 (0.56, 1.32) 0.87 (0.43, 1.79) 0.75 (0.64, 0.88) 0.94 (0.81, 1.10) 0.85 (0.73, 1.00) Wealth (categories) 46.9 50.6 52.3 43.3 60.3 44.5 1.08 (0.60, 1.96) 0.84 (0.49, 1.43) 1.18 (0.64, 2.15) 1.24 (0.97, 1.58) 0.99 (0.80, 1.21) 1.36 (1.12, 1.65) Crowding (categories)‡ 25.7 28.4 35.6 46.1 51.1 50.1 0.56 (0.05, 5.74) 0.55 (0.03, 9.71) 0.71 (0.22, 2.32) 0.85 (0.64, 1.11) 0.64 (0.47, 0.87) 0.85 (0.63, 1.14) Low education (categories) 44.4 45.6 49.0 48.0 52.9 50.7 0.92 (0.61, 1.39) 0.86 (0.55, 1.35) 0.97 (0.63, 1.49) 0.94 (0.80, 1.11) 0.89 (0.76, 1.04) 0.94 (0.80, 1.10) Townsend index (quintiles) 40.4 41.6 47.7 44.2 44.8 49.7 0.91 (0.58, 1.43) 0.93 (0.59, 1.45) 0.96 (0.50, 1.84) 1.00 (0.85, 1.18) 0.92 (0.79, 1.07) 1.00 (0.85, 1.17) Index of Local Economic Resources 43.6 46.0 48.0 43.5 49.3 45.9 1.00 (0.64, 1.56) 0.93 (0.62, 1.41) 1.05 (0.72, 1.51) 1.06 (0.91, 1.25) 0.95 (0.81, 1.11) 1.00 (0.86, 1.17) (quintiles) SEP1 (categories) 41.1 38.6 45.2 44.9 48.6 43.4 0.92 (0.44, 1.90) 0.80 (0.34, 1.84) 1.04 (0.43, 2.51) 0.96 (0.81, 1.14) 0.81 (0.68, 0.96) 1.03 (0.85, 1.24) SEP index (quintiles) 42.8 43.4 48.6 44.4 50.6 48.0 0.96 (0.62, 1.50) 0.86 (0.56, 1.32) 1.01 (0.65, 1.59) 0.93 (0.79, 1.10) 0.96 (0.82, 1.12) 1.10 (0.94, 1.28) Median value 41.1 41.6 48.0 44.5 50.6 48.0 0.92 0.86 1.00 0.96 0.92 1.00 * Age-standardized to the year 2000 standard million (57).

† Average annual age-standardized rates (per 100,000) and age-adjusted comparisons for the incidence rate ratio and the relative index of inequality.

‡ Cutpoints for each variable are presented in the online Appendix, which is also posted on this website.

§ BG, block group; CT, census tract; ZC, zip code; SEP, socioeconomic position. Geocoding and Monitoring of US Socioeconomic Inequalities in Mortality and Cancer Incidence: Does the Choice of Area- based Measure and Geographic Level Matter? The Public Health Disparities Geocoding Project Nancy Krieger, Jarvis T. Chen, Pamela D. Waterman, Mah-Jabeen Soobader, S. V. Subramanian, and Rosa Carson

From the Department of Health and Social Behavior, Harvard School of Public Health, Boston, MA.

APPENDIX

Cutpoints for Area-based Socioeconomic Measures

Working class (categories)

Category 1 = 0–49.9 percent; category 2 = 50–65.9 percent; category 3 = 66–74.9 percent; category 4 = 75–100 percent.

Median household income (quintiles)

Massachusetts—

Block groups: quintile 1 = $4,999–$26,110; quintile 2 = $26,111–$33,749; quintile 3 = $33,750–$40,798; quintile 4 = $40,799–$49,903; quintile 5 = $49,904–$150,001.

Census tracts: quintile 1 = $4,999–$26,471; quintile 2 = $26,472–$33,162; quintile 3 = $33,163–$39,286; quintile 4 = $39,287–$47,124; quintile 5 = $47,125–$102,797.

Zip codes: quintile 1 = $9,762–$30,624; quintile 2 = $30,625–$36,246; quintile 3 = $36,247–41,396; quintile 4 = $41,397–$48,841; quintile 5 = $48,842–$94,898. Rhode Island—

Block groups: quintile 1 = $4,999–$22,088; quintile 2 = $22,089–$30,293; quintile 3 = $30,294–$35,567; quintile 4 = $35,568–$41,204; quintile 5 = $41,205–$150,001.

Census tracts: quintile 1 = $6,462–$23,667; quintile 2 = $23,668–$31,032; quintile 3 = $31,033–$35,300; quintile 4 = $35,301–$40,606; quintile 5 = $40,607–$78,666.

Zip codes: quintile 1 = $8,787–$29,548; quintile 2 = $29,549–$33,614; quintile 3 = $33,615–$36,921; quintile 4 = $36,922–$41,356; quintile 5 = $41,357–$60,705.

Poverty (categories)

Category 1 = 0–4.9 percent; category 2 = 5.0–9.9 percent; category 3 = 10.0–19.9 percent; category 4 = 20–100 percent.

Gini coefficient (quintiles)

Massachusetts—

Block groups: quintile 1 = 0.009–0.314; quintile 2 = 0.315–0.350; quintile 3 = 0.351– 0.379; quintile 4 = 0.380–0.421; quintile 5 = 0.422–0.688.

Census tracts: quintile 1 = 0.009–0.348; quintile 2 = 0.349–0.371; quintile 3 = 0.372– 0.395; quintile 4 = 0.396–0.428; quintile 5 = 0.429–0.650.

Zip codes: quintile 1 = 0.208–0.344; quintile 2 = 0.345–0.369; quintile 3 = 0.370–0.387; quintile 4 = 0.388–0.414; quintile 5 = 0.415–0.614.

Rhode Island—

Block groups: quintile 1 = 0.014–0.318; quintile 2 = 0.319–0.351; quintile 3 = 0.352– 0.381; quintile 4 = 0.382–0.422; quintile 5 = 0.423–0.650.

Census tracts: quintile 1 = 0.050–0.349; quintile 2 = 0.350–0.373; quintile 3 = 0.374– 0.395; quintile 4 = 0.396–0.426; quintile 5 = 0.427–0.595.

Zip codes: quintile 1 = 0.186–0.352; quintile 2 = 0.353–0.364; quintile 3 = 0.365–0.394; quintile 4 = 0.395–0.417; quintile 5 = 0.418–0.551.

Wealth (categories)

Category 1 = 0–4.9 percent; category 2 = 5.0–9.9 percent; category 3 = 10.0–19.9 percent; category 4 = 20–100 percent. Crowding (categories)

Category 1 = 0–4.9 percent; category 2 = 5.0–9.9 percent; category 3 = 10.0–19.9 percent; category 4 = 20–100 percent.

Low education (categories)

Category 1 = 0–14.9 percent; category 2 = 15.0–24.9 percent; category 3 = 25.0–39.9 percent; category 4 = 40–100 percent.

Townsend index (quintiles)

Massachusetts—

Block groups: quintile 1 = –5.531 to –2.468; quintile 2 = –2.467 to –1.331; quintile 3 = – 1.330 to 0.094; quintile 4 = 0.095 to 2.425; quintile 5 = 2.426 to 11.804.

Census tracts: quintile 1 = –8.123 to –2.797; quintile 2 = –2.796 to –1.596; quintile 3 = – 1.595 to –0.051; quintile 4 = –0.050 to 2.860; quintile 5 = 2.861 to 11.223.

Zip codes: quintile 1 = –7.864 to –2.388; quintile 2 = –2.387 to –1.411; quintile 3 = – 1.410 to –0.165; quintile 4 = –0.164 to 1.645; quintile 5 = 1.646 to 13.626.

Rhode Island—

Block groups: quintile 1 = –5.811 to –2.410; quintile 2 = –2.409 to –1.250; quintile 3 = – 1.249 to 0.162; quintile 4 = 0.163 to 2.293; quintile 5 = 2.294 to 9.832.

Census tracts: quintile 1 = –5.572 to –2.595; quintile 2 = –2.594 to –1.502; quintile 3 = – 1.501 to –0.078; quintile 4 = –0.077 to 2.793; quintile 5 = 2.794 to 9.103.

Zip codes: quintile 1 = –8.003 to –1.905; quintile 2 = –1.904 to –0.929; quintile 3 = – 0.928 to –0.246; quintile 4 = –0.245 to 2.301; quintile 5 = 2.302 to 10.060.

Index of Local Economic Resources (quintiles)

Massachusetts—

Block groups: quintile 1 = 0–6; quintile 2 = 7–11; quintile 3 = 12–15; quintile 4 = 16–20; quintile 5 = 21–27.

Census tracts: quintile 1 = 0–5; quintile 2 = 6–10; quintile 3 = 11–15; quintile 4 = 16–19; quintile 5 = 20–26. Zip codes: quintile 1 = 0–8; quintile 2 = 9–12; quintile 3 = 13–15; quintile 4 = 16–19; quintile 5 = 20–26.

Rhode Island—

Block groups: quintile 1 = 0–4; quintile 2 = 5–8; quintile 3 = 9–12; quintile 4 = 13–17; quintile 5 = 18–27.

Census tracts: quintile 1 = 0–4; quintile 2 = 5–8; quintile 3 = 9–12; quintile 4 = 13–16; quintile 5 = 17–26.

Zip codes: quintile 1 = 0–8; quintile 2 = 9–10; quintile 3 = 11–13; quintile 4 = 14–15; quintile 5 = 16–27.

SEP1* (categories)

Category 1: percent below poverty = >=20 percent, percent working class = >=75 percent, percent expensive homes = {–}.

Category 2: percent below poverty = >=20 percent, percent working class = 50–74 percent, percent expensive homes = <10 percent.

Category 3: percent below poverty = <20 percent, percent working class = >=75 percent, percent expensive homes = {–}.

Category 4: percent below poverty = <20 percent, percent working class = 50–74 percent, percent expensive homes = <10 percent.

Category 5: percent below poverty = {–}, percent working class = <50 percent, percent expensive homes = <10 percent.

Category 6: percent below poverty = {–}, percent working class = 50–74 percent, percent expensive homes = >=10 percent.

Category 7: percent below poverty = {–}, percent working class = < 50 percent, percent expensive homes = >=10 percent.

(Note: for percent poverty, categories 5–7 are effectively <20 percent; for percent expensive homes, categories 1 and 3 are effectively <10 percent.)

SEP index (quintiles)

Massachusetts— Block groups: quintile 1 = –16.524 to –2.975; quintile 2 = –2.974 to –1.099; quintile 3 = – 1.098 to 0.479; quintile 4 = 0.480 to 2.701; quintile 5 = 2.702 to 22.208.

Census tracts: quintile 1 = –13.768 to –3.265; quintile 2 = –3.264 to –1.153; quintile 3 = – 1.152 to 0.396; quintile 4 = 0.397 to 3.006; quintile 5 = 3.007 to 20.605.

Zip codes: quintile 1 = –14.165 to –3.122; quintile 2 = –3.121 to –0.956; quintile 3 = – 0.955 to 0.794; quintile 4 = 0.795 to 2.744; quintile 5 = 2.745 to 18.943.

Rhode Island—

Block groups: quintile 1 = –16.457 to –3.001; quintile 2 = –3.000 to –1.282; quintile 3 = – 1.281 to 0.630; quintile 4 = 0.631 to 2.966; quintile 5 = 2.967 to 17.356.

Census tracts: quintile 1 = –15.883 to –3.452; quintile 2 = –3.451 to –1.684; quintile 3 = – 1.683 to 0.388; quintile 4 = 0.389 to 3.767; quintile 5 = 3.768 to 12.140.

Zip codes: quintile 1 = –8.976 to –3.221; quintile 2 = –3.220 to –1.079; quintile 3 = – 1.078 to 0.411; quintile 4 = 0.412 to 2.834; quintile 5 = 2.835 to 13.497.

* SEP, socioeconomic position.

‡ In Rhode Island, analyses at the zip code level pertained only to categories 1–3, as there were no zip codes in category 4 (20–100 percent crowding).

Krieger et al.

Geographic Information Systems and Health Inequalities