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Educational Disparities in Mortality Between Adults Aged 50–64 and 66–79 Years, U.S.
RESEARCH ARTICLE
Educational Disparities in Mortality Between Adults Aged 50–64 and 66–79 Years, U.S. Jiemin Ma, PhD, MHS,1 Sean Altekruse, DVM, PhD,2 Candace Cosgrove, MPH,3 Farhad Islami, MD, PhD,1 Ahmedin Jemal, DVM, PhD1 Introduction: This study estimated differences in educational disparities in mortality between ages 50–64 and 66–79 years in the U.S. and explored factors contributing to the differences. Methods: Based on the follow-up of a nationally representative cohort in the National Longitudinal Mortality Study 2002–2011, relative differences in educational disparities (relative index of inequality) between people aged 50–64 and 66–79 years were calculated for deaths from all causes, cancer, cardiovascular disease, injuries, and other causes by sex and race/ethnicity. Analyses were conducted in 2016. Results: In all racial/ethnic-, sex-, and age-specific groups, death rates were higher among the least educated than the most educated groups for all causes combined and most specific causes except for injuries in non-Hispanic blacks. Among non-Hispanic whites, the relative index of inequality for all causes combined among the younger and older age groups was 5.6 (95% CI¼4.9, 6.5) and 2.8 (95% CI¼2.6, 3.0), respectively. Among non-Hispanic blacks, corresponding index values were 4.1 (95% CI¼3.6, 4.6) and 1.7 (95% CI¼1.6, 1.8). Larger disparities in the younger age group were also observed for cardiovascular disease, cancer, and other causes among non-Hispanic whites, nonHispanic blacks, and all races combined.
Conclusions: Educational disparities in mortality among non-Hispanic whites and blacks were 41%–61% lower in people aged 66–79 years than in those aged 50–64 years. Various factors may contribute to diminished disparities in the elderly, including differences in access to care, health perception, stress level, lifestyle, and health behaviors with advancing age and retirement. Am J Prev Med 2017;52(6):728–734. & 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
S
everal studies have documented larger educational disparities in working-aged Americans than in the elderly in the U.S., in part due to differences in access to health care for preventive and treatment services.1–3 Whereas U.S. residents aged Z65 years have near-universal healthcare coverage through Medicare, those aged o65 years do not have similar uniform healthcare coverage. Approximately 13% of these individuals were uninsured and did not have a routine provider of preventive and medical services in 2014.4 Other factors contributing to the difference in educational disparities in mortality between younger and older populations may include the changes in some social determinants with aging. For example, most Americans will experience changes in family income after 728 Am J Prev Med 2017;52(6):728–734
retirement, as well as some changes in health perception, lifestyle, stress level, and health behaviors, which in turn will affect their health and mortality.5–7 Highlighting these differences will have implications for reducing socioeconomic disparities in the U.S. However, some previous studies may have been limited by using From the 1Surveillance and Health Services Research Program, Intramural Research Department, American Cancer Society, Atlanta, Georgia; 2Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland; and 3National Longitudinal Mortality Study, U.S. Census Bureau, Suitland, Maryland Address correspondence to: Jiemin Ma, PhD, MHS, American Cancer Society, 250 Williams St., 6th Floor, Atlanta GA 30303. E-mail: jiemin. [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2017.02.008
& 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Ma et al / Am J Prev Med 2017;52(6):728–734
educational information on death certificates, which are reported to be inaccurate for the elderly and for some racial/ethnic groups.8 Therefore, in this study, selfreported educational attainment was used to estimate relative differences in race- and sex-specific educational disparities in mortality rates between adults aged 50–64 and 66–79 years for major causes of death in the National Longitudinal Mortality Study (NLMS), 2002–2011.
METHODS Data Sample This study was based on 1,807,970 person-years contributed by NLMS participants who were followed for vital status from 2002 through 2011. Sponsored by the National Cancer Institute, the National Heart, Lung, and Blood Institute, the National Institute on Aging, the National Center for Health Statistics, and the U.S. Census Bureau, NLMS is a national, longitudinal mortality study consisting of sociodemographic data from the Current Population Surveys, Annual Social and Economic Supplements, and a subset of the 1980 Census combined with death information.9 Vital status of participants was ascertained from time of survey through 2011 with a probabilistic match of NLMS records to the National Death Index, which captured cause of death from death certificates in the national vital statistics system. The matching of records to the National Death Index is an effective means of ascertaining mortality information using personal identifiers including social security number, name, date of birth, sex, race, marital status, state of birth, and state of residence10,11; ICD-10 codes12 were used to determine underlying cause of death. In this study, causes of death were categorized into four groups: cardiovascular disease (CVD); cancer; injuries (both intentional and unintentional); and other causes. These groups were chosen because they are major causes of death for ages 50–79 years. Specifically, CVD was identified by codes I00– I78, cancer was identified by codes C00–C97, and injuries were identified by codes V01–Y98. Other causes of death were predominantly chronic obstructive respiratory disease (ICD-10 codes: J40– J47); diabetes mellitus (ICD-10 codes: E10–E14); mental disorders (ICD-10 codes: F01–F99); Alzheimer’s disease (ICD-10 code: G30); and influenza and pneumonia (ICD-10 codes: J10–J18). Based on self-reported number of completed school years, participants’ educational attainment was classified into four categories: o12 years, 12 years, 13–15 years, and Z16 years. Analyses were restricted to individuals aged 50–64 and 66–79 years because: 1. Deaths occurring before age 50 years may have considerably different biology from those occurring at age 50–79 years. 2. Individuals aged Z80 years are less likely to receive aggressive treatments compared with younger individuals owing to comorbidities and attainment of the typical life span.13 3. People aged 65 years will not have a full year enrollment in Medicare if they die at age 65 years.
Statistical Analysis Population-weighted mortality rates per 100,000 person-years and 95% CIs were calculated by educational attainment for all races June 2017
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combined, non-Hispanic whites, and non-Hispanic blacks with additional stratification by age group (attained age of 50–64 and 66–79 years) and sex. Specially, respondents’ age was aged up 1 year every year until death or end of follow-up (2011). For example, a person aged 45 years will enter the age cohort of 50–64 years 5 years later and a person aged 79 years will exit the age cohort of 66–79 years in the following year. Given the small number of deaths in some educational categories, results for Hispanics and for other racial/ethnic groups are reported in Appendix Table 1 (available online). Based on the populationweighted mortality rates in each educational group, the relative index of inequality (RII) and 95% CI were estimated separately for people aged 50–64 and 66–79 years by Poisson regression modeling, in which the cumulative distribution of educational levels (from high to low) in the population was used as independent variable. As such, the RII measures the relative risk of death comparing those at the lowest end of the educational hierarchy to those at the highest end. An RII 41 indicates that the risk of death is higher in less educated than more educated individuals. The relative difference in socioeconomic disparity in mortality between age 50–64 and 66–79 years was calculated using the formula (LogRII[age 50–64 years] – LogRII[age 66–79 years]) / (LogRII[age 50–64 years]). The Delta method14 was used to estimate the 95% CIs for relative differences in educational disparities. All statistical analyses were conducted in 2016 using SAS, version 9.4, and all statistical tests were two-sided. Statistical significance was set at po0.05.
RESULTS Table 1 shows the death rate and RII for all causes combined by educational attainment, age, sex, and race/ ethnicity. Higher death rates for less educated than more educated people were observed in each sex, racial/ethnic, and age group. The magnitude of the excess risk associated with educational attainment was always larger in individuals aged 50–64 years than in those aged 66–79 years. For example, the overall RII was 3.7 (95% CI¼3.3, 4.3) among people aged 50–64 years, compared with 2.4 (95% CI¼2.2, 2.5) for those aged 66–79 years. The corresponding RIIs were 5.6 (95% CI¼4.9, 6.5) and 2.8 (95% CI¼2.6, 3.0) for non-Hispanic whites and 4.1 (95% CI¼3.6, 4.6) and 1.7 (95% CI¼1.6, 1.8) for non-Hispanic blacks. In comparison with non-Hispanic whites and non-Hispanic blacks, mortality rates and RIIs were lower among Hispanics and Asian and Pacific Islanders (Appendix Table 1, available online). The person-years of follow-up for each group (by sex, race/ethnicity, education, and age group) are listed in Appendix Table 2 (available online). Table 2 shows educational disparities in death rates for selected major causes of death by age, race/ethnicity, and sex. A higher risk of death for less educated than more educated individuals was observed in each sex, racial/ ethnic, and age group for all major causes with one exception. Specifically, there was no difference in risk of
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Table 1. All-Cause Mortality (1/100,000) and Relative Index of Inequality (RII) by Educational Attainmenta Years of education Z16 years
13–15 years
o12 years
12 years
Rate (95% CI)
Deaths
Rate (95% CI)
Deaths
Rate (95% CI)
Deaths
Rate (95% CI)
RII (95% CI)
Men and women All races combined 50–64 years
1,248
1,863
722 (671, 777) 2,364 (2,270, 2,461)
1,447
1,562
560 (514, 608) 2,093 (2,005, 2,185)
2,690
66–79 years
346 (311, 385) 1,450 (1,377, 1,527)
1,038 (976, 1,103) 3,081 (2,973, 3,192)
3.7 (3.3, 4.3) 2.4 (2.2, 2.5)
552 (507, 600) 2,134 (2,045, 2,227)
1,848
724 (672, 779) 2,409 (2,314, 2,507)
764
1,359 (1,288, 1,433) 3,485 (3,370, 3,603)
5.6 (4.9, 6.5) 2.8 (2.6, 3.0)
772 (718, 828) 2,501 (2,404, 2,601)
473
1,459 (1,385, 1,535) 3,486 (3,371, 3,604)
4.1 (3.6, 4.6) 1.7 (1.6, 1.8)
1,203 (1,136, 1,273) 3,754 (3,635, 3,876)
3.7 (3.3, 4.2) 2.5 (2.3, 2.6)
1,561 (1,484, 1,640) 4,105 (3,980, 4,232)
5.6 (4.9, 6.3) 2.7 (2.5, 2.9)
1,673 (1,594, 1,755) 4,234 (4,108, 4,364)
3.4 (3.0, 3.7) 1.8 (1.7, 1.9)
877 (820, 937)
3.8 (3.3, 4.4)
Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years
944 1,207
125
66–79 years
176
Men All races combined 50–64 years
776
66–79 years
1,026
Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years
582 818
72
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66–79 years
89
Women All races combined 50–64 years
472
2,128
343 (308, 382) 1,454 (1,380, 1,530)
1,307
448 (407, 491) 2,220 (2,128, 2,314)
292
1,678
243
402 (364, 444) 1,677 (1,597, 1,759)
1,048
389 (351, 430) 1,697 (1,617, 1,779)
734
1,139
897
638 (589, 689) 2,503 (2,406, 2,603)
155
285 (253, 320)
815
129
4,374
3,394
474
678 (628, 731) 2,597 (2,498, 2,699)
1,602
666 (617, 719) 2,659 (2,559, 2,762)
1,109
906 (848, 967) 3,344 (3,232, 3,459)
269
457 (416, 501)
1,088
2,199
1,699
237
996 (935, 1,060) 2,581 (2,482, 2,682)
955 (895, 1,018) 3,001 (2,894, 3,110) 959 (899, 1,022) 3,062 (2,954, 3,172)
3,767
2,234
326 754
822 2,048
449 1,229
1,303 (1,233, 1,376) 3,398 (3,285, 3,515)
176
526 (482, 573)
625
394
(continued on next page)
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Deaths
Sex/race/age
4.8 (4.2, 5.5) 1.7 (1.5, 1.8) 360
1,273 (1,204, 1,345) 2,944 (2,839, 3,053) 150
237
741 (688, 796) 2,081 (1,993, 2,173) 204
DISCUSSION
a
87 66–79 years
Based on the National Longitudinal Mortality Study (2002–2011).
114
53 Non-Hispanic black 50–64 years
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death due to injuries among non-Hispanic blacks. Similar to the results for all causes combined, larger RIIs in younger than in older age groups were found in all sex and racial/ethnic groups for cancer, CVD, and other causes. With the exception of cancer, the highest RIIs for specific causes of death occurred among non-Hispanic whites aged 50–64 years. These patterns persisted among both men and women. The largest RII was for othercause mortality among non-Hispanic white women aged 50–64 years (12.6, 95% CI¼9.5, 16.7). Figure 1 depicts the relative differences in educational disparities between people aged 50–64 and 66–79 years by cause of death and race/ethnicity. The educational disparity in all-cause mortality was 34.6% (95% CI¼28.0%, 41.2%) higher in age 50–64 years than in age 66–79 years for all races combined. For non-Hispanic whites and non-Hispanic blacks, the relative difference in disparity for all causes combined was 41.2% (95% CI¼34.1%, 48.2%) and 60.7% (95% CI¼45.5%, 75.9%), respectively. Larger disparities in the younger age group were also found for deaths from CVD; cancer; and other causes (excluding CVD, cancer, and injuries), for which the relative differences for all races combined were 22.4% (95% CI¼9.2%, 35.6%); 42.1% (95% CI¼28.4%, 55.8%); and 45.9% (95% CI¼33.7%, 58.1%), respectively. No significant relative differences were found for injuries.
670 (620, 723) 1,977 (1,891, 2,067) 137
1,005 1,695 781 389 66–79 years
309 (276, 346) 2,019 (1,932, 2,109)
5.6 (4.8, 6.5) 3.1 (2.9, 3.3) 1,142 (1,077, 1,211) 2,960 (2,854, 3,068) 315 739 362 Non-Hispanic white 50–64 years
291 (259, 327) 1,108 (1,044, 1,176)
573
452 (411, 495) 1,736 (1,655, 1,820)
525 (481, 572) 1,987 (1,901, 2,077)
2.5 (2.3, 2.7) 2,555 (2,457, 2,656) 1,719 2,175 536 66–79 years
1,143 (1,078, 1,212)
989
1,711 (1,631, 1,794)
1,952 (1,867, 2,041)
Rate (95% CI) Rate (95% CI) Deaths Rate (95% CI) Deaths Sex/race/age
Z16 years
Deaths
Rate (95% CI)
12 years
June 2017
13–15 years
Years of education
Table 1. All-Cause Mortality (1/100,000) and Relative Index of Inequality (RII) by Educational Attainmenta (continued)
Deaths
o12 years
RII (95% CI)
Ma et al / Am J Prev Med 2017;52(6):728–734
Based on a nationally representative cohort, educational disparities in all-cause mortality for ages 66–79 years were about 41% and 61% lower than those for ages 50–64 years in non-Hispanic whites and non-Hispanic blacks, respectively. Larger relative disparities in the younger age group were also found for deaths from CVD and cancer in these two racial/ethnic groups. In line with this study, larger socioeconomic disparities in mortality among younger age groups have been reported in previous studies.3,15 The consistency of these differences over time underscores the importance of reducing socioeconomic disparities among workingaged Americans. These results are of greater public health significance in light of increased death rates among some middle-aged Americans in recent years.16 Differences in a range of socioeconomic factors may have contributed to the differences in educational disparities in mortality between these two age groups. Most Americans retire at age 65 years and will subsequently experience changes in family income. With aging, the elderly are also likely to experience changes in lifestyles, stress levels, health behaviors, and mental health.5–7 It has been reported that retirement has a beneficial impact on health through behavior changes, such as
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Table 2. Educational Disparities in Death Rates by Cause of Death, Age, Race/Ethnicity, and Sexa Sex/race/age Men and women All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years Men All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years Women All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years
CVD, RII (95% CI)
Cancer, RII (95% CI)
Injuries, RII (95% CI)
Other causes, RII (95% CI)
3.7 (2.9, 4.8) 2.8 (2.5, 3.2)
2.8 (2.2, 3.5) 1.8 (1.6, 2.1)
2.1 (1.3, 3.4) 2.1 (1.4, 3.1)
6.1 (4.7, 7.9) 2.7 (2.4, 3.0)
5.3 (4.1, 7.0) 3.1 (2.8, 3.6)
4.0 (3.2, 5.0) 2.1 (1.9, 2.4)
3.4 (2.1, 5.3) 2.8 (1.9, 4.2)
10.3 (7.9, 13.4) 3.2 (2.8, 3.6)
3.3 (2.7, 4.0) 2.7 (2.4, 3.0)
5.8 (4.6, 7.3) 1.6 (1.4, 1.8)
1.1 (0.7, 1.8) 1.1 (0.8, 1.6)
4.7 (3.8, 5.8) 1.3 (1.1, 1.4)
3.2 (2.5, 3.9) 3.0 (2.7, 3.4)
3.5 (2.8, 4.4) 1.8 (1.7, 2.1)
2.4 (1.6, 3.6) 2.2 (1.5, 3.1)
5.5 (4.3, 7.0) 2.7 (2.4, 3.0)
4.6 (3.7, 5.8) 3.3 (3.0, 3.7)
5.0 (4.1, 6.3) 2.0 (1.8, 2.2)
3.9 (2.7, 5.8) 2.7 (1.9, 3.7)
8.7 (6.8, 11.1) 3.0 (2.7, 3.3)
3.3 (2.8, 3.9) 2.7 (2.4, 2.9)
5.1 (4.2, 6.2) 1.7 (1.5, 1.9)
1.0 (0.6, 1.5) 0.8 (0.6, 1.2)
2.9 (2.4, 3.6) 1.3 (1.2, 1.5)
5.3 (3.8, 7.3) 2.7 (2.3, 3.1)
2.1 (1.7, 2.7) 1.9 (1.7, 2.2)
1.6 (0.8, 3.1) 2.5 (1.6, 4.0)
7.2 (5.4, 9.6) 2.9 (2.6, 3.4)
7.2 (5.1, 10.1) 3.0 (2.7, 3.5)
3.0 (2.4, 3.8) 2.5 (2.2, 2.8)
2.2 (1.2, 4.1) 4.3 (2.7, 7.0)
12.6 (9.5, 16.7) 3.8 (3.4, 4.4)
3.1 (2.5, 3.9) 2.6 (2.3, 2.9)
6.4 (4.9, 8.3) 1.5 (1.3, 1.7)
0.9 (0.5, 1.6) 0.8 (0.6, 1.2)
7.8 (6.1, 9.9) 1.2 (1.1, 1.3)
a
Based on the National Longitudinal Mortality Study (2002–2011). CVD, cardiovascular disease; RII, Relative Index of Inequality.
Figure 1. Relative differences in educational disparities between individuals aged 50–64 and 66–79 years, men and women combined. Note: The error bar represents 95% CI. NHB, non-Hispanic black; NHW, non-Hispanic white.
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Ma et al / Am J Prev Med 2017;52(6):728–734 17
smoking cessation and increased physical activity. Improved health and life satisfaction after retirement18 may have partly accounted for the diminished educational disparities among those aged 66–79 years. In addition, increased access to health care through the automatic eligibility for Medicare coverage at age 65 years may also have contributed to the decreased disparities in the elderly. In contrast to near universal health insurance coverage by Medicare for ages Z65 years, more than 40% of adults aged o65 years with less than a high school education did not have health insurance in 2010.19 Partly because of lack of health insurance, socioeconomically disadvantaged people are less likely to seek preventive services and to receive timely or high-quality treatment.20 For example, only 39% of people aged 50–75 years with less than high school education were current with their colorectal cancer screening compared with 72% in those with at least a college degree in 2010.19 Beginning in 2010, the federal government implemented the Affordable Care Act (ACA) to address this longstanding problem by improving access to quality health care to all Americans through various provisions, which include expansion of dependent coverage until age 26 years, removal of cost as a barrier to certain preventive health services, expansion of state Medicaid programs, and health insurance exchange subsidies.21 Early results have shown that these provisions have the potential to bridge the gap of socioeconomic health disparities in working-aged adults. An estimated 20 million Americans have gained health insurance since the open enrollment of ACA started in October 2013, with the largest gains among socioeconomically disadvantaged populations in Medicaid expansion states.22–24 In addition, state Medicaid expansions have been associated with improved access to primary care and medications, affordability, utilization of some types of health care, and health.23,25,26 A recent study27 suggests that ACA-dependent coverage expansion increases uptake rate of cervical cancer screening among ACA-dependent coverage beneficiaries. Although the passage of ACA provides an opportunity to achieve equal health care for all in the U.S., the success of ACA in reducing health disparities among U.S. populations will largely hinge on the extent of utilization of health services covered by the ACA among low-SES populations. Healthcare providers and health educators could play a major role on enhancing the utilization of care among the disadvantaged segment of the U.S. population.
Limitations Findings from this study should be interpreted within the context of some limitations. First, this study was not June 2017
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aimed to test the causal relationship between health insurance and educational disparity but to highlight the differences in educational disparities in mortality between two age groups and discuss what factors, including differences in access to health care, may have contributed to the observed results. Second, as the authors only used education as a marker of SES to measure disparities, this study does not capture the whole spectrum of socioeconomic disparities in mortality. However, as education shapes many other social determinants, such as income, occupation, and wealth, the findings could have implications for decreasing health disparities related to a spectrum of SES measures. Third, some of the differences in educational disparity between the groups aged 50–64 and 66–79 years may be due to selective survival of individuals with healthier behaviors.28 As a result, one would expect to see diminished association between SES and mortality with advancing age. However, the contribution of selective survival is expected to be small in the present study, as the authors excluded deaths occurring after age 79 years from analysis.
CONCLUSIONS Educational disparities in mortality among non-Hispanic whites and blacks were 41%–61% lower in people aged 66– 79 years than in those aged 50–64 years. A range of social factors may have contributed to the differential disparities by age, including differences in access to care, health perception, stress level, lifestyle, and health behaviors with advancing age and retirement. Further research is needed to reveal the underlying reasons for diminished educational disparities in mortality after age 65 years.
ACKNOWLEDGMENTS Dr. Ma and Ms. Cosgrove had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Jemal, Ma. Acquisition, analysis, or interpretation of data: all authors. Statistical analysis: Ma, Cosgrove. Drafting of the manuscript: Ma, Jemal, Atlekruse. Critical revision of the manuscript for important intellectual content: all authors. Study supervision: Jemal. This work was supported by the Intramural Research Department of the American Cancer Society. The American Cancer Society had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. This paper is released to inform interested parties of research and to encourage discussion. Any views expressed on statistical, methodologic, technical, or operational issues are those of the authors and not necessarily those of the U.S. Census Bureau or the American Cancer Society.
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No financial disclosures were reported by the authors of this paper. 14.
SUPPLEMENTAL MATERIAL Supplemental materials associated with this article can be found in the online version at http://dx.doi.org/10.1016/j. amepre.2017.02.008.
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Semin Radiat Oncol. 2012;22(4):265–271. http://dx.doi.org/10.1016/j. semradonc.2012.05.002. Oehlert GW. A note on the Delta Method. Am Stat. 1992;46(1):27–29. http://dx.doi.org/10.1080/00031305.1992.10475842. Beckett M. Converging health inequalities in later life—an artifact of mortality selection. J Health Soc Behav. 2000;41(1):106–119. http://dx. doi.org/10.2307/2676363. Case A, Deaton A. Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proc Natl Acad Sci U S A. 2015;112(49):15078–15083. http://dx.doi.org/10.1073/pnas. 1518393112. Insler M. The health consequences of retirement. J Hum Resour. 2014;49(1):195–233. http://dx.doi.org/10.3368/jhr.49.1.195. Gorry A, Gorry D, Slavov S. Does retirement improve health and life satisfaction? NBER Working Paper no. 21326; 2015. https://pdfs. semanticscholar.org/97f9/bf106e09e1ac927b57b6bb1fff721d7bf2b0.pdf. CDC. CDC Health Disparities and Inequalities Report—United States, 2013. MMWR Surveill Summ. 2013;62(suppl 3):1–186. Adler NE, Newman K. Socioeconomic disparities in health: pathways and policies. Health Aff (Millwood). 2002;21(2):60–76. http://dx.doi. org/10.1377/hlthaff.21.2.60. U.S. DHHS. Key features of the Affordable Care Act by year. www.hhs. gov/healthcare/facts-and-features/key-features-of-aca-by-year/index. html#2013. Accessed February 29, 2016. Blumenthal D, Abrams M, Nuzum R. The Affordable Care Act at 5 years. N Engl J Med. 2015;372(25):2451–2458. http://dx.doi.org/ 10.1056/NEJMhpr1503614. Sommers BD, Gunja MZ, Finegold K, Musco T. Changes in selfreported insurance coverage, access to care, and health under the Affordable Care Act. JAMA. 2015;314(4):366–374. http://dx.doi.org/ 10.1001/jama.2015.8421. Frean M, Gruber J, Sommers BD. Disentangling the ACA's coverage effects—lessons for policymakers. N Engl J Med. 2016;375:1605–1608. http://dx.doi.org/10.1056/NEJMp1609016. Sommers BD, Baicker K, Epstein AM. Mortality and access to care among adults after state Medicaid expansions. N Engl J Med. 2012; 367(11):1025–1034. http://dx.doi.org/10.1056/NEJMsa1202099. Wherry LR, Miller S. Early coverage, access, utilization, and health effects associated with the Affordable Care Act Medicaid expansions: a quasi-experimental study. Ann Intern Med. 2016;164(12):795–803. http://dx.doi.org/10.7326/M15-2234. Robbins AS, Han X, Ward EM, Simard EP, Zheng Z, Jemal A. Association between the Affordable Care Act dependent coverage expansion and cervical cancer stage and treatment in young women. JAMA. 2015;314 (20):2189–2191. http://dx.doi.org/10.1001/jama.2015.10546. Zajacova A, Burgard SA. Healthier, wealthier, and wiser: a demonstration of compositional changes in aging cohorts due to selective mortality. Popul Res Policy Rev. 2013;32(3):311–324. http://dx.doi.org/ 10.1007/s11113-013-9273-x.
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Educational Disparities in Mortality Between Adults Aged 50–64 and 66–79 Years, U.S. Jiemin Ma, PhD, MHS,1 Sean Altekruse, DVM, PhD,2 Candace Cosgrove, MPH,3 Farhad Islami, MD, PhD,1 Ahmedin Jemal, DVM, PhD1 Introduction: This study estimated differences in educational disparities in mortality between ages 50–64 and 66–79 years in the U.S. and explored factors contributing to the differences. Methods: Based on the follow-up of a nationally representative cohort in the National Longitudinal Mortality Study 2002–2011, relative differences in educational disparities (relative index of inequality) between people aged 50–64 and 66–79 years were calculated for deaths from all causes, cancer, cardiovascular disease, injuries, and other causes by sex and race/ethnicity. Analyses were conducted in 2016. Results: In all racial/ethnic-, sex-, and age-specific groups, death rates were higher among the least educated than the most educated groups for all causes combined and most specific causes except for injuries in non-Hispanic blacks. Among non-Hispanic whites, the relative index of inequality for all causes combined among the younger and older age groups was 5.6 (95% CI¼4.9, 6.5) and 2.8 (95% CI¼2.6, 3.0), respectively. Among non-Hispanic blacks, corresponding index values were 4.1 (95% CI¼3.6, 4.6) and 1.7 (95% CI¼1.6, 1.8). Larger disparities in the younger age group were also observed for cardiovascular disease, cancer, and other causes among non-Hispanic whites, nonHispanic blacks, and all races combined.
Conclusions: Educational disparities in mortality among non-Hispanic whites and blacks were 41%–61% lower in people aged 66–79 years than in those aged 50–64 years. Various factors may contribute to diminished disparities in the elderly, including differences in access to care, health perception, stress level, lifestyle, and health behaviors with advancing age and retirement. Am J Prev Med 2017;52(6):728–734. & 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
INTRODUCTION
S
everal studies have documented larger educational disparities in working-aged Americans than in the elderly in the U.S., in part due to differences in access to health care for preventive and treatment services.1–3 Whereas U.S. residents aged Z65 years have near-universal healthcare coverage through Medicare, those aged o65 years do not have similar uniform healthcare coverage. Approximately 13% of these individuals were uninsured and did not have a routine provider of preventive and medical services in 2014.4 Other factors contributing to the difference in educational disparities in mortality between younger and older populations may include the changes in some social determinants with aging. For example, most Americans will experience changes in family income after 728 Am J Prev Med 2017;52(6):728–734
retirement, as well as some changes in health perception, lifestyle, stress level, and health behaviors, which in turn will affect their health and mortality.5–7 Highlighting these differences will have implications for reducing socioeconomic disparities in the U.S. However, some previous studies may have been limited by using From the 1Surveillance and Health Services Research Program, Intramural Research Department, American Cancer Society, Atlanta, Georgia; 2Division of Cancer Control and Population Sciences, National Cancer Institute, Rockville, Maryland; and 3National Longitudinal Mortality Study, U.S. Census Bureau, Suitland, Maryland Address correspondence to: Jiemin Ma, PhD, MHS, American Cancer Society, 250 Williams St., 6th Floor, Atlanta GA 30303. E-mail: jiemin. [email protected]. 0749-3797/$36.00 http://dx.doi.org/10.1016/j.amepre.2017.02.008
& 2017 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.
Ma et al / Am J Prev Med 2017;52(6):728–734
educational information on death certificates, which are reported to be inaccurate for the elderly and for some racial/ethnic groups.8 Therefore, in this study, selfreported educational attainment was used to estimate relative differences in race- and sex-specific educational disparities in mortality rates between adults aged 50–64 and 66–79 years for major causes of death in the National Longitudinal Mortality Study (NLMS), 2002–2011.
METHODS Data Sample This study was based on 1,807,970 person-years contributed by NLMS participants who were followed for vital status from 2002 through 2011. Sponsored by the National Cancer Institute, the National Heart, Lung, and Blood Institute, the National Institute on Aging, the National Center for Health Statistics, and the U.S. Census Bureau, NLMS is a national, longitudinal mortality study consisting of sociodemographic data from the Current Population Surveys, Annual Social and Economic Supplements, and a subset of the 1980 Census combined with death information.9 Vital status of participants was ascertained from time of survey through 2011 with a probabilistic match of NLMS records to the National Death Index, which captured cause of death from death certificates in the national vital statistics system. The matching of records to the National Death Index is an effective means of ascertaining mortality information using personal identifiers including social security number, name, date of birth, sex, race, marital status, state of birth, and state of residence10,11; ICD-10 codes12 were used to determine underlying cause of death. In this study, causes of death were categorized into four groups: cardiovascular disease (CVD); cancer; injuries (both intentional and unintentional); and other causes. These groups were chosen because they are major causes of death for ages 50–79 years. Specifically, CVD was identified by codes I00– I78, cancer was identified by codes C00–C97, and injuries were identified by codes V01–Y98. Other causes of death were predominantly chronic obstructive respiratory disease (ICD-10 codes: J40– J47); diabetes mellitus (ICD-10 codes: E10–E14); mental disorders (ICD-10 codes: F01–F99); Alzheimer’s disease (ICD-10 code: G30); and influenza and pneumonia (ICD-10 codes: J10–J18). Based on self-reported number of completed school years, participants’ educational attainment was classified into four categories: o12 years, 12 years, 13–15 years, and Z16 years. Analyses were restricted to individuals aged 50–64 and 66–79 years because: 1. Deaths occurring before age 50 years may have considerably different biology from those occurring at age 50–79 years. 2. Individuals aged Z80 years are less likely to receive aggressive treatments compared with younger individuals owing to comorbidities and attainment of the typical life span.13 3. People aged 65 years will not have a full year enrollment in Medicare if they die at age 65 years.
Statistical Analysis Population-weighted mortality rates per 100,000 person-years and 95% CIs were calculated by educational attainment for all races June 2017
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combined, non-Hispanic whites, and non-Hispanic blacks with additional stratification by age group (attained age of 50–64 and 66–79 years) and sex. Specially, respondents’ age was aged up 1 year every year until death or end of follow-up (2011). For example, a person aged 45 years will enter the age cohort of 50–64 years 5 years later and a person aged 79 years will exit the age cohort of 66–79 years in the following year. Given the small number of deaths in some educational categories, results for Hispanics and for other racial/ethnic groups are reported in Appendix Table 1 (available online). Based on the populationweighted mortality rates in each educational group, the relative index of inequality (RII) and 95% CI were estimated separately for people aged 50–64 and 66–79 years by Poisson regression modeling, in which the cumulative distribution of educational levels (from high to low) in the population was used as independent variable. As such, the RII measures the relative risk of death comparing those at the lowest end of the educational hierarchy to those at the highest end. An RII 41 indicates that the risk of death is higher in less educated than more educated individuals. The relative difference in socioeconomic disparity in mortality between age 50–64 and 66–79 years was calculated using the formula (LogRII[age 50–64 years] – LogRII[age 66–79 years]) / (LogRII[age 50–64 years]). The Delta method14 was used to estimate the 95% CIs for relative differences in educational disparities. All statistical analyses were conducted in 2016 using SAS, version 9.4, and all statistical tests were two-sided. Statistical significance was set at po0.05.
RESULTS Table 1 shows the death rate and RII for all causes combined by educational attainment, age, sex, and race/ ethnicity. Higher death rates for less educated than more educated people were observed in each sex, racial/ethnic, and age group. The magnitude of the excess risk associated with educational attainment was always larger in individuals aged 50–64 years than in those aged 66–79 years. For example, the overall RII was 3.7 (95% CI¼3.3, 4.3) among people aged 50–64 years, compared with 2.4 (95% CI¼2.2, 2.5) for those aged 66–79 years. The corresponding RIIs were 5.6 (95% CI¼4.9, 6.5) and 2.8 (95% CI¼2.6, 3.0) for non-Hispanic whites and 4.1 (95% CI¼3.6, 4.6) and 1.7 (95% CI¼1.6, 1.8) for non-Hispanic blacks. In comparison with non-Hispanic whites and non-Hispanic blacks, mortality rates and RIIs were lower among Hispanics and Asian and Pacific Islanders (Appendix Table 1, available online). The person-years of follow-up for each group (by sex, race/ethnicity, education, and age group) are listed in Appendix Table 2 (available online). Table 2 shows educational disparities in death rates for selected major causes of death by age, race/ethnicity, and sex. A higher risk of death for less educated than more educated individuals was observed in each sex, racial/ ethnic, and age group for all major causes with one exception. Specifically, there was no difference in risk of
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Table 1. All-Cause Mortality (1/100,000) and Relative Index of Inequality (RII) by Educational Attainmenta Years of education Z16 years
13–15 years
o12 years
12 years
Rate (95% CI)
Deaths
Rate (95% CI)
Deaths
Rate (95% CI)
Deaths
Rate (95% CI)
RII (95% CI)
Men and women All races combined 50–64 years
1,248
1,863
722 (671, 777) 2,364 (2,270, 2,461)
1,447
1,562
560 (514, 608) 2,093 (2,005, 2,185)
2,690
66–79 years
346 (311, 385) 1,450 (1,377, 1,527)
1,038 (976, 1,103) 3,081 (2,973, 3,192)
3.7 (3.3, 4.3) 2.4 (2.2, 2.5)
552 (507, 600) 2,134 (2,045, 2,227)
1,848
724 (672, 779) 2,409 (2,314, 2,507)
764
1,359 (1,288, 1,433) 3,485 (3,370, 3,603)
5.6 (4.9, 6.5) 2.8 (2.6, 3.0)
772 (718, 828) 2,501 (2,404, 2,601)
473
1,459 (1,385, 1,535) 3,486 (3,371, 3,604)
4.1 (3.6, 4.6) 1.7 (1.6, 1.8)
1,203 (1,136, 1,273) 3,754 (3,635, 3,876)
3.7 (3.3, 4.2) 2.5 (2.3, 2.6)
1,561 (1,484, 1,640) 4,105 (3,980, 4,232)
5.6 (4.9, 6.3) 2.7 (2.5, 2.9)
1,673 (1,594, 1,755) 4,234 (4,108, 4,364)
3.4 (3.0, 3.7) 1.8 (1.7, 1.9)
877 (820, 937)
3.8 (3.3, 4.4)
Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years
944 1,207
125
66–79 years
176
Men All races combined 50–64 years
776
66–79 years
1,026
Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years
582 818
72
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66–79 years
89
Women All races combined 50–64 years
472
2,128
343 (308, 382) 1,454 (1,380, 1,530)
1,307
448 (407, 491) 2,220 (2,128, 2,314)
292
1,678
243
402 (364, 444) 1,677 (1,597, 1,759)
1,048
389 (351, 430) 1,697 (1,617, 1,779)
734
1,139
897
638 (589, 689) 2,503 (2,406, 2,603)
155
285 (253, 320)
815
129
4,374
3,394
474
678 (628, 731) 2,597 (2,498, 2,699)
1,602
666 (617, 719) 2,659 (2,559, 2,762)
1,109
906 (848, 967) 3,344 (3,232, 3,459)
269
457 (416, 501)
1,088
2,199
1,699
237
996 (935, 1,060) 2,581 (2,482, 2,682)
955 (895, 1,018) 3,001 (2,894, 3,110) 959 (899, 1,022) 3,062 (2,954, 3,172)
3,767
2,234
326 754
822 2,048
449 1,229
1,303 (1,233, 1,376) 3,398 (3,285, 3,515)
176
526 (482, 573)
625
394
(continued on next page)
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Deaths
Sex/race/age
4.8 (4.2, 5.5) 1.7 (1.5, 1.8) 360
1,273 (1,204, 1,345) 2,944 (2,839, 3,053) 150
237
741 (688, 796) 2,081 (1,993, 2,173) 204
DISCUSSION
a
87 66–79 years
Based on the National Longitudinal Mortality Study (2002–2011).
114
53 Non-Hispanic black 50–64 years
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death due to injuries among non-Hispanic blacks. Similar to the results for all causes combined, larger RIIs in younger than in older age groups were found in all sex and racial/ethnic groups for cancer, CVD, and other causes. With the exception of cancer, the highest RIIs for specific causes of death occurred among non-Hispanic whites aged 50–64 years. These patterns persisted among both men and women. The largest RII was for othercause mortality among non-Hispanic white women aged 50–64 years (12.6, 95% CI¼9.5, 16.7). Figure 1 depicts the relative differences in educational disparities between people aged 50–64 and 66–79 years by cause of death and race/ethnicity. The educational disparity in all-cause mortality was 34.6% (95% CI¼28.0%, 41.2%) higher in age 50–64 years than in age 66–79 years for all races combined. For non-Hispanic whites and non-Hispanic blacks, the relative difference in disparity for all causes combined was 41.2% (95% CI¼34.1%, 48.2%) and 60.7% (95% CI¼45.5%, 75.9%), respectively. Larger disparities in the younger age group were also found for deaths from CVD; cancer; and other causes (excluding CVD, cancer, and injuries), for which the relative differences for all races combined were 22.4% (95% CI¼9.2%, 35.6%); 42.1% (95% CI¼28.4%, 55.8%); and 45.9% (95% CI¼33.7%, 58.1%), respectively. No significant relative differences were found for injuries.
670 (620, 723) 1,977 (1,891, 2,067) 137
1,005 1,695 781 389 66–79 years
309 (276, 346) 2,019 (1,932, 2,109)
5.6 (4.8, 6.5) 3.1 (2.9, 3.3) 1,142 (1,077, 1,211) 2,960 (2,854, 3,068) 315 739 362 Non-Hispanic white 50–64 years
291 (259, 327) 1,108 (1,044, 1,176)
573
452 (411, 495) 1,736 (1,655, 1,820)
525 (481, 572) 1,987 (1,901, 2,077)
2.5 (2.3, 2.7) 2,555 (2,457, 2,656) 1,719 2,175 536 66–79 years
1,143 (1,078, 1,212)
989
1,711 (1,631, 1,794)
1,952 (1,867, 2,041)
Rate (95% CI) Rate (95% CI) Deaths Rate (95% CI) Deaths Sex/race/age
Z16 years
Deaths
Rate (95% CI)
12 years
June 2017
13–15 years
Years of education
Table 1. All-Cause Mortality (1/100,000) and Relative Index of Inequality (RII) by Educational Attainmenta (continued)
Deaths
o12 years
RII (95% CI)
Ma et al / Am J Prev Med 2017;52(6):728–734
Based on a nationally representative cohort, educational disparities in all-cause mortality for ages 66–79 years were about 41% and 61% lower than those for ages 50–64 years in non-Hispanic whites and non-Hispanic blacks, respectively. Larger relative disparities in the younger age group were also found for deaths from CVD and cancer in these two racial/ethnic groups. In line with this study, larger socioeconomic disparities in mortality among younger age groups have been reported in previous studies.3,15 The consistency of these differences over time underscores the importance of reducing socioeconomic disparities among workingaged Americans. These results are of greater public health significance in light of increased death rates among some middle-aged Americans in recent years.16 Differences in a range of socioeconomic factors may have contributed to the differences in educational disparities in mortality between these two age groups. Most Americans retire at age 65 years and will subsequently experience changes in family income. With aging, the elderly are also likely to experience changes in lifestyles, stress levels, health behaviors, and mental health.5–7 It has been reported that retirement has a beneficial impact on health through behavior changes, such as
Ma et al / Am J Prev Med 2017;52(6):728–734
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Table 2. Educational Disparities in Death Rates by Cause of Death, Age, Race/Ethnicity, and Sexa Sex/race/age Men and women All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years Men All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years Women All races combined 50–64 years 66–79 years Non-Hispanic white 50–64 years 66–79 years Non-Hispanic black 50–64 years 66–79 years
CVD, RII (95% CI)
Cancer, RII (95% CI)
Injuries, RII (95% CI)
Other causes, RII (95% CI)
3.7 (2.9, 4.8) 2.8 (2.5, 3.2)
2.8 (2.2, 3.5) 1.8 (1.6, 2.1)
2.1 (1.3, 3.4) 2.1 (1.4, 3.1)
6.1 (4.7, 7.9) 2.7 (2.4, 3.0)
5.3 (4.1, 7.0) 3.1 (2.8, 3.6)
4.0 (3.2, 5.0) 2.1 (1.9, 2.4)
3.4 (2.1, 5.3) 2.8 (1.9, 4.2)
10.3 (7.9, 13.4) 3.2 (2.8, 3.6)
3.3 (2.7, 4.0) 2.7 (2.4, 3.0)
5.8 (4.6, 7.3) 1.6 (1.4, 1.8)
1.1 (0.7, 1.8) 1.1 (0.8, 1.6)
4.7 (3.8, 5.8) 1.3 (1.1, 1.4)
3.2 (2.5, 3.9) 3.0 (2.7, 3.4)
3.5 (2.8, 4.4) 1.8 (1.7, 2.1)
2.4 (1.6, 3.6) 2.2 (1.5, 3.1)
5.5 (4.3, 7.0) 2.7 (2.4, 3.0)
4.6 (3.7, 5.8) 3.3 (3.0, 3.7)
5.0 (4.1, 6.3) 2.0 (1.8, 2.2)
3.9 (2.7, 5.8) 2.7 (1.9, 3.7)
8.7 (6.8, 11.1) 3.0 (2.7, 3.3)
3.3 (2.8, 3.9) 2.7 (2.4, 2.9)
5.1 (4.2, 6.2) 1.7 (1.5, 1.9)
1.0 (0.6, 1.5) 0.8 (0.6, 1.2)
2.9 (2.4, 3.6) 1.3 (1.2, 1.5)
5.3 (3.8, 7.3) 2.7 (2.3, 3.1)
2.1 (1.7, 2.7) 1.9 (1.7, 2.2)
1.6 (0.8, 3.1) 2.5 (1.6, 4.0)
7.2 (5.4, 9.6) 2.9 (2.6, 3.4)
7.2 (5.1, 10.1) 3.0 (2.7, 3.5)
3.0 (2.4, 3.8) 2.5 (2.2, 2.8)
2.2 (1.2, 4.1) 4.3 (2.7, 7.0)
12.6 (9.5, 16.7) 3.8 (3.4, 4.4)
3.1 (2.5, 3.9) 2.6 (2.3, 2.9)
6.4 (4.9, 8.3) 1.5 (1.3, 1.7)
0.9 (0.5, 1.6) 0.8 (0.6, 1.2)
7.8 (6.1, 9.9) 1.2 (1.1, 1.3)
a
Based on the National Longitudinal Mortality Study (2002–2011). CVD, cardiovascular disease; RII, Relative Index of Inequality.
Figure 1. Relative differences in educational disparities between individuals aged 50–64 and 66–79 years, men and women combined. Note: The error bar represents 95% CI. NHB, non-Hispanic black; NHW, non-Hispanic white.
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Ma et al / Am J Prev Med 2017;52(6):728–734 17
smoking cessation and increased physical activity. Improved health and life satisfaction after retirement18 may have partly accounted for the diminished educational disparities among those aged 66–79 years. In addition, increased access to health care through the automatic eligibility for Medicare coverage at age 65 years may also have contributed to the decreased disparities in the elderly. In contrast to near universal health insurance coverage by Medicare for ages Z65 years, more than 40% of adults aged o65 years with less than a high school education did not have health insurance in 2010.19 Partly because of lack of health insurance, socioeconomically disadvantaged people are less likely to seek preventive services and to receive timely or high-quality treatment.20 For example, only 39% of people aged 50–75 years with less than high school education were current with their colorectal cancer screening compared with 72% in those with at least a college degree in 2010.19 Beginning in 2010, the federal government implemented the Affordable Care Act (ACA) to address this longstanding problem by improving access to quality health care to all Americans through various provisions, which include expansion of dependent coverage until age 26 years, removal of cost as a barrier to certain preventive health services, expansion of state Medicaid programs, and health insurance exchange subsidies.21 Early results have shown that these provisions have the potential to bridge the gap of socioeconomic health disparities in working-aged adults. An estimated 20 million Americans have gained health insurance since the open enrollment of ACA started in October 2013, with the largest gains among socioeconomically disadvantaged populations in Medicaid expansion states.22–24 In addition, state Medicaid expansions have been associated with improved access to primary care and medications, affordability, utilization of some types of health care, and health.23,25,26 A recent study27 suggests that ACA-dependent coverage expansion increases uptake rate of cervical cancer screening among ACA-dependent coverage beneficiaries. Although the passage of ACA provides an opportunity to achieve equal health care for all in the U.S., the success of ACA in reducing health disparities among U.S. populations will largely hinge on the extent of utilization of health services covered by the ACA among low-SES populations. Healthcare providers and health educators could play a major role on enhancing the utilization of care among the disadvantaged segment of the U.S. population.
Limitations Findings from this study should be interpreted within the context of some limitations. First, this study was not June 2017
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aimed to test the causal relationship between health insurance and educational disparity but to highlight the differences in educational disparities in mortality between two age groups and discuss what factors, including differences in access to health care, may have contributed to the observed results. Second, as the authors only used education as a marker of SES to measure disparities, this study does not capture the whole spectrum of socioeconomic disparities in mortality. However, as education shapes many other social determinants, such as income, occupation, and wealth, the findings could have implications for decreasing health disparities related to a spectrum of SES measures. Third, some of the differences in educational disparity between the groups aged 50–64 and 66–79 years may be due to selective survival of individuals with healthier behaviors.28 As a result, one would expect to see diminished association between SES and mortality with advancing age. However, the contribution of selective survival is expected to be small in the present study, as the authors excluded deaths occurring after age 79 years from analysis.
CONCLUSIONS Educational disparities in mortality among non-Hispanic whites and blacks were 41%–61% lower in people aged 66– 79 years than in those aged 50–64 years. A range of social factors may have contributed to the differential disparities by age, including differences in access to care, health perception, stress level, lifestyle, and health behaviors with advancing age and retirement. Further research is needed to reveal the underlying reasons for diminished educational disparities in mortality after age 65 years.
ACKNOWLEDGMENTS Dr. Ma and Ms. Cosgrove had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Jemal, Ma. Acquisition, analysis, or interpretation of data: all authors. Statistical analysis: Ma, Cosgrove. Drafting of the manuscript: Ma, Jemal, Atlekruse. Critical revision of the manuscript for important intellectual content: all authors. Study supervision: Jemal. This work was supported by the Intramural Research Department of the American Cancer Society. The American Cancer Society had no role in design and conduct of the study; collection, management, analysis, and interpretation of the data; or preparation, review, or approval of the manuscript. This paper is released to inform interested parties of research and to encourage discussion. Any views expressed on statistical, methodologic, technical, or operational issues are those of the authors and not necessarily those of the U.S. Census Bureau or the American Cancer Society.
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No financial disclosures were reported by the authors of this paper. 14.
SUPPLEMENTAL MATERIAL Supplemental materials associated with this article can be found in the online version at http://dx.doi.org/10.1016/j. amepre.2017.02.008.
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