Race/Ethnicity Determines Life Expectancy in Surgically Treated T1aN0M0 Renal Cell Carcinoma Patients.

BACKGROUND: Life expectancy (LE) is an important consideration in the clinical decision-making for T1aN0M0 renal cell cancer (RCC) patients. OBJECTIVE: To test the effect of race/ethnicity (Caucasian, African American, Hispanic/Latino, and Asian) on LE predictions from Social Security Administration (SSA) life tables in male and female T1aN0M0 RCC patients. DESIGN, SETTING, AND PARTICIPANTS: We relied on the Surveillance, Epidemiology, and End Results database. INTERVENTION: Radical nephrectomy (RN) and partial nephrectomy (PN). OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Five-year and 10-yr observed overall survival (OS) of pT1aN0M0 RCC patients treated between 2004 and 2006 were compared with the LE predicted from SSA life tables. We repeated the comparison in a more contemporary cohort (2009-2011), with 5-yr follow-up and higher PN rates. RESULTS AND LIMITATIONS: In the 2004-2006 cohort, PN rate was 40.7%. OS followed the predicted LE in Caucasians, Hispanics/Latinos, and Asians, but not in African Americans, in whom 5-yr OS rates were 5.0% (male) and 8.7% (female) and 10-yr rates were 4.2% (male) and 11.1% (female) lower than predicted. In the 2009-2011 cohort, PN rate was 59.4%. Same observations were made for OS versus predicted LE in Caucasians, Hispanics/Latinos, and Asians. In African Americans, 5-yr OS rates were 1.5% (male) and 4.9% (female) lower than predicted. CONCLUSIONS: In RN- or PN-treated pT1aN0M0 RCC patients, LE predictions closely approximated OS of Caucasians, Hispanics/Latinos, and Asians. In African-American patients, SSA life tables overestimated LE, more in females than in males. The limitations of our study are its retrospective nature, its validity for US patients only, and the under-representation of racial/ethnic minorities. PATIENT SUMMARY: Social Security Administration life tables can be used to estimate long-term life expectancy in patients who are surgically treated for renal cancer (≤4 cm). However, while for Caucasians, Hispanics/Latinos, and Asians, the prediction performs well, life expectancy of African Americans is generally overestimated by life table predictions. TAKE HOME MESSAGE: In the clinical decision-making process for T1aN0M0 renal cell cancer patients eligible for radical or partial nephrectomy, the important influence of patient sex and race/ethnicity on life expectancy should be taken into account, when using Social Security Administration life tables.

Inequality in mortality between Black and White Americans by age, place, and cause and in comparison to Europe, 1990 to 2018.

Although there is a large gap between Black and White American life expectancies, the gap fell 48.9% between 1990 and 2018, mainly due to mortality declines among Black Americans. We examine age-specific mortality trends and racial gaps in life expectancy in high- and low-income US areas and with reference to six European countries. Inequalities in life expectancy are starker in the United States than in Europe. In 1990, White Americans and Europeans in high-income areas had similar overall life expectancy, while life expectancy for White Americans in low-income areas was lower. However, since then, even high-income White Americans have lost ground relative to Europeans. Meanwhile, the gap in life expectancy between Black Americans and Europeans decreased by 8.3%. Black American life expectancy increased more than White American life expectancy in all US areas, but improvements in lower-income areas had the greatest impact on the racial life expectancy gap. The causes that contributed the most to Black Americans' mortality reductions included cancer, homicide, HIV, and causes originating in the fetal or infant period. Life expectancy for both Black and White Americans plateaued or slightly declined after 2012, but this stalling was most evident among Black Americans even prior to the COVID-19 pandemic. If improvements had continued at the 1990 to 2012 rate, the racial gap in life expectancy would have closed by 2036. European life expectancy also stalled after 2014. Still, the comparison with Europe suggests that mortality rates of both Black and White Americans could fall much further across all ages and in both high-income and low-income areas.

Evidence of inequitable use of chemotherapy in New Zealand colorectal cancer patients.

AIMS: To explore variations in the use of and timeliness of chemotherapy in patients diagnosed with colorectal cancer in New Zealand. METHODS: This study included patients diagnosed with colorectal cancer in New Zealand between 1 January 2006 and 31 December 2016. The first chemotherapy regime was identified from Pharmaceutical Collection dataset. Logistic regression model was used to estimate the adjusted odds ratio of having chemotherapy by subgroup after adjustment for other factors. RESULTS: 27.8% (6,737/24,217) of colon cancer patients and 43.8% (3,582/8,170) of rectal cancer patients received publicly funded chemotherapy. The uptake and timeliness of chemotherapy has been improving over time. Pacific people were the least likely to receive chemotherapy, followed by Maori and Asian. Younger patients, New Zealand European, patients with metastatic disease and patients in the Southern Cancer Network were more likely to have chemotherapy in less than 10 weeks post-diagnosis. Over half of the advanced colorectal cancer patients who did not receive chemotherapy were aged 80+ years or had a short life expectancy. CONCLUSIONS: Although the uptake and timeliness of chemotherapy for colorectal cancer has been improving, Maori, Pacific, Asian and older patients were less likely to receive chemotherapy and less likely to receive chemotherapy in a timely manner. There is a variation in use of chemotherapy by Region with patients in the Southern Cancer region appearing to be the most likely to receive chemotherapy and to receive it within a timely period.

Ethnic inequities in life expectancy attributable to smoking.

AIM: To determine the contribution of smoking-related deaths to the life expectancy gap in both Maori and Pacific people compared with non-Maori/non-Pacific people in New Zealand. METHODS: Death registration and population data between 2013 and 2015 were used to calculate life expectancy. To determine the contribution of smoking to the life expectancy gap, population attributable fractions for all causes of death where smoking is a casual risk factor were calculated using age- and ethnic-specific smoking data from the 2013 New Zealand Census and relative risk estimates from the American Cancer Society Cancer Prevention Study II. Population attributable fractions were applied to all deaths registered in New Zealand for the 2013-15 period to estimate the number of deaths attributable to tobacco smoking. The life expectancy gap was decomposed using the Arriaga method. The gap was decomposed both overall and by specific smoking attributable causes of death. RESULTS: Between 2013 and 2015 an estimated 12,421 (13.4% of all deaths) were attributable to smoking. Nearly one in four (22.6%) deaths among Maori were attributable to smoking (2,199 out of 9,717 deaths) and nearly one in seven (13.8%) among Pacific people (512 out of 3,720 deaths). Among non-Maori/non-Pacific people, one in eight (12.3%) deaths were attributable to smoking (9,710 out of 78,759 deaths). Higher rates of smoking attributable mortality were responsible for 2.1 years of the life expectancy gap in Maori men, 2.3 years in Maori women, 1.4 years in Pacific men and 0.3 years among Pacific women. Cancers of the trachea, bronchus and lung, chronic obstructive pulmonary disease (COPD) and ischaemic heart disease were the leading smoking attributable causes of death contributing to the gap. CONCLUSION: Smoking is an important preventable risk factor contributing to ethnic inequities in life expectancy for Maori men and women, and Pacific men. Dramatic declines in smoking-attributable deaths can be achieved by reducing smoking prevalence rates. Preventing smoking initiation and increasing cessation rates must remain a top priority for the Ministry of Health and District Health Boards. Smokefree initiatives should be reoriented to be Tiriti o Waitangi (Treaty of Waitangi) compliant and better meet the needs of Maori and Pacific people who smoke. Addressing the residual risk in ex-smokers through equitable early diagnosis and treatment of smoking-related conditions will further assist a more rapid closing of life expectancy gaps for Maori men and women and Pacific men. The next five years provide the opportunity to demonstrate commitment to achieving a smokefree Aotearoa for all: an aspiration, based on the current trajectory, which is most probably out of reach.

Black and White Differences in Life Expectancy in 4 US States, 1969-2013.

OBJECTIVES: Racial differences in mortality in the United States have narrowed and vary by time and place. The objectives of our study were to (1) examine the gap in life expectancy between white and black persons (hereinafter, racial gap in life expectancy) in 4 states (California, Georgia, Illinois, and New York) and (2) estimate trends in the contribution of major causes of death (CODs) to the racial gap in life expectancy by age group. METHODS: We extracted data on the number of deaths and population sizes for 1969-2013 by state, sex, race, age group, and 6 major CODs. We used a Bayesian time-series model to smooth and impute mortality rates and decomposition methods to estimate trends in sex- and age-specific contributions of CODs to the racial gap in life expectancy. RESULTS: The racial gap in life expectancy at birth decreased in all 4 states, especially among men in New York (from 8.8 to 1.1 years) and women in Georgia (from 8.0 to 1.7 years). Although few deaths occurred among persons aged 1-39, racial differences in mortality at these ages (mostly from injuries and infant mortality) contributed to the racial gap in life expectancy, especially among men in California (1.0 year of the 4.3-year difference in 2013) and Illinois (1.9 years of the 6.7-year difference in 2013). Cardiovascular deaths contributed most to the racial gap in life expectancy for adults aged 40-64, but contributions decreased among women aged 40-64, especially in Georgia (from 2.8 to 0.5 years). The contribution of cancer deaths to inequality increased in California and Illinois, whereas New York had the greatest reductions in inequality attributable to cancer deaths (from 0.6 to 0.2 years among men and from 0.2 to 0 years among women). CONCLUSIONS: Future research should identify policy innovations and economic changes at the state level to better understand New York's success, which may help other states emulate its performance.

Contributors to Wisconsin's persistent black-white gap in life expectancy.

BACKGROUND: Although the black-white gap in life expectancy has narrowed in the U.S., there is considerable variability across states. In Wisconsin, the black-white gap exceeds 6 years, well above the national average. Reducing this disparity is an urgent public health priority, but there is limited understanding of what contributes to Wisconsin's racial gap in longevity. Our investigation identifies causes of death that contribute most to Wisconsin's black-white gap in life expectancy among males and females, and highlights specific ages where each cause of death contributes most to the gap. METHODS: Our study employs 1999-2016 restricted-use mortality data provided by the National Center for Health Statistics. After generating race- and sex-specific life tables for each 3-year period of observation (e.g., 1999-2001), we trace recent trends in the black-white life expectancy gap in Wisconsin. We subsequently conduct a series of analyses to decompose the black-white gap in three time periods into 13 separate causes and 19 different age groups. RESULTS: In 2014-16, Wisconsin's black-white gap in life expectancy was 7.34 years for males (67% larger than the national gap), and 5.61 years for females (115% larger than the national gap). Among males, homicide was the single largest contributor, accounting for 1.56 years of the total gap. Heart disease and cancer followed, contributing 1.43 and 1.42 years, respectively. Among females, heart disease and cancer were the two leading contributors to the gap, accounting for 1.12 and 1.00 years, respectively. Whereas homicide contributed most to the racial gap in male longevity during late adolescence and early adulthood, heart disease and cancer exerted most of their influence between ages 50-70 for both males and females. Other notable contributors were unintentional injuries (males), diabetes and cerebrovascular disease (females), and perinatal conditions (males and females). CONCLUSIONS: Our study identifies targets for future policy interventions that could substantially reduce Wisconsin's racial gap in life expectancy. Concerted efforts to eliminate racial disparities in perinatal mortality and homicide early in the life course, and chronic conditions such as cancer and heart disease in later life, promise to help Wisconsin achieve the public health objective of racial parity in longevity.

The contribution of avoidable mortality to the life expectancy gap in Maori and Pacific populations in New Zealand-a decomposition analysis.

AIM: To determine the contribution of avoidable causes of death to the life expectancy differentials in both Maori and Pacific compared with non-Maori/non-Pacific ethnic groups in New Zealand. METHODS: Death registration data and population data for New Zealand between 2013-15 was used to calculate life expectancy. A recent definition of avoidable mortality was used to identify potentially avoidable deaths. Life expectancy decomposition was undertaken to identify the contribution of avoidable causes of death to the life expectancy differential in the Maori and Pacific populations. RESULTS: Nearly half of all deaths in Pacific (47.3%) and over half in Maori (53.0%) can be attributed to potentially avoidable causes of death, compared with less than one quarter (23.2%) in the non-Maori/non-Pacific population. Conditions both preventable and amenable contribute the greatest to the life expectancy differentials within both ethnic groups, when compared with non-Maori/non-Pacific. Cancers of the trachea, bronchus and lung are significant avoidable causes contributing to the life expectancy differentials in both male and female Maori, contributing 0.8 years and 0.9 years respectively. Avoidable injuries including suicide contribute 1.0 year to the differential in Maori males. Coronary disease, diabetes and cerebrovascular disease are the largest contributors to the differential in both Pacific males and females. CONCLUSION: Avoidable causes of death are large contributors to the life expectancy differentials in Maori and Pacific populations. The findings provide further evidence of the need to address the determinants of health and ensure equitable access to health services to reduce the impact of avoidable mortality on inequalities in life expectancy. It also highlights the importance of looking beyond individual factors and recognising the role of healthcare services and the social determinants in improving health equity.

Comparison of Equity Preferences for Life Expectancy Gains: A Discrete Choice Experiment Among the Japanese and Korean General Public.

BACKGROUND: Setting priorities for limited public resources has become a topic of heated discussion the world over. Assigning different weights for the health gains of different population groups allows for equity considerations in cost-effectiveness analysis. However, only a few empirical works have elicited the preferences of the general public. OBJECTIVE: To compare the equity preferemce assigned by Japanese and Koreans. METHODS: We conducted a Web-based survey in March 2013, including a discrete choice experiment, to elicit the equity preferences of the general public for the life expectancy gains of different population groups. We selected attributes and designed the experiment following Norman et al.'s study (Norman R, Hall J, Street D, Viney R. Efficiency and equity: a stated preference approach. Health Econ 2013;22:568-81). Accordingly, we analyzed preference for sex, smoking status, lifestyle, caring status, income, and age. RESULTS: The Japanese assigned a higher preference for males (P < 0.001), nonsmokers (P < 0.001), those with lower income (P < 0.001), and carers (P < 0 .001), and they assigned a lower preference for those with a life expectancy of 60 years (P = 0.002) and 75-year-olds (P < 0.001). Koreans have the same patterns of preference for lower income (P < 0.001), caring (P < 0.001), and smoking status (P = 0.026). However, they prefer both sexes (P = 0.331) and different age groups equally. In both countries, respondents tend to prefer groups with characteristics similar to their own. CONCLUSIONS: People from the two Asian developed countries, with universal health insurance, show different equity preferences. These may reflect the variations in cultural background and coverage of health care services.

Densidade racial e a situação socioeconômica, demográfica e de saúde nas cidades brasileiras em 2000 e 2010 / Racial density and the socioeconomic, demographic and health context in Brazilian cities in 2000 and 2010

RESUMO: Introdução: A densidade racial ainda não foi explorada nos estudos sobre desigualdades raciais no Brasil. Este estudo identifica categorias de densidade racial para as cidades brasileiras e descreve a situação de vida e saúde nessas categorias nos anos dos Censos Demográficos de 2000 e 2010. Método: Estudo ecológico em que a informação de cor/raça nos dois últimos censos foi usada para calcular a densidade racial (proporçãode pessoas do mesmo grupo racial) nas cidades brasileiras em cada ano. Criaram-se quatro categorias de densidade racial (parda; mistos, mas com maioria negra; branca; e mistos, mas com maioria branca).Paraquais foram descritos indicadores socioeconômicos, demográficos e de saúde. Resultados: As categorias de densidade racial captaram desigualdades importantes ao longo dos censos e apontaram a permanência de piores condições de vida e saúde nas cidades formadas por pardos e mistos, mas com maioria negra, e melhores onde predominaram brancos. As cidades predominadas por pardos e mistos, mas com maioria negra, em relação às demais, apresentam, nos dois censos, estrutura etária mais jovem, piores índices de desenvolvimento humano, maior vulnerabilidade social, concentração de renda, mortalidade infantil e prematura (< 65 anos) e menor esperança de vida de seus moradores. Discussão: Semelhantemente a outros países, a densidade racial espelhou desigualdades na situação de vida e saúde no Brasil, bem como defasagem temporal entre suas cidades. Conclusão: As categorias de densidade racial podem contribuir para os estudos sobre a epidemiologia social e sobre as relações raciais no país.

ABSTRACT: Introduction: Racial density has not yet been explored in studies of racial inequalities in Brazil. Thisstudy identified categories of racial density in Brazilian cities and described the living and health context in these categories in 2000 and 2010, when demographic censuses were conducted. Method: Ecological study which used skin color or race information from the last two censuses to calculate racial density (the ratio of people aggregated to the same racial group) of the Brazilian cities each year. Four categories of racial density (Brown; Mixed-race, predominantly black; White/Caucasian; and Mixed-race, predominantly white). Socioeconomic, demographic and health indicators were described to each category. Results: The categories of racial density captured important inequalities throughout the census and also indicated the continuance of worse living and health conditions in the cities composed by Browns and mixed-race people, predominantly Black; better conditions were indicated in cities where White/Caucasians are predominant. The cities, composed mainly of Browns and mixed-race people, predominantly Black, presented younger age structure, worse human development indexes, greater social vulnerability, income concentration, infant and premature mortality (<65 years) and lower life expectancy in both censuses, as compared to other cities. Discussion: Similarly to other countries, the racial density reflected inequalities in the Brazilian living and health context as well as a time lag among the cities. Conclusion: The categories of racial density may contribute to social epidemiology and race relations studies in Brazil.

Trends in the contribution of major causes of death to the black-white life expectancy gap by US state.

Life expectancy has increased in the United States over many decades. The difference in life expectancy between black and white Americans has also decreased, but some states have made much more progress towards racial equality than others. This paper describes the pattern of contributions of six major causes of death to the black-white life expectancy gap within US states and the District of Columbia between 1969 and 2013, and identifies states diverging from the overall pattern. Across multiple causes, the District of Columbia, Illinois, Wisconsin, and Michigan had the highest contributions to black-white inequality, while New York, Massachusetts, and Rhode Island had the lowest contributions and have either achieved or are the closest to achieving black-white equality in life expectancy.

Widening Disparities In Infant Mortality And Life Expectancy Between Appalachia And The Rest Of The United States, 1990-2013.

Appalachia-a region that stretches from Mississippi to New York-has historically been recognized as a socially and economically disadvantaged part of the United States, and growing evidence suggests that health disparities between it and the rest of the country are widening. We compared infant mortality and life expectancy disparities in Appalachia to those outside the region during the period 1990-2013. We found that infant mortality disparities widened for both whites and blacks, with infant mortality 16 percent higher in Appalachia in 2009-13, and the region's deficit in life expectancy increased from 0.6 years in 1990-92 to 2.4 years in 2009-13. The association between area poverty and life expectancy was stronger in Appalachia than in the rest of the United States. We found wide health disparities, including a thirteen-year gap in life expectancy among black men in high-poverty areas of Appalachia, compared to white women in low-poverty areas elsewhere. Higher mortality in Appalachia from cardiovascular diseases, lung cancer, chronic lower respiratory diseases or chronic obstructive pulmonary disease, diabetes, nephritis or kidney diseases, suicide, unintentional injuries, and drug overdose contributed to lower life expectancy in the region, compared to the rest of the country. Widening health disparities were also due to slower mortality improvements in Appalachia.

Inequalities in non-communicable diseases between the major population groups in Israel: achievements and challenges.

Israel is a high-income country with an advanced health system and universal health-care insurance. Overall, the health status has improved steadily over recent decades. We examined differences in morbidity, mortality, and risk factors for selected non-communicable diseases (NCDs) between subpopulation groups. Between 1975 and 2014, life expectancy in Israel steadily increased and is currently above the average life expectancy for the Organisation for Economic Co-operation and Development countries. Nevertheless, life expectancy has remained lower among Israeli Arabs than Israeli Jews, and this gap has recently widened. Age-adjusted mortality as a result of heart disease, stroke, or diabetes remains higher in Arabs, whereas age-adjusted incidence and mortality of cancer were higher among Jews. The prevalence of obesity and low physical activity in Israel is considerably higher among Arabs than Jews. Smoking prevalence is highest for Arab men and lowest for Arab women. Health inequalities are also evident by the indicators of socioeconomic position and in subpopulations, such as immigrants from the former Soviet Union, ultra-Orthodox Jews, and Bedouin Arabs. Despite universal health coverage and substantial improvements in the overall health of the Israeli population, substantial inequalities in NCDs persist. These differences might be explained, at least in part, by gaps in social determinants of health. The Ministry of Health has developed comprehensive programmes to reduce these inequalities between the major population groups. Sustained coordinated multisectoral efforts are needed to achieve a greater impact and to address other social inequalities.

Population health in an era of rising income inequality: USA, 1980-2015.

Income inequality in the USA has increased over the past four decades. Socioeconomic gaps in survival have also increased. Life expectancy has risen among middle-income and high-income Americans whereas it has stagnated among poor Americans and even declined in some demographic groups. Although the increase in income inequality since 1980 has been driven largely by soaring top incomes, the widening of survival inequalities has occurred lower in the distribution-ie, between the poor and upper-middle class. Growing survival gaps across income percentiles since 2001 reflect falling real incomes among poor Americans as well as an increasingly strong association between low income and poor health. Changes in individual risk factors such as smoking, obesity, and substance abuse play a part but do not fully explain the steeper gradient. Distal factors correlated with rising inequality including unequal access to technological innovations, increased geographical segregation by income, reduced economic mobility, mass incarceration, and increased exposure to the costs of medical care might have reduced access to salutary determinants of health among low-income Americans. Having missed out on decades of income growth and longevity gains, low-income Americans are increasingly left behind. Without interventions to decouple income and health, or to reduce inequalities in income, we might see the emergence of a 21st century health-poverty trap and the further widening and hardening of socioeconomic inequalities in health.

How efficient are New Zealand's District Health Boards at producing life expectancy gains for Maori and Europeans?

OBJECTIVE: Use data envelopment analysis (DEA) to measure the efficiency of New Zealand's District Health Boards (DHBs) at achieving gains in Maori and European life expectancy (LE). METHODS: Using life tables for 2006 and 2013, a two-output DEA model established the production possibility frontier for Maori and European LE gain. Confidence limits were generated from a 10,000 replicate Monte Carlo simulation. RESULTS: Results support the use of LE change as an indicator of DHB efficiency. DHB mean income and education were related to initial LE but not to its rate of change. LE gains were unrelated to either the initial level of life expectancy or to the proportion of Maori in the population. DHB efficiency ranged from 79% to 100%. Efficiency was significantly correlated with DHB financial performance. CONCLUSION: Changes in LE did not depend on the social characteristics of the DHB. The statistically significant association between efficiency and financial performance supports its use as an indicator of managerial effectiveness. Implications for public health: Efficient health systems achieve better population health outcomes. DEA can be used to measure the relative efficiency of sub-national health authorities at achieving health gain and equity outcomes.

Accuracy of advanced cancer patients' life expectancy estimates: The role of race and source of life expectancy information.

BACKGROUND: The objective of this study was to examine the source of advanced cancer patients' information about their prognosis and determine whether this source of information could explain racial disparities in the accuracy of patients' life expectancy estimates (LEEs). METHODS: Coping With Cancer was a prospective, longitudinal, multisite study of terminally ill cancer patients followed until death. In structured interviews, patients reported their LEEs and the sources of these estimates (ie, medical providers, personal beliefs, religious beliefs, and other). The accuracy of LEEs was calculated through a comparison of patients' self-reported LEEs with their actual survival. RESULTS: The sample for this analysis included 229 patients: 31 black patients and 198 white patients. Only 39.30% of the patients estimated their life expectancy within 12 months of their actual survival. Black patients were more likely to have an inaccurate LEE than white patients. A minority of the sample (18.3%) reported that a medical provider was the source of their LEEs; none of the black patients (0%) based their LEEs on a medical provider. Black race remained a significant predictor of an inaccurate LEE, even after the analysis had been controlled for sociodemographic characteristics and the source of LEEs. CONCLUSIONS: The majority of advanced cancer patients have an inaccurate understanding of their life expectancy. Black patients with advanced cancer are more likely to have an inaccurate LEE than white patients. Medical providers are not the source of information for LEEs for most advanced cancer patients and especially for black patients. The source of LEEs does not explain racial differences in LEE accuracy. Additional research into the mechanisms underlying racial differences in prognostic understanding is needed. Cancer 2016;122:1905-12. © 2016 The Authors. Cancer published by Wiley Periodicals, Inc. on behalf of American Cancer Society. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Visible and Invisible Trends in Black Men's Health: Pitfalls and Promises for Addressing Racial, Ethnic, and Gender Inequities in Health.

Over the past two decades, there has been growing interest in improving black men's health and the health disparities affecting them. Yet, the health of black men consistently ranks lowest across nearly all groups in the United States. Evidence on the health and social causes of morbidity and mortality among black men has been narrowly concentrated on public health problems (e.g., violence, prostate cancer, and HIV/AIDS) and determinants of health (e.g., education and male gender socialization). This limited focus omits age-specific leading causes of death and other social determinants of health, such as discrimination, segregation, access to health care, employment, and income. This review discusses the leading causes of death for black men and the associated risk factors, as well as identifies gaps in the literature and presents a racialized and gendered framework to guide efforts to address the persistent inequities in health affecting black men.

Arab-Jewish gap in life expectancy in Israel.

BACKGROUND: Studies about the health status of ethnic minorities in the Middle East are rare. This article examines changes in the life expectancy gap during 1970-2010 between the Arab-Palestinian minority and the Jewish majority in Israel, a persistent gap that has widened over the last 20 years. It examines the gap in a period over which the minority group was undergoing an epidemiological transition and demonstrates consequences of the transition on changes in the main causes of death contributing to the life expectancy gap. METHODS: Decomposition methods estimate the contribution of specific age groups and causes of death to the total gap in life expectancy at any given year and changes in these contributions over the studied period. RESULTS: The contribution of mortality differentials at ages <45 years to the Arab-Jewish gap in life expectancy declined while that of differentials at ages >45 has been gradually growing reaching >70% of the total gap. For both males and females, trends in cancer and diabetes mortality differentials contributed to widening the gap among the elderly. Trends in heart mortality lead to increasing the gap among males but to decreasing it among females. CONCLUSIONS: While differences in infant and child mortality have declined, old-age (>45) mortality differentials have emerged and have been gradually widening. These findings calls for a special attention to the various factors responsible for the widening mortality gap including social inequality between Arabs and Jews and higher levels of smoking and obesity among the Arab population.

Hispanic-White Differences in Lifespan Variability in the United States.

This study is the first to investigate whether and, if so, why Hispanics and non-Hispanic whites in the United States differ in the variability of their lifespans. Although Hispanics enjoy higher life expectancy than whites, very little is known about how lifespan variability-and thus uncertainty about length of life-differs by race/ethnicity. We use 2010 U.S. National Vital Statistics System data to calculate lifespan variance at ages 10+ for Hispanics and whites, and then decompose the Hispanic-white variance difference into cause-specific spread, allocation, and timing effects. In addition to their higher life expectancy relative to whites, Hispanics also exhibit 7 % lower lifespan variability, with a larger gap among women than men. Differences in cause-specific incidence (allocation effects) explain nearly two-thirds of Hispanics' lower lifespan variability, mainly because of the higher mortality from suicide, accidental poisoning, and lung cancer among whites. Most of the remaining Hispanic-white variance difference is due to greater age dispersion (spread effects) in mortality from heart disease and residual causes among whites than Hispanics. Thus, the Hispanic paradox-that a socioeconomically disadvantaged population (Hispanics) enjoys a mortality advantage over a socioeconomically advantaged population (whites)-pertains to lifespan variability as well as to life expectancy. Efforts to reduce U.S. lifespan variability and simultaneously increase life expectancy, especially for whites, should target premature, young adult causes of death-in particular, suicide, accidental poisoning, and homicide. We conclude by discussing how the analysis of Hispanic-white differences in lifespan variability contributes to our understanding of the Hispanic paradox.

Leading Causes of Death Contributing to Decrease in Life Expectancy Gap Between Black and White Populations: United States, 1999-2013.

Life expectancy at birth has increased steadily since 1900 to a record 78.8 years in 2013. But differences in life expectancy between the white and black populations still exist, despite a decrease in the life expectancy gap from 5.9 years in 1999 to 3.6 years in 2013. Differences in the change over time in the leading causes of death for the black and white populations have contributed to this decrease in the gap in life expectancy. Between 1999 and 2013, the decrease in the life expectancy gap between the black and white populations was mostly due to greater decreases in mortality from heart disease, cancer, HIV disease, unintentional injuries, and perinatal conditions among the black population. Similarly, the decrease in the gap between black and white male life expectancy was due to greater decreases in death rates for HIV disease, cancer, unintentional injuries, heart disease, and perinatal conditions in black males. For black females, greater decreases in diabetes death rates, combined with decreased rates for heart disease and HIV disease, were the major causes contributing to the decrease in the life expectancy gap with white females. The decrease in the gap in life expectancy between the white and black populations would have been larger than 3.6 years if not for increases in death rates for the black population for aortic aneurysm, Alzheimer's disease, and maternal conditions. For black males, the causes that showed increases in death rates over white males were hypertension, aortic aneurysm, diabetes, Alzheimer's disease, and kidney disease, while the causes that showed increases in death rates for black females were Alzheimer's disease, maternal conditions, and atherosclerosis. This NCHS Data Brief is the second in a series of data briefs that explore the causes of death contributing to differences in life expectancy between detailed ethnic and racial populations in the United States. The first data brief focused on the racial differences in life expectancy for a single year, 2010 (3).