How does it all end? Trends and disparities in health at the end of life.

OBJECTIVES: To consider trends and disparities in end-of-life health in the US. METHODS: I use data from the National Health Interview Survey, linked to death records through 2015, for respondents who died at ages 65+ to compare the prevalence of three health outcomes in the last six years of life across time, sex, age, race, and educational attainment. Self-rated health (SRH) is available for respondents interviewed in years 1987-2014, while information on activities of daily living (ADL) and instrumental activities of daily living (IADL) is available for the period 1997-2014. RESULTS: By the end of the study period, individuals reported two fewer months of fair/poor health at the end of life than those dying in earlier years. In contrast, time lived with at least one activity limitation at the end of life generally remained comparable. Compared to men, women on average reported an additional year of living with an IADL limitation before death, and an additional eight months with an ADL limitation. Despite sex differences in disability, both sexes reported similar periods of fair/poor SRH before death. Similarly, while individuals who lived to older ages experienced a longer disabled period before death than individuals who died at younger ages, all age groups were equally likely to report fair/poor SRH. Black adults and adults with less formal schooling also spent more time with an end-of-life disability. For men, these racial and socioeconomic disparities lessened as death approached. For women, inequalities persisted until death. DISCUSSION: These findings suggest that despite increasing life expectancy, the period of poor health and disability prior to death has not recently been extended. Black women and women with less than a high school degree, require extended support at the end of life.

Excess mortality in the United States in the 21st century.

We use three indexes to identify how age-specific mortality rates in the United States compare to those in a composite of five large European countries since 2000. First, we examine the ratio of age-specific death rates in the United States to those in Europe. These show a sharp deterioration in the US position since 2000. Applying European age-specific death rates in 2017 to the US population, we then show that adverse mortality conditions in the United States resulted in 400,700 excess deaths that year. Finally, we show that these excess deaths entailed a loss of 13.0 My of life. In 2017, excess deaths and years of life lost in the United States represent a larger annual loss of life than that associated with the COVID-19 epidemic in 2020.

Trends in alcohol-related mortality by educational attainment in the U.S., 2000-2017.

BACKGROUND: Alcohol-related mortality rates in the U.S. have risen since 2000, though how trends vary across socio-economic status is unclear. METHODS: This analysis combines data from vital statistics and the National Health Interview Survey (NHIS) to estimate alcohol-related mortality rates at four levels of educational attainment (less than high school, high school/GED, some college/associate's degree, four-year degree or more) over the period 2000-2017. The analysis includes a comprehensive set of 48 alcohol-related causes of death, including causes which are indirectly influenced by alcohol use. I consider period and cohort patterns in inequality using the relative index of inequality (RII). RESULTS: Mortality rates increased over the study period, at all levels of educational attainment. Relative increases were larger for females than males at nearly all ages and levels of educational attainment, and were largest among 45-59 year-old women. Male and female members of the 1950-1959 birth cohort exhibited elevated rates of alcohol-related mortality relative to neighboring cohorts. Despite widespread increases in alcohol-related mortality, educational inequalities present at the beginning of the analysis persisted and exceeded those in all-cause mortality. Disparities were typically greatest among younger adults ages 30-44, though inequality in this age group declined over time. Inequality increased among females ages 60-74, as well as among males ages 45-74. IMPLICATIONS: While interventions targeting these groups may reduce educational disparities, care should also be taken to stem the increasing prevalence of alcohol-related deaths at all levels of educational attainment.

Life Beyond 65: Changing Spatial Patterns of Survival at Older Ages in the United States, 2000-2016.

OBJECTIVES: To identify levels and trends in life expectancy at age 65 (e65) by geographic region and metropolitan status in the United States. METHODS: Using county-level data on population and deaths from the Census and National Center for Health Statistics, we consider spatial inequality in e65 across 4 metropolitan types and 10 geographic regions from 2000 to 2016. We examine whether changes in e65 are driven by mortality developments in metro types or geographic regions, and compare spatial patterns in the United States to mortality trends in other Organization of Economic Cooperation and Development (OECD) countries. We use decomposition and regression methods to estimate the contributions of 10 causes of death to changes and inequalities in e65. RESULTS: Life expectancy at age 65 increased in all spatial units from 2000 to 2016. Areas with higher e65 in 2000 also experienced larger gains. Longevity increases were greatest in large metropolitan areas and coastal regions. Nonmetropolitan areas and the interior lagged far behind not only other parts of the United States but all OECD comparison countries. Metropolitan status was a better predictor of mortality changes than geographic region. Circulatory diseases and diseases associated with smoking were the principal sources of life expectancy gains and spatial differentiation in those gains. Larger gains in smoking-related mortality accounted for greater improvements among men than women. DISCUSSION: Even at advanced ages, large geographic disparities in life expectancy remain. And as mortality has declined, these disparities have widened. Public health efforts should pay special attention to identifying and ameliorating the sources of lagging life expectancy in nonmetropolitan regions.

Rising geographic inequality in mortality in the United States.

OBJECTIVES: To examine trends in inequality in life expectancy and age-specific death rates across 40 US spatial units from 1990 to 2016. METHODS: We use multiple cause-of-death data from vital statistics to estimate measures of inequality in mortality across metropolitan status and geographic region. We consider trends for 5-year age intervals and examine inequality in cause-specific mortality. RESULTS: For both sexes, spatial inequality in life expectancy and all-cause mortality above age 25 rose between 2002-04 and 2014-16. During this period, the standard deviation in life expectancy at birth increased by 19% for males and by 44% for females. Areas that had higher life expectancy at the beginning of the period enjoyed larger gains in life expectancy. Especially noteworthy are divergent trends between large central metropolitan areas on the coasts and non-metropolitan areas in Appalachia and the South. Spatial inequality in mortality from lung cancer/respiratory diseases rose substantially, particularly for older women. Spatial inequality in mortality from the combination of drug overdose, alcohol use, and suicide increased at ages 30-34, but declined at ages 50-54 and 70-74. Inequality in mortality from circulatory diseases, the largest cause of death, grew for some groups, particularly 30-34 year-old women. Mortality from screenable cancers, an indicator of the performance of medical systems, showed relatively little spatial disparity during the period. CONCLUSIONS: Spatial inequality in life expectancy at birth and adult mortality has increased in recent decades.

Patterns of weight change associated with disease diagnosis in a national sample.

BACKGROUND: The incidence and/or diagnosis of a major disease may activate weight change. Patterns of weight change associated with diagnoses have not been systematically documented. METHODS: We use data on adults ages 30+ in the National Health and Nutrition Examination Survey (NHANES) from 1999-2014. Self-reported current weight and weight one year prior are used to estimate percent weight change in the last year. We use self-reported data on arthritis, diabetes, cancer, cardiovascular disease, liver conditions, and respiratory disease diagnoses to compare weight change among individuals never diagnosed with these conditions, individuals diagnosed 0-1 years ago, and individuals diagnosed 2+ years ago. Multinomial logistic regressions adjust for the presence of multiple conditions. RESULTS: 17.7% of the adult population experienced weight loss of 5.0% or more in the year prior to survey. Individuals diagnosed with any of the conditions were less likely to maintain their weight than those without a diagnosis. Arthritis, diabetes, cancer, cardiovascular disease, and liver conditions were associated with net weight loss, whereas respiratory diseases were associated with higher probabilities of both losing and gaining weight. Among those losing 10% or more, 56.7% had been diagnosed with one of the conditions. Cancer was associated with the highest probability of unintentional weight loss and diabetes with the highest probability of intentional weight loss. CONCLUSIONS: Disease-associated weight changes leave a distinct imprint on patterns of weight change in the population. Individuals losing at least 10% of their weight in the last year have likely been diagnosed with one of the six conditions.

The role of obesity in exceptionally slow US mortality improvement.

Recent studies have described a reduction in the rate of improvement in American mortality. The pace of improvement is also slow by international standards. This paper attempts to identify the extent to which rising body mass index (BMI) is responsible for reductions in the rate of mortality improvement in the United States. The data for this study were obtained from subsequent cohorts of the National Health and Nutrition Examination Survey (NHANES III, 1988-1994; NHANES continuous, 1999-2010) and from the NHANES linked mortality files, which include follow-up into death records through December 2011. The role of BMI was estimated using Cox models comparing mortality trends in the presence and absence of adjustment for maximum lifetime BMI (Max BMI). Introducing Max BMI into a Cox model controlling for age and sex raised the annual rate of mortality decline by 0.54% (95% confidence interval 0.45-0.64%). Results were robust to the inclusion of other variables in the model, to differences in how Max BMI was measured, and to how trends were evaluated. The effect of rising Max BMI is large relative to international mortality trends and to alternative mortality futures simulated by the Social Security Administration. The increase in Max BMI over the period 1988-2011 is estimated to have reduced life expectancy at age 40 by 0.9 years in 2011 (95% confidence interval 0.7-1.1 years) and accounted for 186,000 excess deaths that year. Rising levels of BMI have prevented the United States from enjoying the full benefits of factors working to improve mortality.

The contribution of differences in adiposity to educational disparities in mortality in the United States.

BACKGROUND: There are large differences in life expectancy by educational attainment in the United States. Previous research has found obesity's contribution to these differences to be small. Those findings may be sensitive to how obesity is estimated. METHODS: This analysis uses discrete-time logistic regressions with data from the National Health and Nutrition Examination Survey (NHANES), pooled from 1988 to 1994 and 1999 to 2010, to estimate the contribution of differences in adiposity, or body fat, to educational differences in mortality. I show that results depend upon the measure of adiposity used: body mass index (BMI) at the time of survey or lifetime maximum BMI. RESULTS: College graduates were less likely than high school graduates to be obese at the time of survey (25% vs. 34.6%, respectively) and were also less likely to have ever been obese (35.7% vs. 49.4%, respectively). Lifetime maximum BMI performed better than BMI at the time of survey in predicting mortality using criteria for model selection. Differences in maximum BMI were associated with between 10.3% and 12% of mortality differences between college graduates and all others, compared to between 3.3% and 4.6% for BMI at the time of survey. Among nonsmokers, between 18.4% and 27.6% of mortality differences between college graduates and all others were associated with differences in maximum BMI. CONTRIBUTION: Adiposity is an overlooked contributor to educational differences in mortality. Previous findings that obesity does not contribute to educational disparities were based on BMI at the time of survey, which is less informative than maximum BMI. The contribution of adiposity to educational mortality differences will likely grow as smoking prevalence declines. Health surveys should collect information on weight history.