Declining life expectancy in the Great Lakes region: contributors to Black and white longevity change across educational attainment.

BACKGROUND: The East North Central Census division (aka the Great Lakes region) experienced a decrease in life expectancy of 0.3 years from 2014 to 2016 - one of the largest declines across the nine Census divisions. Disadvantaged groups that typically have below-average life expectancy, including Black individuals and those without a college education, may have been disproportionately affected by this longevity shift. This investigation examines life expectancy changes among different sex, race, and education groups in the Great Lakes region, and how specific causes of death contributed to within-group longevity changes over time and across age. METHODS: We used 2008 to 2017 death counts from the National Center for Health Statistics and American Community Survey population estimates to measure within-group change in life expectancy at age 25 among non-Hispanic Black and white males and females by educational attainment. We decomposed life expectancy change over time for each subgroup by 24 causes of death and measured their contribution to longevity change across 13 age groups. RESULTS: Among persons with ≤ 12 years of education, white males and females experienced 1.3- and 1.7-year longevity declines respectively, compared to a 0.6-year decline among Black males and a 0.3-year decline among Black females. Life expectancy declined among all groups with 13-15 years of education, but especially Black females, who experienced a 2.2-year loss. With the exception of Black males, all groups with 16 + years of education experienced longevity gains. Homicide contributed 0.34 years to longevity decline among Black males with ≤ 12 years of education. Drug poisoning made large contributions to longevity losses among Black females with ≤ 12 years of education (0.31 years), white males and females with 13-15 years of education (0.35 and 0.21 years, respectively), and white males and females with ≤ 12 years of education (0.92 and 0.65 years, respectively). CONCLUSIONS: Public health efforts to reduce the risks of homicide among Black males without a college education and drug poisoning among all groups could improve life expectancy and reduce racial and educational longevity disparities in the Great Lakes region.

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.

A population-based analysis of increasing rates of suicide mortality in Japan and South Korea, 1985-2010.

BACKGROUND: In the past two decades, rates of suicide mortality have declined among most OECD member states. Two notable exceptions are Japan and South Korea, where suicide mortality has increased by 20 % and 280 %, respectively. METHODS: Population and suicide mortality data were collected through national statistics organizations in Japan and South Korea for the period 1985 to 2010. Age, period of observation, and birth cohort membership were divided into five-year increments. We fitted a series of intrinsic estimator age-period-cohort models to estimate the effects of age-related processes, secular changes, and birth cohort dynamics on the rising rates of suicide mortality in the two neighboring countries. RESULTS: In Japan, elevated suicide rates are primarily driven by period effects, initiated during the Asian financial crisis of the late 1990s. In South Korea, multiple factors appear to be responsible for the stark increase in suicide mortality, including recent secular changes, elevated suicide risks at older ages in the context of an aging society, and strong cohort effects for those born between the Great Depression and the aftermath of the Korean War. CONCLUSION: In spite of cultural, demographic and geographic similarities in Japan and South Korea, the underlying causes of increased suicide mortality differ across these societies-suggesting that public health responses should be tailored to fit each country's unique situation.

Mind the gap: race/ethnic and socioeconomic disparities in obesity.

Race/ethnic and socioeconomic status (SES) disparities in obesity are substantial and may widen in the future. We review nine potential mechanisms that recent research has used to explain obesity disparities. Those nine mechanisms fall into three broad groups-health behaviors, biological factors, and the social environment-which incorporate both proximate and upstream determinants of obesity disparities. Efforts to reduce the prevalence of obesity in the US population and to close race/ethnic and SES disparities in obesity will likely require the use of multifaceted interventions that target multiple mechanisms simultaneously. Unfortunately, relatively few of the mechanisms reviewed herein have been tested in an intervention framework.

Cumulative exposure to short sleep and body mass outcomes: a prospective study.

Short sleep duration is associated with excess body mass among adolescents and young adults. The mechanisms theorized to drive that association suggest that persistent exposure to short sleep should be associated with greater accumulations of body mass. We use prospective cohort data from four waves of the National Longitudinal Study of Adolescent to Adult Health (1994-2009; n = 14 800) to examine associations between cumulative exposure to short sleep throughout adolescence and early adulthood and obesity and elevated waist circumference outcomes. We compare several clinical and distribution-based standards of short sleep to assess which measures are associated most strongly with body mass. Cumulative exposure to short sleep exhibits dose-response associations with obesity and elevated waist circumference. Relative to respondents with no instances of short sleep, those who slept -0.50 standard deviations or less than the age and sex-specific average sleep hours in all four waves had 1.45 [95% confidence interval (CI): 1.03, 2.04] times the odds of being obese and 1.45 (95% CI: 1.02, 2.06) times the odds of having an elevated waist circumference. Our findings suggest that cumulative exposure to short sleep during adolescence and young adulthood may play an important role in the etiology of obesity and elevated waist circumference during this important developmental period.

Do sleep-deprived adolescents make less-healthy food choices?

Short sleep duration among children and adolescents has been reported to be associated with elevated BMI and other adverse health outcomes. Food choices are one proposed mechanism through which this association may occur. In the present study, we examined whether self-reported habitual sleep duration is associated with vegetable and fruit consumption and fast food consumption. Using cross-sectional data from the National Longitudinal Study of Adolescent Health (n 13,284), we estimated three nested logistic regression models for two outcome variables: daily vegetable and fruit consumption and previous week's fast food consumption. The adjusted models included demographic and social/behavioural covariates. Self-reported habitual short sleep duration ( < 7 h/night) was associated with reduced odds of vegetable and fruit consumption compared with the recommended sleep duration (>8 h/night) (OR 0·66, P <0·001), even after adjusting for demographic and social/behavioural factors (OR 0·75, P <0·001). Short sleep duration was also associated with increased odds of fast food consumption (OR 1·40, P <0·001) even after adjustment (OR 1·20, P <0·05). Food choices are significantly associated with sleep duration and may play an important role in the mediation of the association between sleep and health among adolescents.

Objectively measured daytime sleepiness predicts weight change among adults: Findings from the Wisconsin Sleep Cohort Study.

OBJECTIVE: Body mass index (BMI) trajectories are associated with night-time sleep, but it is not clear how they relate to daytime sleepiness in population data. This study aimed to examine longitudinal associations between levels and changes in daytime sleepiness and BMI trajectories among men and women. METHODS: We estimated growth curve models among 827 participants in the Wisconsin Sleep Cohort Study (mean [sd] age = 55.2 [8.0] years at baseline). The outcome variable was BMI (kg/m2) and the key predictor was daytime sleepiness measured by Multiple Sleep Latency Test (MSLT) scores. Covariates included demographics, health behaviors, retirement status, stimulant use, and depressive symptoms. In sensitivity analyses, we evaluated the potential effects of cardiovascular disease, shift work status, and sleep apnea on the robustness of sleepiness and BMI associations. RESULTS: At the between-person level, men who were sleepier had higher BMI levels. At the within-person level, age moderated the positive association between sleepiness and BMI among women. Specifically, young women who became sleepier over time gained more BMI than older women with comparable increases in sleepiness. Furthermore, while BMI tended to increase with age among women, BMI trajectories were steeper among sleepy women than among well-rested women, who experienced less increase in BMI over time. CONCLUSION: The study suggested that levels and changes in daytime sleepiness as objectively measured by MSLT scores are associated with body mass among adults.

The impact of obesity on US mortality levels: the importance of age and cohort factors in population estimates.

OBJECTIVES: To estimate the percentage of excess death for US Black and White men and women associated with high body mass, we examined the combined effects of age variation in the obesity-mortality relationship and cohort variation in age-specific obesity prevalence. METHODS: We examined 19 National Health Interview Survey waves linked to individual National Death Index mortality records, 1986-2006, for age and cohort patterns in the population-level association between obesity and US adult mortality. RESULTS: The estimated percentage of adult deaths between 1986 and 2006 associated with overweight and obesity was 5.0% and 15.6% for Black and White men, and 26.8% and 21.7% for Black and White women, respectively. We found a substantially stronger association than previous research between obesity and mortality risk at older ages, and an increasing percentage of mortality attributable to obesity across birth cohorts. CONCLUSIONS: Previous research has likely underestimated obesity's impact on US mortality. Methods attentive to cohort variation in obesity prevalence and age variation in obesity's effect on mortality risk suggest that obesity significantly shapes US mortality levels, placing it at the forefront of concern for public health action.

Black-white disparities in 2009 H1N1 vaccination among adults in the United States: A cautionary tale for the COVID-19 pandemic.

BACKGROUND: Prior research has highlighted racial and ethnic disparities in H1N1 vaccination in the United States. Our study adds to this literature by utilizing an intersectionality framework to examine the joint influence of race and sex on H1N1 vaccination beliefs and behaviors among non-Hispanic blacks and non-Hispanic whites (hereafter blacks and whites). METHODS: Using data from the National H1N1 Flu Survey of U.S. adults, we measured differences in beliefs about the safety and efficacy of the H1N1 vaccine among black women, black men, white women, and white men. We then estimated a series of nested logistic regression models to examine how race/sex vaccination disparities were influenced by health beliefs, socioeconomic status (SES), pre-existing conditions, and healthcare. RESULTS: Black respondents were more likely than white respondents to express reservations about the safety and efficacy of the H1N1 vaccine. Consistent with those beliefs, white females reported the highest rate of H1N1 vaccination (28.4%), followed by white males (26.3%), black males (21.6%), and black females (17.5%). Differences in health beliefs, SES, pre-existing conditions, and healthcare explained lower odds of H1N1 vaccination among white men and black men, relative to white women. However, black women experienced 35-45% lower odds of vaccination than white women across all models, highlighting the intersectional nature of these associations. DISCUSSION: The 2009 H1N1 influenza pandemic provides a cautionary tale about the distribution of new vaccines across large populations with diverse racial, sex, and socioeconomic characteristics. Despite differences between the H1N1 and COVID-19 pandemics, our study warns that many black Americans will forego COVID-19 vaccines unless swift action is taken to address black-white disparities in access to vital resources. Public health stakeholders can also encourage widespread adoption of COVID-19 vaccines by tailoring health promotion messages for different groups of racial minorities, especially groups like black women who face intersecting disadvantages.

Contributors to reduced life expectancy among Native Americans in the Four Corners States.

To assess trends in life expectancy and the contribution of specific causes of death to Native American-White longevity gaps in the Four Corners states, we used death records from the National Center for Health Statistics and population estimates from the U.S. Census Bureau from 1999-2017 to generate period life tables and decompose racial gaps in life expectancy. Native American-White life expectancy gaps narrowed between 2001 and 2012 but widened thereafter, reaching 4.92 years among males and 2.06 years among females in 2015. The life expectancy disadvantage among Native American males was primarily attributable to motor vehicle accidents (0.96 years), liver disease (1.22 years), and diabetes (0.78 years). These causes of deaths were also primary contributors to the gap among females, forming three successive waves of mortality that occurred in young adulthood, midlife, and late adulthood, respectively, among Native American males and females. Interventions to reduce motor vehicle accidents in early adulthood, alcohol-related mortality in midlife, and diabetes complications at older ages could reduce Native American-White longevity disparities in the Four Corners states.

THE USES AND ABUSES OF AN AGE-PERIOD-COHORT METHOD: ON THE LINEAR ALGEBRA AND STATISTICAL PROPERTIES OF INTRINSIC AND RELATED ESTIMATORS.

As a sophisticated and popular age-period-cohort method, the Intrinsic Estimator (IE) and related estimators have evoked intense debate in demography, sociology, epidemiology and statistics. This study aims to provide a more holistic review and critical assessment of the overall methodological significance of the IE and related estimators in age-period-cohort analysis. We derive the statistical properties of the IE from a linear algebraic perspective, provide more precise mathematical proofs relevant to the current debate, and demonstrate the essential, yet overlooked, link between the IE and classical statistical tools that have been employed by scholars for decades. This study offers guidelines for the future use of the IE and related estimators in demographic research. The exposition of the IE and related estimators may help redirect, if not settle, the logic of the debate.

Habitual sleep, sleep duration differential, and weight change among adults: Findings from the Wisconsin Sleep Cohort Study.

OBJECTIVES: Assess longitudinal associations between diary-measured sleep duration and clinically assessed body mass index (BMI). DESIGN: Multilevel growth curve analyses examined how within-person changes and between-person differences in habitual sleep duration were associated with BMI trajectories. SETTING: Sleep diaries across 2-6 consecutive weekday and weekend nights at each data collection point, repeatedly collected at approximate 4-year intervals, for an average of 9.2 (standard deviation [SD] = 3.6) years between 1989 and 2011. PARTICIPANTS: About 784 participants (47% women) enrolled in the Wisconsin Sleep Cohort Study (mean [SD] age = 51.1 [8.0] years at baseline). MEASUREMENTS: The outcome variable was BMI (kg/m2). Key predictors were habitual sleep duration (defined as average weekday nighttime sleep duration) and sleep duration differential (defined as the difference between average weekday and average weekend nighttime sleep duration) at each data collection wave. RESULTS: Men with shorter habitual sleep duration on weekdays had higher BMI than men with longer habitual sleep duration on weekdays (ß = -0.90 kg/m2/hour, se = 0.34, p = .008). Participants with larger differentials between weekday and weekend sleep duration experienced more rapid BMI gain over time for both men (ß = 0.033 kg/m2/year per hour differential, se = 0.017, p = .044) and women (ß = 0.057 kg/m2/year per hour differential, se = 0.027, p = .036). CONCLUSION: This study suggests that habitual short sleep is associated with higher BMI levels in men and that a larger weekday-weekend sleep differential is associated with increasing BMI trajectories among both men and women in mid-to-late life.

Polysomnographic indicators of restorative sleep and body mass trajectories in the Wisconsin Sleep Cohort Study.

STUDY OBJECTIVES: Previous research suggests that reductions in restorative, slow-wave (N3), and rapid eye movement (REM) sleep are associated with weight gain and obesity in mid-to-late life. We extend prior work by examining how within-person (WP) changes and between-person (BP) differences in restorative sleep over several years are associated with body mass trajectories among participants in the Wisconsin Sleep Cohort Study (WSCS). METHODS: We used data from 4,862 polysomnographic (PSG) sleep studies and physical exams collected from 1,187 WSCS participants over an average duration of 14.9 years. Primary measures of interest included body mass index (BMI = kg/m2) and the percentages of time spent in N3 and REM sleep. We estimated a series of linear mixed regression models to examine how WP changes and BP differences in N3 and REM sleep affected BMI trajectories, controlling for other sleep measures, demographic characteristics, and health behaviors as potential confounders. RESULTS: Women in the WSCS experienced more rapid BMI gain than men. With some variation by sex, we found that (1) below-average N3 and REM sleep is associated with above-average BMI, and (2) within-person decreases in N3 and REM sleep over time are associated with gains in BMI. These findings persisted after adjustment for sleep duration and other potential confounders. CONCLUSIONS: Our findings highlight the importance of PSG indices of restorative sleep in mid-to-late life, suggesting that future clinical treatments and public health policies will benefit from heightened attention to sleep quality.

Contributors to the black-white life expectancy gap in Washington D.C.

Although the black-white gap in life expectancy has been shrinking in the U.S., national improvement conceals ongoing disparities. Nowhere is this more evident than Washington D.C., where the black-white gap has persistently exceeded 10 years. Using 1999-2017 mortality data from the National Center for Health Statistics, we employed demographic techniques to pursue three aims: first, we created period life tables to examine longevity trends in Washington D.C.; second, we decomposed black-white life expectancy differences into 23 causes of death in three time periods (2000, 2008, 2016); third, we assessed age-specific contributions for each cause of death. Findings revealed that heart disease (4.14 years), homicide (2.43 years), and cancer (2.30 years) contributed most to the 17.23-year gap among males in 2016. Heart disease and cancer contributed most at ages 55-69; homicide contributed most at ages 20-29. Among females in 2016, heart disease (3.24 years), cancer (2.36 years), and unintentional injuries (0.85 years) contributed most to the 12.06-year gap. Heart disease and cancer contributed most at ages 55-69, and unintentional injuries at ages 50-59. Our investigation provides detailed evidence about contributors to the black-white longevity gap in Washington D.C., which can aid in the development of targeted public health interventions.

Does context matter? A multilevel analysis of neighborhood disadvantage and children's sleep health.

OBJECTIVES: To determine how demographic, socioeconomic, and neighborhood characteristics are associated with bedtimes among US kindergarteners. DESIGN: Parents reported bedtimes of their children as well as personal, household, and residential characteristics via interviews in the Early Childhood Longitudinal Study-Kindergarten (ECLS-K) Class of 1998-1999. The ECLS-K links individual households to US Census tracts. SETTING: A random selection of 1,280 schools and surrounding communities in the US. PARTICIPANTS: A random selection of 16,936 kindergarteners and their parents. MEASUREMENTS: The 2 outcomes were regular and latest weekday bedtimes of kindergarteners. Through a series of nested multilevel regression models, these outcomes were regressed on individual- and neighborhood-level variables, including race/ethnicity, sex, family type, household income, mother's educational attainment, neighborhood disorder, and several additional neighborhood characteristics. RESULTS: Models showed significant (P < .05) bedtime disparities by race/ethnicity, sex, family income, and mother's educational attainment. Additionally, models tended to indicate that kindergarteners from disadvantaged neighborhoods experienced later bedtimes than children from more advantaged areas. Neighborhood characteristics accounted for a portion of racial/ethnic differences, suggesting that bedtime disparities are partly rooted in disparate environmental conditions. CONCLUSIONS: Reducing disparities in childhood sleep may require programs that target not only children and their parents, but also the communities in which they reside.

A procedure to correct proxy-reported weight in the National Health Interview Survey, 1976-2002.

BACKGROUND: Data from the National Health Interview Survey (NHIS) show a larger-than-expected increase in mean BMI between 1996 and 1997. Proxy-reports of height and weight were discontinued as part of the 1997 NHIS redesign, suggesting that the sharp increase between 1996 and 1997 may be artifactual. METHODS: We merged NHIS data from 1976-2002 into a single database consisting of approximately 1.7 million adults aged 18 and over. The analysis consisted of two parts: First, we estimated the magnitude of BMI differences by reporting status (i.e., self-reported versus proxy-reported height and weight). Second, we developed a procedure to correct biases in BMI introduced by reporting status. RESULTS: Our analyses confirmed that proxy-reports of weight tended to be biased downward, with the degree of bias varying by race, sex, and other characteristics. We developed a correction procedure to minimize BMI underestimation associated with proxy-reporting, substantially reducing the larger-than-expected increase found in NHIS data between 1996 and 1997. CONCLUSION: It is imperative that researchers who use reported estimates of height and weight think carefully about flaws in their data and how existing correction procedures might fail to account for them. The development of this particular correction procedure represents an important step toward improving the quality of BMI estimates in a widely used source of epidemiologic data.

The Influence of Hispanic Ethnicity and Nativity Status on 2009 H1N1 Pandemic Vaccination Uptake in the United States.

Previous research suggests Hispanic vaccination rates for H1N1 were similar to non-Hispanic whites. These previous estimates do not take into account nativity status. Using the 2010 National Health Interview Survey, we estimate adult H1N1 vaccination rates for non-Hispanic whites (n = 8780), U.S.-born Hispanics (n = 1142), and foreign-born Hispanics (n = 1912). To test Fundamental Cause Theory, we estimate odds of H1N1 vaccination while controlling for flexible resources (e.g., educational and economic capital), ethnicity, and nativity status. Foreign-born Hispanics experienced the lowest rates of H1N1 vaccination (15%), followed by U.S.-born Hispanics (18%) and non-Hispanic whites (21%). Regression models show odds of H1N1 vaccination did not differ among these three groups after controlling for sociodemographic characteristics. Insufficient access to flexible resources and healthcare coverage among foreign-born Hispanics was responsible for relatively low rates of H1N1 vaccination. Addressing resource disparities among Hispanics could increase vaccination uptake in the future, reducing inequities in disease burden.