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.

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.

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.

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.

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.

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 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.

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 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.

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.

Clarifying hierarchical age-period-cohort models: A rejoinder to Bell and Jones.

Previously, Reither et al. (2015) demonstrated that hierarchical age-period-cohort (HAPC) models perform well when basic assumptions are satisfied. To contest this finding, Bell and Jones (2015) invent a data generating process (DGP) that borrows age, period and cohort effects from different equations in Reither et al. (2015). When HAPC models applied to data simulated from this DGP fail to recover the patterning of APC effects, B&J reiterate their view that these models provide "misleading evidence dressed up as science." Despite such strong words, B&J show no curiosity about their own simulated data--and therefore once again misapply HAPC models to data that violate important assumptions. In this response, we illustrate how a careful analyst could have used simple descriptive plots and model selection statistics to verify that (a) period effects are not present in these data, and (b) age and cohort effects are conflated. By accounting for the characteristics of B&J's artificial data structure, we successfully recover the "true" DGP through an appropriately specified model. We conclude that B&Js main contribution to science is to remind analysts that APC models will fail in the presence of exact algebraic effects (i.e., effects with no random/stochastic components), and when collinear temporal dimensions are included without taking special care in the modeling process. The expanded list of coauthors on this commentary represents an emerging consensus among APC scholars that B&J's essential strategy--testing HAPC models with data simulated from contrived DGPs that violate important assumptions--is not a productive way to advance the discussion about innovative APC methods in epidemiology and the social sciences.

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.

Should age-period-cohort studies return to the methodologies of the 1970s?

Social scientists have recognized the importance of age-period-cohort (APC) models for half a century, but have spent much of this time mired in debates about the feasibility of APC methods. Recently, a new class of APC methods based on modern statistical knowledge has emerged, offering potential solutions. In 2009, Reither, Hauser and Yang used one of these new methods - hierarchical APC (HAPC) modeling - to study how birth cohorts may have contributed to the U.S. obesity epidemic. They found that recent birth cohorts experience higher odds of obesity than their predecessors, but that ubiquitous period-based changes are primarily responsible for the rising prevalence of obesity. Although these findings have been replicated elsewhere, recent commentaries by Bell and Jones call them into question - along with the new class of APC methods. Specifically, Bell and Jones claim that new APC methods do not adequately address model identification and suggest that "solid theory" is often sufficient to remove one of the three temporal dimensions from empirical consideration. They also present a series of simulation models that purportedly show how the HAPC models estimated by Reither et al. (2009) could have produced misleading results. However, these simulation models rest on assumptions that there were no period effects, and associations between period and cohort variables and the outcome were perfectly linear. Those are conditions under which APC models should never be used. Under more tenable assumptions, our own simulations show that HAPC methods perform well, both in recovering the main findings presented by Reither et al. (2009) and the results reported by Bell and Jones. We also respond to critiques about model identification and theoretically-imposed constraints, finding little pragmatic support for such arguments. We conclude by encouraging social scientists to move beyond the debates of the 1970s and toward a deeper appreciation for modern APC methodologies.

Gender and reinforcing associations between socioeconomic disadvantage and body mass over the life course.

Using the 1957-1993 data from the Wisconsin Longitudinal Study, we explore reciprocal associations between socioeconomic status (SES) and body mass in the 1939 birth cohort of non-Hispanic white men and women. We integrate the fundamental cause theory, the gender relations theory, and the life course perspective to analyze gender differences in (a) the ways that early socioeconomic disadvantage launches bidirectional associations of body mass and SES and (b) the extent to which these mutually reinforcing effects generate socioeconomic disparities in midlife body mass. Using structural equation modeling, we find that socioeconomic disadvantage at age 18 is related to higher body mass index and a greater risk of obesity at age 54, and that this relationship is significantly stronger for women than men. Moreover, women are more adversely affected by two mechanisms underlying the focal association: the obesogenic effect of socioeconomic disadvantage and the SES-impeding effect of obesity. These patterns were also replicated in propensity score-matching models. We conclude that gender and SES act synergistically over the life course to shape reciprocal chains of two disadvantaged statuses: heavier body mass and lower SES.

Monitoring receipt of seasonal influenza vaccines with BRFSS and NHIS data: challenges and solutions.

Despite the availability of vaccines that mitigate the health risks associated with seasonal influenza, most individuals in the U.S. remain unvaccinated. Monitoring vaccination uptake for seasonal influenza, especially among disadvantaged or high-risk groups, is therefore an important public health activity. The Behavioral Risk Factor Surveillance System (BRFSS) - the largest telephone-based health surveillance system in the world - is an important resource in monitoring population health trends, including influenza vaccination. However, due to limitations in the question that measures influenza vaccination status, difficulties arise in estimating seasonal vaccination rates. Although researchers have proposed various methodologies to address this issue, no systematic review of these methodologies exists. By subjecting these methods to tests of sensitivity and specificity, we identify their strengths and weaknesses and advance a new method for estimating national and state-level vaccination rates with BRFSS data. To ensure that our findings are not anomalous to the BRFSS, we also analyze data from the National Health Interview Survey (NHIS). For both studies, we find that restricting the sample to interviews conducted between January and September offers the best balance of sensitivity (>90% on average), specificity (>90% on average), and statistical power (retention of 92.2% of vaccinations from the target flu season) over other proposed methods. We conclude that including survey participants from these months provides a simple and effective way to estimate seasonal influenza vaccination rates with BRFSS and NHIS data, and we discuss potential ways to better estimate vaccination rates in future epidemiologic surveys.

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.