Maximum and Time-Dependent Body Mass Index and Breast Cancer Incidence Among Postmenopausal Women in the Black Women's Health Study

While excess weight is an established risk factor for postmenopausal breast cancer, consideration of maximum body mass index (maxBMI; BMI is calculated as weight (kg)/height (m)2) or BMI at a point in time relevant for breast carcinogenesis may offer new insights. We prospectively evaluated maxBMI and time-dependent BMI in relation to breast cancer incidence among 31,028 postmenopausal women in the Black Women's Health Study. During 1995-2015, a total of 1,384 diagnoses occurred, including 787 estrogen-receptor (ER)-positive (ER+) cases and 310 ER-negative (ER-) cases. BMI was assessed at baseline and 2, 4, 6, and 8 years before diagnosis. Cox proportional hazards regression was used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Compared with women with BMI <25, those with BMI ≥35 had increased risk of ER+ breast cancer but not ER- breast cancer. For BMI assessed 2 years before diagnosis, the HRs for ER+ breast cancer associated with maxBMI ≥35 and time-dependent BMI ≥35 were 1.42 (95% confidence interval (CI): 1.10, 1.84) and 1.63 (95% CI: 1.25, 2.13), respectively. The corresponding HR for time-dependent BMI assessed 6 years before diagnosis was 1.95 (95% CI: 1.45, 2.62). These findings suggest strong associations of BMI with risk of ER+ breast cancer in postmenopausal women, regardless of timing of BMI assessment.

County-level estimates of excess mortality associated with COVID-19 in the United States

The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.

County-level estimates of excess mortality associated with COVID-19 in the United States

The COVID-19 pandemic in the U.S. has been largely monitored using death certificates containing reference to COVID-19. However, prior analyses reveal that a significant percentage of excess deaths associated with the pandemic were not directly assigned to COVID-19. In this study, we estimated a generalized linear model of expected mortality based on historical trends in deaths by county of residence between 2011 and 2019. We used the results of the model to generate estimates of excess mortality and excess deaths not assigned to COVID-19 in 2020 for 1470 county sets in the U.S. representing 3138 counties. Across the country, we estimated that 438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19. Some regions (Mideast, Great Lakes, New England, and Far West) reported the most excess deaths in large central metros, whereas other regions (Southwest, Southeast, Plains, and Rocky Mountains) reported the highest excess mortality in nonmetro areas. The proportion assigned to COVID-19 was lowest in large central metro areas (79.3%). Regionally, the proportion of excess deaths assigned to COVID-19 was lowest in the Southeast (81.6%), Southwest (82.6%), Far West (83.7%), and Rocky Mountains (86.7%). Across the regions, the number of excess deaths exceeded the number of directly assigned COVID-19 deaths in most counties. The exception to this pattern occurred in New England, which reported more directly assigned COVID-19 deaths than excess deaths in metro and nonmetro areas. Many county sets had substantial numbers of excess deaths that were not accounted for in direct COVID-19 death counts. Estimates of excess mortality at the local level can inform the allocation of resources to areas most impacted by the pandemic and contribute to positive behavior feedback loops, such as increases in mask-wearing and vaccine uptake.

•

438,386 excess deaths occurred in 2020, among which 87.5% were assigned to COVID-19.

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There was substantial heterogeneity in excess death rates across counties.

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The mortality impact of the Covid-19 pandemic was effectively hidden in many counties.

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The percent of excess deaths assigned to COVID-19 was lowest in the South and West.

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New England uniquely reported more direct COVID-19 deaths than excess deaths.

Association of E-Cigarettes With Erectile Dysfunction: The Population Assessment of Tobacco and Health Study

INTRODUCTION

Smoking is independently associated with erectile dysfunction and cardiovascular disease. Given existing similarities in the constituents of e-cigarettes or ENDS and cigarettes, this study examines the association between ENDS use and erectile dysfunction.

METHODS

Data from Wave 4 (2016-2018) of the Population Assessment of Tobacco and Health study were analyzed in 2020. Male participants aged ≥20 years who responded to the erectile dysfunction question were included. Multivariable logistic regression models examined the association of ENDS use with erectile dysfunction within the full sample and in a restricted sample (adults aged 20-65 years with no previous cardiovascular disease diagnosis) while adjusting for multiple risk factors.

RESULTS

The proportion of erectile dysfunction varied from 20.7% (full sample) to 10.2% (restricted sample). The prevalence of current ENDS use within the full and restricted samples was 4.8% and 5.6%, respectively, with 2.1% and 2.5%, respectively, reporting daily use. Current daily ENDS users were more likely to report erectile dysfunction than never users in both the full (AOR=2.24, 95% CI=1.50, 3.34) and restricted (AOR=2.41, 95% CI=1.55, 3.74) samples. In the full sample, cardiovascular disease history (versus not present) and age ≥65 years (versus age 20-24 years) were associated with erectile dysfunction (AOR=1.39, 95% CI=1.10, 1.77; AOR= 17.4, 95% CI=12.15, 24.91), whereas physical activity was associated with lower odds of erectile dysfunction in both samples (AOR range=0.44-0.58).

CONCLUSIONS

The use of ENDS seems to be associated with erectile dysfunction independent of age, cardiovascular disease, and other risk factors. While ENDS remain under evaluation for harm reduction and smoking-cessation potential, ENDS users should be informed about the possible association between ENDS use and erectile dysfunction.

Widening Socioeconomic Disparities in Pain and Physical Function Among Americans Are Linked with Growing Obesity

Objectives: We investigate whether obesity accounts for widening socioeconomic disparities in pain. Methods: Based on nationally representative samples of Americans aged 25-74 in 1995-1996 and 2011-2014, we use logistic regression to model period change in headaches, backaches, and joint aches as well as physical limitations and to determine whether those changes vary by a multidimensional measure of socioeconomic status. Results: Prevalence of backaches, joint aches, physical limitations, and obesity increased between the mid-1990s and the early 2010s, particularly among more disadvantaged Americans. Socioeconomic disparities in frequent backaches, frequent joint pain, and physical limitations more than doubled over this period. We estimate that obesity and health conditions may account for nearly a quarter of the widening disparity in frequent backaches and about half of the widening disparity in frequent joint pain and physical limitations. Discussion: Widening disparities in backaches, joint pain, and physical limitations have coincided with growing obesity.

The unequal burden of the Covid-19 pandemic: Capturing racial/ethnic disparities in US cause-specific mortality

Despite a growing body of literature focused on racial/ethnic disparities in Covid-19 mortality, few previous studies have examined the pandemic's impact on 2020 cause-specific mortality by race and ethnicity. This paper documents changes in mortality by underlying cause of death and race/ethnicity between 2019 and 2020. Using age-standardized death rates, we attribute changes for Black, Hispanic, and White populations to various underlying causes of death and show how these racial and ethnic patterns vary by age and sex. We find that although Covid-19 death rates in 2020 were highest in the Hispanic community, Black individuals faced the largest increase in all-cause mortality between 2019 and 2020. Exceptionally large increases in mortality from heart disease, diabetes, and external causes of death accounted for the adverse trend in all-cause mortality within the Black population. Within Black and White populations, percentage increases in all-cause mortality were similar for men and women, as well as for ages 25–64 and 65+. Among the Hispanic population, however, percentage increases in mortality were greatest for working-aged men. These findings reveal that the overall impact of the pandemic on racial/ethnic disparities in mortality was much larger than that captured by official Covid-19 death counts alone.

Mortality following workplace injury: Quantitative bias analysis

PURPOSE

Recent studies have shown increased all-cause mortality among workers following disabling workplace injury. These studies did not account for 2 potentially important confounders, smoking and obesity. We estimated injury-related mortality accounting for these factors.

METHODS

We followed workers receiving New Mexico workers' compensation benefits (1994-2000) through 2013. Using data from the Panel Study of Income Dynamics, we derived the joint distribution of smoking status and obesity for workers with and without lost-time injuries. We conducted a quantitative bias analysis (QBA) to determine the adjusted relationship of injury and mortality.

RESULTS

We observed hazard ratios after adjusting for smoking and obesity of 1.13 for women (95% simulation interval (SI) 0.97 to 1.31) and 1.12 for men (95% SI 1.00 to 1.27). The estimated fully adjusted excess hazard was about half the estimates not adjusted for these factors.

CONCLUSIONS

Using QBA to adjust for smoking and obesity reduced the estimated mortality hazard from lost-time injuries and widened the simulation interval. The adjusted estimate still showed more than a 10 percent increase for both women and men. The change in estimates reveals the importance of accounting for these confounders. Of course, the results depend on the methods and assumptions used.

Loneliness, social isolation, and all-cause mortality in the United States

Social isolation and loneliness are both established risk factors for mortality, but it remains unclear how these two conditions interact with each other. We used data from 3975 adults aged 25-74 years who completed self-administered questionnaires (SAQs) for the Midlife in the United States (MIDUS) National Study Wave 2 (2004-2006). Loneliness was measured by asking participants how often they felt lonely. A shortened version of the Berkman-Syme Social Network Index that captured partnerships, friends/family, religious participation, and other forms of social connection was used to assess social isolation. Follow-up for all-cause mortality was censored at the end of 2016. We used progressively adjusted Cox proportional hazard models to examine the mortality risks of loneliness, social isolation, the components of social isolation, and combinations of loneliness and isolation. We adjusted for sociodemographic characteristics in our first models and then added health behaviors and physical and mental health conditions in subsequent models. In the minimally adjusted model, loneliness was associated with higher mortality risk (HR, 1.34; 95% CI, 1.22-1.47), but the association was not significant in the fully adjusted model. Social isolation was significantly associated with mortality in the minimally adjusted model (HR, 1.24; 95% CI, 1.15-1.34) and the fully adjusted model (HR, 1.13; 95% CI, 1.04-1.23). Having infrequent contact with family or friends was the component of isolation that had the strongest association with mortality. Contrary to prior literature, which has found either no interaction or a synergistic interaction between isolation and loneliness, we identified a significant, negative interaction between the two measures, indicating that loneliness and social isolation may partially substitute for one another as risk factors for mortality. Both are associated with a similar increased risk of mortality relative to those who express neither; we find no evidence that the combined effect is worse than experiencing either by itself.

Cannabis vaping among adults in the United States: Prevalence, trends, and association with high-risk behaviors and adverse respiratory conditions

The e-cigarette or vaping product-use-associated lung injury outbreak in the United States has raised concerns about the potential health effects of cannabis vaping, a method of cannabis use that is becoming increasingly popular. We used 2017-2019 Behavioral Risk Factor Surveillance System data to estimate yearly prevalence and trends of past-30-day cannabis use and vaping among US adults. We used multivariable logistic regression to evaluate the associations of cannabis vaping with high-risk behaviors, asthma, and other respiratory symptoms. Our sample size was 160,209 (53,945-2017; 55,475-2018; and 50,789-2019). Past-30-day cannabis use prevalence increased from 10.0% (95% CI, 9.4%-10.7%) in 2017 to 13.4% (12.8%-12.0%) in 2019. Similarly, past-30-day cannabis vaping prevalence increased from 1.0% (0.8%-1.2%) to 2.0% (1.7%-2.2%) over the same period, with the greatest increase, 1.2% to 3.9%, observed among young adults (18-24 years). Individuals who vaped cannabis were more likely to concurrently vape nicotine. Cannabis vaping was associated with increased odds of heavy alcohol use (aOR, 1.95; 95% CI, 1.45-2.63), binge drinking (aOR, 2.82; 95% CI, 2.25-3.54), and other high-risk behaviors (aOR, 2.47; 95% CI, 1.89-3.24). In analyses adjusting for sociodemographic characteristics and body mass index, cannabis vaping was not associated with asthma (aOR, 1.03; 95% CI, 0.64-1.64) or other respiratory symptoms (aOR, 1.08; 95% CI, 0.44-2.63). Adjusting for nicotine vaping did not substantively alter these associations. The prevalence of past-30-day cannabis vaping has increased, particularly among young adults, and was associated with high-risk behaviors. Although there was no association between cannabis vaping and asthma or other respiratory symptoms, the increasing trends of cannabis vaping, particularly among young adults, raise concern and underscore the need for continued surveillance.

Lipid profiles in users of combustible and electronic cigarettes

Electronic cigarette use has especially risen among adolescents and young adults. The aim of this study was to investigate fasting blood glucose and lipid profiles in chronic combustible cigarette and electronic cigarette users. We evaluated participants aged 21 to 45 (n = 525, mean age 31 ± 7 years, 45% women) without established cardiovascular disease or risk factors who were combustible cigarette users (n = 290), electronic cigarette users (n = 131; 65 sole users and 66 dual users), or never users (n = 104). In the first wave of enrollment (2014-2017), electronic cigarette users reported their products as first, second and third generation devices (e-cig users) and were all largely current (i.e., dual) or former (sole) combustible cigarette users, whereas in the second wave of enrollment (2019-2020), electronic cigarette users all reported pod-based device use (pod users) and included more sole users who were never smokers. In multivariable-adjusted analyses comparing to never users, both sole e-cig users and combustible cigarette users had higher glucose and triglycerides and lower high-density lipoprotein (HDL) cholesterol levels. Dual e-cig users showed higher triglycerides and very-low-density lipoprotein cholesterol, and lower HDL cholesterol compared to never users. In contrast, pod users (both sole and dual) had lipid profiles and glucose levels similar to never users. Overall, users of early generation electronic cigarettes display adverse metabolic profiles. In contrast, pod-based electronic cigarette users have similar lipid profiles to never users. Future studies are needed to understand the cumulative effects of electronic cigarette use on cardiometabolic health.

Association of Occupational Exposure to Inhaled Agents in Operating Rooms With Incidence of Chronic Obstructive Pulmonary Disease Among US Female Nurses

IMPORTANCE

Employment in operating rooms (ORs) may involve exposure to several inhaled agents, including surgical smoke and disinfectants, which are associated with adverse respiratory health effects. However, the association of long-term employment in ORs and chronic obstructive pulmonary disease (COPD) remains unknown.

OBJECTIVE

To examine the association of working in an OR with incidence of COPD among female nurses in the US.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from the Nurses' Health Study for US female registered nurses who provided information on questionnaires regarding OR employment history in 1984 and job type in 1982 and who had no history of COPD in 1984 (baseline). Data analyses were conducted from April 1, 2020, to January 31, 2021.

EXPOSURES

Duration of nursing in the OR and job type.

MAIN OUTCOMES AND MEASURES

The associations of any employment as an OR nurse, duration of employment, and duration and job type with incidence of self-reported, physician-diagnosed COPD. Hazard ratios (HRs) and 95% CIs were estimated using Cox proportional hazards regression models stratified by age and calendar year. Models were adjusted for covariates, with model 1 adjusting for age, model 2 also adjusting for cigarette smoking status and pack-year of smoking, and model 3 also adjusting for race and ethnicity, US Census region, and body mass index.

RESULTS

Among 75 011 female nurses included in the analyses, the mean (SD) age at baseline was 50.5 (7.2) years; 29% had a history of employment in an OR, and 3% had 15 or more years of OR experience. In model 3, employment in an OR for 15 or more years was associated with a 46% increased risk of developing COPD compared with no history of OR employment (HR, 1.46; 95% CI, 1.10-1.93). Compared with nurses who never worked in an OR and had an administrative or nursing education function or a nonnursing job in 1982, the risk of developing COPD was greater among nurses who provided outpatient care (HR, 1.24; 95% CI, 1.04-1.47) and nurses employed in inpatient units (HR, 1.31; 95% CI, 1.07-1.59) who had no history of OR employment and was 69% greater among nurses with OR experience of 15 years or more (HR, 1.69; 95% CI, 1.25-2.28).

CONCLUSIONS AND RELEVANCE

In this cohort study, OR employment of 15 years or more was associated with an increased risk of developing COPD among female nurses. Additional studies with more recent and direct environmental monitoring data of multiple occupational exposures are needed to assess the relative role of exposure to surgical smoke and disinfectants in the observed association.

Association of Health Care Factors With Excess Deaths Not Assigned to COVID-19 in the US

This cross-sectional study assesses health care factors associated with excess deaths not assigned to COVID-19 in US counties in 2020.

Body-mass index and diabetes risk in 57 low-income and middle-income countries: a cross-sectional study of nationally representative, individual-level data in 685 616 adults

BACKGROUND

The prevalence of overweight, obesity, and diabetes is rising rapidly in low-income and middle-income countries (LMICs), but there are scant empirical data on the association between body-mass index (BMI) and diabetes in these settings.

METHODS

In this cross-sectional study, we pooled individual-level data from nationally representative surveys across 57 LMICs. We identified all countries in which a WHO Stepwise Approach to Surveillance (STEPS) survey had been done during a year in which the country fell into an eligible World Bank income group category. For LMICs that did not have a STEPS survey, did not have valid contact information, or declined our request for data, we did a systematic search for survey datasets. Eligible surveys were done during or after 2008; had individual-level data; were done in a low-income, lower-middle-income, or upper-middle-income country; were nationally representative; had a response rate of 50% or higher; contained a diabetes biomarker (either a blood glucose measurement or glycated haemoglobin [HbA1c]); and contained data on height and weight. Diabetes was defined biologically as a fasting plasma glucose concentration of 7·0 mmol/L (126·0 mg/dL) or higher; a random plasma glucose concentration of 11·1 mmol/L (200·0 mg/dL) or higher; or a HbA1c of 6·5% (48·0 mmol/mol) or higher, or by self-reported use of diabetes medication. We included individuals aged 25 years or older with complete data on diabetes status, BMI (defined as normal [18·5-22·9 kg/m2], upper-normal [23·0-24·9 kg/m2], overweight [25·0-29·9 kg/m2], or obese [≥30·0 kg/m2]), sex, and age. Countries were categorised into six geographical regions: Latin America and the Caribbean, Europe and central Asia, east, south, and southeast Asia, sub-Saharan Africa, Middle East and north Africa, and Oceania. We estimated the association between BMI and diabetes risk by multivariable Poisson regression and receiver operating curve analyses, stratified by sex and geographical region.

FINDINGS

Our pooled dataset from 58 nationally representative surveys in 57 LMICs included 685 616 individuals. The overall prevalence of overweight was 27·2% (95% CI 26·6-27·8), of obesity was 21·0% (19·6-22·5), and of diabetes was 9·3% (8·4-10·2). In the pooled analysis, a higher risk of diabetes was observed at a BMI of 23 kg/m2 or higher, with a 43% greater risk of diabetes for men and a 41% greater risk for women compared with a BMI of 18·5-22·9 kg/m2. Diabetes risk also increased steeply in individuals aged 35-44 years and in men aged 25-34 years in sub-Saharan Africa. In the stratified analyses, there was considerable regional variability in this association. Optimal BMI thresholds for diabetes screening ranged from 23·8 kg/m2 among men in east, south, and southeast Asia to 28·3 kg/m2 among women in the Middle East and north Africa and in Latin America and the Caribbean.

INTERPRETATION

The association between BMI and diabetes risk in LMICs is subject to substantial regional variability. Diabetes risk is greater at lower BMI thresholds and at younger ages than reflected in currently used BMI cutoffs for assessing diabetes risk. These findings offer an important insight to inform context-specific diabetes screening guidelines.

FUNDING

Harvard T H Chan School of Public Health McLennan Fund: Dean's Challenge Grant Program.

Tobacco Use Prevalence and Transitions From 2013 to 2018 Among Adults With a History of Cardiovascular Disease

Background Although tobacco product use and transitions have been characterized in the general population, few studies have focused on individuals with established cardiovascular disease (CVD) in a population-based sample. Methods and Results We examined tobacco use prevalence and longitudinal patterns of tobacco product transitions in adults (≥18 years) of the nationally representative PATH (Population Assessment of Tobacco and Health) study, from 2013 to 2014 (Wave 1) through 2016 to 2018 (Wave 4). Prevalent CVD was classified through self-report of having had a heart attack, heart failure, stroke, or other heart condition. Factors associated with tobacco product use and transitions were investigated using survey logistic regression. We examined 2615 participants with self-reported CVD at Wave 1. Overall, 28.9% reported current tobacco use, equating to ≈6.2 million adults in the United States with prevalent CVD and current tobacco use. Among adults with CVD who are current tobacco users, the most commonly used product was cigarettes (82.8%), followed by any type of cigar (23.7%), and e-cigarette use (23.3%). E-cigarette use without concurrent cigarette use among participants with prevalent CVD was uncommon (1.1%). Factors associated with tobacco use were younger age, male sex, had lower education level, and lack of knowledge about the association between smoking and CVD. Men with prevalent CVD were less likely to use e-cigarettes compared with women (odds ratio [OR], 0.7; 95% CI, 0.5-0.9). Among cigarette users with CVD, transition rates between Waves 1 and 4 demonstrated <5% decrease in cigarette, with a 0.5% increase in e-cigarette use. Only ≈10% were in formal tobacco cessation programs. Conclusions Despite known harmful cardiovascular effects, over one fourth of adults with prevalent CVD use tobacco products and few quit smoking over the 4 waves of the PATH data set.

COVID-19 and excess mortality in the United States: A county-level analysis

BACKGROUND

Coronavirus Disease 2019 (COVID-19) excess deaths refer to increases in mortality over what would normally have been expected in the absence of the COVID-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to COVID-19. In this study, we take advantage of county-level variation in COVID-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to COVID-19 varies across subsets of counties defined by sociodemographic and health characteristics.

METHODS AND FINDINGS

In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct COVID-19 and all-cause mortality occurring in US counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a 10-week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more COVID-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black, and 59.6% non-Hispanic White. A total of 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and COVID-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to COVID-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than COVID-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to COVID-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of COVID-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to COVID-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

CONCLUSIONS

In this study, we found that direct COVID-19 death counts in the US in 2020 substantially underestimated total excess mortality attributable to COVID-19. Racial and socioeconomic inequities in COVID-19 mortality also increased when excess deaths not assigned to COVID-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Monitoring Information-Seeking Patterns and Obesity Prevalence in Africa With Internet Search Data: Observational Study

BACKGROUND

The prevalence of chronic conditions such as obesity, hypertension, and diabetes is increasing in African countries. Many chronic diseases have been linked to risk factors such as poor diet and physical inactivity. Data for these behavioral risk factors are usually obtained from surveys, which can be delayed by years. Behavioral data from digital sources, including social media and search engines, could be used for timely monitoring of behavioral risk factors.

OBJECTIVE

The objective of our study was to propose the use of digital data from internet sources for monitoring changes in behavioral risk factors in Africa.

METHODS

We obtained the adjusted volume of search queries submitted to Google for 108 terms related to diet, exercise, and disease from 2010 to 2016. We also obtained the obesity and overweight prevalence for 52 African countries from the World Health Organization (WHO) for the same period. Machine learning algorithms (ie, random forest, support vector machine, Bayes generalized linear model, gradient boosting, and an ensemble of the individual methods) were used to identify search terms and patterns that correlate with changes in obesity and overweight prevalence across Africa. Out-of-sample predictions were used to assess and validate the model performance.

RESULTS

The study included 52 African countries. In 2016, the WHO reported an overweight prevalence ranging from 20.9% (95% credible interval [CI] 17.1%-25.0%) to 66.8% (95% CI 62.4%-71.0%) and an obesity prevalence ranging from 4.5% (95% CI 2.9%-6.5%) to 32.5% (95% CI 27.2%-38.1%) in Africa. The highest obesity and overweight prevalence were noted in the northern and southern regions. Google searches for diet-, exercise-, and obesity-related terms explained 97.3% (root-mean-square error [RMSE] 1.15) of the variation in obesity prevalence across all 52 countries. Similarly, the search data explained 96.6% (RMSE 2.26) of the variation in the overweight prevalence. The search terms yoga, exercise, and gym were most correlated with changes in obesity and overweight prevalence in countries with the highest prevalence.

CONCLUSIONS

Information-seeking patterns for diet- and exercise-related terms could indicate changes in attitudes toward and engagement in risk factors or healthy behaviors. These trends could capture population changes in risk factor prevalence, inform digital and physical interventions, and supplement official data from surveys.

Assessing the Impact of the Covid-19 Pandemic on US Mortality: A County-Level Analysis

Background.

Covid-19 excess deaths refer to increases in mortality over what would normally have been expected in the absence of the Covid-19 pandemic. Several prior studies have calculated excess deaths in the United States but were limited to the national or state level, precluding an examination of area-level variation in excess mortality and excess deaths not assigned to Covid-19. In this study, we take advantage of county-level variation in Covid-19 mortality to estimate excess deaths associated with the pandemic and examine how the extent of excess mortality not assigned to Covid-19 varies across subsets of counties defined by sociodemographic and health characteristics.

Methods and Findings.

In this ecological, cross-sectional study, we made use of provisional National Center for Health Statistics (NCHS) data on direct Covid-19 and all-cause mortality occurring in U.S. counties from January 1 to December 31, 2020 and reported before March 12, 2021. We used data with a ten week time lag between the final day that deaths occurred and the last day that deaths could be reported to improve the completeness of data. Our sample included 2,096 counties with 20 or more Covid-19 deaths. The total number of residents living in these counties was 319.1 million. On average, the counties were 18.7% Hispanic, 12.7% non-Hispanic Black and 59.6% non-Hispanic White. 15.9% of the population was older than 65 years. We first modeled the relationship between 2020 all-cause mortality and Covid-19 mortality across all counties and then produced fully stratified models to explore differences in this relationship among strata of sociodemographic and health factors. Overall, we found that for every 100 deaths assigned to Covid-19, 120 all-cause deaths occurred (95% CI, 116 to 124), implying that 17% (95% CI, 14% to 19%) of excess deaths were ascribed to causes of death other than Covid-19 itself. Our stratified models revealed that the percentage of excess deaths not assigned to Covid-19 was substantially higher among counties with lower median household incomes and less formal education, counties with poorer health and more diabetes, and counties in the South and West. Counties with more non-Hispanic Black residents, who were already at high risk of Covid-19 death based on direct counts, also reported higher percentages of excess deaths not assigned to Covid-19. Study limitations include the use of provisional data that may be incomplete and the lack of disaggregated data on county-level mortality by age, sex, race/ethnicity, and sociodemographic and health characteristics.

Conclusions.

In this study, we found that direct Covid-19 death counts in the United States in 2020 substantially underestimated total excess mortality attributable to Covid-19. Racial and socioeconomic inequities in Covid-19 mortality also increased when excess deaths not assigned to Covid-19 were considered. Our results highlight the importance of considering health equity in the policy response to the pandemic.

Association of Coming Out as Lesbian, Gay, and Bisexual+ and Risk of Cigarette Smoking in a Nationally Representative Sample of Youth and Young Adults

Importance

Coming out as lesbian, gay, bisexual, or other identities besides heterosexual (LGB+) may represent a susceptible period for cigarette smoking initiation in youth and young adults.

Objective

To assess whether young people who change their sexual identity have higher risk of cigarette smoking initiation and current smoking compared with those with consistent sexual identities.

Design, Setting, and Participants

This cohort study used data from the nationally representative Population Assessment of Tobacco and Health study (wave 1, 2013-2014; wave 2, 2014-2015; wave 3, 2015-2016; wave 4, 2016-2018). Youth and young adults aged 14 to 29 years who were never smokers at wave 1 were included in this study. Analysis began October 2018 and ended June 2020.

Exposures

Consistent sexual identity (consistently heterosexual, consistently LGB+) vs changing sexual identity (coming out as LGB+, other LGB+ patterns) based on 4 waves of sexual identity data. Identities were further classified by distinguishing between bisexual and lesbian, gay, and other nonheterosexual identities.

Main Outcomes and Measures

Smoking initiation and current cigarette smoking at wave 4.

Results

Among 7843 individuals who never smoked at wave 1, 6991 (90.7%) reported a consistent sexual identity, and 852 (9.3%) changed sexual identity across waves. The mean (SE) baseline age of participants who reported consistent heterosexuality was 20.1 (0.8) years; consistently LGB+, 20.0 (3.7) years; coming out as LGB+, 18.0 (2.9) years, and other LGB+ pattern, 20.3 (3.8) years. A total of 14.1% (weighted) initiated smoking, and 6.3% were current smokers at wave 4. Compared with consistently heterosexual identities, coming out as LGB+ (23% vs 13%; odds ratio [OR], 1.72; 95% CI, 1.34-2.20), consistently LGB+ identities (17% vs 13%; OR, 1.45; 95% CI, 1.03-2.04), and other LGB+ patterns (17% vs 13%; OR, 1.47; 95% CI, 1.04-2.08) were positively associated with smoking initiation by wave 4. Compared with consistently heterosexual identities, ORs for smoking initiation were 2.24 (28% vs 13%; 95% CI, 1.72-2.92) for coming out as bisexual, 1.99 (23% vs 13%; 95% CI, 1.20-3.29) for consistently LGB+ with change to/from bisexual, and 2.20 (23% vs 13%; 95% CI, 1.40-3.46) for other LGB+ patterns with change to/from bisexual identity. Current smoking estimates were similar to those for smoking initiation.

Conclusions and Relevance

Compared with consistently heterosexual identities, changing sexual identity over follow-up was associated with smoking initiation and current smoking. The risk associated with changing sexual identities was concentrated among participants coming out as bisexual or reporting other changes in their identity to/from being bisexual. More research is needed on mechanisms underlying the association between changing sexual identity and smoking initiation to inform tailored prevention programs and tobacco regulations.

Estimates of the Association of Dementia With US Mortality Levels Using Linked Survey and Mortality Records

Importance

Vital statistics are the primary source of data used to understand the mortality burden of dementia in the US, despite evidence that dementia is underreported on death certificates. Alternative estimates, drawing on population-based samples, are needed.

Objective

To estimate the percentage of deaths attributable to dementia in the US.

Design, Setting, and Participants

A prospective cohort study of the Health and Retirement Study of noninstitutionalized US individuals with baseline exposure assessment in 2000 and follow-up through 2009 was conducted. Data were analyzed from November 2018 to May 2020. The sample was drawn from 7489 adults aged 70 to 99 years interviewed directly or by proxy. Ninety participants with missing covariates or sample weights and 57 participants lost to follow-up were excluded. The final analytic sample included 7342 adults.

Exposure

Dementia and cognitive impairment without dementia (CIND) were identified at baseline using Health and Retirement Study self- or proxy-reported cognitive measures and the validated Langa-Weir score cutoff.

Main Outcomes and Measures

Hazard ratios relating dementia and CIND status to all-cause mortality were estimated using Cox proportional hazards regression models, accounting for covariates, and were used to calculate population-attributable fractions. Results were compared with information on cause of death from death certificates.

Results

Of the 7342 total sample, 4348 participants (60.3%) were women. At baseline, 4533 individuals (64.0%) were between ages 70 and 79 years, 2393 individuals (31.0%) were between 80 and 89 years, and 416 individuals (5.0%) were between 90 and 99 years; percentages were weighted. The percentage of deaths attributable to dementia was 13.6% (95% CI, 12.2%-15.0%) between 2000 and 2009. The mortality burden of dementia was significantly higher among non-Hispanic Black participants (24.7%; 95% CI, 17.3-31.4) than non-Hispanic White participants (12.2%; 95% CI, 10.7-13.6) and among adults with less than a high school education (16.2%; 95% CI, 13.2%-19.0%) compared with those with a college education (9.8%; 95% CI, 7.0%-12.5%). Underlying cause of death recorded on death certificates (5.0%; 95% CI, 4.3%-5.8%) underestimated the contribution of dementia to US mortality by a factor of 2.7. Incorporating deaths attributable to CIND revealed an even greater underestimation.

Conclusions and Relevance

The findings of this study suggest that the mortality burden associated with dementia is underestimated using vital statistics, especially when considering CIND in addition to dementia.

Association of Electronic Cigarette Use With Incident Respiratory Conditions Among US Adults From 2013 to 2018

Importance

Generating robust and timely evidence about the respiratory health risks of electronic cigarettes (e-cigarettes) is critical for informing state and federal regulatory standards for product safety.

Objective

To examine the association of e-cigarette use with incident respiratory conditions, including chronic obstructive pulmonary disease (COPD), emphysema, chronic bronchitis, and asthma.

Design, Setting, and Participants

This prospective cohort study used data from the nationally representative cohort of US adults from the Population Assessment of Tobacco and Health (PATH) study, including wave 1 from 2013 to 2014, wave 2 from 2014 to 2015, wave 3 from 2015 to 2016, and wave 4 from 2016 to 2018. Individuals aged 18 years and older at baseline with no prevalent respiratory conditions were included in the analyses. Analyses were conducted from February to July 2020.

Exposures

e-Cigarette use was assessed by self-reported current use status (never, former, or current) at baseline.

Main Outcomes and Measures

Incident respiratory conditions, including COPD, emphysema, chronic bronchitis, and asthma, as well as a composite respiratory disease encompassing all 4 conditions.

Results

Among 21 618 respondents included in the analyses, 11 017 (491%) were men and 12 969 (65.2%) were non-Hispanic White. A total of 14 213 respondents were never e-cigarette users, 5076 respondents (11.6%) were former e-cigarette users, and 2329 respondents (5.2%) were current e-cigarette users. Adjusted for cigarette and other combustible tobacco product use, demographic characteristics, and chronic health conditions, there was an increased risk of respiratory disease among former e-cigarette uses (incidence rate ratio [IRR], 1.28; 95% CI, 1.09-1.50) and current e-cigarette users (IRR, 1.31; 95% CI, 1.08-1.59). Among respondents with good self-rated health, the IRR for former e-cigarette users was 1.21 (95%CI, 1.00-1.46) and the IRR for current e-cigarette users was 1.43 (95% CI, 1.14-1.79). For specific respiratory diseases among current e-cigarette users, the IRR was 1.33 (95% CI, 1.06-1.67) for chronic bronchitis, 1.69 (95% CI, 1.15-2.49) for emphysema, 1.57 (95% CI, 1.15-2.13) for COPD, and 1.31 (95% CI, 1.01-1.71) for asthma.

Conclusions and Relevance

This cohort study found that e-cigarette use was associated with an increased risk of developing respiratory disease independent of cigarette smoking. These findings add important evidence on the risk profile of novel tobacco products.

Racial/Ethnic Differences in Associations of Non-cigarette Tobacco Product Use With Subsequent Initiation of Cigarettes in US Youths

Introduction

Understanding which non-cigarette tobacco products precede smoking in youth across different racial/ethnic groups can inform policies that consider tobacco-related health disparities.

Methods

We used nationally representative, longitudinal data from the Population Assessment of Tobacco and Health Study waves 1–4. The sample was a dynamic cohort of cigarette-naïve youth aged 12–17 years. Mixed-effects models were used to assess non-cigarette product (e-cigarette, cigar product, or other product) use with cigarette use over 1-year intervals.

Results

Of the 28 788 observations pooled across waves 1–4, respondents were 48.7% non-Hispanic white, 13.9% non-Hispanic black, and 23.1% Hispanic. Odds of cigarette initiation over 1-year follow-up were higher among youth with prior use of e-cigarettes (odds ratio [OR], 2.76; 95% confidence interval [CI], 2.21–3.45), cigars (OR, 2.00; 95% CI, 1.42–2.80), or other products (OR, 1.66; 95% CI, 1.28–2.14) compared to never users. At the population level, 20.6% of cigarette initiation was attributable to e-cigarette use among white youth and 21.6% among Hispanic youth, while only 3.5% of cigarette initiation was attributable to e-cigarette use among black youth. In contrast, 9.1% of cigarette initiation for black youth was attributable to cigar use compared to only 3.9% for both white and Hispanic youth.

Conclusions

Prior use of e-cigarettes, cigars, and other non-cigarette products were all associated with subsequent cigarette initiation. However, white and Hispanic youth were more likely to initiate cigarettes through e-cigarette use (vs. cigar or other product use), while black youth were more likely to initiate cigarettes through cigar use (vs. e-cigarette or other product use).

Implications

Our findings suggest that previous studies on effects of non-cigarette tobacco products may overlook the critical role of cigar products as a pathway into cigarette smoking among US youth, particularly black youth. While our data support the importance of e-cigarette use as a pathway into smoking, regulatory actions aimed at addressing youth e-cigarette use alone may contribute to disparities in black versus white tobacco use and further exacerbate inequities in tobacco-related disease. Thus, contemporary policy development and discourse about the effects of non-cigarette tobacco products on cigarette initiation should consider cigar and other non-cigarette products as well as e-cigarettes.