Social-Economic Backgrounds to US County-Based COVID-19 Deaths: PLS-SEM Analysis

A complex interplay of social, economic, and environmental factors drove the COVID-19 epidemic. Understanding these factors is crucial in explaining the racial disparities observed in COVID-19 deaths. This research investigated various hypotheses, including ecological, racial, demographic, economic, and political party factors, to determine their impact on COVID-19 deaths. The study utilized data from the National Center for Health Statistics (NCHS), specifically focusing on COVID-19 deaths categorized by race and Hispanic origin in US counties, with over 100 recorded deaths as of July 11, 2022.

METHOD

To analyze the data, the study employed partial least squares (PLS) as the statistical approach, considering the presence of multicollinearity in the county-level socioeconomic data. SmartPLS4 software was utilized to illustrate paths depicting variance and covariance and to conduct significance tests. The analysis encompassed overall COVID-19 deaths and deaths among White, Black, and Hispanic Americans, utilizing the same latent variables and paths.

RESULTS

The results revealed that the number of residents aged 65 years or older in a county was the most influential predictor of COVID-19 deaths, irrespective of race. Economic factors emerged as the second strongest predictors. However, when considering each racial group separately, distinct factors aligned with the five hypotheses emerged as significant contributors to COVID-19 deaths. Furthermore, the diagrams illustrating the relationships between these factors (covariates) varied among racial groups, indicating that the underlying social influences differed across races.

DISCUSSION

In light of these findings, it becomes evident that a "one-size-fits-all" approach to prevention strategies is suboptimal. Instead, targeted prevention efforts tailored to specific racial and social classes at high risk of COVID-19 death could have provided more precise messaging and necessitate direct engagement.

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.

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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.

Dataset: percent of population covered by local government mask orders in the US

We present a dataset covering the extent of local mask orders between April and August 2020, in states which did not have statewide orders (and hence 100% coverage).  We obtained data from national and regional newspaper and broadcaster web-based articles, and city and county web pages. The information that we abstracted included: city or county of ordinance, date that the ordinance took effect, and the population of the city or county. In 14 states, city or county governments issued mask-wearing orders, and from our dataset it can been seen that the median population covered in the states was 37.5%; the coverage ranged from 1.6% (New Hampshire) to 77.1% (Arizona).  The dataset can be accessed from: https://doi.org/10.7939/DVN/A9C1UU.

Analyzing the spatial determinants of local Covid-19 transmission in the United States

The Coronavirus Disease 19 (COVID-19) has quickly spread across the United States (U.S.) since community transmission was first identified in January 2020. While a number of studies have examined individual-level risk factors for COVID-19, few studies have examined geographic hotspots and community drivers associated with spatial patterns in local transmission. The objective of the study is to understand the spatial determinants of the pandemic in counties across the U.S. by comparing socioeconomic variables to case and death data from January 22nd to June 30th 2020. A cluster analysis was performed to examine areas of high-risk, followed by a three-stage regression to examine contextual factors associated with elevated risk patterns for morbidity and mortality. The factors associated with community-level vulnerability included age, disability, language, race, occupation, and urban status. We recommend that cluster detection and spatial analysis be included in population-based surveillance strategies to better inform early case detection and prioritize healthcare resources.

Comparisons of individual- and area-level socioeconomic status as proxies for individual-level measures: evidence from the Mortality Disparities in American Communities study

Background

Area-level measures are often used to approximate socioeconomic status (SES) when individual-level data are not available. However, no national studies have examined the validity of these measures in approximating individual-level SES.

Methods

Data came from ~ 3,471,000 participants in the Mortality Disparities in American Communities study, which links data from 2008 American Community Survey to National Death Index (through 2015). We calculated correlations, specificity, sensitivity, and odds ratios to summarize the concordance between individual-, census tract-, and county-level SES indicators (e.g., household income, college degree, unemployment). We estimated the association between each SES measure and mortality to illustrate the implications of misclassification for estimates of the SES-mortality association.

Results

Participants with high individual-level SES were more likely than other participants to live in high-SES areas. For example, individuals with high household incomes were more likely to live in census tracts (r = 0.232; odds ratio [OR] = 2.284) or counties (r = 0.157; OR = 1.325) whose median household income was above the US median. Across indicators, mortality was higher among low-SES groups (all p < .0001). Compared to county-level, census tract-level measures more closely approximated individual-level associations with mortality.

Conclusions

Moderate agreement emerged among binary indicators of SES across individual, census tract, and county levels, with increased precision for census tract compared to county measures when approximating individual-level values. When area level measures were used as proxies for individual SES, the SES-mortality associations were systematically underestimated. Studies using area-level SES proxies should use caution when selecting, analyzing, and interpreting associations with health outcomes.

Social Distancing as a Health Behavior: County-Level Movement in the United States During the COVID-19 Pandemic Is Associated with Conventional Health Behaviors

BACKGROUND

Social distancing-when people limit close contact with others outside their household-is a primary intervention available to combat the COVID-19 pandemic. The importance of social distancing is unlikely to change until effective treatments or vaccines become widely available. However, relatively little is known about how best to promote social distancing. Applying knowledge from social and behavioral research on conventional health behaviors (e.g., smoking, physical activity) to support public health efforts and research on social distancing is promising, but empirical evidence supporting this approach is needed.

PURPOSE

We examined whether one type of social distancing behavior-reduced movement outside the home-was associated with conventional health behaviors.

METHOD

We examined the association between GPS-derived movement behavior in 2,858 counties in USA from March 1 to April 7, 2020 and the prevalence of county-level indicators influenced by residents' conventional health behaviors.

RESULTS

Changes in movement were associated with conventional health behaviors, and the magnitude of these associations were similar to the associations among the conventional health behaviors. Counties with healthier behaviors-particularly less obesity and greater physical activity-evidenced greater reduction in movement outside the home during the initial phases of the pandemic in the USA.

CONCLUSIONS

Social distancing, in the form of reduced movement outside the home, is associated with conventional health behaviors. Existing scientific literature on health behavior and health behavior change can be more confidently used to promote social distancing behaviors during the COVID-19 pandemic.

Medicaid Spending Differences for Child/Youth Community-Based Care in California's Decentralized Public Mental Health System

This study evaluated spending differences across counties during the decade after California decentralized its public mental health system. Medicaid data for 0-25 year olds using mental health services were collapsed to the county-year level (n = 627). Multivariate models with county fixed effects were used to predict per capita spending for community-based mental health care. While counties increased their spending over time, those with relatively low initial expenditures per user continued to spend less than counties with historically higher spending levels. Spending differences per user were most noticeable in counties with larger racial/ethnic minority populations that also had historically lower spending levels.

[Association of Notified Cases and Treatment Success Rates in Pulmonary Tuberculosis]

Background

Tuberculosis has long been recognized as a public health problem in large cities. The goals of the "Stop TB" strategy of the WHO specifically promote its study at the subnational level. Therefore, we aimed to describe the state of pulmonary tuberculosis (PTB) at the municipality level in Mexico.

Methods

We obtained data on new cases of PTB and treatment success rates (TSRs) per municipality from each state in Mexico, reported by the Mexican Social Security Institute to the National Epidemiological Surveillance System during 2013. Regression model was used to quantify associations between PTB and TSR by the municipality.

Results

We included 4090 cases of PTB distributed in 432 municipalities. There were 121 municipalities with TSRs < 85%. Lower TSRs were associated with older age, male sex, and comorbidities.

Conclusions

Results suggest a negative outcome of PTB treatment in patients with HIV and in those with malnutrition. The number of reported cases by the municipality was not associated with a negative treatment outcome.

Does Population Diversity Matter for Economic Development in the Very Long Term? Historic Migration, Diversity and County Wealth in the US

Does population diversity matter for economic development in the long run? Is there a different impact of diversity across time? This paper traces the short-, medium- and long-term economic impact of population diversity resulting from the big migration waves of the late nineteenth and early twentieth centuries to the United States (US). Using census data from 1880, 1900 and 1910, the settlement pattern of migrants across the counties of the 48 US continental states is tracked in order to construct measures of population fractionalization and polarization at county level. Factors which may have influenced both the individual settlement decision at the time of migration and county-level economic development in recent years are controlled for. The results of the analysis show that high levels of population fractionalization have a strong and positive influence on economic development in the short, medium and long run. High levels of polarization, by contrast, undermine development. Despite a stronger effect on income levels in the first 30 years, we find these relationships to be extremely long lasting: counties with a more heterogeneous population composition over 130 years ago are significantly richer today, whereas counties that were strongly polarized at the time of the migration waves have endured persistent negative economic effects.

Older adult social participation and its relationship with health: Rural-urban differences

In an aging world, there is increased need to identify places and characteristics of places that promote health among older adults. This study examines whether there are rural-urban differences in older adult social participation and its relationship with health. Using the 2003 and 2011 waves of the Wisconsin Longitudinal Study (n=3006), I find that older adults living in rural counties are less socially active than their counterparts in more-urban counties. I also find that relationships between social participation and health vary by the type of activity and rural-urban context.

Poor people on the move: county-to-county migration and the spatial concentration of poverty

"Poverty rates in high-poverty and low-poverty rural [U.S.] counties, and, thus, the spatial concentration of poverty, are affected by poverty-specific differences in in-migration and out-migration patterns. These patterns are investigated using 1985-90 county-to-county migration data from the decennial census. Effects on poverty rates of four migration flows (in- and out-migration of poor, in- and out-migration of nonpoor) are quantified, and their impacts on spatial concentration of poverty are assessed. The effect of selected county characteristics on the migration of the poor and nonpoor in nonmetro counties [is] estimated."

An evaluation of population projection errors for census tracts

"In this article we evaluate the accuracy and bias of projections of total population and population by age group for census tracts in three counties in Florida. We use [U.S. census] data from 1970 and 1980 and several simple extrapolation techniques to produce projections for 1990; we then compare these projections with 1990 census counts and evaluate the differences. For the total sample, we find mean absolute errors of 17%-20% for the three most accurate techniques for projecting total population and find no indication of overall bias. For individual age groups, mean absolute errors range from 20%-29%." This is a revised version of a paper presented at the 1993 Annual Meeting of the Population Association of America.

Age-specific migration and regional diversity

"This author examines patterns of age-specific migration between 1980 and 1990 for a small, growing region, the Pacific Northwest of the U.S.A., with the purpose of assessing the degree of geographic diversity in experience. A simple typology of the expected spatial and structural pattern of age-specific migration is proposed. Cluster analysis is used to group counties on the basis of age-specific rates of net migration. Even this fairly small region is found to exemplify most of the patterns that might be expected to occur in the nation as a whole."

Abortion services in the United States, 1991 and 1992

According to a survey by The Alan Guttmacher Institute, 1,529,000 abortions were performed in 1992, the lowest number of abortions since 1979. The abortion rate has gradually declined, from a high of 29 per 1,000 women of reproductive age in 1981 to 26 per 1,000 in 1992. The number of hospitals, clinics and physicians' offices that provide abortions--2,380 in 1992--has been declining at a rate of about 65 a year. Most of the decline has occurred among hospitals; the number providing abortions decreased by 18% between 1988 and 1992. Most U.S. counties (84%) have no known abortion provider, and in nonmetropolitan areas, 94% of counties have no provider. Among metropolitan areas, 33% have either no abortion provider or none that serves at least 50 women per year. Among states, North Dakota and South Dakota have only one provider each. Most abortions (69%) are performed in abortion clinics, and only 7% are performed in hospitals. Fewer than 1% of women who have an abortion are hospitalized for the procedure.

An evaluation of population forecast errors for Florida and its counties

The authors evaluate the forecasting accuracy of population projections formulated at state and county levels for Florida. They find that "projections of Florida population made in the 1970s and 1980s had errors...of approximately 2-3 percent for 5-year horizons, 5-6 percent for 10-year horizons and 8-9 percent for 15-year horizons. County projections had errors averaging approximately 5, 10 and 15 percent for these three lengths of horizon, respectively. Based on comparisons with other studies of state and substate population projections, we believe this is a good record of forecast accuracy...."

Population change and its components in Pennsylvania, 1980-1990

The author analyzes patterns of population growth in Pennsylvania by county. "Although Pennsylvania's population increased only slightly from 1980-1990, the pattern of change portrays noteworthy growth in many counties in the eastern half of the Commonwealth and decline throughout much of the west.... Analysis of the components of change--fertility, mortality, and net-migration--reveals significant differences in the role played by reproductive change in the demographic equation among counties which grew in population and, to a lesser extent, among those which declined. Changes in numbers of inhabitants and their components are related to location and selected demographic, social, and economic characteristics of the county populations."

Land use and demographic change: results from fast-growth counties

The authors analyze and compare two data sets on land-use change in U.S. counties with rapidly growing populations for the period from 1960 to the early 1980s. The results show that "the net effect of changing household numbers, household characteristics, and economic constraints on demand for land is likely to mean less conversion of land for urban uses in the future. Our studies showed that marginal urban land consumption remained nearly constant between 1960 and the early 1980s."

Oral contraceptives in women with diabetes

We evaluated the association of oral contraceptive use with the presence and severity of diabetic retinopathy, hypertension, and glycosylated hemoglobin in women of childbearing age who have diabetes. Neither current or past use nor number of years of use of oral contraceptives was associated with severity of retinopathy, hypertension, or current glycosylated hemoglobin. In conclusion, further study of various birth control methods in young women of childbearing age should be considered.

Height and mortality in the counties of England and Wales

Average heights of adults and children in the counties of England and Wales were examined using national samples of people born between 1920 and 1970. Although height increased over this 50-year period the differences between counties persisted. Average height in a county is closely related to its pattern of death rates, which were derived from all deaths during 1968-78. Counties with taller populations have lower mortality from chronic bronchitis, rheumatic heart disease, ischaemic heart disease and stroke, and higher mortality from three hormone-related cancers, of the breast, prostate and ovary. The inverse relation of height with bronchitis and cardiovascular disease is further evidence of risk factors acting in early childhood. The positive relation between height and cancers of the breast, ovary and prostate could suggest that promotion of child growth has disadvantages as well as benefits.

Mortality from diabetes mellitus, ischemic heart disease, and cerebrovascular disease among blacks in a higher income area

According to the 1980 census, blacks in Suffolk County on Long Island, NY, had a median family income of almost $20,000 versus $12,618 for blacks in the entire United States, or only 20 percent lower than that for whites in the county. Black-white ratios of age-specific death rates for 1979-83 in Suffolk County were elevated for all causes for men and women in age groups from 35-44 to 55-64 years (but not for those 75 years or older), for ischemic heart disease for women (but not men) for age groups from 35-44 to 55-64 years, for diabetes mellitus for most ages (especially for females), and for cerebrovascular disease for both men and women for all age groups from 35-44 to 65-74 years. The age-specific proportional mortality ratios (PMRs) for ischemic heart disease within educational level (less than 12 years and 12 or more years of school) were lower for black than for white men but more similar for black and white women. For diabetes, the PMRs were higher for black versus white women within both educational levels. PMRs for cerebrovascular disease were higher for black than white men within the group of decedents with less than 12 years of education. The findings are discussed with reference to racial differences in the prevalence of poverty as well as possible differences in risk factors (for example, obesity) or medical care independent of poverty.

Public policy, local labor demand, and migration in Sweden, 1979-84

"A model of private local labor demand and interjurisdictional migration is presented and estimated using data from Swedish counties and municipalities for 1979-84. Our goal is to compare the effects on local labor markets of distinctive public-sector programs with those of traditional market variables. We find that local income taxes and tax-equalization grants have important effects on local labor markets; regional development policy measures and geographical-mobility subsidies do not. Thus, recent efforts scaling back some of these programs may not materially alter the regional economy's performance. Wages and other traditional market variables are also often found to influence significantly local labor markets."

Tests of forecast accuracy and bias for county population projections

"This article deals with the forecast accuracy and bias of population projections for 2,971 counties in the United States. It uses three different projection techniques and data from 1950, 1960, 1970, and 1980 to make two sets of 10-year projections and one set of 20-year projections. These projections are compared with census counts to determine forecast errors. The size, direction, and distribution of forecast errors are analyzed by size of place, rate of growth, and length of projection horizon. A number of consistent patterns are noted, and an extension of the empirical results to the production of confidence intervals for population projections is considered." A comment by Paul M. Beaumont and Andrew M. Isserman is included (pp. 1,004-9) together with a rejoinder by the author (pp. 1,009-12). This is a revised version of a paper presented at the 1986 Annual Meeting of the Population Association of America (see Population Index, Vol. 52, No. 3, Fall 1986, p. 456).

Local authority fiscal stance and the pattern of residential migration in the north west of England

The degree of fiscal mobility present in household migration flows between local authority areas in northwestern England is assessed. Following an introduction, the paper is divided into three sections. "The first reviews the methodologies of previous attempts to assess the extent of fiscally induced migration, noting the dominance of American studies, and outlines a choice-theoretic structure within which it is possible to model human migration patterns. Section III considers the problems inherent in modelling migration flows, and Section IV presents results for a Compound Poisson analysis of migration between local authority areas within the four counties of the North West region of England, as well as an assessment of the prevalence of fiscal mobility."

Migration as a demographic response: the age differentials

"This study uses the theory of demographic response as the background against which regional human migration is examined as a response to selected environmental conditions for the 1,056 counties in the North Central Region [of the United States]. Specifically, this study addresses two migration-related questions concerning county populations in the North Central Region: (1) What are the socioeconomic, demographic, and ecological factors to which county populations respond in adjusting their migration behavior? (2) Do socially important age cohorts respond to these factors differently or in a similar manner?" Factors affecting migration are employment status, income levels, educational status, ethnic group, residence location, marital status, home ownership, and age. Data are from the U.S. Census Bureau for the period 1965-1970.