Abstract
Purpose.
Access to paid sick leave is critically important to promoting good health, caregiving, and stopping the spread of disease. In this study, we estimate whether access to paid sick leave among U.S. full-time workers differs between rural and urban residents.
Methods.
We used data from the 2020 National Health Interview Survey and included adult respondents between the ages of 18–64 who were employed full-time (n=12,086). We estimated bivariate differences in access to paid sick leave by rural/urban residence, and then calculated the predicted probability of access to paid sick leave, adjusting for socio-demographic and health characteristics, across different education levels.
Findings.
We find a nearly 10-percentage point difference in access to paid sick leave between rural and urban adults (68.1% vs. 77.1%, P<0.001). The difference in access to paid sick leave between rural and urban residents remained significant even after adjusting for socio-demographic and health characteristics. The fully-adjusted predicted probability of paid sick leave for rural full-time workers was 69.8%, compared with 76.4% for urban full-time workers (P<0.001). We also identified lower levels of paid leave for rural (vs. urban) workers within each educational category.
Conclusions.
Full-time workers in rural areas have less access to paid sick leave than full-time workers in urban areas. Without access to paid sick leave, rural and urban residents may go to work while contagious or forego necessary health care. Left to individual employers or localities, rural inequities in access to paid sick leave will likely persist.
Keywords: Employment, chronic conditions, paid sick leave, COVID-19
Employment is important for individual, family, and public health.1,2 Employment-based policies shape public health through effects on employees, their customers and clients, their families, and their communities. For example, employment is a key determinant for most working-aged adults in access to health insurance, financial resources, and how they structure their time. One key public health facet of employment-based policy is paid sick leave, that is, whether an employee has paid time off to attend to health and health care needs, both for themselves and for those they care for. Paid sick leave is important for promoting good health, especially during personal and collective health crises, such as the ongoing COVID-19 pandemic. Sick leave with pay makes it possible for people to take time off work to avoiding spreading a virus when infected and to allow time for testing, quarantining, and caregiving.2,3 Indeed, there is strong evidence that access to paid sick leave can reduce the likelihood of people working while sick, because it affords them financial stability to take time off work while they are healing – and potentially infectious.4 This, in turn, therefore decreases the likelihood that workers will show up to work while sick and infect their co-workers and community members.3
Beyond the critical importance of paid sick leave in a pandemic context, paid sick leave is also associated other positive health outcomes, such as a decrease in occupational injuries.5 This is because employees to show up to work while sick may be fatigued, taking medications, or experiencing other symptoms that interfere with their job performance, which can be especially risky in physically demanding occupations.5 Further, paid sick leave is fundamentally important for individual economic security, so that people do not need to choose between attending to their health and maintaining their income.6 However, paid sick leave is not uniformly available and there is no federal law requiring it.7 Part-time workers have more limited access to paid sick leave than full-time employees,8 with a recent Pew Research Center report showing that less than half (43%) of part-time workers across the U.S. have access to paid sick leave.9 Additionally, while most states have no laws requiring employers to provide paid sick leave, even in states and local areas that do require paid sick leave, many smaller employers are exempt. For example, Connecticut, Michigan, and Nevada require that employers provide paid sick leave, but those with less than 50 employees are exempt.7
Rural areas are qualitatively different from urban areas in ways that impact health, occupational opportunities, and workplace policies and supports.10,11 Rural residents have poorer health outcomes, and more limited access to health care.12,13 If they get sick and need to seek care, they often need to travel further for that care, and take more time off work to get it.14 For people without access to paid sick leave, that may mean a difficult choice between a paycheck, or keeping their job, and taking time to attend to their health, or the health of a loved one.4,15 Rural residents also have fewer financial resources and more transportation barriers,16,17 making choices between working and attending to health needs even more challenging.18 The jobs available to rural residents are also different, with lower-skilled (“blue-collar”) occupations constituting a larger share of the rural workforce than the urban workforce, where higher-skilled (“white-collar”) occupations are more common.19 In turn, higher-skilled jobs are more likely to have more comprehensive employment benefits, including paid sick leave,20 which may disadvantage rural workers who are disproportionately represented in lower-skilled jobs.
During the first two years of the COVID-19 pandemic, rural areas have had lower vaccination rates,21 and have borne a disproportionate burden of mortality compared to urban communities.22 As of May 30, 2022, the cumulative death rate from COVID-19 was 380.3 per 100,000 in rural areas, compared with 277.3 per 100,000 in urban areas.23 Access to paid sick leave can affect these outcomes, as it makes it more difficult to take time off of work when someone, or a family member, is feeling ill.15 Rural residents have also been less likely to work remotely during the pandemic, and more likely to work in jobs deemed “essential” (e.g., meatpacking plants), requiring that they show up to work in person.10 For example, a few months into the pandemic, in May 2020, less than 20% (19.8%) of rural employees were working remotely, compared with nearly 40% (38.4%) of urban employees.10 Without access to paid sick leave, this may mean increased community spread of the virus, as reflected in higher COVID-19 case and mortality rates among rural residents at many points in the pandemic.23,24
Given differences in health, socio-demographic characteristics, access to care, and occupational opportunities, paid sick leave might be especially important for rural residents. Yet, little is known about rural/urban differences to paid sick leave across population characteristics. Limited evidence from more than a decade ago, as well as from particular population groups, including informal caregivers who also work outside of the home, suggest that rural employees may have less access to workplace benefits, including paid sick leave.11,25 But, more recent evidence is needed to fully understand geographic differences access to paid sick leave and how current and future employment and leave policies can improve health equity across communities. This paper uses data from a nationally-representative sample of full-time workers to assess rural/urban differences in paid sick leave, accounting for health and socio-demographic characteristics.
Methods
Data and sample.
Data for this study come from 2020 National Health Interview Survey (NHIS), via IPUMS Health Surveys.26 The NHIS is a nationally-representative survey of civilian, non-institutionalized U.S. residents, which has been field annually since 1957. We limited our analysis to full-time workers, ages 18–64. We excluded part-time workers because part-time employment in the US is structured differently than full-time work and far less likely to include paid sick leave.9,20,27,28 Part-time workers also differ from full-time workers demographically; they are more likely to be women, younger than 20, or older than 65.28,29 Illuminating geographic disparities among working-age adults who are employed full time is an important first step in understanding differences in access to paid leave and the potential public health effects. In the NHIS, 13,287 respondents were employed full-time, and an additional 3,848 were employed part-time. The percentage of part-time workers was nearly identical in rural and urban areas (23.2% of the weighted sample in both.) Of the remaining full-time workers, 1,725 were 65 or older and excluded from the sample. We excluded workers age 65 and older because they are significantly less likely to be in the labor force and more likely to work part-time, indicating that they are substantively different from other working-aged adults.28,30 We further limited the sample to respondents with no missing data on any co-variates, leaving us with an analytic sample of 12,086 full-time employees.
Measures.
Paid sick leave was identified by respondents’ answer “yes” to this question in the NHIS: “Regarding your job or work, is paid sick leave available if you need it?” Employment status was measured using a combination of two questions. First, respondents were asked whether they had worked for pay within the last week at a job or business. Then, they were asked how many hours they usually work total at all jobs and businesses where they are employed. We created a binary variable, where full-time employed respondents were categorized as those who usually work for pay for 35 hours or more total per week.31 Rural location was defined using the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme for Counties. Urban counties included all of those within a metropolitan statistical area (MSA), including “large central metro,” “large fringe metro,” and “medium and small metro.” Rural counties included all nonmetropolitan counties not within an MSA. Respondents were categorized to rural/urban locations based on their home address, and not their employment address. (The latter is not available in the data.)
Socio-demographic covariates included age, sex (male or female), marital status (married/cohabitating, separated/divorced/widowed, or never married), sexual orientation (lesbian/gay/bisexual or heterosexual), race and ethnicity (non-Hispanic white, Hispanic, non-Hispanic Black, and Asian/Indigenous/other race or ethnicity), and educational attainment (less than high school, high school, some college, college degree or higher). Each of these was included because structural factors (e.g., racism, classism, ageism, sexism, homophobia) affect employment opportunities and occupational characteristics.28,32,33
We also included health characteristics, which might impact both employment and the need for paid leave in various ways, including the potential impacts of underlying health conditions or functional limitations in finding or maintaining employment. And yet, access to income and workplace benefits, like employer-sponsored insurance and paid sick leave, may be especially important for people with poorer health. To account for this, we included a count of chronic conditions (0, 1, 2, or 3 or more), which included arthritis/gout/lupus/fibromyalgia, asthma, cancer, coronary heart disease, high cholesterol, depression, anxiety disorder, diabetes, heart attack, hypertension, stroke, and chronic obstructive pulmonary disorder (COPD); for each, respondents were asked whether they had ever received a diagnosis. We show bivariate differences in access to paid sick leave for each chronic condition, but only include the cumulative count measure in fully-adjusted models because of multicollinearity. Finally, we included a measure of self-rated health (fair/poor vs. good/very good/excellent) in order to account for overall differences in health status. To check for potential multicollinearity, we generated the correlation coefficient between the count of chronic conditions and self-rated health. The coefficient was 0.27, indicating limited risk of multicollinearity with both variables in the model.
Analysis.
First, we generated bivariate comparisons of access to paid sick leave between rural and urban full-time employees across all socio-demographic characteristics and health status, using chi-squared tests to detect significant differences by location. Then, we used logistic regression models to paid sick leave adjusting for rurality and all covariates. We also conducted stratified logistic regression models by rural/urban location to see differences in the associations between socio-demographic, health, and paid sick leave. Finally, we calculated the predicted probability of having paid sick leave for rural and urban residents, holding all other measured covariates at their means and using Wald tests for significance. Because educational attainment is a primary sorting mechanism for employment opportunities, we also calculated predicted probabilities for rural and urban residents within each educational category. All analyses were conducted in Stata v.16 using survey weights to generate nationally-representative estimates.
Results
Compared with full-time employed adults in urban areas, full-time employed adults in rural areas were older, more likely to be married and non-Hispanic white, and less likely to identify as lesbian, gay, or bisexual (see Table 1 for sample characteristics). Full-time employed adults in rural areas also had lower educational attainment (22.8% with a college degree, vs. 40.0% of full-time employed adults in urban areas, p<0.001) and were in poorer health. While full-time employed adults in urban areas reported higher rates of asthma, full-time employed adults in rural areas reported significantly higher rates of several other chronic conditions (arthritis, cancer, anxiety disorder, hypertension, and COPD), higher overall counts of chronic conditions, and poorer self-rated health.
Table 1:
Sample Characteristics
| Total | Rural | Urban | P-value | ||
|---|---|---|---|---|---|
| Demographic Characteristics | |||||
| Age | <0.001 | ||||
| 18–24 | 9.6% | 9.8% | 9.6% | ||
| 25–34 | 25.3% | 21.8% | 25.8% | ||
| 35–44 | 23.9% | 20.5% | 24.3% | ||
| 45–54 | 22.9% | 26.5% | 22.4% | ||
| 55–64 | 18.3% | 21.4% | 17.9% | ||
| Sex | |||||
| Female | 42.9% | 44.6% | 42.6% | 0.273 | |
| Marital status | <0.001 | ||||
| Married/cohabitating | 66.1% | 70.6% | 65.4% | ||
| Separated/divorced/widowed | 10.6% | 11.6% | 10.5% | ||
| Never married | 23.3% | 17.9% | 24.1% | ||
| Sexual orientation | <0.01 | ||||
| Heterosexual | 96.1% | 97.5% | 95.9% | ||
| Lesbian, gay, bisexual | 3.9% | 2.5% | 4.1% | ||
| Race and ethnicity | <0.001 | ||||
| Non-Hispanic White | 62.8% | 82.5% | 60.1% | ||
| Hispanic | 17.7% | 6.4% | 19.3% | ||
| Non-Hispanic Black | 10.7% | 5.7% | 11.4% | ||
| Asian, Indigenous, Other | 8.8% | 5.5% | 9.3% | ||
| Socio-economic Status | |||||
| Educational attainment | <0.001 | ||||
| Less than high school | 7.3% | 9.5% | 7.0% | ||
| High school degree | 24.9% | 32.5% | 23.9% | ||
| Some college | 29.9% | 35.2% | 29.2% | ||
| College degree | 37.9% | 22.8% | 40.0% | ||
| Health Characteristics | |||||
| Chronic conditions | |||||
| Arthritis/gout/lupus/fibromyalgia | 10.8% | 15.2% | 10.1% | <0.001 | |
| Asthma | 13.8% | 11.1% | 14.2% | <0.01 | |
| Cancer | 4.5% | 6.4% | 4.2% | <0.001 | |
| Coronary heart disease | 1.2% | 1.0% | 1.2% | 0.655 | |
| High cholesterol | 17.7% | 18.2% | 17.6% | 0.592 | |
| Depression | 12.6% | 14.0% | 12.4% | 0.191 | |
| Anxiety disorder | 4.9% | 6.5% | 4.7% | <0.01 | |
| Diabetes | 12.5% | 14.0% | 12.3% | 0.100 | |
| Heart attack | 0.8% | 0.9% | 0.8% | 0.770 | |
| Hypertension | 21.3% | 24.0% | 20.9% | <0.05 | |
| Stroke | 0.7% | 0.7% | 0.7% | 0.972 | |
| COPD | 1.8% | 3.9% | 1.5% | <0.001 | |
| Count of chronic conditions | <0.05 | ||||
| 0 | 45.1% | 41.4% | 45.6% | ||
| 1 | 27.3% | 26.9% | 27.4% | ||
| 2 | 15.0% | 16.2% | 14.8% | ||
| 3+ | 12.7% | 15.5% | 12.3% | ||
| Self-rated health | <0.05 | ||||
| Fair/poor | 6.1% | 7.9% | 5.8% | ||
| Good/very good/excellent | 93.9% | 92.1% | 94.2% | ||
| N | 12,086 | 1,527 | 10,559 | ||
| Weighted percent | 100% | 12.3% | 87.7% | ||
Data are from the 2020 National Health Interview Survey and include all working-age (18–64 years old) adults who were employed full-time. P-value represents differences between rural and urban employed adults.
Rural full-time employed adults were nearly ten percentage points less likely than urban employed adults to report having access to any paid sick leave (68.1% vs. 77.1%, P<0.001; see Table 2). With the exception of employed adults with a college degree or higher, rural employed adults reported lower rates of access to paid sick leave across every socio-demographic and health characteristic, with the majority of those differences being statistically significant at P<0.05. The largest statistically significant rural/urban differences were observed for adults ages 18–24 (38.8% vs. 65.1%, P<0.001), adults who were never married (53.5% vs. 74.3%, P<0.001), adults with less than a high school education (28.1% vs. 53.4%, P<0.001), and adults who had been diagnosed with diabetes (56.7% vs. 76.9%, P<0.01); in each instance, the rural/urban difference was greater than 20 percentage points.
Table 2:
Frequency of Paid Sick Leave by Individual Characteristics
| Total | Rural | Urban | P-value | ||
|---|---|---|---|---|---|
| Overall | 76.0% | 68.1% | 77.1% | <0.001 | |
| Demographic Characteristics | |||||
| Age | |||||
| 18–24 | 61.8% | 38.8% | 65.1% | <0.001 | |
| 25–34 | 78.5% | 71.4% | 79.3% | <0.05 | |
| 35–44 | 79.0% | 73.4% | 79.6% | 0.059 | |
| 45–54 | 75.5% | 68.5% | 76.6% | <0.05 | |
| 55–64 | 76.7% | 72.7% | 77.4% | 0.104 | |
| Sex | |||||
| Female | 79.2% | 76.1% | 79.7% | 0.093 | |
| Male | 73.6% | 61.7% | 75.2% | <0.001 | |
| Marital status | |||||
| Married/cohabitating | 77.4% | 71.7% | 78.3% | <0.01 | |
| Separated/divorced/widowed | 74.9% | 68.9% | 75.8% | 0.085 | |
| Never married | 72.4% | 53.5% | 74.3% | <0.001 | |
| Sexual orientation | |||||
| Heterosexual | 75.9% | 68.0% | 77.1% | <0.001 | |
| Lesbian, gay, bisexual | 77.0% | 72.6% | 77.3% | 0.591 | |
| Race and ethnicity | |||||
| Non-Hispanic White | 77.7% | 69.0% | 79.4% | <0.001 | |
| Hispanic | 67.4% | 57.2% | 67.8% | 0.114 | |
| Non-Hispanic Black | 76.4% | 66.4% | 77.1% | 0.197 | |
| Asian, Indigenous, Other | 80.7% | 70.3% | 81.5% | 0.102 | |
| Socio-economic Status | |||||
| Educational attainment | |||||
| Less than high school | 49.3% | 28.1% | 53.4% | <0.001 | |
| High school degree | 67.3% | 62.1% | 68.2% | 0.061 | |
| Some college | 76.0% | 72.0% | 76.7% | <0.05 | |
| College degree | 86.9% | 87.5% | 86.8% | 0.712 | |
| Health Characteristics | |||||
| Chronic conditions | |||||
| Arthritis/gout/lupus/fibromyalgia | 74.8% | 68.2% | 76.2% | 0.079 | |
| Asthma | 77.9% | 71.0% | 78.6% | 0.061 | |
| Cancer | 80.5% | 72.7% | 82.2% | 0.058 | |
| Coronary heart disease | 78.4% | 70.6% | 79.4% | 0.515 | |
| High cholesterol | 79.8% | 72.4% | 80.9% | <0.01 | |
| Depression | 75.4% | 63.2% | 77.3% | <0.01 | |
| Anxiety disorder | 73.6% | 67.6% | 78.2% | <0.05 | |
| Diabetes | 76.7% | 56.7% | 76.9% | <0.01 | |
| Heart attack | 75.5% | 65.4% | 77.1% | 0.423 | |
| Hypertension | 78.1% | 69.3% | 79.6% | <0.01 | |
| Stroke | 72.4% | 48.0% | 75.9% | 0.225 | |
| COPD | 66.0% | 55.6% | 69.8% | 0.177 | |
| Count of chronic conditions | |||||
| 0 | 74.1% | 65.0% | 75.3% | <0.001 | |
| 1 | 77.7% | 74.6% | 78.1% | 0.269 | |
| 2 | 78.4% | 70.5% | 79.6% | <0.05 | |
| 3+ | 76.0% | 62.8% | 78.4% | <0.001 | |
| Self-rated health | |||||
| Fair/poor | 67.8% | 55.4% | 70.2% | <0.05 | |
| Good/very good/excellent | 76.5% | 69.3% | 77.5% | <0.001 | |
| N | 12,086 | 1,527 | 10,559 | ||
Data are from the 2020 National Health Interview Survey. P-value represents differences between rural and urban full-time employed adults ages 18–64 in frequency of paid sick leave across each socio-demographic and health characteristic.
Rural employed adults had lower odds of access to paid sick leave after adjusting for socio-demographic characteristics, health status, and hours worked (adjusted odds ratio [AOR]: 0.71, P<0.001; see Table 3). Being between the ages of 25–64 (vs. 18–24), female, having higher education, and better self-rated health were all associated with higher odds of paid sick leave in the fully adjusted model. In models stratified by rurality, the associations between covariates and paid sick leave were similar for rural and urban employed adults, with a few notable exceptions. The associations between education and paid sick leave were nearly double, or higher, at every level for rural employed adults vs. urban employed adults and the association between chronic conditions and paid sick leave was only significant for urban employed adults.
Table 3:
Logistic Regression Models Predicting Access to Paid Sick Leave
| Total | Rural Only | Urban Only | |||||
|---|---|---|---|---|---|---|---|
| AOR | 95% CI | AOR | 95% CI | AOR | 95% CI | ||
| Rural | 0.71*** | (0.60, 0.84) | |||||
| Demographic Characteristics | |||||||
| Age (Ref: 18–24) | |||||||
| 25–34 | 1.81*** | (1.33, 2.20) | 2.61** | (1.44, 4.74) | 1.60** | (1.21, 2.11) | |
| 35–44 | 1.79*** | (1.40, 2.28) | 2.86** | (1.58, 5.17) | 1.65*** | (1.26, 2.16) | |
| 45–54 | 1.51** | (1.16, 1.97) | 2.26** | (1.30, 3.94) | 1.40* | (1.04, 1.89) | |
| 55–64 | 1.68*** | (1.29, 2.17) | 3.00*** | (1.66, 5.42) | 1.50** | (1.12, 1.99) | |
| Female | 1.25*** | (1.11, 1.41) | 1.61** | (1.18, 2.21) | 1.19** | (1.05, 1.35) | |
| Marital status (Ref: Married/cohabitating) | |||||||
| Separated/divorced/widowed | 0.87 | (0.74, 1.02) | 0.69 | (0.47, 1.03) | 0.90 | (0.76, 1.07) | |
| Never married | 0.90 | (0.78, 1.05) | 0.65 | (0.40, 1.06) | 0.94 | (0.81, 1.11) | |
| Lesbian, gay, bisexual | 0.92 | (0.69, 1.22) | 1.22 | (0.45, 3.29) | 0.89 | (0.66, 1.19) | |
| Race and ethnicity (Ref: non-Hispanic white) | |||||||
| Hispanic | 0.87 | (0.73, 1.04) | 1.16 | (0.64, 2.09) | 0.84 | (0.70, 1.00) | |
| Non-Hispanic Black | 1.03 | (0.84, 1.28) | 1.11 | (0.47, 2.61) | 1.02 | (0.83, 1.27) | |
| Asian, Indigenous, Other | 1.09 | (0.87, 1.36) | 1.24 | (0.50, 3.03) | 1.08 | (0.86, 1.36) | |
| Socio-economic Status | |||||||
| Educational attainment (Ref: <high school) | |||||||
| High school degree | 2.16*** | (1.57, 2.59) | 3.03*** | (2.40, 6.76) | 1.75*** | (1.32, 2.32) | |
| Some college | 2.94*** | (2.28, 3.79) | 5.99*** | (3.57, 10.02) | 2.55*** | (1.92, 3.39) | |
| College degree | 5.60*** | (4.22, 7.23) | 14.38*** | (7.57, 27.30) | 4.79*** | (3.62, 6.24) | |
| Health Characteristics | |||||||
| Count of chronic conditions (Ref: 0) | |||||||
| 1 | 1.20* | (1.03, 1.39) | 1.35 | (0.89, 2.05) | 1.17 | (1.00, 1.37) | |
| 2 | 1.27* | (1.05, 1.53) | 1.23 | (0.78, 1.91) | 1.27* | (1.04, 1.56) | |
| 3+ | 1.18 | (0.97, 1.44) | 0.84 | (0.52, 1.36) | 1.26* | (1.02, 1.57) | |
| Good/very good/excellent self-rated health | 1.29* | (1.03, 1.62) | 1.36 | (0.73, 2.51) | 1.27 | (0.99, 1.62) | |
| N | 12,086 | 10,559 | 1,527 | ||||
Notes: AOR=adjusted odds ratio; CI=confidence interval. Results significant at
p<0.05,
p<0.01,
p<0.001.
Adjusting for all socio-demographic and health covariates, full-time employed adults in rural areas had a 69.8% predicted probability of access to paid sick leave, compared with 76.4% for full-time employed adults in urban areas (P<0.001; see Table 4).
Table 4:
Predicted Probability of Paid Sick Leave by Rural/Urban Location and Educational Attainment
| Rural | Urban | Difference | |||
|---|---|---|---|---|---|
| Predicted probability | 95% Confidence interval | Predicted probability | 95% Confidence interval | Urban – Rural | |
| Full sample | 69.8% | (0.66, 0.73) | 76.4% | (0.74, 0.78) | 6.6% |
| Educational attainment | |||||
| <High School | 44.5% | (0.38, 0.51) | 53.0% | (0.47, 0.59) | 8.5% |
| High School | 61.8% | (0.58, 0.66) | 69.5% | (0.67, 0.72) | 7.6% |
| Some College | 70.3% | (0.67, 0.74) | 76.8% | (0.74, 0.79) | 6.6% |
| College+ | 81.8% | (0.79, 0.85) | 86.3% | (0.85, 0.88) | 4.5% |
Data are from the 2020 National Health Interview Survey and include all full-time employed adults ages 18–64 (n=12,086). Differences between rural and urban employed adults in access to paid sick leave significant at ***p<0.001 for full sample and across educational attainment categories. All other co-variates held at their means.
Holding all else constant, rural residents with less than a high school degree had the lowest predicted probability of having access to paid sick leave, at 44.5%, and urban residents with a college degree or more had the highest predicted probability, at 86.3%. The differences by educational attainment within rural and urban location were significant at P<0.001.
Discussion
In this study, we found that rural adults who are employed full-time have less access to paid sick leave than urban adults who are employed full-time, above and beyond known rural/urban differences in socio-demographics and health. Within rural areas, the likelihood of having access to paid leave was not uniformly distributed, with the lowest rates among young adults (ages 18–24), people who have never been married, Hispanic adults, adults with a history of diabetes or stroke, and adults in fair/poor health. We found the very lowest access to paid sick leave among rural full-time employed adults with less than a high school degree, at 28.1%. These rural disparities in access to paid sick leave persisted in fully-adjusted models, highlighting the intersecting public health risks posed by geographic location and socio-demographic characteristics.
The geographic inequities we identified in access to paid leave compound other structural barriers to good health that rural residents experience. Rural areas have more limited access to health care, including declining availability of hospital services,34 often putting rural residents in the position of traveling further to receive care. As a result, rural residents may need to invest more time in receiving care when they or their loved ones are sick. This can be difficult, or even impossible, without access to paid sick leave.4,35 Further, in light of the COVID-19 pandemic, not having access to paid sick leave may mean that people show up to work while sick, increasing the chances of spreading their illness. Indeed, research on the 2020 Families First Coronavirus Response Act (FFCRA)’s expansion of paid sick leave benefits during the COVID-19 pandemic indicated that access to paid sick leave was associated with a decrease in COVID-19 cases.36
This study’s findings showing differences in access to paid sick leave by both geography and educational attainment also illuminate the structural inequities that undergird U.S. economic and health care systems.37 For people with lower educational attainment, who are disproportionately represented in rural areas, employment is less likely to offer paid access to sick leave. Yet, people with lower educational attainment also tend to be in poorer health and have fewer financial resources. As such, attending to their health may be especially urgent, but they are in the most precarious position to do so. People with less education are overrepresented in rural areas, where health outcomes are worse, incomes are lower, and health care is scarcer.11,12,17,38
The differences that we found in access to paid sick leave by level of educational attainment for both rural and urban full-time workers was stark. Above and beyond other socio-demographic and health characteristics, the predicted probability of having paid sick leave at one’s job went up with each level of educational attainment (from less than high school, to high school, to some college, to college degree or higher.) In fact, the jump between levels was often at least 10 percentage points. For rural residents, there was more than a 17 percentage point difference in the predicted probability of having access to paid sick leave between those who have less than a high school degree and those who have a high school degree (44.5% vs. 61.8%). Further, within each level of educational attainment, access to paid sick leave was lower among rural residents, highlighting the potential importance of access to educational opportunities for narrowing gaps in paid sick leave and the intersecting risks posed by lower education and geographic inequity. Scholars have identified these patterns as a dual-labor market, where workers with a college degree have access to higher wages and employment benefits, including paid sick leave, while workers without a college degree are constrained to a secondary labor market with lower wages and limited employment benefits.20
Limitations
As with any of study of this type, our findings should be considered in light of their potential limitations. The NHIS does not allow us to see detail on quality or duration of paid sick leave, job type, or working conditions, nor does it allow us to see information on the employer, such as firm size. Additionally, our measure of full-time work was based on self-report of number of hours worked; it is possible that some respondents worked multiple part-time jobs, for which the total hours qualified as full-time. As such, we are missing nuance in our analyses and are unable to tell which employees would be potentially exempt from FFCRA protections. Further, we are using data from 2020, during which FFCRA took effect. To the extent that employees gained sick leave protections from that act, we may be overestimating the typical access to paid leave for rural and urban employed adults. Finally, by focusing only on full-time workers, we leave out part-time employees and people who are unemployed, who may be hardest hit by a lack of benefits.39 Future research should build on this study to add nuance to our understanding of rural/urban differences in access to paid sick leave and other workplace protections among other populations, including part-time workers.
Public Health Implications
Rural residents working full time have more limited access to paid sick leave than urban full-time workers, and there are important public health implications of this inequity. Lack of access to paid sick leave may compound the challenges that rural residents face when they, or a loved one, are ill. Paid sick leave allows employees to take time off if they are sick – even contagious – or injured,4 which may help to facilitate more rapid access to care, treatment, and healing, as well as decreased spread of infectious diseases. Paid sick leave is also associated with greater use of preventive services35,40 and decreased emergency department use,40 promoting better health outcomes and less unnecessary health care spending across the population. And, access to paid sick leave is associated with greater job security,15,41 allowing one to attend to their health without fear of losing their income. Such security has implications not only for individual and family health, but for broader community and public health, as clearly evidenced by the COVID-19 pandemic.36
Currently, most decisions about workplace benefits, including paid sick leave, are left to individual employers, with some notable exceptions. The 2020 FFCRA expanded access to paid sick leave for many employees, but has since expired.39 Additional legislation to expand access to paid sick leave has been proposed at the federal level, but has yet to be passed.42 Sixteen states have passed legislation to require paid sick leave statewide, but those laws vary in who is covered, with many exempting small employers,7 as well as in how full and part-time work is defined.43 Additionally, of the 18 states across the U.S. where 30% of more of the population lives in a rural area,44 only two (Maine and Vermont) are included in the list of 16 states with paid leave legislation. Some individual local governments have passed paid sick leave, but those are almost exclusively large urban areas, such as New York City, Chicago, and Los Angeles.7 If paid sick leave policies are left to individual employers, municipalities, or states, unequal distribution of paid sick leave may continue to exacerbate rural inequities in health.
Acknowledgments
This material is the result of work supported with resources and the use of facilities at the Minneapolis VA Health Care System.
Source of Funding
The authors gratefully acknowledge support from the Minnesota Population Center (P2C HD041023) funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD). This research was also supported by the National Institutes of Health’s National Center for Advancing Translational Sciences, grants KL2TR002492 and UL1TR002494.
Footnotes
Declaration of interests
All other authors declare that they have no conflict of interests related to this study.
Disclaimer
The views expressed in this article are those of the authors and do not reflect the views of the United States Government, the Department of Veterans Affairs, the National Institutes of Health, the National Institutes of Health’s National Center for Advancing Translational Sciences or any of the authors’ affiliated academic institutions.
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