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. 2025 May 9;68(7):598–606. doi: 10.1002/ajim.23733

The Impact of Employment Status, Income, and Occupation on the Association Between Workplace Benefits and Health‐Related Work Absences

Jim P Stimpson 1,✉, Jessica Billig 1, Tami Gurley 1, Joshua M Liao 1
PMCID: PMC12159521  PMID: 40345984

ABSTRACT

Background

Workplace benefits such as paid sick leave and employer‐sponsored health insurance influence workers' ability to take time off when ill or injured. We examined whether and to what extent these workplace benefits complement each other in affecting health‐related work absences, and whether associations varied by employment status, income, and occupation.

Methods

This cross‐sectional study analyzed pooled data from the 2021 and 2023 National Health Interview Survey (NHIS), a nationally representative survey of US adults. The sample included 31,280 employed adults. Workers were classified into four workplace benefits groups: paid sick leave only, employer‐sponsored health insurance only, both benefits, and neither benefit. The primary outcome was health‐related work absence in the past 12 months. Interaction terms assessed differences in probability of absence by employment status (full‐time vs. part‐time), income (< 400% vs. ≥ 400% of the federal poverty level), and occupation type (Management, Professional, Service, Sales, and Production).

Results

Compared to those with neither benefit, the probability of work absence was 7.3 points higher with employer‐sponsored health insurance only (p < 0.001), 4.6 points higher with paid sick leave only (p = 0.002), and 12.0 points higher with both benefits (p < 0.001). The association between workplace benefits and health‐related work absence varied by employment status, income level, and occupation type (p < 0.001 for all interactions).

Conclusions

Access to paid sick leave and health insurance increased the likelihood of taking time off due to illness or injury, with differences by employment status, income, and occupation.

Keywords: absenteeism, employment status, health insurance, income, injury, occupations, sick leave, workplace

1. Introduction

Workplace benefits such as paid sick leave and employer‐sponsored health insurance play a crucial role in shaping workers' ability to take time off due to illness or injury [1, 2, 3, 4, 5]. Access to these benefits has been associated with improved health outcomes, reduced financial strain, and lower presenteeism (working while sick), which can negatively affect both individual and public health [6, 7, 8, 9, 10, 11, 12]. However, access to these workplace benefits is highly variable across different segments of the workforce, raising questions about how effectively they facilitate time off when needed [13, 14, 15].

Nationally, approximately 78% of civilian workers in the U.S. have access to employer‐sponsored health insurance, while only 77% have access to paid sick leave—and this coverage drops substantially for part‐time and low‐wage workers [2, 3]. Workers in part‐time roles are 43% less likely to receive paid sick leave compared to their full‐time counterparts, despite often working in high‐contact service occupations where illness transmission risks are elevated [5]. These coverage gaps raise important questions about who is both eligible for and able to make use of workplace benefits—questions that are central to informing more equitable employment and health policies.

The United States is the only wealthy nation with no federally mandated sick leave law, leaving this governance to the states [16, 17, 18]. Currently, less than half of the states have mandatory paid sick leave laws, resulting in heterogeneity in the provision of paid sick leave across the United States [19, 20]. While the Family and Medical Leave Act mandates companies with greater than 50 employees offer long‐term leave with job protection‐typically defined as up to 12 weeks‐, this leave is unpaid and does not provide short‐term leave for illness or injury [21, 22, 23, 24, 25].

Such gaps are concerning not only given the potential benefits of paid sick leave (e.g., greater likelihood of staying home when sick, thereby reducing the spread of infectious diseases and allowing for adequate recovery) [26, 27, 28]. The role of paid sick leave on time away from work among workers facing financial constraints—such as those without full‐time employment or those with lower incomes—is unclear [5, 7, 8, 29, 30, 31]. Use of sick leave may also vary based on type of occupation, as certain industries such as manufacturing, food service, and retail, or occupations such as production, service, and sales, may discourage or restrict leave‐taking despite formal policies, but there is a dearth of data on this issue [3].

In addition to structural access, benefit utilization is shaped by workplace culture. Research has documented that workers may avoid using sick leave or health‐related benefits due to fear of retaliation, stigma, or job insecurity, especially in precarious or hourly positions [23, 30]. For example, part‐time and low‐wage workers may perceive taking leave as risking reduced hours or job loss, even when formally entitled to time off [8, 10]. Despite legal protections, workplace norms and power dynamics can suppress benefit use and exacerbate disparities in leave‐taking behavior [31].

Beyond paid sick leave, employer‐sponsored health insurance can also influence work absences by facilitating access to medical care, including treatment for acute conditions and ongoing management of chronic diseases [32, 33]. Prior studies have shown that insured workers are more likely to seek preventive care and receive early treatment, potentially reducing the severity and duration of illness [34]. Additionally, workers with health insurance may be more likely to take leave following hospitalization or medical procedures, as they face lower financial barriers to seeking necessary care [35]. However, less is known on the complementary effects of paid sick leave and employer‐sponsored health insurance on health‐related work absences and how factors such as individuals' socioeconomic circumstances (e.g., employment status, income level) or occupation type influence leave after illness or injury.

This analysis sought to address these knowledge gaps about how socioeconomic and occupational factors affect the relationship between paid sick leave and employer‐sponsored health insurance as workplace benefits and the likelihood of taking leave following illness or injury. We hypothesized that the potentially complementary roles of paid sick leave and employer‐sponsored health insurance in facilitating leave for illness or injury, access to both types of workplace benefits would be associated with the highest likelihood of health‐related work absences. We further hypothesized that the association of workplace benefits would vary based on socioeconomic and occupational factors.

2. Methods

2.1. Study Design and Sample

This cross‐sectional study analyzed pooled data from the National Health Interview Survey (NHIS) for the years 2021 and 2023 [36]. The NHIS is an annual, nationally representative survey of the civilian, noninstitutionalized population of the United States. The NHIS data set enables population‐level analysis of workplace benefits, with robust survey weights applied to ensure national representativeness and address sampling variability among diverse employment groups.

We included adults aged 18 and older who reported being employed during the study period (N = 32,788). To ensure the study accurately captures the relationship between workplace benefits and health‐related work absences, we applied several exclusion criteria. We excluded 2020 because of mandated paid sick leave associated with the Federal Families First Coronavirus Response Act, which was in effect between April 1, 2020 and December 31, 2020. We also excluded unemployed individuals as workplace benefits such as paid sick leave and employer‐sponsored health insurance apply only to employed persons. To address potential biases from missing data, we applied listwise deletion and excluded 4% of the sample, yielding a final analytic sample of 31,280 employed adults. The major contributors to missing data were related to employment characteristics. This study was determined as nonhuman subjects by the University of Texas Southwestern Medical Center's institutional review board given its exclusive use of publicly available data.

2.2. Outcome

The study outcome was the number of workdays missed over the past 12 months due to illness or injury (defined as health‐related work absence). Reports of workdays missed excluded absences for maternity or paternity leave, focusing solely on days missed due to respondents’ own health. For the primary analysis, health‐related work absence was dichotomized into “None” (0 days) and “Any” (1 or more days) workdays missed to reflect whether the respondent took any health‐related time off in the past year. This threshold was selected because a majority of the sample (54%) reported no work absence, making it a meaningful distinction for population‐level comparison. As a sensitivity analysis, we also modeled the outcome as an ordinal variable with three levels: no absence, 1–5 days (1 week), and 6–366 days (more than a week). This allowed us to assess the robustness of our findings across gradations of absence severity. The weighted distribution (and unweighted n) of the outcome was: 54% (n = 16,848) had no absence, 30% (n = 9513) had 1–5 days of absence, and 16% (n = 4,919) had more than 5 days.

2.3. Exposure

The study exposure was workplace benefits, categorized into four mutually exclusive groups based on workers' access to paid sick leave and employer‐sponsored health insurance. Workers were classified as having both workplace benefits, paid sick leave only, employer‐sponsored health insurance only, or neither benefit (lacking both paid sick leave and employer‐sponsored health insurance).

2.4. Covariates

Demographic characteristics included age (categorized as 18–34, 35–49, 50–64, 65+ years), sex (female or male), metropolitan residence (metro vs. nonmetro), region of residence (Northeast, North Central/Midwest, South, and West), number of household adults (categorized as 1, 2, or 3+), number of household children (categorized as 0, 1, 2, 3+), marital status (married or cohabiting vs. not married), and race/ethnicity (Non‐Hispanic White, Non‐Hispanic Black, Latino, Non‐Hispanic Asian, and Other race or ethnicity).

Socioeconomic factors included educational attainment (categorized as less than high school, high school graduate, or more than high school), employment status (categorized as full‐time, defined as ≥ 35 h per week, vs. part‐time, defined as < 35 h per week), income level (categorized as lower‐income, defined as household income below 400% of the federal poverty level, vs. higher‐income, defined as household income 400% or above the federal poverty level. The 400% threshold aligns with the eligibility threshold for Affordable Care Act premium tax credits and accounts for household size through FPL standardization. Occupation type was categorized using standard industry classifications (Management, Professional, Service, Sales, and Production). Health insurance status was included as a binary indicator (insured vs. uninsured).

Health‐related covariates included general health status, categorized as Excellent/Very Good/Good versus Fair/Poor. Disability status, defined using the Washington Group Short Set Composite Disability Indicator, classified respondents as disabled if they reported “a lot of difficulty” or inability in at least one of six domains: vision, hearing, mobility, communication, self‐care, and cognition [37]. Use of medication for anxiety or depression was measured as a binary variable (yes/no) and used as a proxy indicator for mental health status.

2.5. Statistical Analysis

Sample characteristics were summarized using descriptive statistics (Table A1). We conducted bivariable analyses to examine the association between study exposure (workplace benefits) and outcome (health‐related work absence) and show row percentages. Pearson chi‐square tests were used to evaluate statistical significance in the bivariable analyses. Multivariable logistic regression models, adjusted for demographic, socioeconomic, and health‐related covariates and incorporating year fixed effects, were employed to assess the association between workplace benefits and health‐related work absence. Predicted probabilities (margins) were calculated to facilitate the interpretation of the effects of workplace benefits on the likelihood of health‐related work absence. Pairwise contrasts of these predictive margins were performed to test differences between specific groups, with statistical significance assessed using design‐based Wald tests. Separate regression models were used to test interactions between workplace benefits and employment (workplace*employment status), income level (workplace benefits*income level), and occupation type (workplace benefits*occupation type). Marginal probabilities were estimated for each interaction term.

We conducted several sensitivity analyses to assess the robustness of findings. First, analyses were repeated with the study outcome, health‐related work absence, recoded as an ordinal variable with three categories: none (0 days), short‐term (1–5 days), and extended (6–366 days). Ordered logistic regression models were used to capture the increasing levels of health‐related work absence. Second, the sample was restricted to adults aged 18–64 to focus on working‐age individuals who are more likely to rely on employer‐provided benefits, excluding those at or above the typical retirement age who may qualify for Medicare. Third, the sample was further restricted to insured individuals, either through their employer or a government program, to isolate the role of paid sick leave independently of insurance status. The results from sensitivity analyses are reported in the online appendix (Tables A2–A4) and demonstrate findings consistent with the primary analyses.

All analyses were conducted using Stata 19 MP/Parallel edition. Survey weights, primary sampling units, and strata provided by the NHIS were applied to account for the complex sampling design, adjust for unequal probabilities of selection, and ensure national representativeness. Statistical significance was set at a two‐tailed p‐value of < 0.05. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines to ensure transparent and rigorous reporting of observational data [38].

3. Results

Among 31,280 adult workers, access to workplace benefits differed significantly between those who reported any health‐related work absence and those who did not (Pearson Chi² p < 0.001) (Table 1). Among workers with no workplace benefits, 35% reported a health‐related work absence in the past 12 months. In contrast, 45% of those with employer‐sponsored health insurance only, 40% of those with paid sick leave only, and 51% of those with both benefits reported a work absence. The highest proportion of reported absences was among workers with access to both benefits, while the lowest was among those with no benefits.

Table 1.

Survey weighted bivariable association between health‐related work absence and workplace benefits: NHIS 2021 and 2023, N = 31,280.

Any work absence
No Yes
% N % N
Workplace benefits
No benefits 65 4405 35 2261
Health insurance only 55 1509 45 1192
Paid sick leave only 60 1189 40 827
Both benefits 49 9745 51 10152
Total 54 16848 46 14432
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Note: Row percentages shown. Pearson Chi2 p < 0.001

As shown in Table 2, workers with both health insurance and paid sick leave and employer‐sponsored health insurance had the highest probability of health‐related work absence (49.4%; 95% CI: 48.5%, 50.3%), followed by those with health insurance only (44.7%; 95% CI: 42.6%, 46.8%) and sick leave only (42.0%; 95% CI: 39.4%, 44.5%). Workers with no benefits had the lowest probability of health‐related work absence (37.4%; 95% CI: 35.9%, 38.9%). Compared to those with neither benefit, individuals with employer‐sponsored health insurance only were 7.3 percentage points more likely to report work absence (p < 0.001), while those with paid sick leave only were 4.6 percentage points more likely (p = 0.002). Workers with both benefits had the highest probability of work absence, with an increase of 12.0 percentage points relative to those with neither benefit (p < 0.001).

Table 2.

Multivariable adjusted marginal association of health‐related work absence by workplace benefits among employed adults 18 years of age and older: NHIS 2021 and 2023, N = 31,280.

Margin 95% CI Contrast p‐value
Workplace benefits
No benefits 37.4% 35.9, 38.9% Reference
Health insurance only 44.7% 42.6, 46.8% 7.3% < 0.001
Paid sick leave only 42.0% 39.4, 44.5% 4.6% 0.002
Both benefits 49.4% 48.5, 50.3% 12.0% < 0.001
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Note: Marginal effects were calculated from multivariable logistic regression adjusted for age, sex, metropolitan residence, region of residence, number of household adults, number of household children, marital status, race/ethnicity, education, household income, occupation category, general health, disability status, and medication use for anxiety or depression. p values were calculated based on a survey design adjusted Wald test.

The relationship between workplace benefits and health‐related work absence varied by individuals' employment status (p < 0.001) (Figure 1, Table A5). Among both full‐time and part‐time workers, the probability of work absence increased with greater access to workplace benefits. Full‐time workers had a significantly higher probability of work absence than part‐time workers when receiving either no benefits 39.9% [95% CI: 37.8%, 41.3%] versus 31.0% [95% CI: 29.1%, 32.9%], only one benefit 45.1% [95% CI: 43.1%, 47.0%] versus 37.5% [95% CI: 34.5%, 42.3%], and both benefits 50.6% [95% CI: 49.7%, 51.5%] versus 46.0% [95% CI: 43.0%, 49.1%].

Figure 1.

Figure 1

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Multivariable adjusted marginal effects (95% confidence intervals) of health‐related work absence by workplace benefits and employment status among employed adults 18 years of age and older: NHIS 2021 and 2023, N = 31,280. Note: Marginal effects and 95% confidence intervals were calculated from multivariable logistic regression adjusted for age, sex, metropolitan residence, region of residence, number of household adults and children, marital status, race/ethnicity, education, household income, occupation category, general health, medication use for anxiety or depression, and disability status. Benefits included employer‐sponsored health insurance and paid sick leave. Interaction terms were included for workplace benefits (none, one benefit, both benefits) and employment status (full‐time vs. part‐time). Wald test for interaction effect: p < 0.001.

Household income level affected the association between workplace benefits and health‐related work absence (p < 0.001) (Figure 2, Table A6). Among workers with neither benefit, lower‐income workers (< 400% FPL) had a significantly higher probability of health‐related work absence (39.8% [95% CI: 37.9%, 41.7%]) than higher‐income workers (≥ 400% FPL) (34.1% [95% CI: 31.7%, 36.5%]). However, the probability of health‐related work absence did not significantly differ between lower‐ and higher‐income groups among individuals with one or both workplace benefits.

Figure 2.

Figure 2

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Multivariable adjusted marginal effects (95% confidence intervals) of health‐related work absence by workplace benefits and household income among employed adults 18 years of age and older: NHIS 2021 and 2023, N = 31,280. Note: FPL = federal poverty level. Marginal effects and 95% confidence intervals were calculated from multivariable logistic regression adjusted for age, sex, metropolitan residence, region of residence, number of household adults and children, marital status, race/ethnicity, education, household income, occupation category, general health, medication use for anxiety or depression, and disability status. Benefits included employer‐sponsored health insurance and paid sick leave. Interaction terms were included for workplace benefits (none, one benefit, both benefits) and household income (< 400% FPL vs. 400% + FPL). Wald test for interaction effect: p < 0.001.

Finally, the interaction of workplace benefits and occupation type was statistically significant (p < 0.001) (Figure 3, Table A7). Across all occupation type groups, the probability of work absence was highest for those with both benefits, though the magnitude of this association varied by occupation. In management and professional occupations, those with both benefits had a significantly higher probability of work absence (47.4% [95% CI: 45.3%, 49.5%] and 51.1% [95% CI: 49.7%, 52.5%]) than those with no benefits (35.0% [95% CI: 30.8%, 39.3%] and 36.8% [95% CI: 33.8%, 39.7%]) or one benefit (35.4% [95% CI: 30.0%, 40.7%] and 42.0% [95% CI: 38.7%, 45.4%]). Similarily, in service and sales occupations, those with both benefits had a significantly higher probability of health‐related work absence (46.9% [95% CI: 44.2%, 49.6%] and 47.1% [95% CI: 43.9%, 50.3%]) compared to those with no benefits (39.2% [95% CI: 36.4%, 42.0%] and 38.1% [95% CI: 33.8%, 42.5%]). Among production workers, those with neither benefit had a significantly lower probability of work absence (36.4% [95% CI: 33.9%, 39.0%]) compared to those with at least one benefit, but the difference between one benefit (45.8% [95% CI: 43.2%, 48.4%]) and both benefits (49.5% [95% CI: 47.9%, 51.1%]) was not statistically significant.

Figure 3.

Figure 3

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Faceted line plot of multivariable adjusted marginal effects (95% confidence intervals) of health‐related work absence by workplace benefits and occupational category among employed adults 18 years of age and older: NHIS 2021 and 2023, N = 31,280. Note: Marginal effects and 95% confidence intervals were calculated from multivariable logistic regression adjusted for age, sex, metropolitan residence, region of residence, number of household adults and children, marital status, race/ethnicity, education, household income, occupation category, general health, medication use for anxiety or depression, and disability status. Benefits included employer‐sponsored health insurance and paid sick leave. Interaction terms were included for workplace benefits (none, one benefit, both benefits) and occupational category (management, professional, service, sales, production). Wald test for interaction effect: p < 0.001.

4. Discussion

This study demonstrated associations between workplace benefits—paid sick leave and employer‐sponsored health insurance—and health‐related work absence, as well as the impact of employment status, income level, and occupation type on those associations. Together, these findings contribute new evidence to a growing body of work and suggest that policies must consider broader employment factors in order for individuals to accrue benefits from workplace benefits such as paid sick leave and employer‐sponsored health insurance coverage [14, 25, 29, 39].

We found that workers with both paid sick leave and employer‐sponsored health insurance were the most likely to take time off due to illness or injury, followed by those with only health insurance or sick leave alone. On one level, this finding aligns with prior evidence suggesting that access to workplace benefits reduces financial and job‐related barriers to taking time off when ill [23, 40, 41, 42, 43]. On another level, these results yield new insight by demonstrating that paid sick leave and employer‐sponsored health insurance can complement each other—for instance, because paid sick leave provides job protection and wage replacement, while health insurance facilitates access to medical care and greater recognition of the need for recovery time.

We found that the association of workplace benefits and work absence varied by employment status. Full‐time workers were significantly more likely to take time off than part‐time workers across all levels of benefit access [5, 7, 31]. This finding suggests that part‐time employment may introduce structural barriers that limit the practical use of sick leave and health insurance, such as reduced work‐hour flexibility, fear of job loss, or employer expectations to continue working while sick [13, 14, 44]. While many state and local policies extend sick leave mandates to part‐time workers, the ability to use these benefits may be constrained by workplace norms and economic insecurity [20, 22].

The association between workplace benefits and work absences differed by income level. Our results indicated that lower‐income workers with no benefits were more likely to take time off compared to their higher‐income counterparts, yet there was not a difference by income level for workers with at least one benefit, suggesting that access to benefits—not just economic security—affects leave‐taking decisions. These findings underscore that expanding both paid sick leave and health insurance may support lower‐income workers in taking needed time off, thereby reducing economic disparities in leave‐taking [45].

Our analysis revealed that while workers in professional and management occupations were more likely to report health‐related work absence when benefits were available, those in production and service roles—despite greater physical demands—had lower probabilities of absence when fewer or no benefits were available. These patterns suggest that the availability of benefits alone may be insufficient to enable leave‐taking in lower‐wage or part‐time positions. Structural and cultural factors, such as job insecurity, inflexible scheduling, perceived or actual employer retaliation, and workplace norms that discourage absence, may create significant barriers to benefit utilization. These dynamics are particularly salient for part‐time workers and those in production occupations, who may be most vulnerable to adverse consequences from taking time off. Our findings add to a growing body of research highlighting how occupational context and employment conditions shape not only access to benefits but also workers' ability to use them [23, 29, 30, 41, 46].

Together, our findings underscore the importance of addressing both access to workplace benefits as well as structural factors that determine whether workers can use those benefits effectively. While expanding paid sick leave and employer‐sponsored health insurance remain important policy goals, simply offering these benefits does not ensure their utilization. Policymakers could strengthen protections for part‐time employees by not only expanding eligibility for paid sick leave but also addressing workplace barriers that prevent employees from using their benefits, such as employer policies and workplace cultures that discourage work absence [8, 10, 11]. Because financial constraints may limit workers' ability to take time off when sick [15, 47], policies that enhance wage replacement for sick leave could help mitigate presenteeism and improve benefit utilization. Differences by occupation type suggest that industry‐specific policies may be necessary to ensure equitable access across job sectors. In production industries, where workplace norms may discourage absenteeism despite legal protections, stronger enforcement mechanisms and employer accountability measures could help ensure that workers can take time off without fear of retaliation [44, 45]. Education and awareness campaigns targeted at both employers and employees may be necessary to shift workplace cultures and normalize the use of paid sick leave.

This study had limitations. First, the cross‐sectional design limits causal inferences that might be drawn between workplace benefits and work absence. Second, self‐reported measures of workplace benefit access may be subject to reporting bias. Third, this study does not account for the potential influence of spousal work benefits on an individual's ability to be absent from work. Workers whose spouses have access to paid sick leave or employer‐sponsored health insurance may experience different constraints and opportunities, shaping their leave‐taking behavior within the broader economic structure of the household. Fourth, while this study accounts for multiple employment‐related interactions, additional workplace‐level factors such as employer enforcement of policies, job tenure, and unionization could further shape how workers utilize workplace benefits.

In this study, access to both paid sick leave and employer‐sponsored health insurance were associated with a greater likelihood of health‐related work absence, reinforcing the complementary role of these workplace benefits. However, the ability to utilize these benefits was not uniform across workers; instead, there was substantial heterogeneity in health‐related work absence based on employment, income, and occupational factors. Expanding paid sick leave and employer‐sponsored health insurance may be particularly effective for part‐time and lower‐income workers, as well as those in certain occupations.

Author Contributions

Jim P. Stimpson: conceptualization, funding acquisition, formal analysis, investigation, methodology, writing – original draft, writing – review and editing. Jessica Billig: conceptualization, writing – original draft, writing – review and editing. Tami Gurley: writing – review and editing. Joshua M. Liao: conceptualization, writing – review and editing.

Ethics Statement

This is an observational study that used publicly available data. The university institutional review board has confirmed that no ethical approval is required.

Consent

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Disclosure by AJIM Editor of Record

John Meyer declares that he has no conflict of interest in the review and publication decision regarding this article.

Supporting information

Online Appendix.

AJIM-68-598-s001.docx (35.6KB, docx)

Acknowledgments

For this study, JPS was supported by the American Cancer Society (DBG‐23‐1155771‐01‐HOPS). The content is solely the responsibility of the authors and does not necessarily represent the official views of the ACS. The funders had no role in study design, data analysis, decision to publish, or preparation of the manuscript.

Data Availability Statement

The data that support the findings of this study are openly available in IPUMS at https://nhis.ipums.org/nhis/, reference number 10.18128/D070.V7.4. The NHIS data are publicly available from the National Center for Health Statistics at https://www.cdc.gov/nchs/nhis/, which includes detailed information about the survey. We downloaded a publicly available version of the NHIS from IPUMS at https://nhis.ipums.org/nhis/.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Online Appendix.

AJIM-68-598-s001.docx (35.6KB, docx)

Data Availability Statement

The data that support the findings of this study are openly available in IPUMS at https://nhis.ipums.org/nhis/, reference number 10.18128/D070.V7.4. The NHIS data are publicly available from the National Center for Health Statistics at https://www.cdc.gov/nchs/nhis/, which includes detailed information about the survey. We downloaded a publicly available version of the NHIS from IPUMS at https://nhis.ipums.org/nhis/.

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