Abstract
Background:
This study examined perinatal experiences of pandemic-related hardships and disparities by race/ethnicity, income, insurance type at childbirth, and urban/rural residency.
Materials and Methods:
We used cross-sectional survey data from the 2020 Pregnancy Risk Assessment Monitoring System COVID-19 supplement in 26 states, the District of Columbia, and New York City to explore: (1) job loss or cut work hours/pay, (2) having to move/relocate or becoming homeless, (3) problems paying the rent, mortgage, or bills, or (4) worries that food would run out. We estimated the prevalence of outcomes overall and by race/ethnicity, income, insurance, and urban/rural residency. We used weighted multivariable logistic regression models to calculate adjusted predicted probabilities.
Results:
Due to the COVID-19 pandemic, 31.9% of respondents reported losing their job or having a cut in work hours or pay, 11.2% of respondents had to move/relocate or became homeless, 21.8% had problems paying the rent, mortgage, or bills, and 16.86% reported worries that food would run out. Compared to overall, rates of all hardships were higher among respondents who were non-Hispanic Black, Hispanic, uninsured, or Medicaid insured. The adjusted predicted probability of employment instability, financial hardships, and food insecurity was significantly higher among non-Hispanic Black respondents and respondents who were uninsured. The adjusted predicted probability of all hardships was significantly higher among respondents with Medicaid.
Conclusions:
Black, Medicaid-insured, and uninsured respondents were particularly vulnerable to perinatal hardships during COVID-19. Our results suggest a need to alleviate the overall and disparate consequences of hardships for individuals who gave birth during the COVID-19 pandemic.
Keywords: perinatal period, financial stress, social determinants of health, COVID-19 pandemic, health equity
Introduction
Hardship experiences such as unemployment and housing instability are important social determinants of health and well-being, including in the perinatal period, but these occurrences are not evenly distributed across demographic groups.1,2 Before the COVID-19 pandemic, significant inequities existed in employment, housing, food, and financial hardships based on factors such as race/ethnicity, rurality, and socioeconomic status.3–5 Previous studies have documented that the COVID-19 pandemic worsened several stressors that impact health outcomes, including increased economic instability and food insecurity, particularly among disadvantaged communities.6,7
Effects of the COVID-19 pandemic on maternal stress and poor maternal mental health have been well-documented, with pregnant people identified as a key group requiring increased attention during the COVID-19 context.8–10 Research has found that pregnant people, especially pregnant people with multiple disadvantaged identities, are especially vulnerable to experiencing elevated stress during a state of emergency or natural disaster.8,11 As a result, it is particularly important to identify disparate consequences of the COVID-19 pandemic on these hardship stressors in the perinatal period.
Differential effects of the COVID-19 pandemic on employment, housing, and financial hardships could potentially widen inequities in the social and structural forces affecting maternal health outcomes, particularly for Black and low-income pregnant people.12–14 Employment changes from the COVID-19 pandemic in the perinatal period could have additional effects on insurance stability,15 which is particularly important during and after pregnancy to ensure access to prenatal and postpartum care.16,17 Thus, the objective of this study was to examine the prevalence of hardship experiences in the perinatal period due to the COVID-19 pandemic and disparities by race/ethnicity, income, insurance, and urban/rural residency.
Materials and Methods
Data and sample
This cross-sectional study used the 2020 Pregnancy Risk Assessment Monitoring System (PRAMS) survey, which included a questionnaire supplement focusing on COVID-19 pandemic experiences.18 PRAMS has been conducted since 1987 and is processed in monthly batches from birth certificate files in participating states.19 Respondents are routinely sampled 2–6 months after childbirth about their experiences before, during, and after pregnancy.19 Questions about perinatal experiences during the COVID-19 pandemic were asked of PRAMS respondents as a one-time 2020 supplement to the PRAMS survey.
We limited the sample to the 26 states, the District of Columbia, and New York City that had available COVID-19 supplement data, excluding Puerto Rico, as it did not include questions on variables of interest for this analysis. Data are available from participating PRAMS states only if that state meets the minimum survey response rate thresholds for data release (50% in 2020). The list of states included in the analysis along with their response rates is listed in Supplementary Table S1, which had a median unweighted response rate of 55.6% and a median weighted response rate of 58.4%.
After all exclusions, our final study sample consisted of 11,945 respondents, representing a weighted total of 637,790 individuals with a live birth during June–December 2020. This June–December 2020 period reflects the experiences of individuals with births in the first calendar year of the COVID-19 pandemic, which was characterized by high rates of COVID-19 prevalence, strain on the health care system, and widespread lockdowns of varying levels.20 This study was considered to be not human subjects research by the Brown University Institutional Review Board and was conducted from December 2022 to September 2023.
Variables
Outcomes of interest for this study included: (1) job loss or having pay or work hours cut, (2) having to move or relocate or becoming homeless, (3) having problems paying the rent, mortgage, or other bills, or (4) worries whether food would run out before receiving money to buy more. These incidents were specifically measured as pandemic-related experiences through the survey question “Did any of the following things happen to you due to the COVID-19 pandemic?” Respondents could answer yes to more than one response option. These hardship outcomes capture all responses that signal indicators of hardships directly affecting the birthing parent respondent. Although outcomes were asked of respondents in the 2–6 month postpartum period, the timeframe for the experiences was not specified and events could have therefore also occurred during pregnancy or preconception.
Key demographic variables of interest included race/ethnicity (non-Hispanic Asian or Pacific Islander, non-Hispanic Black, Hispanic, non-Hispanic White, non-Hispanic Other), urban/rural geography (based on the National Center for Health Statistics urban–rural classification scheme), household income as a percent of the federal poverty level (FPL; 100% or less, 101%–200%, 201% or more), and insurance type at childbirth (private or military coverage, Medicaid, uninsured, other). FPL was calculated using household size and the mid-point of the PRAMS income category. Additional sociodemographic variables included age (<17–24, 25–29, 30–34, 35–39, 40+), marital status (married, unmarried), educational attainment (high school or less, more than high school), month of delivery, and state of residence. Sociodemographic variables were selected based on previous research indicating an association between these characteristics and perinatal outcomes.12,13,21 Indicator variables were created to capture missingness among any covariates.
Statistical analysis
We calculated the survey-weighted demographic characteristics of the respondent sample, including age, marital status, education, race/ethnicity, urban/rural residency, income, and insurance type at childbirth.
We estimated the unadjusted weighted prevalence of outcomes overall and by key demographic characteristics: race/ethnicity, urban/rural residency, income, and insurance type at childbirth. Chi-squared tests were used to test for differences in the proportions across these demographic characteristics.
We used weighted multivariable logistic regression models adjusted for age, marital status, education, delivery month, and state to calculate the adjusted average predicted probabilities and marginal differences in predicted probabilities by race/ethnicity, insurance type at childbirth, income, and urban/rural residency, holding covariates at observed values. The adjusted odds ratios from the multivariable logistic regression models are presented in Supplementary Table S2. All analyses used PRAMS survey weights calculated by the Centers for Disease Control and Prevention to account for the complex survey design, including differential sampling, nonresponse, and noncoverage in the survey.19
Additional Analysis
As the sample included individuals with births during June–December 2020, there is variation in pandemic timing during the perinatal period. For respondents who gave birth in June–November, the March 2020 beginning of the COVID-19 public health emergency would have occurred during their pregnancies, so hardship experiences resulting from COVID-19 would have to have occurred during pregnancy or by the 2–6 month postpartum survey period. For respondents who gave birth in December, it is possible that hardship experiences resulting from COVID-19 could have also occurred preconception. As a result, we conducted a sensitivity analysis presented in Supplementary Figure S1 excluding December 2020 births to restrict the sample to pregnancies that began before the beginning of the pandemic.
Results
The demographic characteristics of the study sample are described in Table 1. Respondents were primarily age 25–29 (27.64%, 95% confidence interval [CI]: 26.41%–28.91%) or 30–34 years old (30.54%, 95% CI: 29.30%–31.81%) and married (61.18%, 95% CI: 59.82%–62.51%) at delivery. The majority of respondents, 62.93% (95% CI: 61.57–64.26), had educational attainment of more than high school and lived in urban (88.09%, 95% CI: 87.21–88.93) rather than rural areas. The highest share of respondents were non-Hispanic White at 55.36% (95% CI: 54.10–56.61), with 19.93% (95% CI: 18.88–21.02) reporting a Hispanic ethnicity and 14.79% (95% CI: 13.97–15.65) identifying as non-Hispanic Black. Respondents primarily had incomes at 200% or more of the FPL (22.41, 95% CI: 21.29–23.56) and had private or military coverage at delivery (53.49, 95% CI: 52.16–54.82), with 40.81% (95% CI: 39.51–42.13) covered through Medicaid and 3.44% (95% CI: 2.96–3.99) uninsured at delivery.
Table 1.
Demographic Characteristics of the Study Sample
| Variables | % | (95% CI) |
|---|---|---|
| Age | ||
| <17–24 years old | 21.17 | (20.02–22.37) |
| 25–29 years old | 27.64 | (26.41–28.91) |
| 30–34 years old | 30.54 | (29.30–31.81) |
| 35–39 years old | 16.79 | (15.82–17.81) |
| 40+ years old | 3.86 | (3.37–4.41) |
| Marital status | ||
| Unmarried | 38.77 | (37.43–40.12) |
| Married | 61.18 | (59.82–62.51) |
| Educational attainment | ||
| High school or less | 36.33 | (35.00–37.67) |
| More than high school | 62.93 | (61.57–64.26) |
| Race/ethnicity | ||
| Asian or Pacific Islander, NH | 5.66 | (5.16–6.21) |
| Black, NH | 14.79 | (13.97–15.65) |
| Hispanic | 19.93 | (18.88–21.02) |
| White, NH | 55.36 | (54.10–56.61) |
| Other, NH | 3.62 | (3.17–4.14) |
| Geography | ||
| Urban | 88.09 | (87.21–88.93) |
| Rural | 11.90 | (11.07–12.79) |
| Income (% of the FPL) | ||
| 100% or less | 20.35 | (19.24–21.49) |
| 101%–199% | 17.97 | (16.90–19.10) |
| 200% or more | 22.41 | (21.29–23.56) |
| Insurance at delivery | ||
| Uninsured | 3.44 | (2.96–3.99) |
| Medicaid | 40.81 | (39.51–42.13) |
| Private or military | 53.49 | (52.16–54.82) |
| Other | 1.56 | (1.25–1.94) |
N = 11,945. Weighted proportions are presented.
CI, confidence interval; FPL, federal poverty level; NH, non-Hispanic.
Table 2 shows the proportion of respondents who reported pandemic-related hardships in this sample of individuals with a birth during the pandemic in the 26 participating states, District of Columbia, and New York City. Due to the COVID-19 pandemic, 31.94% (95% CI: 30.64%–33.27%) of respondents reported losing their job or having a cut in work hours or pay overall, 11.63% (95% CI: 10.76%–12.56%) of respondents had to move/relocate or became homeless, 21.77% (95% CI: 20.64%–22.95%) had problems paying the rent, mortgage, or bills, and 16.86% (95% CI: 15.83%–17.93%) reported worries that food would run out.
Table 2.
COVID-19 Pandemic-Induced Hardships in the Perinatal Period by Demographic Characteristics
| Variables | Lost job, work hours, or pay |
Had to move/relocate or became homeless |
Problems with rent, mortgage, or bills |
Worries that food would run out |
||||
|---|---|---|---|---|---|---|---|---|
| % | (95% CI) | % | (95% CI) | % | (95% CI) | % | (95% CI) | |
| Overall | 31.94 | (30.64–33.27) | 11.63 | (10.76–12.56) | 21.77 | (20.64–22.95) | 16.86 | (15.83–17.93) |
| Race/ethnicitya | ||||||||
| Asian or Pacific Islander, NH | 25.60 | (21.48–30.21) | 9.38 | (6.74–12.91) | 16.82 | (13.31–21.03) | 10.81 | (7.91–14.61) |
| Black, NH | 42.36 | (39.02–45.78) | 16.52 | (14.16–19.18) | 33.20 | (30.12–36.44) | 23.36 | (20.57–26.39) |
| Hispanic | 38.99 | (35.81–42.26) | 15.08 | (12.86–17.61) | 28.19 | (25.38–31.18) | 32.76 | (29.76–35.9) |
| White, NH | 27.44 | (25.74–29.2) | 8.99 | (7.94–10.18) | 16.77 | (15.33–18.32) | 9.99 | (8.88–11.23) |
| Other, NH | 30.19 | (24.58–36.46) | 16.77 | (12.62–21.94) | 23.46 | (18.37–29.44) | 17.72 | (13.32–23.18) |
| Geography | ||||||||
| Urban | 32.28 | (30.89–33.69) | 11.84 | (10.90–12.84) | 21.51 | (20.31–22.76) | 16.80 | (15.72–17.95) |
| Rural | 29.46 | (25.86–33.34) | 10.11 | (8.00–12.70) | 23.73 | (20.42–27.38) | 17.23 | (14.33–20.57) |
| Income (% of the FPL)a | ||||||||
| 100% or less | 41.07 | (37.98–44.22) | 16.67 | (14.49–19.12) | 39.85 | (36.77–43.02) | 35.22 | (32.23–38.33) |
| 101%–199% | 45.55 | (42.14–49.01) | 15.48 | (13.07–18.24) | 34.35 | (31.13–37.72) | 25.58 | (22.70–28.68) |
| 200% or more | 30.88 | (28.28–33.61) | 11.15 | (9.44–13.12) | 16.53 | (14.55–18.73) | 10.04 | (8.44–11.90) |
| Insurance at deliverya | ||||||||
| Uninsured | 36.67 | (29.3–44.72) | 12.36 | (8.04–18.54) | 25.27 | (19.14–32.57) | 29.03 | (22.53–36.51) |
| Medicaid | 42.49 | (40.28–44.74) | 17.01 | (15.39–18.76) | 35.18 | (33.05–37.36) | 29.20 | (27.18–31.3) |
| Private or military | 23.37 | (21.81–25.00) | 7.33 | (6.43–8.34) | 11.09 | (9.98–12.30) | 6.65 | (5.81–7.60) |
| Other | 33.87 | (24.55–44.63) | 17.64 | (9.56–30.26) | 26.26 | (17.46–37.50) | 15.49 | (9.44–24.38) |
N = 11,945. Weighted proportions are presented. Chi-square tests were used to test for differences in proportions by demographic category. ap < 0.001.
Compared to overall prevalence, unadjusted rates of all perinatal hardships were higher among non-Hispanic Black respondents, Hispanic respondents, respondents in the lower income categories, and respondents who were uninsured or had Medicaid at delivery. The lowest rates of all perinatal hardships were reported among non-Hispanic White respondents, non-Hispanic Asian or Pacific Islander respondents, respondents with incomes at 200% of the FPL or more, and respondents with private or military coverage at childbirth. Job loss or cuts in work hours or pay was the most highly reported outcome for all groups, while housing instability was the least reported for all groups. There were significant differences in the prevalence of all hardship outcomes by race/ethnicity, income, and coverage at delivery, with no significant differences by urban/rural residence.
In adjusted analyses, the predicted probability of job loss or a cut in work hours or pay was 35.20% (95% CI: 32.02%–38.38%) for non-Hispanic Black respondents, which was statistically significantly higher by 4.41% (95% CI: 0.48%–8.34%) compared to non-Hispanic White respondents (Fig. 1). The adjusted predicted probability of job loss or a cut in work hours or pay among respondents who had Medicaid was 36.76% (95% CI: 34.33%–39.20%) and 38.15% (95% CI: 30.50%–45.80%) among respondents uninsured at delivery, which was statistically significantly higher compared to respondents with private coverage. Respondents with incomes 101%–199% of the FPL saw the highest adjusted predicted probabilities of job loss or a cut in work hours or pay at 41.38% (95% CI: 38.04%–44.72%), which was statistically significantly higher by 8.06% (95% CI: 3.61%–12.50%) compared to higher income respondents. The probability of job loss or a cut in work hours or pay did not statistically significantly differ by urban/rural residence.
FIG. 1.
Adjusted predicted probabilities of COVID-19 pandemic-induced hardships in the perinatal period by demographic characteristics. N = 11,945. Predicted probabilities are presented, based on weighted multivariable logistic regression models adjusted for race/ethnicity, urban/rural geography, income, insurance at delivery, age, marital status, educational attainment, month of delivery, and state of residence. Adjusted average marginal differences in predicted probabilities were calculated for each demographic category relative to the reference category. Error bars represent 95% CIs. *p < 0.05, **p < 0.01, ***p < 0.001. CI, confidence interval; FPL, federal poverty level; NH, non-Hispanic.
The adjusted predicted probability of having to move, relocate, or becoming homeless statistically significantly differed by insurance type at childbirth, with the highest predicted probability of 14.05% (95% CI: 12.30%–15.79%) among respondents with Medicaid-paid deliveries, which was statistically significantly higher by 5.23% (95% CI: 2.71%–7.76%) compared to respondents with private coverage. There were no significant differences in the adjusted predicted probability of housing instability by race/ethnicity, urban/rural geography, or income.
The adjusted predicted probability of problems paying the rent, mortgage, or bills statistically significantly varied by race/ethnicity, insurance coverage, and income. For non-Hispanic Black respondents, the predicted probability of problems paying the rent, mortgage, or bills was 24.49% (95% CI: 21.82%–27.16%), which was statistically significantly higher by 3.76% (95% CI: 0.35%–7.16%) compared to non-Hispanic White respondents.
The predicted probability of problems paying the rent, mortgage, or bills was the highest among respondents with incomes at 100% or less of the FPL at 29.81% (95% CI: 26.80%–32.82%) and 29.22% (95% CI: 26.19%–32.25%) among respondents with incomes 101%–199% of the FPL, which were both statistically significantly higher compared to the highest income respondents by 10.26% (95% CI: 6.17%–14.35%) and 9.68% (95% CI: 5.68%–13.67%), respectively. The adjusted predicted probability of problems paying the rent, mortgage, or bills was also statistically significantly higher among respondents who had Medicaid (26.86%, 95% CI: 24.77%–28.94%) by 11.43% (95% CI: 8.30%–14.57%) or were uninsured at delivery (24.45%, 95% CI: 17.89%–31.01%) by 9.03% (95% CI: 2.19%–15.87%) compared to respondents with private or military coverage. There were no significant differences in the predicted probability of problems paying the rent, mortgage, or bills by urban/rural residence.
The adjusted predicted probability of worries that food would run out significantly differed by race/ethnicity, income, and insurance type at delivery. Among non-Hispanic Black respondents, the predicted probability of food insecurity was 17.46% (95% CI: 15.19%–19.73%), which was statistically significantly higher by 4.65 (95% CI: 1.76%–7.55%) compared to non-Hispanic White respondents. The predicted probability of food insecurity was 24.35% (95% CI: 21.77%–26.94%) among Hispanic respondents, which was statistically significantly higher than non-Hispanic White respondents by 11.55% (95% CI: 8.40%–14.70%).
The predicted probability of food insecurity was 23.40 (95% CI: 20.84%–25.96%) among respondents with incomes 100% or less of the FPL and 21.22% (95% CI: 18.71%–23.72%) among respondents with incomes 100%–199% of the FPL. Respondents who were uninsured or Medicaid-insured had significantly higher adjusted predicted probabilities of food insecurity compared to respondents with private coverage. Respondents who were uninsured at delivery had the highest adjusted predicted probabilities of food insecurity by insurance type at 23.35% (95% CI: 17.39%–29.31%), which was statistically significantly higher by 12.64% (95% CI: 6.48%–18.80%) compared to respondents with private coverage at delivery. There were no significant differences by urban/rural geography in the adjusted predicted probability of worries that food would run out.
In supplementary analyses excluding December 2020 births, we find adjusted predicted probabilities that are largely consistent with main models in regards to effect size and statistical significance (Supplementary Fig. S1). These supplemental analyses suggest that the experiences of pandemic-related hardships that we are capturing are not sensitive to including hardship events that may have occurred in the preconception period.
Discussion
In this cross-sectional analysis of multistate survey data during the COVID-19 pandemic, we found that nearly one-third of individuals with a recent birth experienced a change in their employment, work hours, or pay in the perinatal period due to the pandemic, which was the most highly reported hardship outcome. In addition, about 1 in 5 respondents reported problems with rent or bills or worries that food would run out, and about 1 in 10 had to move, relocate, or became homeless in the perinatal period as a result of the COVID-19 pandemic.
Non-Hispanic Black respondents reported a higher prevalence of all perinatal hardships compared to non-Hispanic White respondents by ∼5%–10% points. Similarly, the probability of all perinatal hardships was significantly higher among respondents who had Medicaid at delivery by ∼2%–5% relative to respondents with private insurance. These results suggest that marginalized and minoritized communities were subject to greater perinatal financial, housing, and food hardships to varying degrees as a consequence of the COVID-19 pandemic. The COVID-19 pandemic may have exacerbated inequities in health and economic well-being, particularly for low-income individuals and people of color, as systemic racism and structural factors have resulted in inequitable health care access and inequitable employment conditions and opportunities.22,23
Several previous studies have documented increased disparities in hardships among the overall population during the COVID-19 pandemic, including pandemic-related work and financial stressors, difficulties paying bills, rent, or the mortgage, and receiving assistance for food.24,25 As key social determinants of health, these hardships are particularly important to consider in the perinatal period and are associated with a higher risk of adverse maternal and infant health outcomes.1,21 Our study is consistent with previous research that found disparities in material hardships by income level among pregnant people during COVID-19.26
Previous studies have shown a strong relationship between the hardships described in this article, including financial stress,27 housing instability,28 food insecurity,29 and job loss,30 and poor maternal mental health. As a result, the perinatal hardships documented in this study could be one mechanism contributing to the pandemic-related disparities in maternal stress and poor maternal mental health outcomes previously established in the literature.9,14,26,31 This study builds on the previous literature using a large, population-representative dataset of individuals who gave birth during the first calendar year of the pandemic to examine several types of perinatal hardships and disparities among sociodemographic groups.
In our study, nearly half of Black, low-income, and publicly-insured respondents reported pandemic-related employment changes, around 10% points higher than the perinatal population overall. Changes in perinatal employment and pay could increase birthing parents' vulnerability to financial difficulties stemming from high health care costs associated with pregnancy, childbirth, and postpartum care.32 The costs of perinatal health care can be unaffordable and leave families at risk of incurring medical debt, especially among Black and lower income individuals.3,33
Pandemic-related employment changes in the perinatal period could additionally have direct consequences for access to employer-sponsored health insurance, which could leave some individuals uninsured during a period of high health care need.34 Research has found reductions in postpartum uninsurance during COVID-19, likely indicating that health policy changes during the pandemic such as increases in subsidies for Marketplace coverage and a freeze in Medicaid redeterminations may have provided some insurance pathways to alleviate potential uninsurance resulting from pandemic-related job loss in the perinatal period; however, that research did not investigate differences by demographics.35
Although a less reported perinatal hardship, our study also finds notable disparities in pandemic-related hardships for housing and food insecurity, particularly for Medicaid enrollees. Housing is an important social determinant of health that can have consequences for health and well-being through changes in housing stability, affordability, safety, and neighborhood factors, including the built environment and support in the community.36 In particular, homelessness during pregnancy is associated with increased risk of adverse perinatal outcomes, as well as pregnancy complications.37,38 In addition, food insecurity is strongly associated with increased risk of chronic diseases, including obesity, hypertension, and diabetes, and worse maternal mental health and pregnancy outcomes.39
Our findings suggest several opportunities to address perinatal hardships and ensure that these social determinants that negatively impact health do not persist beyond the early pandemic period reflected in this study. The increased probability of all hardships among individuals with Medicaid specifically suggests support for Medicaid initiatives to consider the health-related social needs of enrollees to improve health outcomes.40
Identifying the experiences of hardships in the perinatal period is essential for developing policies to address inequities worsened by the COVID-19 pandemic, especially for Black, Medicaid-insured, and low-income birthing parents.41 Our results suggest a need for policies and programs aimed at alleviating the overall and disparate consequences of pandemic-related hardships for individuals who gave birth during COVID-19. As the COVID-19 stimulus checks were issued in April 2020 and December 2020, these payments may have reduced some of the effects of job loss on financial insecurity during this period.42 Research has found that the primary use of COVID-19 stimulus check payments among parents in the United States was to pay rent or other bills,43 which could have offset some of the problems with rent, the mortgage, or bills reported among one in five respondents in this study.
Our findings may also indicate a need for screening for the social determinants of health in clinical settings or implementing other interventions aimed at addressing basic resource needs to address inequities during the perinatal period, which is recommended by professional organizations such as the American Academy of Pediatrics, American Academy of Family Physicians, and American College of Obstetricians and Gynecologists.44,45 Access to resources such as financial assistance, insurance navigation, and stable housing is essential for providing necessary support to perinatal patients experiencing financial hardship during COVID-19.31
Limitations
This study has several limitations. First, these estimates are based on self-report in the PRAMS survey, which can result in measurement error. Second, our study included respondents in 26 states, the District of Columbia, and New York City. Hardship experiences may have differed in states not included in this survey, as state policies relating to benefits, housing, or health care could have mitigated pandemic hardships in varying ways. Third, this study relied on cross-sectional data from a PRAMS survey supplement that was only conducted in 2020. As a result, we could not assess changes in outcomes before and during the pandemic. Instead, outcomes are attributable to the COVID-19 pandemic due to the survey question wording.
Fourth, this study includes individuals with a live birth during June–December 2020, who were primarily surveyed 2–6 months after childbirth. As a result, this survey encapsulates experiences occurring in the early pandemic period in 2020 and 2021. Effects of the pandemic on hardships likely changed later in the pandemic period, especially as employment statistics report that the largest job losses occurred in the early months of the pandemic.46 Finally, the timing of when the hardship outcomes occurred in the perinatal period was not ascertained in the PRAMS survey question. When excluding December 2020 births to isolate hardship experiences occurring during or after pregnancy, we find results that are similar to main models with regards to effect size and statistical significance. These supplemental analyses suggest that the experiences of pandemic-related hardships that we are capturing are not sensitive to including hardship events that may have occurred in the preconception period.
Conclusions
This cross-sectional survey study of individuals with a recent birth during the COVID-19 pandemic found that hardships were experienced among up to one in three individuals. Black respondents were particularly vulnerable to hardships in the perinatal period due to the COVID-19 pandemic relating to employment and financial difficulties. Respondents with Medicaid-paid deliveries were more likely to experience all hardships, including having to move/relocate or becoming homeless. These hardship experiences could have important implications for maternal mental and physical health, financial security, and economic well-being. These findings indicate disparities in perinatal pandemic-related stressors and suggest a need for resources to support parents who gave birth during the COVID-19 pandemic.
Supplementary Material
Authors' Contributions
All authors meet the requirements of authorship, including substantial contributions to the conception and design of the analysis, drafting and revising the article, and final approval of the article.
Author Disclosure Statement
No competing financial interests exist.
Funding Information
E.L.E. reports research support from the Agency for Healthcare Research and Quality under grant award T32 HS000011.
Supplementary Material
References
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