Social Impacts of the COVID-19 Pandemic on Women’s Health in the Greater Los Angeles Area

Abstract

Background:

Since the COVID-19 pandemic started, women have experienced more job loss owing to an increase in household and caregiving responsibilities. Gender inequities coupled with pandemic-related stressors have resulted in poor health outcomes among women. Globally, women have reported higher levels of anxiety, depression, and stress in response to the pandemic. Evidence suggests that social determinants of health have contributed to women’s poor health outcomes.

Materials and Methods:

We used the Understanding America Study to describe the social impacts women have experienced during the COVID-19 pandemic when compared with men and to explore the association between partnership status and social impacts in Los Angeles. We hypothesize that women experienced greater social impacts than men and that partnership status modified these social impacts.

Results:

In a sample of predominantly racial and ethnic minorities, we found that women experienced more social impacts related to housing insecurity compared with men. When exploring how partnership status modified these social impacts, we found that women without partners experienced more social impacts specific to financial hardships when compared with women who were in a partnership.

Conclusions:

It is likely that the COVID-19 relief efforts helped women mitigate social impacts but not housing or financial security. The overall goal is to inform policies so that better measures can be implemented to prepare for the next public health disaster or global health threat.

Introduction

The COVID-19 pandemic changed the lives of people around the globe. Measures that were put in place to prevent disease spread, including social distancing and stay-at-home orders, had unintended consequences on women’s ability to progress socially and economically.¹ Women who were overrepresented in minimum-wage industries before the pandemic were burdened by the economic shocks brought upon by the COVID-19 pandemic.^2
–4 Since the pandemic started, women have experienced higher financial instability owing to being laid off, being furloughed, and/or leaving the workforce because of an increase in household and caregiving responsibilities.^2,5,6 According to the Centers for Disease and Control Prevention,⁷ two out of every three caregivers are women. Caregivers are at a higher risk of poor physical and mental health.⁷ Gender inequities coupled with pandemic-related stressors have resulted in poor health outcomes among women, including those who are caregivers.^6,8,9

Stress-induced conditions such as psychological distress, anxiety, depression, and substance use have been on the rise.^10
–12 Globally, women have reported higher levels of anxiety, depression, and stress in response to the pandemic.^6,8,9 Evidence suggests that social determinants of health (SDH) have contributed to women’s poor health outcomes.^13,14 SDH are social, economic, physical, and environmental or nonmedical factors affecting health.¹⁵ A study examining health-related socioeconomic risk factors among women during the pandemic found that women reported higher food insecurity and intimate partner and other interpersonal violence.¹ Versey and Russell¹⁶ found that the pandemic exacerbated housing instability for African American and Latinx women. A Kaiser Foundation report on women’s health indicated that women delayed health care more than men during the pandemic.¹⁷ It will take women decades to recover from the social impacts inflicted by the pandemic.¹

Recent literature revealed that women who are married or in a cohabiting relationship reported better mental health outcomes during the pandemic.^18
–20 Literature often focuses on how marriage and stable partnerships buffer the effects of stress.²¹ Evidence shows that married women and women in stable relationships have better health outcomes and life satisfaction.²² However, there is a lack of research showing how social impacts experienced during the pandemic have affected women, including those with different partnership status (i.e., those with a partner vs. those without a partner).

We will use the Understanding America Study (UAS)²³ to describe the social impacts women have experienced during the COVID-19 pandemic compared with men and to explore the association between partnership status and social impacts in Los Angeles. We hypothesize that women experienced greater social impacts than men and that partnership status modified these social impacts. The overall goal is to inform policies so that better measures can be implemented to prepare for the next public health disaster or global health threat.

Methods

Study sample

The project described in this article relies on data from surveys administered by the UAS, which is maintained by the Center for Economic and Social Research (CESR) at the University of Southern California (USC). Secondary analyses were performed on the USC, CESR, UAS²³ project. The publicly available UAS uses a longitudinal probability-based internet survey to capture information on an ongoing basis on American household demographics and health nationwide via laptops, PCs, tablets, or smartphones.²³ The UAS uses address-based sampling.²³ With address-based sampling, postal records are used to sample from across the nation via random sampling.²³ Participants completed a baseline survey that collected information on basic demographics and provided consent to participate in future longitudinal surveys. As part of Wave 28 of data collection between May 12, 2021, and June 22, 2021, UAS 347 targeted all Los Angeles area residents who had consented to participate in future surveys (UAS 46). This survey captured information on diet, lifestyle, employment, health, housing, and COVID-19.²³ Adult respondents over 18 years of age were included in the sample. The survey was distributed to 1,626 respondents, of whom 1,117 completed the study (response rate: 68.0%). Response rates vary according to topic, time of the year, population selected, and the amount of time the survey is in the field.²³ A total of 138 (12.3%) respondents indicated they no longer resided in the Los Angeles area and were excluded from further analysis. The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of USC or UAS. We received an institutional review board exemption from the University of San Francisco.

Measures

To describe the social impacts of the COVID-19 pandemic, we examined three outcome variables related to the SDH, including financial difficulties, delayed payment of health expenses, and housing insecurity brought on by COVID-19 since the pandemic began in March 2020. The survey items followed a 5-point Likert scale to measure the frequency of each social impact (1 = never, 2 = rarely, 3 = sometimes, 4 = often, and 5 = all of the time) (Figs. 1 and 2). We categorized respondents into dichotomous groups based on self-reported responses: (1) those experiencing any social impact and (2) those experiencing a social impact frequently. We defined those experiencing any social impact as those who reported ever experiencing a social issue. Those who reported never experiencing a social issue were considered to have never experienced a social impact. Those who experienced “frequent” social impacts were defined as those reporting experiencing a social impact all of the time or often. Those who experienced the issue sometimes, rarely, or never were considered to have experienced a social issue infrequently. We examined each outcome by gender to identify whether women experienced greater social impacts during the COVID-19 pandemic compared with men. Gender was defined as those reporting being female or male. We then examined partnership status among women to evaluate whether women in a partnership experienced social impacts differently compared with women not in a partnership. Partnership status was defined as partnership if respondents reported being married or living with a partner and without partnership if respondents reported being separated, divorce, widowed, and never married.

FIG. 1.

Frequency of self-reported social impacts with (a) financial difficulties, (b) delay payment of health expenses, and (c) housing insecurity, by sex—Understanding America Survey, Los Angeles, California, 2021.

FIG. 2.

Frequency of self-reported problems with (a) financial difficulties, (b) delay payment of health expenses, and (c) housing insecurity by partnership status—Understanding America Survey, Los Angeles, California, 2021.

Statistical analysis

The survey assigned poststratification weights to ensure a representative survey sample. We compared respondents’ demographic characteristics and self-reported social impacts by gender and partnership status groups using chi-square tests. Logistic regression models were used to examine the association between social impacts (outcome) by gender (exposure) and partnership status (among women only). Models were adjusted for age, race, ethnicity, and employment. All models provide adjusted odds ratios (aORs) and corresponding 95% confidence intervals (CIs). All analyses were conducted using Stata statistical software, version 17.²⁴

Results

Among 979 respondents residing in the Los Angeles area, 592 (60.4%) identified as women and 387 (39.5%) as men (Table 1). The sample was predominantly composed of racial and ethnic minorities. A total of 408 (68.9%) women identified as racial and ethnic minority women compared with 217 (56.1%) men. Non-Hispanic White women and men comprised 154 (26.0%) and 157 (40.6%) respondents in our sample, respectively. Non-Hispanic mixed women and men were 30 (5.1%) and 13 (3.4%) respondents in our sample, respectively. The majority of women and men were between the ages of 19–54 years old (n = 427/592, 72.2%; n = 255/387, 65.4%, respectively). More than one-third of women, (n = 230/592, 38.9%) reported a household income of less than $39,999, whereas one-half of male respondents reported a household income of more than $75,000 (n = 187/387, 48.3%).

Table 1.

Characteristics of Participants—Understanding America Survey, Los Angeles, California, 2021

Characteristic	Women n (%)	Men n (%)	Chi-squared p-value
Total	592 (60.4%)	387 (39.5%)
Age			0.13
19–34 years	181 (30.6%)	101 (26.1%)
35–54 years	246 (41.6%)	152 (39.3%)
55–64 years	85 (14.4%)	66 (17.1%)
65–91 years	80 (13.5%)	68 (17.6%)
Household income			<0.001
Low income (<$40,000)	230 (38.9%)	121 (31.3%)
Moderate income ($40,000–74,999)	152 (25.7%)	79 (20.4%)
High income ($75,000 and above)	210 (35.5%)	187 (48.3%)
Race			0.13
White only	365 (61.7%)	268 (69.3%)
Black only	57 (9.6%)	22 (5.7%)
American Indian or Alaskan Native only	32 (5.4%)	18 (4.7%)
Asian only	87 (14.7%)	48 (12.4%)
Hawaiian/Pacific Islander only	9 (1.5%)	8 (2.1%)
Mixed	42 (7.1%)	23 (5.9%)
Ethnicity (Hispanic)			0.014
No	320 (54.1%)	240 (62%)
Yes	272 (45.9%)	147 (38%)
Employment status			0.006
Currently working	318 (53.7%)	222 (57.4%)
Disabled/On leave	25 (4.2%)	20 (5.2%)
Unemployed	98 (16.6%)	54 (14.0%)
Retired	55 (9.3%)	53 (13.7%)
Other labor force status	48 (8.1%)	12 (3.1%)
Mixed status	48 (8.1%)	26 (6.7%)
Partnership status			0.031
Partnership	326 (55.0%)	240 (62.0%)
Without partnership	266 (45.0%)	147 (38.0%)

Social impacts by gender

When exploring any social impacts brought on by the COVID-19 pandemic that women experienced compared with men, we found that the odds of experiencing any financial difficulties and delayed payment for health expenses to afford housing expenses were slightly higher for women compared with men (aOR = 1.14; 95% CI = 0.93, 1.68; and aOR = 1.17; 95% CI = 0.86, 1.59, respectively) (Table 2). The largest disparate social impact was housing insecurity, with women experiencing 42% higher odds of housing insecurity compared with men (aOR = 1.42; 95% CI = 1.03, 1.96). When considering the frequency of these social impacts, more frequent financial difficulties were reported by women compared with men (aOR = 1.22; 95% CI = 0.79, 1.89), but this difference was not significant and frequent issues for other social impacts were not more commonly reported by women compared with men (Table 2).

Table 2.

Unadjusted and Adjusted Odds Ratios Comparing the Odds of Experiencing Social Impacts from the COVID-19 Pandemic Among Women vs. Men—Understanding America Survey, Los Angeles, California, 2021

Factor	Women n (%)	Men n (%)	Women vs. Men
Factor	Women n (%)	Men n (%)	Unadjusted OR (95% CI)	Adjusted ORa (95% CI)
Any experiences with COVID-19 social impacts
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic affected your physical or mental health?
Any	394 (66.6%)	224 (57.9%)	1.45 (1.11–1.89)†	1.14 (0.93–1.68)
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic forced you to delay payment of health expenses in order afford your housing expenses?
Any	222 (37.5%)	116 (30%)	1.40 (1.07–1.84)†	1.17 (0.86–1.59)
Since March 2020, how often have you experienced housing insecurity due to financial difficulties brought on by the COVID-19 pandemic?
Any	198 (33.4%)	91 (23.5%)	1.63 (1.22–2.19)†	1.42 (1.03–1.96)†
Frequency of experiences with COVID-19 social impacts
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic affected your physical or mental health?
Frequently	82 (13.9%)	39 (10.1%)	1.43 (0.96–2.15)	1.22 (0.79–1.89)
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic forced you to delay payment of health expenses in order afford your housing expenses?
Frequently	29 (4.9%)	20 (5.2%)	0.95 (0.53–1.70)	0.81 (0.44–1.49)
Since March 2020, how often have you experienced housing insecurity due to financial difficulties brought on by the COVID-19 pandemic?
Frequently	38 (6.4%)	19 (4.9%)	1.33 (0.75–2.34)	1.08 (0.60–1.95)

Models were adjusted for age, race, ethnicity, and employment.

^†Significant at p < 0.05.

OR, odds ratio.

Social impacts by partnership status

When exploring any social impacts by partnership status, we found that the odds of experiencing any financial difficulties brought on by the COVID-19 pandemic that affected physical or mental health were higher for women without partnership compared with women in partnership (aOR = 1.72; 95% CI = 1.14, 2.59) (Table 3). The odds of experiencing delayed payment for health expenses to afford housing were higher for unpartnered women compared with partnered women (aOR = 1.21; 95% CI = 0.82, 1.80) (Table 3), although this difference was not statistically significant. Similar results were observed for housing insecurity. When considering the frequency of these social impacts by partnership status, we found that the odds of experiencing frequent financial difficulties were nearly three times higher for unpartnered women compared with partnered women (aOR = 2.77; 95% CI = 1.56, 4.81) (Table 3). Similarly, the odds of frequent housing insecurity was two times higher for unpartnered women compared with partnered women (aOR = 2.12; 95% CI = 0.99, 4.52). Unpartnered women had slightly greater odds of frequent experiences with delayed payment for health expenses compared with partnered women (aOR = 1.17; 95% CI = 0.52, 2.61), and this difference was not statistically significant.

Table 3.

Unadjusted and Adjusted Odds Ratios Comparing the Odds of Social Impacts of the COVID-19 Pandemic among Women in a Partnership vs. Women not in a Partnership—Understanding America Survey, Los Angeles, California, 2021

Factor	Partnership n (%)	No partnership n (%)	Partnership (reference) vs. No partnership
Factor	Partnership n (%)	No partnership n (%)	Unadjusted OR (95% CI)	Adjusted ORa (95% CI)
Any experiences with COVID-19 social impacts
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic affected your physical or mental health?
Any	199 (61%)	195 (73.3%)	1.75 (1.23–2.49)†	1.72 (1.14–2.59)†
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic forced you to delay payment of health expenses in order afford your housing expenses?
Any	112 (34.4%)	110 (41.4%)	1.35 (0.96–1.88)	1.21 (0.82–1.80)
Since March 2020, how often have you experienced housing insecurity due to financial difficulties brought on by the COVID-19 pandemic?
Any	96 (29.4%)	102 (38.4%)	1.49 (1.06–2.10)†	1.21 (0.81–1.80)
Frequency of experiences with COVID-19 social impacts
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic affected your physical or mental health?
Frequently	28 (8.6%)	54 (20.3%)	2.71 (1.66–4.42)†	2.77 (1.60–4.81)†
Since March 2020, how often have financial difficulties brought on by the COVID-19 pandemic forced you to delay payment of health expenses in order afford your housing expenses?
Frequently	14 (4.3%)	15 (5.6%)	1.33 (0.63–2.81)	1.17 (0.52–2.61)
Since March 2020, how often have you experienced housing insecurity due to financial difficulties brought on by the COVID-19 pandemic?
Frequently	13 (4%)	25 (9.4%)	2.50 (1.25–4.98)†	2.12 (0.99–4.52)

Models were adjusted for age, race, ethnicity, and employment.

^†Significant at p < 0.05.

OR, odds ratio.

Discussion

Results from the UAS administered to a diverse sample of adults in Los Angeles, California, indicate that women experienced more social impacts from the COVID-19 pandemic, particularly women without a partner. The strongest disparities were observed for housing insecurity. It is likely that the COVID-19 relief efforts have helped women mitigate social impacts but not housing. In places such as Los Angeles, housing insecurity continues to be a social factor affecting Black, Latina, and Native American women, single mothers, and the elderly.²⁵ Housing insecurity is described as not being able to afford rent or mortgage payments, often leading to moving, foreclosure, eviction, overcrowding, and/or spending majority of income on housing.^26,27 Those spending 30% of income on housing are considered cost burdened, whereas spending 50% of income on housing is considered severely cost burdened.²⁷ Most renters have experienced higher cost burden rates than homeowners during the pandemic.²⁸

Housing can, directly and indirectly, affect health.²⁹ Overcrowding has been associated with high mortality rates, infectious diseases, chronic diseases, and other health issues.^30
–32 Because affordable housing and housing stability are fundamental determinants of health for women, COVID-19 relief efforts must be extended to prevent evictions. Literature is being published showing that housing relief efforts have assisted in reducing evictions since the pandemic started.^33
–35 Close to 5.3 million payments were issued for current and outstanding rents with some utility assistance in 2022.³⁶

As the national COVID-19 relief efforts came to an end in 2023, there is an expectation for measures and policies to be in place to provide long-term assistance for housing. Housing instability is slowly becoming a national problem that requires federal intervention. Federal subsidies appear to reduce housing instability. Reports show that subsidies can lower rent to affordable rates and reduce the cost burden by 15% for those using Section 8 vouchers.³⁶ Additional measures are needed to expand the development and preservation of housing for low-income households, including constructing affordable housing units.³⁶ More immediate policies are needed to protect against eviction, given that historically those evicted have been women of color, including single mothers.^37,38

Women who reported being without a partner experienced more frequent financial difficulties than partnered women. Our findings align with research showing that unpartnered adults experience more financial hardships compared with partnered adults.³⁹ Research shows that having a partner buffers financial stress.^40,41 However, more women are choosing to be alone. It is well documented that socioeconomic factors and other personal matters influence women’s life satisfaction and happiness, whereas men are influenced by pleasurable experiences.^42,43 Globally, women are choosing to reach independence, pursue career opportunities, and restructure who becomes part of their social support system.⁴⁴ In this cultural shift, marriage is no longer considered a necessity but a choice. The Pew Research Center published a report on earnings by gender and found that young women are making the same or more money than men in some metropolitan cities.⁴⁵ However, this is the case for some but not all women.

The gender pay gap still exists, making it hard for some women to progress socially and economically. The gender pay gap explores the discrepancies in employment, occupations, and pay between all women and men.⁴⁶ Historically, women have been paid disproportionately less than men.⁴⁷ Factors that contribute to the gender pay gap are overrepresentation in low-wage industries that offer fewer benefits, discrimination, and biases in hiring, promotion, and paying practices among women and men; educational and career choices; lack of workplace accommodations for women caring for children; and greater responsibilities in positions.^46,48,49

The COVID-19 pandemic has exacerbated the gender pay gap for racial and ethnic minority women. A U.S. Government Accountability Office report found that Hispanic women make nearly $0.58 for every dollar White men make. In comparison, Black women make about $0.63 for every dollar White men make.⁵⁰ Those reaching parity are Asian and White women.⁵¹ Research has repeatedly shown a strong association between low socioeconomic status and poor health outcomes.⁵² Researchers have started to document how socioeconomic status is a significant contributor to racial disparities in health along with other structural factors.⁵³

Better measures are needed to help all women reach parity with men. Some states, such as California, are implementing policies that require employees to disclose the salary ranges for positions.⁵⁴ A study exploring the effects of pay transparency among faculty earnings found that laws could lower the gender pay gap by 20% to 40% between men and women.⁵⁵ Pay transparency can reduce the gender pay gap when combined with a salary history ban.^55
–57 A study examining bans on pay history discovered that the gender gap was reduced by 4.2% among hourly pay employees and 4.5% among weekly pay employees.⁵⁷ For racial and ethnic minority women, banning salary history increased wages by 5.9%.⁵⁶

By not disclosing previous salary and having transparency in pay, women, particularly women of color, can prevent perpetual inequities in pay from persisting. Additional resources and research are needed to help women of color progress socially and economically. Although these associations may apply to other areas of the United States, including other metropolitan cities, our results do not generalize nationally.

Limitations

This study used secondary, retrospective data, thus introducing recall bias. The questions asked respondents to recall events that occurred at the beginning of the pandemic or since March 2020. It relied on self-reported responses, which are prone to social-desirability bias.⁵⁸ The study specifically focused on women in the Los Angeles area, and the sample was restricted to those with internet access and technological literacy. As a result, our findings may not generalize to the national population of women. Finally, although the study helped highlight the importance of addressing social impacts brought upon by the pandemic, social impacts have likely decreased, given the amount of resources, programs, and initiatives established to improve gender equity and equality.

Conclusion

For women to recover from current and future public health disasters or global health threats, policies are needed now to mitigate the effects. Designated relief should be provided for single women who are not married or in a partnership to improve their financial and economic well-being, particularly for women of color. Stable housing is critical to reaching optimal health and well-being. Additional resources and measures are needed to keep women sheltered. A more comprehensive approach is needed to help women all around. An intersectional approach focuses on how multiple systems of oppression affect women’s health. Women’s health does not happen in a vacuum. More research is needed on how race, ethnicity, gender, and sexuality interact with social factors to mediate health outcomes. This includes exploring how structural inequalities perpetuate the gender and racial pay gap.

Footnotes

Acknowledgments

This research was conducted in partnership with the Los Angeles County Commission for Women’s Health Committee and the Iris Cantor—UCLA Women’s Health Education & Research Center.

Authors’ Contribution

J.M.: Conceptualization, Methodology, Resources, Writing—Original Draft, Writing—Review & Editing, Project administration. B.G.: Data Curation, Formal Analysis, Visualization, Writing—Review & Editing. A.R.: Writing—Review & Editing, Supervision, Validation.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

References

UN Women. COVID-19 and Its Economic Toll on Women: The Story Behind the Numbers. New York, NY; 2020. Available from: https://www.unwomen.org/en/news/stories/2020/9/feature-covid-19-economic-impacts-on-women [Last accessed: March 30, 2023 ].

Karageorge

. Monthly Labor Review. COVID-19 Recession is Tougher on Women. Washington, DC; 2020 Available from: https://www.bls.gov/opub/mlr/2020/beyond-bls/covid-19-recession-is-tougher-on-women.htm [Last accessed: April 5, 2023 ].

Dunn

. U.S. Bureau of Labor Statistics. Demographic Changes in Employment During The COVID-19 Pandemic. Washington, DC; 2022. Available from: https://www.bls.gov/spotlight/2022/demographic-changes-in-employment-during-the-pandemic/home.htm [Last accessed: April 5, 2023 ].

Kabeer

, Razavi

, Van Der Meulen Rodgers

. Feminist economic perspectives on the COVID-19 pandemic. Fem Econ, 2021; 27(1–2):1–29.

Thomason

, Macias-Alonso

. COVID‐19 and raising the value of care. Gend Work Organ, 2020; 27(5):705–708.

Raile

ANW

, Raile

, Parker

, et al. Women and the weight of a pandemic: A survey of four Western US states early in the Coronavirus outbreak. Gend Work Organ, 2021; 28(Suppl 2):554–565.

Centers for Disease Control and Prevention (CDC). For caregivers, family and friends. Atlanta, GA; 2023. Available from: https://www.cdc.gov/aging/caregiving/index.htm [Last accessed: May 4, 2023 ].

Lindau

, Makelarski

, Boyd

, et al. Change in health-related socioeconomic risk factors and mental health during the early phase of the COVID-19 pandemic: A national survey of U.S. women. J Womens Health, 2021; 30(4):502–513.

Ding

, Yang

, Ji

, et al. Women suffered more emotional and life distress than men during the COVID-19 pandemic: The role of pathogen disgust sensitivity. Int J Environ Res Public Health, 2021; 18(16):8539.

10.

McKnight-Eily

, Okoro

, Strine

, et al. Racial and ethnic disparities in the prevalence of stress and worry, mental health conditions, and increased substance use among adults during the COVID-19 pandemic—United States, April and May 2020. MMWR Morb Mortal Wkly Rep, 2021; 70(5):162–166.

11.

Devoto

, Himelein-Wachowiak

, Liu

, et al. Women’s substance use and mental health during the COVID-19 pandemic. Womens Health Issues, 2022; 32(3):235–240.

12.

Ettman

, Abdalla

, Cohen

, et al. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open, 2020; 3(9):e2019686–12.

13.

Paremoer

, Nandi

, Serag

, et al. Covid-19 pandemic and the social determinants of health. Bmj, 2021; 372:n129.

14.

Short

, Zacher

. Women’s health: Population patterns and social determinants. Annu Rev Sociol, 2022; 48(1):277–298.

15.

World Health Organization. Social Determinants of Health. Geneva; 2019. Available from: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1 [Last accessed: March 30, 2023 ].

16.

Versey

, Russell

. The impact of COVID‐19 and housing insecurity on lower‐income Black women. J Soc Issues, 2022; 79(2):773–793.

17.

Ranji

, Frederiksen

, Salganicoff

, et al. Kaiser Family Foundation KFF. Women, Work, and Family During COVID-19: Findings from the KFF Women’s Health Survey. San Francisco, CA; 2021. Available from: https://www.kff.org/womens-health-policy/issue-brief/women-work-and-family-during-covid-19-findings-from-the-kff-womens-health-survey/ [Last accessed: April 5, 2023 ].

18.

Soares

, Rodrigues

, De Paula

, et al. Partner responsiveness moderates the relation between COVID-19-related stressors and changes in mood during the pandemic. Curr Psychol, 2021; 42:1–8.

19.

Gualano

, Lo Moro

, Voglino

, et al. Effects of COVID-19 lockdown on mental health and sleep disturbances in Italy. Int J Environ Res Public Health, 2020; 17(13):4779.

20.

Stanton

, To

, Khalesi

, et al. Depression, anxiety and stress during COVID-19: Associations with changes in physical activity, sleep, tobacco and alcohol use in Australian adults. Int J Environ Res Public Health, 2020; 17(11):4065.

21.

Chin

, Murphy

, Janicki-Deverts

, et al. Marital status as a predictor of diurnal salivary cortisol levels and slopes in a community sample of healthy adults. Psychoneuroendocrinology, 2017; 78:68–75.

22.

Grover

, Helliwell

. How’s life at home? New evidence on marriage and the set point for happiness. J Happiness Stud, 2017; 20(2):373–390.

23.

The University of Southern California Dornsife Center for Economic and Social Research. Understanding America Study. Los Angeles, CA; 2017. Available from: https://uasdata.usc.edu/index.php [Last accessed: March 30, 2023 ].

24.

StataCorp. Stata Statistical Software: Release 17. College Station, TX; 2021. Available from: https://www.stata.com [Last accessed: April 5, 2023 ].

25.

Ong

, Gonzalez

, Nazario

. UCLA’s Center for Neighborhood Knowledge. Housing Insecurity Persists for Renters of Color Amid the COVID-19 Pandemic. Los Angeles, CA; 2022. Available from: https://knowledge.luskin.ucla.edu/wp-content/uploads/2022/04/Housing_Insecurity_COVID_Report.pdf [Last accessed: April 10, 2023 ].

26.

Healthy People 2030. Housing Instability. Rockville, MD; [date unknown] Available from: https://health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/housing-instability [Last accessed: March 30, 2023 ].

27.

U.S. Department of Housing and Urban Development. Glossary of Terms to Affordable Housing. Washington, DC; 2006. Available from: https://archives.hud.gov/local/nv/goodstories/2006-04-06glos.cfm [Last accessed: April 5, 2023 ].

28.

US Census Bureau. More Than 19 Million Renters Burdened by Housing Costs. Washington, DC; 2022. Available from: https://www.census.gov/newsroom/press-releases/2022/renters-burdened-by-housing-costs.html [Last accessed: March 30, 2023 ].

29.

Swope

, Hernández

. Housing as a determinant of health equity: A conceptual model. Soc Sci Med, 2019; 243:112571.

30.

Cockerham

, Hamby

, Oates

. The social determinants of chronic disease. Am J Prev Med, 2017; 52(1S1):S5–S12.

31.

Matsuoka

, Lucky

, Desautels

. Urban and Environmental Policy Institute. Power, Place, and Public Health: A Review of The Literature on The Health Impacts of Displacement and Promise of Inclusive Community Development. Los Angeles, CA; 2017. Available from: https://www.oxy.edu/sites/default/files/assets/URC/Power%2520Place%2520and%2520Public%2520Health-%2520June%25202017.pdf [Last accessed: April 5, 2023 ].

32.

Haas

, Rangel

, Garnham

, et al. Eviction Lab. Preliminary Analysis: Eviction Filing Trends After the CDC Moratorium Expiration. Princeton, NJ; 2021. Available from: https://evictionlab.org/updates/research/eviction-filing-trends-after-cdc-moratorium/ [Last accessed: May 21, 2023 ].

33.

U.S. Department of The Treasury. Emergency Rental Assistance Program: Keeping Families in Their Homes. Washington, DC; 2023. Available from: https://home.treasury.gov/policy-issues/coronavirus/assistance-for-state-local-and-tribal-governments/emergency-rental-assistance-program [Last accessed: May 24, 2023 ].

34.

Center on Budget and Policy Priorities (CBPP). Robust COVID Relief Achieved Historic Gains Against Poverty and Hardship, Bolstered Economy. Washington, DC; 2022. Available from: https://www.cbpp.org/sites/default/files/6-14-22pov-testimony.pdf [Last accessed: May 24, 2023 ].

35.

Joint Center for Housing Studies (JCHS) of Harvard University. The State of the Nation's Housing 2022. Cambridge, MA; 2022. Available from: https://www.jchs.harvard.edu/sites/default/files/reports/files/Harvard_JCHS_State_Nations_Housing_2022.pdf [Last accessed: May 24, 2023 ].

36.

Reynolds

, Lo

, Boshart

, et al. Urban Institute. Federal Reforms to Strengthen Housing Stability, Affordability, And Choice: Opportunity for All. Washington, DC; 2021. Available from: https://www.urban.org/sites/default/files/publication/103916/federal-reforms-to-strengthen-housing-stability-affordability-and-choice.pdf [Last accessed: August 17, 2023 ].

37.

Desmond

, Gershenson

. Who gets evicted? assessing individual, neighborhood, and network factors. Soc Sci Res, 2017; 62:362–377.

38.

Vásquez-Vera

, Palència

, Magna

, et al. The threat of home eviction and its effects on health through the equity lens: A systematic review. Soc Sci Med, 2017; 175:199–208.

39.

Fry

, Parker

. Pew Research Center. Rising Share of U.S. Adults Are Living Without A Spouse or Partner. Washington, DC; 2022 Oct 5. Available from: https://www.pewresearch.org/social-trends/2021/10/05/rising-share-of-u-s-adults-are-living-without-a-spouse-or-partner/ [Last accessed: August 28, 2023 ].

40.

Kelley

, LeBaron

, Hill

. Financial stress and marital quality: The moderating influence of couple communication. J Financ Ther, 2018; 9(2):1–20.

41.

Ryu

, Fan

. The relationship between financial worries and psychological distress among U.S. adults. J Fam Econ Issues, 2023; 44(1):16–33.

42.

Montgomery

. Reversing the gender gap in happiness. Soc Sci Res Netw, 2022; 196:65–78.

43.

Brakus

, Chen

, Schmitt

, et al. Experiences and happiness: The role of gender. Psychology and Marketing, 2022; 39(8):1646–1659.

44.

Jones

, G’Sell

, Takeyama

, et al. Opting Out: Women Messing with Marriage Around the World. Rutgers University Press: New Brunswick, NJ; 2022. Available from: https://muse.jhu.edu/book/102660 [Last accessed: September 13, 2023 ].

45.

Fry

. Pew Research Center. Young Women Are Out-Earning Young Men in Several U.S. Cities. Washington, DC; 2022. Available from: https://www.pewresearch.org/short-reads/2022/03/28/young-women-are-out-earning-young-men-in-several-u-s-cities/#:∼:text=The%20New%20York%2C%20Washington%2C%20D.C [Last accessed: September 13, 2023 ].

46.

Bishu

, Alkadry

. A systematic review of the gender pay gap and factors that predict it. Adm Soc, 2016; 49(1):65–104.

47.

Chun-Hoon

. US Department of Labor Blog. 5 Fast Facts: The Gender Wage Gap. Washington DC; 2023. Available from: https://blog.dol.gov/2023/03/14/5-fast-facts-the-gender-wage-gap [Last accessed: September 19, 2023 ].

48.

Foster

, Murray-Close

, Landivar

, et al. The United States Census Bureau. An Evaluation of The Gender Wage Gap Using Linked Survey and Administrative Data. Washington, DC; 2020. Available from: https://www.census.gov/library/working-papers/2020/adrm/CES-WP-20-34.html [Last accessed: September 19, 2023 ].

49.

U.S. Department of Labor. Bearing the Cost: How Overrepresentation in Undervalued Jobs Disadvantaged Women During the Pandemic. Washington, DC; [date unkonown]. Available from: https://www.dol.gov/sites/dolgov/files/WB/media/BearingTheCostReportFactSheet.pdf [Last accessed: September 22, 2023 ].

50.

U.S. Government Accountability Office. Women in The Workforce: The Gender Pay Gap Is Greater for Certain Racial and Ethnic Groups and Varies by Education Level. Washington, DC; 2022. Available from: https://www.gao.gov/products/gao-23-106041 [Last accessed: September 23, 2023 ].

51.

Kochhar

. The Enduring Grip of The Gender Pay Gap. Pew Research Center; Washington, DC; 2023. Available from: https://www.pewresearch.org/social-trends/2023/03/01/the-enduring-grip-of-the-gender-pay-gap/ [Last accessed: October 10, 2023 ].

52.

World Health Organization (WHO). Social Determinants of Health (SDH). Geneva; 2024. Available from: https://www.who.int/health-topics/social-determinants-of-health#tab=tab_1 [Last accessed: October 10, 2023 ].

53.

Williams

, Priest

, Anderson

. Understanding Associations Between Race, Socioeconomic Status, and Health. Duke University Press: Durham, NC; 2019. Available from: doi: 10.1215/9781478004363-031 [Last accessed: October 12, 2023 ]

54.

State of California Department of Industrial Relations. California Equal Pay Act. Los Angeles, CA; 2023. Available from: https://www.dir.ca.gov/dlse/california_equal_pay_act.htm [Last accessed: November 11, 2023 ].

55.

Baker

, Halberstam

, Kroft

, et al. Pay transparency and the gender gap. Am Econ J Appl Econ, 2023; 15(2):157–183.

56.

Bessen

, Chen

, Denk

. Perpetuating inequality: What salary history bans reveal about wages. Soc Sci Res Netw, 2020; 1(2):83–112, doi: 10.2139/ssrn.3628729

57.

Sinha

. Salary history ban: Gender pay gap and spillover effects. SSRN Journal, 2019.

58.

Rosenman

, Tennekoon

, Hill

. Measuring bias in self-reported data. Int J Behav Healthc Res, 2011; 2(4):320–332.