Socioeconomic Disparity in Birth Rates During the COVID-19 Pandemic in New York City

Abstract

Background:

The differential impact of the coronavirus disease 2019 (COVID-19) pandemic across race, ethnicity, and socioeconomic status remains poorly understood. While recent explorations into birthrates during the pandemic have revealed significant declines, how birthrates may have differed between racial and socioeconomic subgroups during the pandemic remains to be detailed.

Methods:

Using electronic health records from a large hospital network in New York serving a racially and socioeconomically diverse population, we explored birthrates associated with conceptions that occurred during the COVID-19 pandemic lockdown for demographic and obstetric differences.

Results:

Two thousand five hundred twenty-three unique patient deliveries corresponded with conceptions that occurred during the COVID-19 pandemic lockdown in New York. Compared to the same period the previous year, there was a 22.85% decrease in births. Explorations into differences in birthrates by socioeconomic status revealed that much of the decline could be explained by fewer births among individuals living in higher socioeconomic status as opposed to individuals living in urban economic poverty [χ²(n = 5588) = 18.35, p < 0.01].

Conclusion:

On March 22, 2020, New York instituted a prohibition of all nonessential social gatherings and the closure of all nonessential businesses. Although the full impact of the COVID-19 pandemic on reproductive health and outcomes remains largely unknown, the decreased birthrate associated with the initial COVID-19 wave in New York was not entirely unexpected. While the mechanisms that drive health disparities are complex and multifactorial, most of the decrease occurred among those living in higher socioeconomic status. This finding has important implications for understanding health behaviors and disparities among minorities living in low socioeconomic status.

Introduction

Across the United States and globally, the coronavirus disease 2019 (COVID-19) pandemic has impacted numerous aspects of daily living, including employment, education, worship, access to preventative health care, and mortality. Even in the best of times, each of these is well understood to disproportionally impact communities of racial and socioeconomic diversity—but rarely more negatively than in times of crisis.¹ Indeed, the coronavirus pandemic has spotlighted numerous disparities associated with the health and well-being of those living in the most vulnerable communities.^2
–4 Given the profound impact of the COVID-19 pandemic on racially and socioeconomically diverse communities, clarifying how the pandemic lockdown may have differentially impacted those living across the socioeconomic spectrum is important for future pandemic planning and improving health equity.⁵

On March 22, 2020, New York banned all nonessential social gatherings and called for the complete closure of all nonessential businesses in response to the World Health Organization's declaration of COVID-19 as a global pandemic. Not long thereafter, speculation about the potential impact of the COVID-19 pandemic on fertility and conception began appearing in the lay press and academic literatures.⁶ Interestingly, while much of the lay media assumed a forthcoming baby boom due to the presumptive “romantic isolation of a pandemic lockdown,” the vast majority of academic publications hypothesized subsequent decreases in birthrates.⁷ The latter based on historical evidence of fertility rates following other high casualty events⁸ and reduced access to sexual reproductive services.⁹

The objectives of the study were twofold. The first aim was to determine differences in the rates of deliveries during the pandemic lockdown in New York City. Given that the pandemic lockdown occurred from March 22, 2020, to June 30, 2020, these deliveries would be expected to take place between January 1, 2021, and March 31, 2021. The second aim was to explore the differences in birth rates among those with commercial insurance payers versus Medicaid payors. For both aims, births that occurred during the same period the previous year were used for comparison.

Understanding how the COVID-19 lockdown and other restrictions that were intended to control disease transmission may have had differential effects on the health and well-being of marginalized communities will inform future reproductive health service planning in times of crisis.

Methods

Sample population

The study cohort consisted of the entire population of unique patients who delivered an infant between January 1, 2021, and March 31, 2021, at the Mount Sinai Health System. These dates are consistent with conceptions that would have occurred during the pandemic lockdown in New York from March 22, 2020, to June 30, 2020. The same dates of delivery for the previous year (January 1, 2020, and March 31, 2020) were used for comparison. Because the study involved comparing patients seeking care at hospital-based community clinics to those utilizing faculty practice services, retrospective data were obtained from Mount Sinai Hospital Obstetrics and Gynecology Associates, Mount Sinai West, and Mount Sinai Hospital Faculty Practices.

Socioeconomic status

The Mount Sinai Hospital Obstetrics and Gynecology Ambulatory Practice and Mount Sinai West Obstetrics and Gynecology Ambulatory Practice are New York State public health law-designated community practices. They are certified as participants of the New York State Medicaid Program and serve a population that primarily self-identifies as minority.

Hispanic and African-American individuals who reside in the inner city comprise the vast majority of the population served (90%). The remaining 10% of patients self-identify as Asian, Native American, Indian, Filipino, Islander, Caucasian, and “unknown.” All patients who utilize the hospital-based community clinics live at or below 133% of the federal poverty line and are enrolled or “pending enrollment into” a US government-funded health care plan when they arrive for initial treatment. All hospitals within the Mount Sinai Network collect race and ethnicity information from all patients according to New York State Department of Health guidelines. This is accomplished using a standardized self-report form (Supplementary Appendix A1).

The Mount Sinai Faculty Practices consist of a group of independent physicians servicing a population of patients with a commercial payor. Approximately 59% of these individuals self-identify as a minority. Patients of the Faculty Practices have commercial insurance, independently subscribe to a private insurance plan, or choose to self-pay.

All experimental protocols were approved and performed in compliance with the Icahn School of Medicine at Mount Sinai (ISMMS) Program for the Protection of Human Subjects, and in accordance with the Health Insurance Portability and Accountability Act (HIPAA) security rule guidelines enacted in 2003 (ISMMS IRB protocol #20-03633).

Data acquisition and analysis

Electronic health information relating to the study, including the date of service, payor source, and demographic information, was downloaded directly from the Mount Sinai Hospital's network and imported into SPSS Statistics 27.0 (IBM Corporation, 2020) for analysis.

Data were collected for all births occurring between January 1, 2021, and March 31, 2021. This time period coincided with conceptions that would have occurred during the pandemic lockdown. For comparison, data were also collected for all births occurring between January 1, 2020, and March 31, 2020. The difference in birthrate between these two time periods was calculated as a simple percentage.

To determine if there was any birth rate difference due to payor status that occurred as a result of the pandemic lockdown, patients were separated into two groups based on the payor status recorded in their record. Given that the Obstetrics and Gynecology Ambulatory Practice only accepted Medicaid payors, whereas patients who received their prenatal care through the Mount Sinai Faculty Practices or other private voluntary faculty groups had commercial payors or self-paid, each individual's location of prenatal service, that is, where they received prenatal care was used for confirmation.

Because the total number of births is calculated from observed counts, differences in what was observed from what was statistically expected were assessed using Chi-Square tests, a nonparametric statistical test of difference. A chi-square (χ²; 2 × 2) test was run to explore any difference in the birth census between the two payor groups consistent with conceptions occurring during the lockdown and implementation of the March 22, 2020, through June 30, 2020, social restrictions in New York City.

Results

Characteristics of the sample

A total of 2523 unique patients with primiparous or multiparous deliveries were identified between January 1, 2021, and March 31, 2021, compared to 3228 for the same time period the previous year. These totals represent a net difference of 22.85% fewer births occurred during the pandemic lockdown (Table 1).

Table 1.

Demographics by Year

January 1–March 31	2020	2021
Total	3228	2523
Age range	15–53	13–55
Delivery route
Vaginal	2217	1728
Cesarean	1011	795
Parity	0–15	0–16

For the secondary analysis, of the total 5751 deliveries identified from January 1 to March 31 for the years 2020 and 2021, 163 observations were discarded (100 from the 2020 sample and 63 from 2021 sample) because their location of service and payor status could not be confirmed. The age of patients who delivered after receiving care through the Obstetrics and Gynecology Ambulatory Practices ranged from 13 to 52 years, with a mean age of 29 years. The rate of cesarean deliveries for these patients in the Ambulatory Practices was 24.0%. The average parity was 2.8. Patients of the Obstetrics and Gynecology Faculty Practice ranged in age from 17 to 55 years, with a mean age of 33 years. The rate of cesarean deliveries in the Faculty Practice was 34.20%. The average parity for this group was 1.6 (Table 2).

Table 2.

Birthing Characteristics by Payor

January 1–March 31	Medicaid payor		Commercial payor
January 1–March 31	2020	2021	2020	2021
Total	896	836	2232	1624
Age range	15–49	13–52	17–53	17–55
Under 21	70	56	13	16
21–29	438	411	352	288
30–39^a	340	323	1636	1179
40–49	48	45	226	138
50+	—	1	5	3
Race/Ethnicity
American Indian or Alaska Native	1 (0.1%)	1 (0.1%)	2 (0.1%)	2 (0.1%)
Asian	30 (3.3%)	17 (2.0%)	325 (14.6%)	240 (14.8%)
Black	197 (22%)	166 (19.9%)	170 (7.6%)	153 (9.4%)
Hispanic	275 (30.7%)	268 (32.1%)	235 (10.5%)	176 (10.8%)
White	324 (36.2%)	326 (39.0%)	1262 (56.5%)	960 (59.1%)
Other	58 (6.5%)	51 (6.1%)	139 (5.2%)	67 (4.1%)
Unknown	11 (1.2%)	7 (0.8%)	99 (5.5%)	26 (1.7%)
Parity	0–14	0–16	0–15	0–13
Delivery route
Vaginal	686 (77%)	630 (75%)	1472 (66%)	1062 (65%)
Cesarean	210 (23%)	206 (25%)	760 (34%)	562 (35%)

χ²(n = 3478) = 10.22, p < 0.01.

A 2 × 2 chi-square (χ²) exploring whether the decrease in observed birthrates could be explained by differences among socioeconomic status demonstrated that the decline in birthrate could be explained by a significant number of fewer births among those individuals using commercial payors or self-paying in comparison to those with Medicaid payors [27.3% vs. 6.7%: χ²(n = 5588) = 18.35, p < 0.01].

Discussion

The number of births associated with conceptions that occurred during the first wave of the COVID-19 pandemic (March 22, 2020–June 30, 2020) in a large New York City hospital network decreased when compared to the same time period the previous year. Results also demonstrated that the vast majority of the birth rate decline from January 1, 2021, to March 31, 2021, in New York City could be explained by a significant reduction of observed deliveries among obstetric patients with a commercial payor insurance (27.3%), compared to obstetric patients with a Medicaid payor (6.7%).

Globally, the pandemic resulted in individuals across Europe reportedly reducing their fertility intentions,¹⁰ with recent observations confirming a significant decrease in birth rates.^11,12 Similarly, preliminary reports from the US Centers for Disease Control and Prevention (CDC) and more recently from the US Center for National Health Statistics have pointed to an equally dramatic reduction in birth rates.¹³ Indeed, the year 2020 had the lowest US birth rate in over a century,¹⁴ and while the birth rate in the United States has declined every year since 2008, except 2014,¹⁵ the findings from this study are consistent with previous studies demonstrating that high fatality epidemics such as the Spanish flu pandemic of 1918¹⁶ and the Severe Acute Respiratory Syndrome (SARS) epidemic of 2003¹⁷ led to further decreases in observed birth rates.

Unfortunately, attempting to compare fertility dynamics between the COVID-19 pandemic and other pandemic events is complicated by many factors. For example, the fatality distribution during the influenza pandemic of 1918 greatly impacted the birthing age population, whereas the COVID-19 pandemic generally impacted the more senior population. Similarly, differences in enlistment rates across the socioeconomic spectrum during World War I (1914–1918) immediately before the 1918 pandemic and the changing “marital market” played additional roles in reproductive dynamics at that time.¹⁸

Interestingly, while we confirmed a significant decrease in births in New York City during the first wave of the COVID-19 pandemic, we were also able to identify that this decrease was more prevalent among individuals using a commercial insurance payor. Notably, although the birth rate in the United States has continued to decline and while the general fertility rate has steadily decreased for the three largest US race groups (non-Hispanic white, non-Hispanic black, and Hispanic), this decline has not been distributed equally and has seemingly been driven more by racial factors than socio economic ones, as different groups have demonstrated similar trends.¹⁹ In contrast, and surprisingly, the differences noted during the COVID-19 pandemic in our sample population appear to demonstrate an important and possibly counterintuitive interaction between socioeconomic class and reproductive choice in response to pandemic restrictions.

Precisely, why individuals with a commercial payor were less likely to deliver a child during the observation period that corresponded with conceptions during the COVID-19 pandemic lockdown in New York City remains unknown. However, we are aware of a few possible contributory explanations for this finding. First, those patients using a commercial payor may have increased opportunities for mobility during times of crisis. Racial and socioeconomic inequities in mobility during the early days of the COVID-19 pandemic have been documented throughout the United States and globally.^20

–23 Similarly, data from New York City have demonstrated a population decline among the wealthiest individuals during the height of the COVID-19 pandemic,²⁴ with many New York City residents seeking temporary and permanent residence outside the city.

Data from the US CDC further suggest an initial trend suggesting that out-of-town births increased significantly during the early days of the pandemic for white individuals compared to those of minority status living in lower-income environments in New York.²⁵ Although inconclusive, the CDC's observation does provide additional evidence that individuals of increased means may have moved out of the city to deliver their children. While it is unknown how many New York residents returned in the first months of 2021, it is possible that those who sought more permanent residence may have continued to be partially responsible for the lower inner-city delivery rate among those with commercial payor status. Second, the COVID-19 pandemic restrictions directly impacted access to reproductive therapies in New York.

Given that fertility assistance such as in vitro fertilization (IVF) is unavailable to those living in urban economic poverty and using a Medicaid payor, it is possible that the decreased use among those with greater economic means could have contributed, at least in small part, to the observation of lower birth rates among the commercial payor population.

Interestingly, although IVF-assisted births are nationally observed to represent between 1% and 2% of all conceptions, in New York, this rate approaches 5.5%.²⁶ Furthermore, studies have consistently shown substantial differences in the use and access to assistant reproductive therapies by race and socioeconomic status.^27
–29 Third, there is a considerable literature detailing the relationship between stress, fertility, and reproduction, as well as a handful of more recent retroactive studies exploring fertility dynamics in response to pandemics that extend beyond biologic factors.¹⁸

However, while the mechanisms of change (biologic, environmental, and psychological) and the direction of causality remain indeterminate, the link between an individual's reported levels of stress and the decreased likelihood of conception is well understood.³⁰ To this point, research has begun to reveal how individuals living in lower socioeconomic status in New York City during the pandemic restrictions demonstrated a surprising improvement in early pregnancy and postpartum mood, indicating less stress symptomatology compared to those with commercial payor status.^31,32 It was also observed that individuals with higher income demonstrated a curvilinear response of decreased life satisfaction and mental health compared to those who earned less during the pandemic.³³

How the relationship between stress, fertility, and reproductive decision making among those with a Medicaid payor may be further related to policies implemented during the lockdown, such as eviction moratoriums, economic stimulus payments, as well as to the increasing body of research demonstrating that patients with a Medicaid payor may be more physically resilient to the effects of stressful life events,³⁴ and more emotionally resilient in the face of opportunistic illness,³⁵ remains to be further explored. Interestingly, it could be argued that in respect to reproductive decision making, decreased interest in reproduction would be mostly felt by those with the greatest loss event concerns.³⁶

It is well understood that childbearing intention tends to rise and fall based on how optimistic or pessimistic an individual feels.³⁷ Because the social restrictions instituted during the COVID-19 pandemic favored an increased sense of emotional well-being among those in lower socioeconomic status by affording a greater balance of employment-family-childcare demands,³² while simultaneously decreasing life satisfaction among those in higher socioeconomic status,³⁸ it is possible that the observed birthrate variation among the different payer populations was due to changes in perceived emotional well-being and economic stability tied directly to their socioeconomic position.³³

The finding of differential birthrates by payor status during the pandemic is important for the continued understanding of socioeconomic disparities and health outcomes. Furthermore, because birthrates offer a proxy to assess a community's sense of health and well-being, this observation has additional importance toward further understanding avenues of addressing the declining US birthrate.^14,15

Nevertheless, we do recognize that there are limitations of the study. First, the sample population explored was a treatment-seeking clinical sample from care-based centers in New York City. As convenience samples that only include those seeking treatment, the general population of socioeconomic and racial diversity in New York City may not be fully representative of the population of health behaviors in New York City, New York State, or the entire United States. Second, our method of determining a subject's socioeconomic status was based on payor status and which was then confirmed by their location of service. While the Obstetrics and Gynecology Ambulatory Practices did not accept commercial insurance, it is possible that a subject living in urban economic poverty had commercial insurance coverage, for example, either purchased through the Affordable Care Act or provided by an employer.

In such a case, someone living in urban economic poverty, who delivered an infant during the observed periods, would be classified as a patient living in higher socioeconomic status. This is a limitation of registry resolution and while it is difficult to estimate whether incomplete sensitivity could lead to an estimation error, the reversed error of classifying a woman with a commercial payor among Medicaid payors is far less likely secondary to our method of confirmation.

Similarly, given that the overall birth rate was observed to be significantly lower among the commercial payor group, even if such a classification error had been made, it would mean that the observed effect size was actually larger and that the difference observed would have been underestimated. Third, we only used the previous year's birth rate for comparison. While it is possible that our chosen observation period before the pandemic restrictions represented an outlier, annual birth data available from The New York City Department of Health and Mental Hygiene, Bureau of Vital Statistics,³⁹ and the US Center for National Health Statistics do not support this possibility. In fact, the annual birth rate in New York City has dropped every year since 2008 and a total of 12.5% since 2009.⁴⁰

Finally, although we present data on birthrate differences between payor types from a large and diverse socioeconomic sample in New York City, our birthing population was not large enough to reliably explore how other covariates may have been associated with the observed differences in birthrates during the first wave of the COVID-19 pandemic, nor were we able to explore maternal birth outcomes. However, these explorations should be possible with the collection of additional data and once the spread of COVID-19 is no longer considered pandemic.

In conclusion, this is the first study to demonstrate that the decrease in birth rates in New York City during the COVID-19 pandemic could be explained by significantly fewer births among those using commercial payor insurance compared to Medicaid payors. Despite the considerable amount of attention that disparities in clinical care have received, vast inequities in population health remain, in part, not only because of uneven access to resources but also because the social determinants of health outcomes fail to be adequately addressed.^41,42

Although the full impact of the COVID-19 pandemic on reproductive health and reproductive decision making remains largely unknown and requires further study, that the reproductive behaviors among the higher socio economic status population in our sample explained the birthrate decline observed in New York City during the early days COVID-19 pandemic points to the need to better understand the social, economic, and situational determinants that drive reproductive health decision making.

Availability of Data and Material

The datasets generated during and analyzed during this study are not publicly available due to patient protections and institutional policy.

Ethics Approval

The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All experimental protocols were approved by the ISMMS Program for the Protection of Human Subjects and in accordance with the HIPAA security rule guidelines enacted in 2003. (ISMMS IRB Protocol #20-03633).

Consent to Participate

Under the Federal Policy for the Protection of Human Subjects (45 CFR 46.116; a.k.a. the “Common Rule”), informed consent was waived by determination of the Mount Sinai School of Medicine Program for the Protection of Human Subjects.

Consent for Publication

All authors.

Footnotes

Authors' Contributions

General: M.E.S., T.A.S., and T.J.S. had full access to all data and take responsibility for the integrity of data and the accuracy of data analysis. Study concept and design: all authors. Drafting of the article: all authors. Acquisition, analysis, or interpretation of data: all authors. Critical revision of the article for important intellectual content: all authors. Statistical analysis: M.E.S. Administrative, technical, or material support: M.E.S., T.A.S, T.S.K., and T.J.S. Study supervision: T.A.S.

Author Disclosure Statement

All authors certify that they have no affiliation with or involvement in any organization or entity with any financial interest or nonfinancial interest in the subject matter or materials discussed in this article.

Funding Information

No funding was received for this article.

Supplementary Material

Supplementary Appendix A1

References

U.S. Department of Health and Human Services. Social Determinants of Health, 2020. Available at: https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-of-health Accessed March 23, 2022 .

Millet

, Jones

, Benkeser

, et al. Assessing differential impacts of COVID-19 on Black communities. Ann Epidemiol, 2020; 47:37–44.

Webb Hooper

, Nápoles

, Pérez-Stable

. COVID-19 and Racial/Ethnic Disparities. JAMA, 2020; 323:2466–2467.

Wadhera

, Wadhera

, Gaba

, et al. Variation in COVID-19 hospitalizations and deaths across New York City boroughs. JAMA, 2020; 323:2192–2195.

Chowkwanyun

, Reed

Jr . Racial health disparities and Covid-19-caution and context. N Engl J Med, 2020; 383:201–203.

Gromski

, Smith

ADAC

, Lawlor

, Sharara

, Nelson

. 2008 financial crisis versus 2020 economic fallout: How COVID-19 might influence fertility treatment and live births. Reprod Biomed Online, 2021; 42:1087–1096.

Kearney

, Levine

. The coming COVID-19 baby bust: Update. Washington, DC: Brookings Institution, 2020. https://www.brookings.edu/blog/up-front/2020/12/17/the-coming-covid-19-baby-bust-update/

Ullah

, Moin

, Araf

, Bhuiyan

, Griffiths

, Gozal

. Potential Effects of the COVID-19 pandemic on future birth rate. Front Public Health, 2020; 8:578438.

Lindberg

, VandeVusse

, Mueller

, Kirstein

Early impacts of the COVID-19 pandemic: Findings from the 2020 Guttmacher Survey of Reproductive Health Experiences. New York: Guttmacher Institute, 2020. DOI: https://doi.org/10.1363/2020.31482.

10.

Luppi

, Arpino

, Rosina

. The impact of COVID-19 on fertility plans in Italy, Germany, France, Spain, and the United Kingdom. Demogr Res, 2020; 43:1399–1412.

11.

De Rose

, Mantica

, Ambrosini

, et al. COVID-19 impact on birth rates: First data from Metropolitan City of Genoa, Northern Italy (published online ahead of print, 2021 Apr 12). Int J Impot Res, 2021; 34:111–112.

12.

Aassve

, Cavalli

, Mencarini

, Plach

, Sanders

. Early assessment of the relationship between the COVID-19 pandemic and births in high-income countries. Proc Natl Acad Sci U S A, 2021; 118:e2105709118.

13.

Martin

, Hamilton

, Osterman

MJK

. Births in the United States, 2019. NCHS Data Brief, no 387. Hyattsville, MD: National Center for Health Statistics, 2020.

14.

Hamilton

, Martin

, Osterman

MJK

. Births: Provisional data for 2020. Vital Statistics Rapid Release; no. 12. Hyattsville, MD: National Center for Health Statistics, 2021.

15.

U.S. Census Bureau. U.S. Births declined during the pandemic, 2021. Available at: https://www.census.gov/library/stories/2021/09/united-states-births-declined-during-the-pandemic.html Accessed March 23, 2022 .

16.

Jester

, Uyeki

, Jernigan

. Readiness for responding to a severe pandemic 100 years after 1918. Am J Epidemiol, 2018; 187:2596–2602.

17.

Lee

, Huang

, Chang

, Hsu

, Wang

, Chou

. The immediate effects of the severe acute respiratory syndrome (SARS) epidemic on childbirth in Taiwan. BMC Public Health, 2005; 5:30.

18.

Boberg-Fazlic

, Ivets

, Karlsson

, Nilsson

. Disease and fertility: Evidence from the 1918–1919 influenza pandemic in Sweden. Econ Hum Biol, 2021; 43:101020.

19.

Hollmann

, Mulder

, Kallan

. “Methodology and Assumptions for the Population Projections of the United States: 1999 to 2100,” Population Division Working Paper No. 38. U.S. Census, 2000.

20.

Unwin

HJT

, Mishra

, Bradley

, et al. State-level tracking of COVID-19 in the United States. Nat Commun, 2020; 11:6189.

21.

Saha

, Chouhan

. Lockdown and unlock for the COVID-19 pandemic and associated residential mobility in India. Int J Infect Dis, 2021; 104:382–389.

22.

Duque-Calvache

, Torrado

, Mesa-Pedrazas

. Lockdown and adaptation: Residential mobility in Spain during the COVID-19 crisis. Eur Soc, 2021; 23 Supp 1:S759–S776.

23.

Lee

, Qian

, Schwanen

. The association between socioeconomic status and mobility reductions in the early stage of England's COVID-19 epidemic. Health Place, 2021; 69:102563.

24.

Office of the New York City Comptroller. “The Pandemic's Impact on NYC Migration Patterns,” 2021. Available at:https://comptroller.nyc.gov/reports/the-pandemics-impact-on-nyc-migration-patterns/ Accessed February 13, 2022 .

25.

Gregory

ECW

, Osterman

MJK

, Valenzuela

. Changes in births to New York City residents occurring outside New York City, by race and Hispanic origin of the. mother: 2018–2019 and 2019–2020. Vital Statistics Rapid Release; no 13. Hyattsville, MD: National Center for Health Statistics, 2021.

26.

U.S. Centers for Disease Control and Prevention. State-Specific Assisted Reproductive Technology Surveillance, 2021. Available at: https://www.cdc.gov/art/state-specific-surveillance/index.html Accessed March 23, 2022 .

27.

Seifer

, Simsek

, Wantman

, Kotlyar

. Status of racial disparities between black and white women undergoing assisted reproductive technology in the US. Reprod Biol Endocrinol, 2020; 18:125.

28.

Dieke

, Zhang

, Kissin

, Barfield

, Boulet

. Disparities in assisted reproductive technology utilization by Race and Ethnicity, United States, 2014: A commentary. J Womens Health (Larchmt), 2017; 26:605–608.

29.

Chambers

, Hoang

, Sullivan

, et al. The impact of consumer affordability on access to assisted reproductive technologies and embryo transfer practices: An international analysis. Fertil Steril, 2014; 101:191–198.e4.

30.

Rooney

, Domar

. The relationship between stress and infertility. Dialogues Clin Neurosci, 2018; 20:41–47.

31.

Silverman

, Medeiros

, Burgos

. Early pregnancy mood before and during COVID-19 community restrictions among women of low socioeconomic status in New York City: A preliminary study. Arch Womens Ment Health, 2020; 23:779–782.

32.

Silverman

, Burgos

, Rodriguez

, et al. Postpartum mood among universally screened high and low socioeconomic status patients during COVID-19 social restrictions in New York City. Sci Rep, 2020; 10:22380.

33.

Wanberg

, Csillag

, Douglass

, Zhou

, Pollard

. Socioeconomic status and well-being during COVID-19: A resource-based examination. J Appl Psychol, 2020; 105:1382–1396.

34.

Assari

, Lankarani

. Association between stressful life events and depression; intersection of race and gender. J Racial Ethn Health Disparities, 2016; 3:349–356.

35.

Dale

, Safren

. Resilience takes a village: Black women utilize support from their community to foster resilience against multiple adversities. AIDS Care, 2018; 30(sup5):S18–S26.

36.

Balbo

, Billari

, Mills

. Fertility in advanced societies: A review of research: La fécondité dans les sociétés avancées: Un examen des recherches. Eur J Popul, 2013; 29:1–38.

37.

Hashemzadeh

, Shariati

, Mohammad Nazari

, Keramat

. Childbearing intention and its associated factors: A systematic review. Nurs Open, 2021; 8:2354–2368.

38.

Talev

Axios-Ipsos Coronavirus Index: Rich sheltered, poor shafted amid virus: Working status and emotional well-being by socioeconomic group. Axios [Internet], 2020. Available at https://www.axios.com/axios-ipsos-coronavirus-index-rich-sheltered-poor-shafted-9e592100-b8e6-4dcd-aee0-a6516892874b.html Accessed March 23, 2022 .

39.

New York City Department of Health and Mental

Hygiene

, Bureau of Vital

Statistics

, Summary of Vital Statistics (2000–2018). Available at https://data.cccnewyork.org/data/map/48/live-births#48/a/3/85/40/a/a Accessed March 23, 2022 .

40.

, Onyebeke

, Huynh

, et al. Summary of vital statistics, 2018. New York, NY: New York City Department Of Health And Mental Hygiene, Bureau Of Vital Statistics, 2020. Available at https://www1.nyc.gov/assets/doh/downloads/pdf/vs/2018sum.pdf Accessed March 23, 2022 .

41.

Aleligne

, Appiah

, Ebong

. Racial disparities in Coronavirus Disease 2019 (COVID-19) outcomes. Curr Opin Cardiol, 2021; 36:360–366.

42.

Magnan

Social determinants of health 101 for health care: Five plus five. NAM Perspectives. Washington, DC: Discussion Paper, National Academy of Medicine, 2017. https://doi.org/10.31478/201710c

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.13 MB