Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-13T00:46:13.981Z Has data issue: false hasContentIssue false

Association Between Social Determinants of Health, COVID-19 Stressors, and Mental Health Among New York Residents Early in the Pandemic

Published online by Cambridge University Press:  28 October 2024

Alexa Riobueno-Naylor*
Affiliation:
Department of Counseling, Developmental, and Educational Psychology, Lynch School of Education and Human Development, Boston College, Chestnut Hill, MA, USA
Lauren Clay
Affiliation:
Department of Emergency Health Services, University of Maryland Baltimore County, Baltimore, MD, USA
Samantha S. Aubé
Affiliation:
Division of Psychological and Educational Services, Graduate School of Education, Fordham University, New York, NY, USA
Betty S. Lai
Affiliation:
Department of Counseling, Developmental, and Educational Psychology, Lynch School of Education and Human Development, Boston College, Chestnut Hill, MA, USA
*
Corresponding author: Alexa Riobueno-Naylor; Email: ariobuenonaylor@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

Objective

The COVID-19 pandemic is a disaster event. Exposure to stressors during and after disaster events is associated with negative mental health symptoms. To inform targeted COVID-19 recovery efforts, data are needed to understand which stressors play a key role in this relationship.

Methods

Cross-sectional survey data (demographics, impacts of COVID-19, social determinants of health, depression, and anxiety) were collected online from adults living in New York state between May and June 2020. Differences in the proportion of stressors (COVID-19 and social determinants) experienced by race/ethnicity were assessed using chi-square analyses. Logistic regression was used to assess which factors were associated with increased odds of depression and anxiety.

Results

A majority (n = 258, 62.2%) of the 415 respondents reported being directly impacted by the pandemic. Non-white respondents reported a significantly larger proportion of stressors compared to white respondents. Under half of respondents reported depression (n = 171, 41.2%) and anxiety (n = 164, 39.5%). Healthcare and food concerns were associated with increased odds of depression and anxiety, and economic concerns were associated with increased odds of anxiety.

Conclusions

Findings underscore the need to respond to the COVID-19 mental health crisis by addressing social determinants of health.

Type
Original Research
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Society for Disaster Medicine and Public Health, Inc.

The coronavirus disease 2019 (COVID-19) pandemic has contributed to increased rates of depression and anxiety. Through nationally representative survey and community-based research, rates of depression for US adults during the pandemic have been between 20 and 40%, compared to pre-pandemic rates of 3 to 4%.Reference Ettman, Abdalla and Cohen 1 Reference Lakhan, Agrawal and Sharma 5 Similarly, current prevalence rates of adult anxiety in the US are 20 to 45%, compared to pre-pandemic rates of 3 to 10%.Reference Ettman, Abdalla and Cohen 1 Reference Bueno-Notivol, Gracia-García and Olaya 3 It is critical to understand the factors that influence mental health distress during the pandemic in order to design policies and inform clinical practice. This is the focus of the current study.

The COVID-19 pandemic is a disaster event. Disasters are defined as large-scale potentially traumatic events that impact communities.Reference McFarlane, Norris, Norris, Galea, Friedman and Watson 6 Estimates of the prevalence of depression following disasters such as hurricanes and earthquakes range between 5 and 54%, whereas estimates of post-disaster anxiety are between 10 and 50%.Reference Tang, Liu and Liu 7 Reference Beaglehole, Mulder and Frampton 11 Individual-level factors increase risk for developing depression and anxiety symptoms post-disaster. These factors include disaster exposure, female gender, younger or older age (i.e., children and the elderly), minoritized race/ethnicity, low socioeconomic status, family instability, diminished pre-disaster functioning, a lack of psychological coping and resources, and low levels of social support.Reference Goldmann and Galea 12 Reference Srinivasan, Llorente, Magley and Cefalu 21

Despite research evaluating the relationship between disaster exposure and mental health distress, research to date has failed to consistently consider the impact of social determinants of health. This is a shortcoming, as social determinants of health are linked to mental health distress for people and communities.Reference Alegría, NeMoyer and Falgàs Bagué 22 Social determinants of health theories link social positionality, institutional processes, and policies to an unequal distribution of resources that negatively affect health.Reference Lucyk and McLaren 23 Social determinants of health include inequitable contextual and environmental conditions such as poverty, unemployment, housing insecurity, discrimination, racism, neighborhood violence.Reference Bromet 16,22,24 Reference Rhodes, Chan and Paxson 26 These stressors cumulatively and uniquely impact people and communities. For example, daily stressors associated with racism, food insecurity, and housing concerns cumulatively contribute to an increased risk for mental health distress.Reference Alegría, NeMoyer and Falgàs Bagué 22 The inequities perpetuated by social determinants of health also have intergenerational effects given that stressor exposure is linked to factors such as parental stress and community cohesion.Reference Tracy, Norris and Galea 9,27

To develop a more comprehensive understanding of the COVID-19 pandemic’s impact, evaluations of both individual risk factors and social determinants of health, and their impact on mental health, are needed. Individual risk factors including gender identity and personality characteristics have been associated with an increased risk for developing post-traumatic stress due to exposure to pandemic-related stressors.Reference Di Crosta, Palumbo and Marchetti 28Additionally, communities of color and low-income communities have experienced disparate negative effects of the pandemic such as high infection and mortality rates, housing and financial insecurity, and unemployment.Reference Galea, Tracy and Norris 13 Reference Maeda and Oe 15

This paper addresses this gap in the disaster literature by integrating individual risk research with a public health framework to evaluate how contextual factors related to social determinants of health impact individual depression and anxiety symptoms. To guide pandemic-related federal and local aid, more data are needed to understand how stressor exposure differs due to individual and contextual factors. It is unclear which COVID-related stressors or components of social determinants of health are key drivers of the relationship between disaster exposure and mental health.

The current study investigated which COVID-19 and social determinants of health-related stressors were reported within an adult sample, to what degree stressors differed by respondent race/ethnicity, and which stressors were associated with increased odds of depression and anxiety. We expected that ethnically and/or racially minoritized respondents would report a significantly larger proportion of stressors compared to white respondents, and that the presence of COVID-19 and social determinants of health-related stressors would be associated with higher odds of depression and anxiety.

Methods

Participants and Procedures

This study was reviewed and approved as Exempt by the Institutional Review Board at [omitted for review]. Using quotas, a purposive sample of adults (18+ years) residing in New York state with increased risk for COVID-19 was recruited online between May and June 2020 by Qualtrics.Reference Clay and Rogus 29 The goal was to recruit approximately 500 participants. The New York City metropolitan area was excluded because the experience and context differed from the rest of the state due to its population density and the impact of the early pandemic surge in COVID-19 cases on infrastructure including health care.Reference Axelson 30 32 The 415 participants were classified into four quotas with target sample proportions: Black or African American (50%), Hispanic (50%), 2019 income below $25,000 or high school education or less (50%), and male (50%). Participants consented to participating before completing the survey. Survey participants were required to answer all questions, consistent with Qualtrics recommendations for survey panels. Poor quality responses (e.g., straight lining, gibberish, and nonsense answers) were removed.Reference Miller, Guidry and Dahman 33

Demographics (gender identity, 2019 income, age, education, and race/ethnicity), COVID-19 impacts, social determinants of health, and mental health were self-reported. COVID-19 impact questions were adapted from the National Institute of Environmental Health Sciences Disaster Research Response COVID-19 initiative, the PhenX Toolkit COVID-19 Protocol Library, and the COVID-19 and Social Determinants of Health Instrument Repository.Reference Clay 34 37 Early in the pandemic, these were the best available sources of questions to support replication and consistency across studies and facilitate rapid data collection efforts.

COVID-19-related stressors

Pandemic-related stressors assessed included participant health risk, direct impacts of the COVID-19 pandemic (direct impacts), and COVID-19’s impact on the respondent (self-impacts). Health risk was assessed by asking participants about 1) whether they experienced at least one of the following pre-existing health concerns: cancer, chronic respiratory disease like asthma or chronic obstructive pulmonary disease, hypertension or high blood pressure, heart disease, cerebrovascular disease, gastrointestinal disease, rheumatoid disorder, diabetes, or other health disorder; 2) whether they were above 65 years; and 3) whether they were an essential worker (e.g., health care and grocery workers). Participants were classified as having health risk during the pandemic if they endorsed any of these three conditions.

Direct COVID-19 impacts were assessed by summing dichotomous (yes/no) responses to the following questions: the respondent 1) knew someone who tested positive for COVID-19, 2) knew someone who was quarantined, 3) knew someone who had been hospitalized, or 4) knew someone who died due to COVID-19. Self-impacts were assessed by summing variables indicating whether respondents had 1) tested positive, 2) quarantined, or 3) been hospitalized due to COVID-19 (yes/no). Direct and self-impacts were summed to indicate whether the respondent experienced 0 to 4 and 0 to 3 impacts, respectively, and coded dichotomously to indicate presence of at least one direct or self-impact.

Social determinants of health-related stressors

Economic concerns were assessed by asking participants whether they experienced 1) reduced work due to job loss, furlough, or reduced hours using a yes/no response scale, and concerns about 2) job security, 3) debt, 4) affording mortgage or rent, and 5) retirement or savings, using a 4-point Likert scale (never, sometimes, most of the time, always). For each of the 4 economic concerns answered using the Likert scale, participants were classified as never or ever (sometimes, most of the time, always) concerned. Economic concerns were summed to indicate whether the respondent experienced 0 to 5 stressors and were also coded dichotomously to indicate presence of at least one economic stressor.

Food and childcare concerns were evaluated using a 4-point Likert scale (never, sometimes, most of the time, always) to assess how often respondents were concerned about 1) being able to afford enough food, 2) finding the foods their household wanted or needed, 3) finding quality foods, 4) not being able to get food through a food pantry, 5) not being able to get meals through a community meal program, and 6) childcare access.Reference Niles, Neff and Biehl 38 For each concern, participants were classified as never or ever (sometimes, most of the time, always) concerned. Food concerns were summed to indicate whether the respondent experienced 0 to 5 concerns and were also coded dichotomously to indicate presence of at least one stressor. Childcare concerns were assessed dichotomously to capture whether respondents never or sometimes, most of the time, or always experienced concerns.

Healthcare concerns assessed included 1) health insurance (insured or uninsured), 2) concerns about health care access during the pandemic (never, sometimes, most of the time, always), and 3) concerns about medical expenses during the pandemic (never, sometimes, most of the time, always). Participants were classified as never or ever (sometimes, most of the time, always) concerned about health care access and medical expenses. Healthcare concerns were summed to indicate whether the respondent experienced 0 to 3 health care-related stressors and were also coded dichotomously to indicate presence of at least one stressor.

Mental health

Depression was assessed using the Patient Health Questionnaire-2 (PHQ-2), a validated screener for Major Depressive Disorder. Items assessed loss of interest or pleasure and feeling down or depressed. Anxiety symptoms were assessed using the Generalized Anxiety Disorder-2 (GAD-2), a validated screener for Generalized Anxiety Disorder.Reference Kroenke, Spitzer and Williams 39 Questions asked about feelings of nervousness, anxiety, and not being able to control or stop worrying. All questions were answered on a 4-point Likert scale (“Not at all”= 0; “Several days”= 1; “More than half the days”= 2; “Nearly every day”= 3). Potential scores for each screen ranged from 0 to 6. Scores for each screen were summed, and a cut point of 3 was used to identify cases with likely anxiety (86% sensitivity, 83% specificity)Reference Niles, Neff and Biehl 38 or depression (83% sensitivity, 92% specificity).Reference Kroenke, Spitzer and Williams 40

Statistical Analysis

Analyses were conducted with SPSS Statistics (Version 27). Descriptive statistics for demographics (gender identity, income, age, and education) were calculated. Next, chi-square analyses evaluated racial/ethnic differences (non-Hispanic white vs. Hispanic vs. non-Hispanic/ non-white) in COVID-19 impacts, social determinants of health-related stressors (concerns about economics, health care, food, child care), and mental health (depression and anxiety). Chi-square analyses also evaluated differences in COVID-19 impacts and social determinants of health-related stressors by categorical mental health outcomes. Two simultaneous logistic regression analyses assessed the association between COVID-19 impacts and social determinants of health-related stressors and depression and anxiety. Within the models, COVID-19 health risk, direct impacts, and self-impacts, as well as economic concerns, health care concerns, and food concerns, were evaluated continuously. Race/ethnicity and gender identity were dummy coded with non-Hispanic white and males as the identified groups, respectively, given evidence suggesting that non-white individuals and non-cisgender males are at higher risk for developing anxiety and depression.Reference Strine, Mokdad and Balluz 41 Analyses were assessed using an alpha level of 0.05.

Results

Sample Characteristics (Table 1)

A total of 415 people completed the full survey with quality responses. Respondents identified as non-Hispanic white (n = 90, 21.7%), Hispanic (n = 182, 43.9%), and non-Hispanic/non-white (n = 143, 34.5%). A majority (n = 230, 55.4%) of respondents identified as non-male (female: n = 230, 55.4%; other gender: n = 5, 1.3%), whereas 43.4% (n = 180) identified as male. The most commonly reported household income (n = 106, 25.5%) was between $25,000 and $49,000. The largest proportion of those in the lowest income bracket were Hispanic (n = 42, 56.8%), compared to non-Hispanic white (n = 4, 5.4%) and non-Hispanic/non-white (n = 28, 37.8%; p =.002). A majority of the sample was below the age of 44 (n = 128, 30.8%, ages 18-24, and n = 155, 37.4%, ages 25-44). Non-Hispanic white participants had the largest proportion of ages 65+ (n = 27, 61.4%) compared to Hispanic (n = 7, 15.9%) and non-Hispanic/non-white respondents (n = 10, 22.7%; p <.001). Under half of respondents (n = 126, 30.4%) reported earning a bachelor’s or graduate degree, whereas 31.6% (n = 131) reported a high school or less than a high school education.

Table 1. Sample demographics of New York state residents with completed measures in May to June 2020 by race/ethnicity (N = 415)

Note: Chi-square tests of independence compared the proportion of non-Hispanic white, Hispanic, and non-white/non-Hispanic respondents represented in each demographic category.

*p<.05; **p<.01; ***p<.001.

a Gender identity response options included male, female, transgender, non-binary, and other.

b A total of 90 participants (21.7%) reported non-Hispanic white race/ethnicity.

c Hispanic respondents (n = 182) reported the following races: white (n = 52, 39.0%), Black/African American (n = 55, 30.2%), other races (n = 52, 28.6%), and Asian or Pacific Islander (n = 14, 7.7%).

d Non-white/non-Hispanic respondents (n = 143) identified their race as Black or African American (n = 129, 90.2%), Asian or Pacific Islander (n = 8, 5.6%), and other (n = 6, 4.2%).

COVID-19 and Social Determinants of Health-Related Stressors by Race/Ethnicity (Table 2)

Over half (n = 258, 62.2%) of the sample (N = 415) reported direct COVID-19 impacts, whereas 20.2% (n = 84) reported self-impacts. Over half (n = 264, 63.3%) reported health risks for COVID-19 due to a health condition (n = 147, 35.4%), older age (n = 44, 10.6%), or being an essential worker (n = 151, 36.4%). The most frequently reported stressors included concerns about finding wanted or needed food (n = 296, 71.3%), finding the quality of food that was needed (n = 292, 70.4%), health care access (n = 276, 66.5%), job security (n = 269, 64.8%), and debt (n = 269, 64.8%). Of the 208 respondents who indicated having at least one child under the age of 18, 59.1% (n = 123) reported childcare concerns. Hispanic and non-Hispanic/non-white respondents reported a significantly larger proportion of stressors compared to non-Hispanic white respondents across all COVID-19 impacts and social determinants of health stressor categories. No significant differences emerged in rates of depression or anxiety across racial/ethnic groups.

Table 2. COVID-19 and social determinants of health-related stressors and mental health by race/ethnicity (N = 415)

Note: Chi-square tests of independence compared the proportion of non-Hispanic white, Hispanic, and non-white/non-Hispanic respondents represented in each COVID-19 impact, social determinant of health, or mental health category.

* p<.05, **p<.01, ***p<.001.

a Includes the 208 respondents who indicated having at least 1 child under the age of 18 in the home.

COVID-19 Stressors, Social Determinants of Health-Related Stressors, and Mental Health Symptoms (Table 3)

A total of 132 (31.8%) respondents reported symptoms of depression, 164 (39.5%) reported symptoms of anxiety, and 132 (31.8%) reported both. A significantly larger proportion of respondents who reported depression reported direct COVID-19 impacts and concerns about job security, debt, mortgage/rent payments, retirement, health care access, medical expenses, affording food, accessing as much food as wanted/needed, accessing quality food, accessing food pantries, and accessing community meals, compared to respondents who did not report depression symptoms. A significantly larger proportion of respondents with anxiety reported direct COVID-19 impacts and concerns about reduced work, job security, debt, mortgage/rent payments, retirement, health care access, medical expenses, affording food, accessing as much food as wanted/needed, accessing quality food, accessing food pantries, and accessing community meals, compared to respondents who did not report anxiety symptoms.

Table 3. COVID-19 and social determinants of health-related stressors and mental health (N = 415)

Note: Chi-square tests of independence compared the proportion of respondents with versus without depression and anxiety in each COVID-19 impact and social determinant of health category.

*p<.05, **p<.01, ***p<.001.

a Includes the 208 respondents who indicated having at least 1 child under the age of 18 in the home; total N with anxiety = 99; total N without anxiety = 99; total N with depression = 102; total N without depression = 106.

Table 4. COVID-19 and social determinants of health-related stressors associated with depression and anxiety (N = 415)

Note: Two simultaneous logistic regression analyses were run (one depression model and one anxiety model).

a Health risk (range: 0-3); direct impacts (range: 0-4); self-impacts (range: 0-3); economic concerns (range: 0-5); healthcare concerns (range: 0-3); food concerns (range: 0-5); non-male (male vs. non-male [female and other]); race/ethnicity (non-Hispanic white vs. other).

COVID-19 and Social Determinants of Health-Related Stressors Associated with Depression and Anxiety (Table 4)

Healthcare concerns were significantly associated with depression and anxiety (depression: odds ratio [OR] = 1.42, 95% confidence interval [CI] = 1.08-1.90; anxiety: OR = 1.43, 95% CI = 1.08-1.90). Food concerns were significantly associated with depression and anxiety (depression: OR = 1.34, 95% CI = 1.15–1.55; anxiety: OR = 1.31, 95% CI = 1.12–1.52). Economic concerns were significantly associated with anxiety only (OR = 1.20, 95% CI = 1.02–1.41; Table 3). Non-male gender identity (female and other) was significantly associated with higher odds of depression and anxiety (depression: 1.99, 95% CI = 1.28-3.11; anxiety: 2.06, 95% CI = 1.31–3.27).

Discussion

This study evaluated the association between COVID-19 impacts, social determinants of health, and symptoms of depression and anxiety among adults during the initial months of the pandemic. Findings indicate that pandemic and social determinants of health-related stressors were associated with increased odds of depression and anxiety. Non-male gender identity and health care, food, and economic concerns were associated with increased odds of mental health symptoms. These findings align with the social and economic realities of the pandemic, including an overburdened global health care system,Reference Papoutsi, Giannakoulis and Ntella 42 food supply chain disruptions,Reference Tasnim 43 and economic turmoil and job loss.Reference Montenovo, Jiang and Lozano Rojas 44

Due to the pandemic and its economic and psychological burden on the health care system and workers, people seeking out non–COVID-19 related health care have experienced negative effects on care, including delays in treatment and medication shortages.Reference Kaye, Okeagu and Pham 45 , Reference Chudasama, Gillies and Zaccardi 46 Regarding food insecurity, worker shortages and the closure of food production facilitiesReference Aday and Aday 47 have led to disruptions in daily food supplies.Reference Hobbs 48 Additionally, the significant impact of the pandemic on the economy has placed millions out of work.Reference Monte 49 Parents and people in hospitality and service jobs have been particularly affected by unemployment.Reference Albanesi and Kim 50

In this study, a significantly larger proportion of Hispanic and non-Hispanic/non-white respondents experienced COVID-19 and social determinants of health-related stressors compared to non-Hispanic white respondents. These findings are consistent with data indicating that communities of color are disproportionately negatively affected by disaster eventsReference Davies, Haugo and Robertson 51 including the COVID-19 pandemic.Reference Lai, Hoskova and Riobueno-Naylor 52 , 53 Data have indicated that in the United States, Black and Hispanic adults have been more likely to both test positive for COVID-19 and die from the virus.Reference Rentsch, Kidwai-Khan and Tate 54 , Reference Gross, Essien and Pasha 55 Black and Hispanic adults have also been found to be experiencing depression, suicidal ideation, and substance use at significantly higher rates than white adults during the pandemic.Reference McKnight-Eily, Okoro and Strine 56 These findings underscore the importance of assessing how structural inequalities and individual-level risk and resilience factors impact the immediate and long-term physical and mental health of communities of color within the context of disaster events.Reference Rentsch, Kidwai-Khan and Tate 54 , Reference Gross, Essien and Pasha 55 , Reference Eriksson, Ghazinour and Hammarström 57 , Reference Brofenbrenner, Morris, Damon and Lerner 58

Although Hispanic and non-Hispanic/non-white respondents reported a larger proportion of stressors, they did not report higher proportions of depression and anxiety compared to non-Hispanic white respondents. In addition, minoritized race/ethnicity was not associated with increased odds of depression or anxiety. These findings may be consistent with research indicating that immigrants, including Hispanic immigrants, demonstrate fewer clinically significant mental health problems compared to non-immigrant adults due to the protective factors of family collectivism, social support, and religiosity.Reference Gallo, Penedo and Espinosa de los Monteros 59 Given that the current study did not ask respondents to indicate whether they identified as immigrants, future studies that include questions about immigrant identification would aid in further evaluating this issue.

Limitations

Although this study has many strengths, including sample diversity and survey timing, several limitations should be considered. The study focused on a restricted geographic area, which limits the generalizability of findings. In addition, the COVID-19 stressor measure was not validated due to the timing of data collection. Thus, formal scale evaluation was not conducted to ensure that measures captured the intended domains within the targeted population. Nevertheless, the timeliness of the data is important, given the assessment of early impacts of the pandemic. Finally, due to the number of comparisons made in analyzing the data, the risk for Type I error (falsely rejecting the null hypothesis) was elevated.

Conclusion

The current study found that COVID-19 had significant direct and indirect impacts on individuals even early on in the pandemic, with concerns about food, health care access, job security, and debt being the most frequently reported stressors. Depression and anxiety symptoms were prevalent among participants, with health care and food concerns being significantly associated with both depression and anxiety. In sum, both social determinants of health and COVID-19 stressor exposure were shown to negatively impact individual mental health. In the United States, the mental health needs of the population continue to be inadequately addressed.Reference Vazquez, Islam and Gursky 60 , Reference Pfender 61 Researchers, policy-makers, and health care providers must take individual and structural approaches to tailoring mental health care to the needs of the population in the aftermath of the pandemic. Institutional resources, such as community health centers and schools, may be key to supporting the mental health of people and communities affected by the pandemic.

Competing interest

The authors declare none.

Author contribution

The authors confirm contribution to the paper as follows: study conception and design: LC; data collection: LC; analysis and interpretation of results: LC, BSL, ARN; SSA; draft manuscript preparation: ARN, LC, BSL, SSA. All authors reviewed the results and approved the final version of the manuscript.

Funding statement

None.

References

Ettman, CK, Abdalla, SM, Cohen, GH, et al. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open. 2020;3(9):e2019686. doi:10.1001/jamanetworkopen.2020.19686CrossRefGoogle ScholarPubMed
Kessler, RC, Meron Ruscio, A, Shear, K, et al. Epidemiology of anxiety disorders. In: Stein, MB, Steckler, T, eds. Behavioral Neurobiology of Anxiety and Its Treatment. Springer; 2009:2135.CrossRefGoogle Scholar
Bueno-Notivol, J, Gracia-García, P, Olaya, B, et al. Prevalence of depression during the COVID-19 outbreak: a meta-analysis of community-based studies. Int J Clin Health Psychol. 2021;21(1):100196.CrossRefGoogle ScholarPubMed
Liu, CH, Zhang, E, Wong, GTF, et al. Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: clinical implications for U.S. young adult mental health. Psychiatry Res. 2020;290:113172.CrossRefGoogle ScholarPubMed
Lakhan, R, Agrawal, A, Sharma, M. Prevalence of depression, anxiety, and stress during COVID-19 pandemic. J Neurosci Rural Pract. 2020;11(4):519525.CrossRefGoogle ScholarPubMed
McFarlane, AC, Norris, FH. Definitions and concepts in disaster research. In: Norris, FH, Galea, S, Friedman, MJ, Watson, PJ, eds. Methods for Disaster Mental Health Research. The Guilford Press; 2006:319.Google Scholar
Tang, B, Liu, X, Liu, Y, et al. A meta-analysis of risk factors for depression in adults and children after natural disasters. BMC Public Health. 2014;14(1):623. doi:10.1186/1471-2458-14-623CrossRefGoogle Scholar
Chan, CLW, Wang, C-W, Ho, AHY, et al. Symptoms of posttraumatic stress disorder and depression among bereaved and non-bereaved survivors following the 2008 Sichuan earthquake. J Anxiety Disord. 2012;26(6):673679.CrossRefGoogle ScholarPubMed
Tracy, M, Norris, FH, Galea, S. Differences in the determinants of posttraumatic stress disorder and depression after a mass traumatic event. Depress Anxiety. 2011;28(8):666675.CrossRefGoogle ScholarPubMed
Warsini, S, West, C, Ed (TT), GD, et al. The psychosocial impact of natural disasters among adult survivors: an integrative review. Issues Ment Health Nurs. 2014;35(6):420436.CrossRefGoogle Scholar
Beaglehole, B, Mulder, RT, Frampton, CM, et al. Psychological distress and psychiatric disorder after natural disasters: systematic review and meta-analysis. Br J Psychiatry. 2018;213(6):716722.CrossRefGoogle Scholar
Goldmann, E, Galea, S. Mental health consequences of disasters. Annu Rev Public Health. 2014;35(1):169183.CrossRefGoogle ScholarPubMed
Galea, S, Tracy, M, Norris, F, et al. Financial and social circumstances and the incidence and course of PTSD in Mississippi during the first two years after hurricane Katrina. J Trauma Stress. 2008;21(4):357368.CrossRefGoogle ScholarPubMed
Boscarino, JA, Hoffman, SN, Adams, RE, et al. Mental health outcomes among vulnerable residents after hurricane Sandy: implications for disaster research and planning. Am J Disaster Med. 2014;9(2):97106.CrossRefGoogle ScholarPubMed
Maeda, M, Oe, M. Mental health consequences and social issues after the Fukushima disaster. Asia Pac J Public Health. 2017;29(2_suppl):36S-46S.CrossRefGoogle Scholar
Bromet, EJ. Mental health consequences of the Chernobyl disaster. J Radiol Prot. 2012;32(1):N71N75.CrossRefGoogle ScholarPubMed
Norris, FH, Elrod, CL. Psychosocial consequences of disaster: a review of past research. In: Methods for Disaster Mental Health Research. The Guilford Press; 2006:2042.Google Scholar
Galea, S, Brewin, CR, Gruber, M, et al. Exposure to hurricane-related stressors and mental illness after hurricane Katrina. Arch Gen Psychiatry. 2007;64(12):14271434.CrossRefGoogle ScholarPubMed
Leon, GR. Overview of the psychosocial impact of disasters. Prehospital Disaster Med. 2004;19(1):49.CrossRefGoogle ScholarPubMed
Farooqi, Y, Habib, M. Gender differences in anxiety, depression and stress among survivors of suicide bombing. Pak J Soc Clin Psychol. 2010;8(2):145153.Google Scholar
Srinivasan, S, Llorente, MD, Magley, M. Mental health consequences of disaster exposure in older adults. In: Cefalu, CA, ed. Disaster Preparedness for Seniors: A Comprehensive Guide for Healthcare Professionals. Springer; 2014:311327.CrossRefGoogle Scholar
Alegría, M, NeMoyer, A, Falgàs Bagué, I, et al. Social determinants of mental health: where we are and where we need to go. Curr Psychiatry Rep. 2018;20(11):95.CrossRefGoogle ScholarPubMed
Lucyk, K, McLaren, L. Taking stock of the social determinants of health: a scoping review. PLOS ONE. 2017;12(5):e0177306. doi:10.1371/journal.pone.0177306CrossRefGoogle ScholarPubMed
Social Determinants of Health. Office of Disease Prevention and Health Promotion. Healthy People 2030. Accessed April 1, 2021. https://health.gov/healthypeople/objectives-and-data/social-determinants-healthGoogle Scholar
Nandi, A, Tracy, M, Beard, JR, et al. Patterns and predictors of trajectories of depression after an urban disaster. Ann Epidemiol. 2009;19(11):761770.CrossRefGoogle Scholar
Rhodes, J, Chan, C, Paxson, C, et al. The impact of hurricane Katrina on the mental and physical health of low-income parents in New Orleans. Am J Orthopsychiatry. 2010;80(2):237247.CrossRefGoogle ScholarPubMed
Bergstrand, K, Mayer, B.The community helped me”: community cohesion and environmental concerns in personal assessments of post-disaster recovery. Soc Nat Resour. 2020;33(3):386405.CrossRefGoogle ScholarPubMed
Di Crosta, A, Palumbo, R, Marchetti, D, et al. Individual differences, economic stability, and fear of contagion as risk factors for PTSD symptoms in the COVID-19 emergency. Front Psychol. 2020;11. doi:10.3389/fpsyg.2020.567367CrossRefGoogle Scholar
Clay, LA, Rogus, S. Primary and secondary health impacts of COVID-19 among minority individuals in New York state. Int J Environ Res Public Health. 2021;18(2):683. doi:10.3390/ijerph18020683CrossRefGoogle ScholarPubMed
Axelson, B. Coronavirus Timeline: How Gov. Cuomo Has Responded to Pandemic Since January. Syracuse.com. Published April 14, 2020. Accessed October 5, 2021. https://www.syracuse.com/coronavirus/2020/04/coronavirus-timeline-in-ny-heres-how-gov-cuomo-has-responded-to-covid-19-pandemic-since-january.htmlGoogle Scholar
Lieberman-Cribbin, W, Tuminello, S, Flores, RM, et al. Disparities in COVID-19 testing and positivity in New York City. Am J Prev Med. 2020;59(3):326332.CrossRefGoogle ScholarPubMed
Workbook: NYS-COVID19-Tracker. New York State Department of Health COVID-19 Tracker. NY State Department of Health. Published 2021. Accessed October 5, 2021. https://covid19tracker.health.ny.gov/views/NYS-COVID19-Tracker/NYSDOHCOVID-19Tracker-Fatalities?%3Aembed=yes&%3Atoolbar=no&%3Atabs=nGoogle Scholar
Miller, CA, Guidry, JPD, Dahman, B, et al. A tale of two diverse qualtrics samples: information for online survey researchers. Cancer Epidemiol Prev Biomark. 2020;29(4):731735.CrossRefGoogle ScholarPubMed
Clay, L. Disaster Research Response (DR2) Resources Portal Resource Details: COVID-19 & Social Determinants of Health Data Collection Instrument Repository. National Institute of Environmental Health Sciences. Published March 1, 2020. Accessed October 28, 2021. https://tools.niehs.nih.gov/dr2/index.cfm/resource/24230Google Scholar
Clay, L. COVID-19 & social determinants of health data collection instrument repository. DesignSafe. doi:10.17603/ds2-nay0-j518CrossRefGoogle Scholar
Disaster Research Response (DR2) Resources Portal. National Institute for Environmental Health Sciences. Published October 17, 2024 Accessed October 28, 2021. https://tools.niehs.nih.gov/dr2/index.cfm/main/search/#/params?selectedFacets=EXP_BIO_VI_COV&searchTerm=Google Scholar
COVID-19 Protocols. PhenX Toolkit. Published June 21, 2023. Accessed June 16, 2020. https://www.phenxtoolkit.org/covid19/Google Scholar
Niles, MT, Neff, R, Biehl, E, et al. Food access and security during coronavirus: A Vermont Study. University of Vermont College of Agriculture and Life SciencesFaculty Publications. Published April, 2020. Accessed June 16, 2021. https://scholarworks.uvm.edu/calsfac/21Google Scholar
Kroenke, K, Spitzer, RL, Williams, JBW, et al. Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Ann Intern Med. 2007;146(5):317325.CrossRefGoogle ScholarPubMed
Kroenke, K, Spitzer, RL, Williams, JBW. The patient health questionnaire-2: validity of a two-item depression screener. Med Care. 2003;41(11):12841292.CrossRefGoogle Scholar
Strine, TW, Mokdad, AH, Balluz, LS, et al. Depression and anxiety in the United States: findings from the 2006 Behavioral Risk Factor Surveillance System. Psychiatr Serv. 2008;59(12):13831390. doi:10.1176/ps.2008.59.12.1383CrossRefGoogle ScholarPubMed
Papoutsi, E, Giannakoulis, VG, Ntella, V, et al. Global burden of COVID-19 pandemic on health care workers | European Respiratory Society. ERJ Open Res. 2020;6. doi:10.1183/23120541.00195-2020CrossRefGoogle Scholar
Montenovo, L, Jiang, X, Lozano Rojas, F, et al. Determinants of disparities in Covid-19 job losses. Natl Bur Econ Res Work Pap Ser. 2020;(w27132). doi:10.3386/w27132CrossRefGoogle Scholar
Kaye, AD, Okeagu, CN, Pham, AD, et al. Economic impact of COVID-19 pandemic on health care facilities and systems: international perspectives. Best Pract Res Clin Anaesthesiol. 2021;35(3):293306.CrossRefGoogle ScholarPubMed
Chudasama, YV, Gillies, CL, Zaccardi, F, et al. Impact of COVID-19 on routine care for chronic diseases: a global survey of views from health care professionals. Diabetes Metab Syndr Clin Res Rev. 2020;14(5):965967.CrossRefGoogle Scholar
Aday, S, Aday, MS. Impact of COVID-19 on the food supply chain. Food Qual Saf. 2020;4(4):167180.CrossRefGoogle Scholar
Hobbs, JE. Food supply chains during the COVID-19 pandemic. Can J Agric Econ Can Agroeconomie. 2020;68(2):171176.CrossRefGoogle Scholar
Monte, LM. Historical Look at Unemployment, Sectors Shows Magnitude of COVID-19 Impact on Economy. United States Census Bureau. Published March 15, 2021. Accessed October 28, 2021. https://www.census.gov/library/stories/2021/03/putting-economic-impact-of-pandemic-in-context.htmlGoogle Scholar
Albanesi, S, Kim, J. Effects of the COVID-19 recession on the US labor market: occupation, family, and gender. J Econ Perspect. 2021;35(3):324.CrossRefGoogle Scholar
Davies, IP, Haugo, RD, Robertson, JC, et al. The unequal vulnerability of communities of color to wildfire. PLOS ONE. 2018;13(11):e0205825. doi:10.1371/journal.pone.0205825CrossRefGoogle ScholarPubMed
Lai, B, Hoskova, B, Riobueno-Naylor, A, et al. College students and COVID-19: mental health and purpose formation. J Emerg Manag. 2022;20(9). doi:10.5055/jem.0609Google Scholar
Introduction to COVID-19 Racial and Ethnic Health Disparities. Centers for Disease Control and Prevention. Published December 10, 2020. Accessed October 28, 2021. https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/racial-ethnic-disparities/index.htmlGoogle Scholar
Rentsch, CT, Kidwai-Khan, F, Tate, JP, et al. Covid-19 by race and ethnicity: a national cohort study of 6 million United States veterans. Preprint. medRxiv. 2020:2020.05.12.20099135. doi:10.1101/2020.05.12.20099135CrossRefGoogle Scholar
Gross, CP, Essien, UR, Pasha, S, et al. Racial and ethnic disparities in population-level Covid-19 mortality. J Gen Intern Med. 2020;35(10):30973099.CrossRefGoogle ScholarPubMed
McKnight-Eily, LR, Okoro, CA, Strine, TW, 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. Morb Mortal Wkly Rep. 2021;70(5):162166.CrossRefGoogle ScholarPubMed
Eriksson, M, Ghazinour, M, Hammarström, A. Different uses of Bronfenbrenner’s ecological theory in public mental health research: what is their value for guiding public mental health policy and practice? Soc Theory Health. 2018;16(4):414433.CrossRefGoogle Scholar
Brofenbrenner, U, Morris, PA. The ecology of developmental processes. In: Damon, W, Lerner, RM, eds. Handbook of Child Psychology: Theoretical Models of Human Development. Wiley; 1998:9931028.Google Scholar
Gallo, LC, Penedo, FJ, Espinosa de los Monteros, K, et al. Resiliency in the face of disadvantage: do Hispanic cultural characteristics protect health outcomes? J Pers. 2009;77(6):17071746.CrossRefGoogle ScholarPubMed
Vazquez, J, Islam, T, Gursky, J, et al. Access to care matters: remote health care needs during COVID-19. Telemed E-Health. 2021;27(4):468471.CrossRefGoogle Scholar
Pfender, E. Mental health and COVID-19: implications for the future of telehealth. J Patient Exp. 2020;7(4):433435.CrossRefGoogle Scholar
Figure 0

Table 1. Sample demographics of New York state residents with completed measures in May to June 2020 by race/ethnicity (N = 415)

Figure 1

Table 2. COVID-19 and social determinants of health-related stressors and mental health by race/ethnicity (N = 415)

Figure 2

Table 3. COVID-19 and social determinants of health-related stressors and mental health (N = 415)

Figure 3

Table 4. COVID-19 and social determinants of health-related stressors associated with depression and anxiety (N = 415)