PCD logo

Prevalence of Chronic Diseases, Depression, and Stress Among US Childcare Professionals During the COVID-19 Pandemic

Jad A. Elharake, MPH1,2; Mehr Shafiq, MPH2,3; Ayse Cobanoglu, PhD4; Amyn A. Malik, PhD, MBBS, MPH1,2; Madeline Klotz, BA5; John Eric Humphries, PhD6; Thomas Murray, MD, PhD7; Kavin M. Patel, MD1; David Wilkinson, JD8; Inci Yildirim, MD, PhD, MSc2,7,9; Rachel Diaz, BA8; Rosalia Rojas, BA4; Anael Kuperwajs Cohen, BA4; Aiden Lee6; Saad B. Omer, PhD, MBBS, MPH1,2,9,10; Walter S. Gilliam, PhD4 (View author affiliations)

Suggested citation for this article: Elharake JA, Shafiq M, Cobanoglu A, Malik AA, Klotz M, Humphries JE, et al. Prevalence of Chronic Diseases, Depression, and Stress Among US Childcare Professionals During the COVID-19 Pandemic. Prev Chronic Dis 2022;19:220132. DOI: http://dx.doi.org/10.5888/pcd19.220132.

MEDSCAPE CME

In support of improving patient care, this activity has been planned and implemented by Medscape, LLC and Preventing Chronic Disease. Medscape, LLC is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC), to provide continuing education for the healthcare team.

Medscape, LLC designates this Journal-based CME activity for a maximum of 1.00 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Joint Accredited Provider Interprofessional Continuing Education

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to 1.0 MOC points in the American Board of Internal Medicine’s (ABIM) Maintenance of Certification (MOC) program. Participants will earn MOC points equivalent to the amount of CME credits claimed for the activity. It is the CME activity provider’s responsibility to submit participant completion information to ACCME for the purpose of granting ABIM MOC credit.

Release date: September 22, 2022; Expiration date: September 22, 2023

Learning Objectives

Upon completion of this activity, participants will be able to:

  1. Assess common chronic illnesses among US childcare professionals
  2. Distinguish racial/ethnic groups at higher risk for chronic illness among US childcare professionals
  3. Distinguish the rate of positive screening for depression among US childcare professionals
  4. Evaluate variables associated with higher stress among US childcare professionals

EDITOR

Ellen Taratus, MS

Senior Editor

Preventing Chronic Disease

Atlanta, GA

CME AUTHOR

Charles P. Vega, MD

Health Sciences Clinical Professor of Family Medicine

University of California, Irvine School of Medicine

Charles P. Vega, MD, has the following relevant financial relationships:

Consultant or advisor for: GlaxoSmithKline; Johnson & Johnson Pharmaceutical Research & Development, LLC

AUTHORS

Jad A. Elharake, MPH

Yale School of Medicine, New Haven, CT; Yale Institute for Global Health, New Haven, CT

Mehr Shafiq, MPH

Yale Institute for Global Health, New Haven, CT; Mailman School of Public Health, Columbia University, New York, NY

Ayse Cobanoglu, PhD

Yale Child Study Center, Yale School of Medicine, New Haven, CT

Amyn A. Malik, PhD, MBBS, MPH

Yale School of Medicine, New Haven, CT; Yale Institute for Global Health, New Haven, CT

Madeline Klotz, BA

Human Development and Family Studies, Michigan State University, East Lansing, MI

John Eric Humphries, PhD

Department of Economics, Yale University, New Haven, CT

Thomas Murray, MD, PhD

Department of Pediatrics, Yale School of Medicine, New Haven, CT

Kavin M. Patel, MD

Yale School of Medicine, New Haven, CT

David Wilkinson, JD

Tobin Center for Economic Policy, Yale University, New Haven, CT

Inci Yildirim, MD, PhD, MSc

Yale Institute for Global Health, New Haven, CT; Department of Pediatrics, Yale School of Medicine, New Haven, CT

Rachel Diaz, BA

Tobin Center for Economic Policy, Yale University, New Haven, CT

Rosalia Rojas, BA

Yale Child Study Center, Yale School of Medicine, New Haven, CT

Anael Kuperwajs Cohen, BA

Yale Child Study Center, Yale School of Medicine, New Haven, CT

Aiden Lee

Department of Economics, Yale University, New Haven, CT

Saad B. Omer, MBBS, MPH, PhD

Yale School of Medicine, New Haven, CT; Yale Institute for Global Health, New Haven, CT; Yale School of Public Health, New Haven, CT; Yale School of Nursing, New Haven, CT

Walter S. Gilliam, PhD

Yale Child Study Center, Yale School of Medicine, New Haven, CT

PEER REVIEWED

Summary

What is already known on this topic?

No national research has been published on the physical or mental health of childcare professionals during the COVID-19 pandemic.

What is added by this report?

Childcare professionals had a higher rate of depression during the pandemic than before the pandemic; rates of asthma, depression, and stress were greater among childcare professionals than among US adults overall during the pandemic. We found disparities in chronic disease rates by race, ethnicity, and sex/gender.

What are the implications for public health practice?

Efforts should be directed toward developing effective and scalable interventions for improving the physical and mental health of childcare professionals and addressing stressors that may undermine their well-being.

Abstract

Introduction

Given their central role in supporting children’s development, childcare professionals’ overall physical and mental health is important. We evaluated the prevalence of chronic diseases, depression, and stress levels during the COVID-19 pandemic among US childcare professionals.

Methods

Data were obtained from US childcare professionals (N = 81,682) through an online survey from May 22, 2020, through June 8, 2020. We used multivariable logistic and linear regression models to assess the association of sociodemographic characteristics with 4 physical health conditions (asthma, heart disease, diabetes, and obesity), depression, and stress weighted to national representativeness.

Results

For physical health conditions, 14.3% (n = 11,717) reported moderate to severe asthma, 6.5% (n = 5,317) diabetes, 4.9% (n = 3,971) heart disease, and 19.8% (n = 16,207) obesity. For mental health, 45.7% (n = 37,376) screened positive for depression and 66.5% (n = 54,381) reported moderate to high stress levels. Race, ethnicity, and sex/gender disparities were found for physical health conditions but not mental health of childcare professionals during the COVID-19 pandemic.

Conclusion

Our findings highlighted that childcare professionals’ depression rates during the pandemic were higher than before the pandemic, and depression, stress, and asthma rates were higher than rates among US adults overall during the pandemic. Given the essential work childcare professionals provided during the pandemic, policy makers and public health officials should consider what can be done to support their physical and mental health.

Top

Introduction

Approximately 1.1 million paid and registered childcare professionals in the US provide care for 10 million children in center-based and home-based settings (1). Childcare professionals (eg, childcare center workers, family childcare providers, nannies) make up a socially vulnerable workforce (2). As of 2019, this workforce consisted largely of women (94%) and in many childcare sectors, members of racial and ethnic minority groups (40%), immigrants (22%), and low-income individuals (average salary of $16,443, 67% below the national average) (3,4). Childcare professionals also face challenging work conditions, including long hours and physical and emotional demands (5), leading to staff turnover, absenteeism, poor physical health conditions, high rates of burnout, emotional exhaustion, and mental health problems (6). Additionally, the unpredictability and impact of the COVID-19 pandemic has exacerbated the financial and work-related stress faced by childcare professionals (7).

No national research has been published on the physical or mental health (eg, depression, stress) of childcare professionals during the COVID-19 pandemic. Prepandemic studies on childcare professionals reported a diabetes rate of 7.3% (8), obesity rates ranging from 34% to 66.3% (8–11), and clinical depression rates ranging from 16.0% to 36.1% (11–15). The overall rates among US adult women were 8.7% for diabetes (16), 41.9% for obesity (17), and 9.6% for depression (18) before the pandemic, and 27.8% to 32.8% for depression during the pandemic (19–21). Only 1 study focused on the stress levels of childcare professionals during the pandemic; conducted in Indiana, it found that 63% of childcare professionals had moderate to high stress levels (7), almost twice the national estimate of 37% among US adults during the pandemic (22). Before the pandemic, 36.8% to 62.1% of childcare professionals were reported to be experiencing moderate to high levels of stress (7,10,23).

Given that the mental and physical well-being of childcare professionals is associated with children’s academic and emotional learning outcomes (5,15,23), it is imperative to understand and address the condition of childcare professionals during the pandemic and beyond. Although relatively small-scale studies documented the mental health status of early childhood educators before the COVID-19 pandemic (5,8–11,14,15,23), little is known about their physical and mental health status during the pandemic. This study evaluated the prevalence of chronic diseases, depression, and stress levels during the COVID-19 pandemic among US childcare professionals.

Top

Methods

Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020, approximately 10 to 13 weeks into the COVID-19 pandemic, through various contact lists of individuals associated with the childcare industry, as described previously (24). Inclusion criteria were participants who self-identified as childcare professionals working in childcare before or during the pandemic; consented to the study; were aged 18 years or older; and resided in a US state or the District of Columbia. Of the 94,390 individuals who accessed the survey, 82,613 satisfied inclusion criteria and 81,682 (98.9%) provided data necessary for analyses. Participants were offered entry into a raffle for 1 of 20 gift cards valued at $500 each. The research protocol was approved by the Yale University Institutional Review Board as a Category 2(ii) exempt protocol (#2000028232).

Variables

Chronic diseases and health conditions. The survey asked about 10 chronic diseases and physical health conditions, identified as risk factors for COVID-19 complications by the Centers for Disease Control and Prevention at the time of the survey (25). Respondents indicated which applied to them: chronic lung disease/chronic obstructive pulmonary disease (COPD), chronic/severe kidney disease, liver disease, heart disease, immune-compromising conditions (such as immune deficiencies or bone marrow/organ transplant), immunosuppressive treatments of cancer/inflammatory disease (such as lupus or rheumatoid arthritis), smoking, diabetes, asthma (moderate to severe), and obesity. The highest prevalence in our sample was for asthma, diabetes, heart disease, and obesity; therefore, we selected these conditions for further analysis. We analyzed the prevalence of the remaining 6 physical health conditions by sociodemographic characteristics.

Depressive symptoms. The 10-item Center for Epidemiological Studies–Depression (CES-D-10) scale is a reliable and valid self-report scale designed to measure depressive symptomatology and screen for major depression (26). Items assess depression-related symptoms experienced in the previous week (0 = rarely or none of the time; 1 = some or little of the time; 2 = occasionally or a moderate amount of the time; 3 = all of the time), such as restless sleep, poor appetite, and feelings of loneliness. We reverse coded positively stated items (eg, “I felt hopeful about the future”) before calculating summary scores (possible range, 0–30). We calculated summary scores by totaling all items scored. As in other studies (20), summary scores greater than or equal to 10 were considered positive for depression.

Stress. The 10-item Perceived Stress Scale (PSS-10) is a validated short-form version of the PSS, the most widely used psychological instrument for measuring the perception of stress (27). Questions ask about feelings and thoughts during the previous month and are rated on a 5-point Likert scale (0 = never; 1 = almost never; 2 = sometimes; 3 = fairly often; 4 = very often) (27). Positively stated items (eg, “felt that things were going your way”) were reverse coded before calculating summary scores (range, 0–40). We calculated summary scores by totaling all items scored. Summary scores ranging from 0 to 13 are considered low stress; 14 to 26, moderate stress; and 27 to 40, high stress (27).

Sociodemographic factors. Respondents were asked to provide information on their race and ethnicity, with items worded identically to the most recent US Census questionnaire. Options for race were White, Black/African American, American Indian/Alaska Native, Native Hawaiian/Pacific Islander, and Asian; respondents who selected more than 1 race were coded as multiracial. Additionally, ethnicity (Hispanic, Latino, or Spanish origin versus not), access to medical insurance (yes or no), sex/gender (female, male, nonbinary, prefer to self-describe as something else, prefer not to answer), age, and childcare program type (for-profit center, nonprofit agency center, school-based center, Head Start or Early Head Start, other center-based, drop-in childcare, home-based or family childcare, nanny or in-home childcare) were considered in the analysis.

Data weighting and missing data analysis and treatment

The sample was weighted to national representativeness for US childcare professionals by state, age, race, and ethnicity based on the 2019 American Community Survey (28), with the top and bottom 5% of the weights trimmed to reduce sampling variance.

Analysis of missing data included visual examination of missing data patterns and descriptive measures of missing values. Chronic diseases and health conditions had 9.7% missing values, while CES-D-10 and PSS-10 scores had 36.1% and 37.3% missing values, respectively. Missingness in covariates ranged from 0.5% to 16%. We used Little’s missing completely at random test to examine the missing data mechanism, and results suggested that the data were not missing completely at random (χ29 = 1,515.8; P < .001) (29). We used multiple imputation to address missingness (30). Variables used for imputation included race, ethnicity, sex/gender, age, childcare program type, access to medical insurance, and all outcome variables (CES-D-10, PSS-10, diabetes, heart disease, asthma, and obesity). Weight was also incorporated to fit imputation models. To ensure the precision and replicability of point estimates, we imputed 20 data sets using the fully conditional specification imputation method (31) and reported the pooled results from the 20 data sets.

Statistical analysis

We used descriptive statistics to present all variables. We used separate multivariable logistic regression models to assess the association of covariates (age, race, ethnicity, sex/gender, program type, and medical insurance) with the prevalence of heart disease, asthma, diabetes, and obesity. We used separate multivariable linear regression models to assess the association of these covariates with self-reported depression and stress scores. Significance was set to α = .05 (2-tailed). Effect size of odds ratios (ORs) were interpreted as being very small (<1.44), small (1.44–2.47), medium (2.48–4.26), or large (≥4.27) (32). We conducted all analyses in SPSS Statistics version 28.0.1 (IBM Corp) and R version 4.1.1 (R Foundation for Statistical Computing).

Top

Results

Of the total sample (N = 81,682), the mean age was 42.1 years (SD, 14.1 y). Across racial categories, 63.8% (n = 52,164) were White, 14.5% (n = 11,837) Black/African American, 3.6% (n = 2,949) Asian, 3.6% (n = 2,944) multiracial, 1.9% (n = 1,582) American Indian/Alaska Native, 0.6% (n = 491) Native Hawaiian/Pacific Islander, and 11.9% (n = 9,731) preferred not to identify their race; 21.7% (n = 17,753) identified as Hispanic. Also, 96.4% (n = 78,725) of the sample identified as female, 2.5% (n = 2,033) as male, and 0.3% (n = 225) as nonbinary. Most (76.5%) respondents worked in childcare centers; of these, 24.5% (n = 19,976) worked in for-profit centers. Of the total sample, 89.2% (n = 72,890) reported access to medical insurance (Table 1).

Chronic diseases and physical health conditions

Of the 10 chronic diseases and physical health conditions considered, we found the highest rates for asthma (14.3%; n = 11,717), diabetes (6.5%; n = 5,317), heart disease (4.9%; n = 3,971), and obesity (19.8%; n = 16,207) (Table 1).

Asthma

Compared with White respondents, American Indian/Alaska Native (OR, 1.44; 95% CI, 1.23–1.69), Black/African American (OR, 1.09; 95% CI, 1.02–1.16), and multiracial (OR, 1.62; 95% CI, 1.47–1.79) respondents had higher odds of having asthma, while controlling for other covariates, whereas Asian (OR, 0.74; 95% CI, 0.64–0.84) respondents had lower odds of having asthma (Table 2). Respondents who identified as Hispanic had lower odds (OR, 0.90; 95% CI, 0.85–0.96) of having asthma than those who did not identify as Hispanic, while controlling for other covariates. Compared with female respondents, respondents who identified as nonbinary had higher odds of asthma (OR, 1.58; 95% CI, 1.11–2.25). Respondents without medical insurance had lower odds of having asthma (OR, 0.74; 95% CI, 0.68–0.80) than respondents with medical insurance, while controlling for other covariates.

Diabetes

Compared with White respondents, American Indian/Alaska Native (OR, 2.34; 95% CI, 1.96–2.80), Asian (OR, 1.34; 95% CI, 1.11–1.62), Black/African American (OR, 1.86; 95% CI, 1.71–2.03), and Native Hawaiian/Pacific Islander (OR, 1.88; 95% CI, 1.34–2.64) respondents had higher odds of having diabetes, while controlling for other covariates (Table 2). Respondents who identified as Hispanic had higher odds (OR, 1.34; 95% CI, 1.22–1.47) of having diabetes than those who did not identify as Hispanic, while controlling for other covariates. Respondents without medical insurance had lower odds of having diabetes (OR, 0.81; 95% CI, 0.72–0.92) than those with medical insurance, while controlling for other covariates.

Heart disease

Compared with White respondents, American Indian/Alaska Native (OR, 1.42; 95% CI, 1.11–1.82), Black/African American (OR, 1.14; 95% CI, 1.03–1.26), and multiracial (OR, 1.74; 95% CI, 1.46–2.08) respondents had higher odds of having heart disease, while controlling for ethnicity, sex/gender, age, medical insurance, and program type (Table 2). Male respondents (OR, 1.49; 95% CI, 1.22–1.80) and nonbinary respondents (OR, 1.97; 95% CI, 1.01–3.84) had higher odds of having heart disease than did female respondents.

Obesity

Compared with White respondents, multiracial (OR, 1.30; 95% CI, 1.18–1.43) respondents had higher odds of having obesity, while controlling for other covariates, whereas Asian (OR, 0.27; 95% CI, 0.22–0.31) and Native Hawaiian/Pacific Islander (OR, 0.76; 95% CI, 0.58–0.99) respondents had lower odds of having obesity (Table 2). Participants who identified as Hispanic had lower odds (OR, 0.75; 95% CI, 0.71–0.80) of having obesity than respondents who did not identify as Hispanic, while controlling for other covariates. Respondents without medical insurance had lower odds of having obesity (OR, 0.94; 95% CI, 0.88–1.00) than respondents with medical insurance, while controlling for other covariates.

Other physical health conditions

The prevalence of the remaining 6 chronic diseases and physical health conditions were 4.4% (n = 3,619) for smoking, 4.7% (n = 3,851) for immunosuppressive treatments of cancer/inflammatory disease, 2.3% (n = 1,884) for immune-compromising conditions, 1.0% (n = 814) for chronic lung disease/COPD, 0.7% (n = 562) for chronic/severe kidney disease, and 0.7% (n = 545) for liver disease (Supplemental Table 1 in Appendix). Overall, 26.2% (n = 21,398) of respondents reported at least 1 medically compromising condition, 9.7% (n = 7,962) reported 2 conditions, and 4.0% (n = 3,239) reported 3 or more conditions (Supplemental Table 2 in Appendix).

Mental health

Depressive symptoms

Of the total sample, 45.7% (n = 37,376) of respondents screened positive for depression, with a mean score of 10.2 (SD, 6.0) (Table 3). For every 1-year increase in age, on average, the CES-D-10 summary score decreased (β = −0.11; 95% CI, −0.16 to −0.05) (Table 4). Compared with respondents who worked in for-profit centers, participants in home-based programs reported lower CES-D-10 summary scores (β = −2.30; 95% CI, −3.89 to −0.72) while controlling for other covariates (Table 4).

Stress

Of the total sample, 33.4% (n = 27,317) of respondents reported low stress levels, 42.5% (n = 34,752) reported moderate stress levels, and 24.0% (n = 19,629) reported high stress levels, with a mean score of 17.5 (SD, 7.4) (Table 3). For every 1-year increase in age, on average, the PSS-10 summary score decreased (β = −0.07; 95% CI, −0.11 to −0.03) (Table 4). Compared with participants who worked in for-profit centers, participants in home-based programs reported lower PSS-10 summary scores (β = −1.54; 95% CI, −2.45 to −0.63) while controlling for other covariates (Table 4).

Top

Discussion

In our study, the largest national study of the physical and mental health of US childcare professionals to date, the prevalence of depression was higher among childcare professionals during the COVID-19 pandemic than before the pandemic, and asthma, stress, and depression rates were higher among childcare professionals than among US adult overall during the pandemic. Additionally, race, ethnicity, and sex/gender disparities were found for physical health conditions but not mental health conditions of childcare professionals during the pandemic. Our findings highlight a need for effective supports for the overall well-being of this socially vulnerable, yet essential, workforce.

The depression rate for childcare professionals (45.7%) 2 or 3 months into the COVID-19 pandemic was greater than estimates for childcare professionals before the pandemic (16.0% to 36.1%) (11–15), and greater than estimates for US adults during the pandemic (27.8% to 32.8%) (19–21). Approximately two-thirds (66.5%) of childcare professionals reported moderate (42.5%) or high (24.0%) stress levels, almost twice the estimate for US adults during the pandemic (22). This rate of stress among childcare professionals is greater than prepandemic rates for childcare professionals (7,10,23) and similar to rates during the early months of the pandemic reported by others (7).

The increased levels of stress and depressive symptoms may be due to the challenging working conditions that childcare professionals face, including low wages. Although these conditions existed before the COVID-19 pandemic, they have been exacerbated by the pandemic. Childcare professionals’ compensation decreased at the beginning of the pandemic because of low child enrollment (7), and low compensation has been linked to increases in burnout and stress (33). The increased levels of stress and depressive symptoms found in our study are concerning because poor mental health status among childcare professionals is associated with increased teacher–child conflicts and negative social–emotional teaching (23). Another explanation for the increased levels of stress and depressive symptoms may be the decrease in physical activity and mobility and increase in sedentary behavior, as childcare professionals adapted to the COVID-19 pandemic lockdowns, which were found to be associated with worse mental health outcomes (34–36). Overall, identifying mental health interventions that support the well-being of childcare professionals is an important step toward improving the quality of childcare programs and children’s academic and personal development.

Across the 10 medical conditions identified by the Centers for Disease Control and Prevention near the beginning of the pandemic as risk factors for COVID-19 complications (25), 26.2% of survey respondents reported 1 condition, 9.7% reported 2 conditions, and 4.0% reported 3 or more conditions. Asthma rates among childcare professionals in this study (14.3%) were about 1.2 times the national average among US women (37). Our finding on the high rate of asthma among childcare professionals requires immediate attention because people with asthma are more likely than people without asthma to be hospitalized for COVID-19 (38). Also, childcare centers are often poorly ventilated and have high levels of indoor air pollutants (39), suggesting the need to monitor air quality in childcare facilities to protect the health of childcare professionals and reduce their vulnerability to health complications. In contrast to the high rate of asthma among childcare professionals, the rates for diabetes (6.5%), heart disease (4.9%), and obesity (19.8%) among childcare professionals were below national rates for US adult women (16,17,40).

Race, ethnicity, and sex/gender disparities were evidenced for physical health conditions of childcare professionals but not for mental health during the pandemic. Compared with White childcare professionals, those who identified as either American Indian/Native Alaskan or Black/African American had increased odds for asthma, heart disease, and diabetes, and multiracial childcare professionals had increased odds of asthma, heart disease, and obesity. Both findings are consistent with the racial and ethnic disparities among US adult women (17,37,40). Illustrating these disparities, 7.4% of American Indian/Native Alaska childcare professionals reported 3 or more chronic health conditions that place them at greater risk of COVID-19 complications, compared with 4.0% among childcare professionals overall. Of the physical health conditions examined, diabetes showed the greatest level of disparities, with all racial groups (except multiracial) and the Hispanic group showing increased odds when compared with White childcare professionals, which is consistent with racial and ethnic disparities among US adult women (41). Also, childcare professionals who reported nonbinary gender identity had increased odds of both asthma and heart disease compared with female childcare professionals.

Although our study found racial and ethnic disparities in the rates of chronic diseases, the reason for these differences may not be simply racial and ethnic minority status but also socioeconomic status. With an average salary of $16,443 (as of 2019) (4), childcare professionals are economically disadvantaged. However, childcare professionals of color are paid considerably less per hour than their White counterparts, even when controlling for educational level (42). Therefore, the higher prevalence of chronic diseases, especially heart disease, diabetes, and obesity, among childcare providers of color, who are likely to come from low-income communities, may be due to poor nutritional habits, lack of adequate exercise, and other behavioral and environmental factors that are associated with low-income status (43).

Professionals working in the federally funded Head Start or Early Head Start program had greater odds for diabetes and obesity, compared with professionals working in for-profit childcare centers, even when controlling for sociodemographic characteristics. Childcare professionals with asthma, diabetes, or obesity were more likely to have access to medical insurance, regardless of age or other sociodemographic characteristics, perhaps explainable by previous findings showing that people with medical insurance are more likely to use basic clinical services and therefore more likely to receive a diagnosis and treatment from a primary care provider (44).

Strengths and limitations

The major strength of our study is that it is a large national sample weighted to representativeness, allowing robust estimates of US childcare professionals’ physical and mental health status and enough statistical power to explore subgroup conditions. The greatest methodologic limitation is the sole reliance on self-reported information, without medical or psychiatric examination to verify the reporting. Also, findings were obtained during the early months of the COVID-19 pandemic (May–June 2020), and the mental health impacts of the COVID-19 pandemic may have changed after that time. Lastly, our data do not contribute to identifying interventions that may help manage the high levels of stress and depressive symptoms among childcare professionals.

Conclusion

Given the impacts of the pandemic on this essential workforce, efforts should be directed toward developing effective and scalable interventions for improving the physical and mental health of childcare professionals and addressing stressors that may undermine their well-being. Our findings emphasize the need to further examine the health behaviors of childcare professionals, via mixed-methods research, to identify health initiatives that might improve their overall health.

Top

Acknowledgments

All phases of this study were funded and supported by the Andrew & Julie Klingenstein Family Fund, the Esther A & Joseph Klingenstein Fund, the Heising-Simons Foundation, the WK Kellogg Foundation, the Foundation for Child Development, the Early Educator Investment Collaborative, Scholastic Inc, the Yale Institute for Global Health, and the Tobin Center for Economic Policy at Yale University. The funders/sponsors did not participate in the work.

Invaluable assistance with obtaining contact information for childcare providers was provided by the National Workforce Registry Alliance (and its network of state childcare workforce registries), Child Care Aware of America, and the National Association for the Education of Young Children. Drs Amalia Londono Tobon (Warren Alpert Medical School of Brown University) and Adrián Cerezo Caballero (Yale Child Study Center) provided Spanish translations and back translations of the survey measures and recruitment information. Louise Scrivani (Yale Child Study Center) provided project administrative assistance. Alicia Alonso, Catherine Chang, Renee Dauerman, Stella FitzGerald, Harleen Kaur, Emma Knight, and Helen Mooney (Yale College) assisted in qualitative data categorization of respondent comments.

No copyrighted materials were used in this research.

Top

Author Information

Corresponding Author: Jad A. Elharake, MPH, Yale Institute for Global Health, 1 Church St, New Haven, CT 06510. Telephone: 313-443-5150. Email: jad.elharake@yale.edu.

Author Affiliations: 1Yale School of Medicine, New Haven, Connecticut. 2Yale Institute for Global Health, New Haven, Connecticut. 3Mailman School of Public Health, Columbia University, New York, New York. 4Yale Child Study Center, Yale School of Medicine, New Haven, Connecticut. 5Human Development and Family Studies, Michigan State University, East Lansing, Michigan. 6Department of Economics, Yale University, New Haven, Connecticut. 7Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut. 8Tobin Center for Economic Policy, Yale University, New Haven, Connecticut. 9Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut. 10Yale School of Nursing, New Haven, Connecticut.

Top

References

  1. US Bureau of Labor Statistics. Childcare workers. 2020. Accessed January 15, 2022. https://www.bls.gov/ooh/personal-care-and-service/childcare-workers.htm
  2. Whitebook M, McLean C, Austin LJE, Edwards B. The Early Childhood Workforce Index — 2018. Berkeley (CA): Center for the Study of Child Care Employment, University of California, Berkeley; 2018. Accessed January 15, 2022. https://cscce.berkeley.edu/wp-content/uploads/2022/04/Early-Childhood-Workforce-Index-2018.pdf
  3. Chang DI. Connecting the dots: improving child care workers’ conditions leads to better health, economic stability, and greater equity. Health Affairs Forefront. Published October 20, 2020. Accessed January 15, 2022. https://www.healthaffairs.org/do/10.1377/forefront.20201019.28108/full
  4. Deloitte, Datawheel. Data USA: childcare workers. 2021. Accessed May 15, 2022. https://datausa.io/profile/soc/childcare-workers#about
  5. Kwon K-A, Horm DM, Amirault C. Early childhood teachers’ well-being: what we know and why we should care. Zero to Three Journal 2021;41(3):35–44.
  6. Haberman M. Teacher burnout in black and white. New Educator 2005;1(3):153–75. CrossRef
  7. Swigonski NL, James B, Wynns W, Casavan K. Physical, mental, and financial stress impacts of COVID-19 on early childhood educators. Early Child Educ J 2021;49(5):799–806. CrossRef PubMed
  8. Otten JJ, Bradford VA, Stover B, Hill HD, Osborne C, Getts K, et al. The culture of health in early care and education: workers’ wages, health, and job characteristics. Health Aff (Millwood) 2019;38(5):709–20. CrossRef PubMed
  9. Sharma S, Dortch KS, Byrd-Williams C, Truxillio JB, Rahman GA, Bonsu P, et al. Nutrition-related knowledge, attitudes, and dietary behaviors among head start teachers in Texas: a cross-sectional study. J Acad Nutr Diet 2013;113(4):558–62. CrossRef PubMed
  10. Tovar A, Vaughn AE, Grummon A, Burney R, Erinosho T, Østbye T, et al. Family child care home providers as role models for children: cause for concern? Prev Med Rep 2016;5:308–13. CrossRef PubMed
  11. Linnan L, Arandia G, Bateman LA, Vaughn A, Smith N, Ward D. The health and working conditions of women employed in child care. Int J Environ Res Public Health 2017;14(3):283. CrossRef PubMed
  12. Aikens N, Tarullo L, Hulsey L, Ross C, West J, Xue Y. A year in Head Start: children, families and programs. US Department of Health and Human Services, Administration for Children & Families, Office of Planning, Research & Evaluation; 2010. Accessed January 15, 2022. https://www.acf.hhs.gov/opre/report/year-head-start-children-families-and-programs
  13. Whitebook M, King E, Philipp G, Sakai L. Teachers’ voices: work environment conditions that impact teacher practice and program quality. Berkeley (CA): Center for the Study of Child Care Employment, University of California, Berkeley; 2017. Accessed January 15, 2022. https://cscce.berkeley.edu/wp-content/uploads/publications/2016-Alameda-SEQUAL-Report-FINAL-for-Dissemination-v2.pdf
  14. Whitaker RC, Becker BD, Herman AN, Gooze RA. The physical and mental health of Head Start staff: the Pennsylvania Head Start staff wellness survey, 2012. Prev Chronic Dis 2013;10:E181. CrossRef PubMed
  15. Whitaker RC, Dearth-Wesley T, Gooze RA. Workplace stress and the quality of teacher–children relationships in Head Start. Early Childhood Research Quarterly 2015;30:57–69. CrossRef
  16. Statista. Percent of women in the U.S. who were diagnosed with diabetes in selected periods between 1988 and 2018. March 2021. Accessed January 15, 2022. https://www.statista.com/statistics/666206/female-diabetes-prevalence-us
  17. Fryar CD, Carroll MD, Afful J. Prevalence of overweight, obesity, and severe obesity among adults aged 20 and over: United States, 1960–1962 through 2017–2018. NCHS Health E-Stats. 2020. Accessed January 15, 2022. https://www.cdc.gov/nchs/data/hestat/obesity-adult-17-18/obesity-adult.htm
  18. National Institute of Mental Health. Major depression. 2019. Accessed January 15, 2022. https://www.nimh.nih.gov/health/statistics/major-depression
  19. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open 2020;3(9):e2019686. CrossRef PubMed
  20. Rosenberg M, Luetke M, Hensel D, Kianersi S, Fu T-C, Herbenick D. Depression and loneliness during April 2020 COVID-19 restrictions in the United States, and their associations with frequency of social and sexual connections. Soc Psychiatry Psychiatr Epidemiol 2021;56(7):1221–32. CrossRef PubMed
  21. Ettman CK, Cohen GH, Abdalla SM, Sampson L, Trinquart L, Castrucci BC, et al. Persistent depressive symptoms during COVID-19: a national, population-representative, longitudinal study of U.S. adults. Lancet Reg Health Am 2022;5:100091. CrossRef PubMed
  22. Park AL, Velez CV, Kannan K, Chorpita BF. Stress, functioning, and coping during the COVID-19 pandemic: results from an online convenience sample. The Behavior Therapist 2020;43(6):210–6. CrossRef
  23. Smith S, Lawrence SM. Early care and education teacher well-being: associations with children’s experience, outcomes, and workplace conditions: a research-to-policy brief. DataCite 2019. CrossRef
  24. Gilliam WS, Malik AA, Shafiq M, Klotz M, Reyes C, Humphries JE, et al. COVID-19 transmission in US child care programs. Pediatrics 2021;147(1):e2020031971. CrossRef PubMed
  25. Centers for Disease Control and Prevention. COVID-19: people with certain medical conditions. 2022. Accessed February 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html
  26. Cosco TD, Prina M, Stubbs B, Wu Y-T. Reliability and validity of the Center for Epidemiologic Studies Depression Scale in a population-based cohort of middle-aged US adults. J Nurs Meas 2017;25(3):476–85. CrossRef PubMed
  27. Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983;24(4):385–96. CrossRef PubMed
  28. US Census Bureau. Data profiles. 2015–2019 ACS 5-year data profile. 2019. Accessed January 15, 2022. https://www.census.gov/acs/www/data/data-tables-and-tools/data-profiles/2019
  29. Little RJ. A test of missing completely at random for multivariate data with missing values. J Am Stat Assoc 1988;83(404):1198–202. CrossRef
  30. Sterne JA, White IR, Carlin JB, Spratt M, Royston P, Kenward MG, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ 2009;338:b2393. CrossRef PubMed
  31. Lee KJ, Carlin JB. Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation. Am J Epidemiol 2010;171(5):624–32. CrossRef PubMed
  32. Cohen J. Statistical power analysis for the behavioral sciences. Hillsdale (NJ): Lawrence Erlbaum Associates; 1988. p. 18–74.
  33. Cumming T. Early childhood educators’ well-being: an updated review of the literature. Early Childhood Education Journal 2017;45(5):583–93. CrossRef
  34. Randall K, Ford TG, Kwon K-A, Sisson SS, Bice MR, Dinkel D, et al. Physical activity, physical well-being, and psychological well-being: associations with life satisfaction during the COVID-19 pandemic among early childhood educators. Int J Environ Res Public Health 2021;18(18):9430. CrossRef PubMed
  35. Mishra R, Park C, York MK, Kunik ME, Wung SF, Naik AD, et al. Decrease in mobility during the COVID-19 pandemic and its association with increase in depression among older adults: a longitudinal remote mobility monitoring using a wearable sensor. Sensors (Basel) 2021;21(9):3090. CrossRef PubMed
  36. Lin W, Bai G, He W, Yang F, Li W, Min Y, et al. Association between napping status and depressive symptoms in urban residents during the COVID-19 epidemic. Zhejiang Da Xue Xue Bao Yi Xue Ban 2021;50(6):741–7. CrossRef PubMed
  37. United Health Foundation. Asthma — women. 2019. Accessed January 15, 2022. https://www.americashealthrankings.org/explore/health-of-women-and-children/measure/asthma_women/state/ALL
  38. Centers for Disease Control and Prevention. COVID-19: people with moderate to severe asthma. Updated April 7, 2021. Accessed February 15, 2022. https://www.cdc.gov/coronavirus/2019-ncov/need-extra-precautions/asthma.html
  39. Carreiro-Martins P, Papoila AL, Caires I, Azevedo S, Cano MM, Virella D, et al. Effect of indoor air quality of day care centers in children with different predisposition for asthma. Pediatr Allergy Immunol 2016;27(3):299–306. CrossRef PubMed
  40. Centers for Disease Control and Prevention. Women and heart disease. 2020. Accessed January 15, 2022. https://www.cdc.gov/heartdisease/women.htm
  41. Centers for Disease Control and Prevention. National diabetes statistics report, 2020. Atlanta (GA): US Department of Health and Human Services, Centers for Disease Control and Prevention; 2020. p. 12–15.
  42. Gillispie C, Codella C, Merchen A, Davis J, Cappo A. Equity in child care is everyone’s business. Education Trust. February 22, 2021. Accessed January 15, 2022. https://edtrust.org/resource/equity-in-child-care-is-everyones-business
  43. Baciu A, Negussie Y, Geller A, Weinstein JN; National Academies of Sciences, Engineering, and Medicine. The state of health disparities in the United States. In: Communities in action: pathways to health equity. National Academies Press; 2017.
  44. US Department of Health and Human Services, Office of Disease Prevention and Health Promotion. Healthy people 2020. Access to health services. Updated February 6, 2022. Accessed January 15, 2022. https://www.healthypeople.gov/2020/topics-objectives/topic/social-determinants-health/interventions-resources/access-to-health

Top

Tables

Return to your place in the text

Table 1. Prevalence of Physical Health Conditions Among US Childcare Professionals, by Sociodemographic Characteristics, 2020a
Characteristic Total Physical health condition
Asthma Heart disease Diabetes Obesity
Totalb 81,682 11,717 (14.3) 3,971 (4.9) 5,317 (6.5) 16,207 (19.8)
Age, mean (SD), y 42.1 (14.1) 40.9 (14.1) 50.3 (13.8) 51.3 (12.8) 44.0 (13.3)
Race
American Indian/Alaska Native 1,582 (1.9) 298 (18.8) 91 (5.8) 178 (11.2) 330 (20.9)
Asian 2,949 (3.6) 325 (11.0) 121 (4.1) 195 (6.6) 195 (6.6)
Black/African American 11,837 (14.5) 1,787 (15.1) 674 (5.7) 1,209 (10.2) 2,587 (21.9)
Multiracial 2,944 (3.6) 638 (21.7) 179 (6.1) 130 (4.4) 703 (23.9)
Native Hawaiian/Pacific Islander 491 (0.6) 67 (13.6) 21 (4.3) 53 (10.9) 77 (15.7)
Prefer to not answer 9,731 (11.9) 1,189 (12.2) 364 (3.7) 606 (6.2) 1,410 (14.5)
White 52,164 (63.8) 7,413 (14.2) 2,520 (4.8) 2,946 (5.6) 10,905 (20.9)
Hispanic ethnicity
No 61,806 (75.7) 9,099 (14.7) 3,207 (5.2) 4,043 (6.5) 13,121 (21.2)
Yes 17,753 (21.7) 2,362 (13.3) 676 (3.8) 1,112 (6.3) 2,723 (15.3)
Prefer to not answer 2,139 (2.6) 255 (11.9) 88 (4.1) 163 (7.6) 363 (17.0)
Sex/gender
Female 78,725 (96.4) 11,358 (14.4) 3,789 (4.8) 5,106 (6.5) 15,780 (20.0)
Male 2,033 (2.5) 231 (11.4) 139 (6.8) 149 (7.3) 267 (13.1)
Nonbinary 225 (0.3) 51 (22.8) 14 (6.3) 11 (4.8) 51 (22.7)
Prefer to not answer 715 (0.9) 76 (10.6) 29 (4.1) 52 (7.3) 109 (15.2)
Medical insurance
No 8,808 (10.8) 1,012 (11.5) 327 (3.7) 424 (4.8) 1,551 (17.6)
Yes 72,890 (89.2) 10,705 (14.7) 3,644 (5.0) 4,893 (6.7) 14,656 (20.1)
Program type
Center-based
  For-profit center 19,976 (24.5) 2,861 (14.3) 1,050 (5.3) 1,222 (6.1) 4,133 (20.7)
  School-based 10,604 (13.0) 1,529 (14.4) 450 (4.2) 465 (4.4) 1,729 (16.3)
  Head Start/Early Head Start 8,506 (10.4) 1,309 (15.4) 370 (4.4) 637 (7.5) 1,992 (23.4)
  Drop-in center 1,596 (2.0) 220 (13.8) 49 (3.1) 69 (4.3) 210 (13.1)
  Nonprofit agency center 15,875 (19.4) 2,336 (14.7) 802 (5.1) 1,076 (6.8) 3,588 (22.6)
  Other center-based 5,949 (7.3) 945 (15.9) 267 (4.5) 352 (5.9) 1,073 (18.0)
Home-based/family childcare 18,078 (22.1) 2,348 (13.0) 946 (5.2) 1,435 (7.9) 3,309 (18.3)
Nanny/home visiting 1,115 (1.4) 169 (15.2) 37 (3.3) 61 (5.4) 174 (15.6)

a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020. All values are number (percentage) unless otherwise indicated.
b Because of sample weighting, frequencies may not add exactly to totals.

Return to your place in the text

Table 2. Logistic Regression of Physical Health Conditions and Sociodemographic Characteristics Among US Childcare Professionals, 2020a
Characteristic Asthma Heart disease Diabetes Obesity
Age 0.99 (0.99–0.99)b 1.04 (1.04–1.05)b 1.05 (1.05–1.06)b 1.01 (1.01–1.01)b
Race
American Indian/Alaska Native 1.44 (1.23–1.69)b 1.42 (1.11–1.82)b 2.34 (1.96–2.80)b 1.11 (0.95–1.29)
Asian 0.74 (0.64–0.84)b 0.89 (0.72–1.11) 1.34 (1.11–1.62)b 0.27 (0.22–0.31)b
Black/African American 1.09 (1.02–1.16)b 1.14 (1.03–1.26)b 1.86 (1.71–2.03)b 1.01 (0.96–1.07)
Multiracial 1.62 (1.47–1.79)b 1.74 (1.46–2.08)b 1.07 (0.87–1.31) 1.30 (1.18–1.43)b
Native Hawaiian/Pacific Islander 1.00 (0.73–1.37) 0.88 (0.53–1.45) 1.88 (1.34–2.64)b 0.76 (0.58–0.99)b
Prefer not to answer 0.91 (0.83–0.99) 0.95 (0.81–1.11) 1.09 (0.96–1.23) 0.78 (0.72–0.85)b
White 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
Hispanic
No 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
Yes 0.90 (0.85–0.96)b 0.95 (0.85–1.06) 1.34 (1.22–1.47)b 0.75 (0.71–0.80)b
Prefer to not answer 0.90 (0.76–1.07) 0.82 (0.61–1.12) 1.23 (0.98–1.54) 0.93 (0.80–1.08)
Sex/gender
Female 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
Male 0.74 (0.63–0.88)b 1.49 (1.22–1.80)b 1.18 (0.96–1.44) 0.62 (0.53–0.73)b
Nonbinary 1.58 (1.11–2.25)b 1.97 (1.01–3.84)b 1.06 (0.45–2.48) 1.32 (0.90–1.93)
Prefer to not answer 0.80 (0.55–1.17) 0.93 (0.53–1.65) 0.99 (0.66–1.50) 0.82 (0.63–1.07)
Medical insurance
Yes 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
No 0.74 (0.68–0.80)b 0.89 (0.77–1.02) 0.81 (0.72–0.92)b 0.94 (0.88–1.00)b
Program type
For-profit center 1 [Reference] 1 [Reference] 1 [Reference] 1 [Reference]
Home-based/family childcare 0.94 (0.88–1.01) 0.83 (0.74–0.92)b 0.99 (0.89–1.10) 0.85 (0.80–0.91)b
Nanny/home visiting 1.02 (0.84–1.25) 0.89 (0.58–1.36) 1.27 (0.91–1.77) 0.82 (0.67–1.00)b
Nonprofit agency center 1.05 (0.98–1.12) 0.87 (0.78–0.97)b 1.01 (0.91–1.11) 1.10 (1.03–1.17)b
School-based 0.99 (0.91–1.08) 0.90 (0.78–1.04) 0.78 (0.69–0.88)b 0.81 (0.75–0.87)b
Head Start/Early Head Start 1.08 (0.99–1.17) 0.89 (0.77–1.02) 1.21 (1.08–1.35)b 1.28 (1.19–1.37)b
Drop-in center 0.92 (0.78–1.09) 0.86 (0.59–1.24) 0.95 (0.69–1.30) 0.69 (0.57–0.84)b
Other center-based 1.14 (1.03–1.26)b 0.91 (0.77–1.06) 1.00 (0.87–1.16) 0.89 (0.81–0.98)b

a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020. All values are odds ratio (95% CI).
b P < .05; determined by logistic regression.

Return to your place in the text

Table 3. Prevalence of Mental Health Outcomes, by Sociodemographic Characteristics, Among US Childcare Professionals, 2020a
Characteristic Depression (CES-D-10)b Stress (PSS-10)c
Mean (SD) score Screened negative, no. (%) Screened positive, no. (%) Mean (SD) score Low stress, no. (%) Moderate stress, no. (%) High stress, no. (%)
Total 10.2 (6.0) 44,322 (54.3) 37,376 (45.7) 17.5 (7.4) 27,317 (33.4) 34,752 (42.5) 19,629 (24.0)
Race
American Indian/Alaska Native 10.5 (5.9) 776 (49.1) 805 (50.9) 17.9 (7.2) 518 (32.7) 679 (42.9) 385 (24.3)
Asian 9.9 (5.8) 1,659 (56.3) 1,290 (43.7) 18.2 (6.9) 773 (26.2) 1,402 (47.5) 774 (26.2)
Black/African American 9.8 (5.8) 6,990 (59.1) 4,847 (40.9) 16.5 (7.6) 4,669 (39.4) 4,265 (36.0) 2,904 (24.5)
Multiracial 11.3 (5.9) 1,330 (45.2) 1,614 (54.8) 18.4 (7.1) 816 (27.7) 1,357 (46.1) 771 (26.2)
Native Hawaiian/Pacific Islander 8.9 (5.2) 308 (62.7) 183 (37.3) 16.5 (7.5) 223 (45.3) 164 (33.4) 104 (21.3)
Prefer to not answer 10.4 (5.7) 5,183 (53.3) 4,548 (46.7) 17.6 (7.3) 3,156 (32.4) 4,029 (41.4) 2,547 (26.2)
White 10.2 (6.0) 28,075 (53.8) 24,089 (46.2) 17.6 (7.3) 17,163 (32.9) 22,856 (43.8) 12,145 (23.3)
Hispanic
No 10.2 (6.0) 33,644 (54.4) 28,162 (45.6) 17.5 (7.4) 20,647 (33.4) 26,538 (42.9) 14,621 (23.7)
Yes 10.3 (5.8) 9,494 (53.5) 8,259 (46.5) 17.5 (7.3) 5,932 (33.4) 7,390 (41.6) 4,431 (25.0)
Prefer to not answer 10.5 (5.7) 1,184 (55.3) 955 (44.7) 17.4 (7.3) 739 (34.5) 823 (38.5) 577 (27.0)
Sex/gender
Female 10.2 (6.0) 42,714 (54.3) 36,011 (45.7) 17.5 (7.4) 26,346 (33.5) 33,459 (42.5) 18,921 (24.0)
Male 10.1 (6.0) 1,169 (57.5) 864 (42.5) 17.0 (7.5) 667 (32.8) 883 (43.5) 482 (23.7)
Nonbinary 13.7 (6.3) 75 (33.5) 150 (66.5) 19.7 (7.3) 65 (29.0) 91 (40.5) 69 (30.5)
Prefer to not answer 10.2 (5.3) 364 (51.0) 351 (49.0) 17.1 (6.6) 239 (33.4) 319 (44.6) 158 (22.0)
Health insurance
No 10.6 (6.0) 4,516 (51.3) 4,292 (48.7) 18.0 (7.5) 2,908 (33.0) 3,593 (40.8) 2,306 (26.2)
Yes 10.2 (5.9) 39,807 (54.6) 33,083 (45.4) 17.4 (7.4) 24,409 (33.5) 31,159 (42.7) 17,322 (23.8)
Program type
For-profit center 10.6 (6.0) 10,707 (53.6) 9,269 (46.4) 18.3 (7.4) 6,193 (31.0) 8,400 (42.0) 5,383 (27.0)
Home-based/family childcare 8.6 (5.9) 11,552 (63.9) 6,526 (36.1) 15.4 (7.6) 7,748 (42.9) 7,100 (39.3) 3,230 (17.8)
Nanny/home visiting 11.0 (6.0) 533 (47.7) 581 (52.3) 18.7 (7.3) 291 (26.2) 470 (42.1) 353 (31.7)
Nonprofit agency center 10.7 (5.9) 8,163 (51.5) 7,712 (48.5) 18.0 (7.2) 4,959 (31.2) 7,245 (45.6) 3671 (23.1)
School-based 10.9 (5.9) 5,135 (48.4) 5,469 (51.6) 18.2 (7.1) 3,146 (29.6) 4,564 (43.1) 2,894 (27.3)
Head Start/Early Head Start 10.6 (5.7) 4,308 (50.6) 4,198 (49.4) 17.6 (7.0) 2,644 (31.1) 3,980 (46.8) 1,881 (22.2)
Drop-in center 11.9 (5.8) 795 (49.6) 801 (50.4) 18.9 (6.9) 522 (32.9) 620 (38.7) 454 (28.4)
Other center-based 10.5 (5.7) 3,129 (52.5) 2,820 (47.5) 17.8 (6.9) 1,816 (30.5) 2,371 (39.9) 1,762 (29.6)

Abbreviations: CES-D-10, Epidemiological Studies–Depression-10; PSS-10, Perceived Stress Scale-10.
a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020.
b CES-D-10 items assess depression-related symptoms experienced in the previous week (0 = rarely or none of the time; 1 = some or little of the time; 2 = occasionally or a moderate amount of the time; 3 = all of the time), such as restless sleep, poor appetite, and feelings of loneliness (26). Possible scores range from 0 to 30. Scores ≥10 were considered positive for depression.
c PSS-10 questions ask about feelings and thoughts during the previous month and are rated on a 5-point Likert Scale (0 = never; 1 = almost never; 2 = sometimes; 3 = fairly often; 4 = very often) (27). Possible scores range from 0 to 40; scores of 0 to 13 are considered low stress, 14 to 26 moderate stress, and 27 to 40 high stress.

Return to your place in the text

Table 4. Linear Regression of CES-D-10, PSS-10, and Sociodemographic Characteristics Among US Childcare Professionals, 2020a
Characteristic Depressive Symptoms (CES-D-10) Stress (PSS-10)
β (95% CI) SE β (95% CI) SE
Age −0.11 (−0.16 to −0.05)b 0.03 −0.07 (−0.11 to −0.03)b 0.02
Race
American Indian/Alaska Native 0.28 (−1.60 to 2.15) 0.90 0.14 (−1.53 to 1.82) 0.81
Asian 0.53 (−2.52 to 3.57) 1.45 −0.39 (−2.34 to 1.55) 0.93
Black/African American −0.83 (−2.17 to 0.51) 0.64 −0.26 (−1.18 to 0.66) 0.44
Multiracial 0.11 (−1.91 to 2.13) 0.97 0.58 (−1.29 to 2.46) 0.90
Native Hawaiian/Pacific Islander −0.60 (−5.21 to 4.01) 2.21 −1.09 (−4.59 to 2.41) 1.68
Prefer to not answer 0.16 (−1.83 to 2.16) 0.95 0.28 (−1.07 to 1.63) 0.65
White 1 [Reference] 1 [Reference]
Hispanic
No 1 [Reference] 1 [Reference]
Yes −0.46 (−1.67 to 0.75) 0.58 −0.33 (−1.50 to 0.84) 0.56
Prefer to not answer −0.16 (−2.46 to 2.13) 1.10 0.08 (−2.62 to 2.79) 1.29
Sex/gender
Female 1 [Reference] 1 [Reference]
Male −0.95 (−3.52 to 1.61) 1.23 −0.45 (−2.29 to 1.38) 0.88
Nonbinary 0.97 (−5.53 to 7.47) 3.11 2.61 (0.26 to 4.95) 1.14
Prefer to not answer −0.42 (−6.37 to 5.53) 2.84 −0.27 (−5.00 to 4.47) 2.26
Health insurance
Yes 1 [Reference] 1 [Reference]
No 0.26 (−1.49 to 2.01) 0.83 0.27 (−1.09 to 1.63) 0.65
Program type
For-profit center 1 [Reference] 1 [Reference]
Home-based/family childcare −2.30 (−3.89 to −0.72)b 0.76 −1.54 (−2.45 to −0.63)b 0.43
Nanny/home visiting −0.49 (−3.70 to 2.73) 1.54 −0.20 (−3.03 to 2.63) 1.35
Nonprofit agency center −0.02 (−1.18 to 1.13) 0.55 0.30 (−0.47 to 1.07) 0.37
School-based −0.40 (−2.10 to 1.30) 0.81 0.11 (−0.87 to 1.09) 0.47
Head Start/Early Head Start −0.73 (−2.77 to 1.30) 0.97 −0.07 (−1.24 to 1.10) 0.56
Drop-in center −0.27 (−4.06 to 3.52) 1.81 0.73 (−2.15 to 3.61) 1.38
Other center-based −0.68 (−2.58 to 1.22) 0.91 −0.13 (−1.59 to 1.33) 0.70

Abbreviations: Abbreviations: CES-D-10, Epidemiological Studies–Depression-10; PSS-10, Perceived Stress Scale-10.
a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020.
b P < .05; determined by linear regression.

Top

Return to your place in the text

Appendix. Supplemental Tables

Supplemental Table 1. Prevalence of 6 Physical Health Outcomes, by Sociodemographic Characteristics, Among US Childcare Professionals, 2020a
Characteristic Total Chronic lung disease/chronic obstructive pulmonary disease Smoking Chronic/severe kidney disease Liver disease Immunosuppressive treatments of cancer/inflammatory disease Immune-compromising conditions
Total 81,682 814 (1.0) 3,619 (4.4) 562 (0.7) 545 (0.7) 3,851 (4.7) 1,884 (2.3)
Age, mean (SD), y 42.1 (14.1) 54.0 (13.0) 39.7 (13.4) 48.6 (14.9) 46.1 (13.4) 47.4 (13.1) 40.5 (14.0)
Race
American Indian/Alaska Native 1,582 (1.9) 33 (2.1) 110 (7.0) 26 (1.6) 31 (2.0) 74 (4.7) 41 (2.6)
Asian 2,949 (3.6) 12 (0.4) 43 (1.4) 10 (0.3) 12 (0.4) 67 (2.3) 17 (0.6)
Black/African American 11,837 (14.5) 108 (0.9) 484 (4.1) 82 (0.7) 55 (0.5) 559 (4.7) 192 (1.6)
Multiracial 2,944 (3.6) 18 (0.6) 186 (6.3) 13 (0.4) 22 (0.8) 138 (4.7) 108 (3.7)
Native Hawaiian/Pacific Islander 491 (0.6) 12 (2.4) 26 (5.3) 2 (0.3) 3 (0.5) 24 (4.9) 17 (3.4)
Prefer to not answer 9,731 (11.9) 57 (0.6) 260 (2.7) 56 (0.6) 75 (0.8) 371 (3.8) 141 (1.5)
White 52,164 (63.8) 575 (1.1) 2,510 (4.8) 375 (0.7) 348 (0.7) 2,617 (5.0) 1,369 (2.6)
Hispanic
No 61,806 (75.7) 714 (1.2) 3,081 (5.0) 450 (0.7) 381 (0.6) 3,151 (5.1) 1,573 (2.5)
Yes 17,753 (21.7) 69 (0.4) 466 (2.6) 104 (0.6) 144 (0.8) 613 (3.5) 271 (1.5)
Prefer to not answer 2,139 (2.6) 30 (1.4) 72 (3.4) 8 (0.4) 21 (1.0) 87 (4.0) 40 (1.9)
Sex/gender
Female 78,725 (96.4) 786 (1.0) 3,422 (4.3) 534 (0.7) 498 (0.6) 3,759 (4.8) 1,811 (2.3)
Male 2,033 (2.5) 12 (0.6) 135 (6.6) 19 (0.9) 29 (1.4) 41 (2.0) 38 (1.9)
Nonbinary 225 (0.3) 5 (2.1) 38 (16.7) 8 (3.4) 0 (0) 22 (9.7) 27 (12.0)
Prefer to not answer 715 (0.9) 12 (1.7) 25 (3.4) 2 (0.2) 3 (0.5) 29 (4.0) 9 (1.3)
Health insurance
No 8,808 (10.8) 64 (0.7) 569 (6.5) 42 (0.5) 49 (0.6) 253 (2.9) 136 (1.5)
Yes 72,890 (89.2) 750 (1.0) 3,050 (4.2) 520 (0.7) 496 (0.7) 3,598 (4.9) 1,749 (2.4)
Program type
For-profit center 19,976 (24.5) 203 (1.0) 1,112 (5.6) 146 (0.7) 119 (0.6) 946 (4.7) 521 (2.6)
Home-based/family childcare 18,078 (22.1) 214 (1.2) 500 (2.8) 127 (0.7) 120 (0.7) 922 (5.1) 339 (1.9)
Nanny/home visiting 1,115 (1.4) 23 (2.1) 49 (4.4) 9 (0.8) 5 (0.5) 56 (5.0) 48 (4.3)
Nonprofit agency center 15,875 (19.4) 165 (1.0) 665 (4.2) 98 (0.6) 110 (0.7) 806 (5.1) 395 (2.5)
School-based 10,604 (13.0) 78 (0.7) 359 (3.4) 65 (0.6) 82 (0.8) 457 (4.3) 247 (2.3)
Head Start/Early Head Start 8,506 (10.4) 82 (1.0) 532 (6.3) 71 (0.8) 60 (0.7) 382 (4.5) 189 (2.2)
Drop-in center 1,596 (2.0) 8 (0.5) 134 (8.4) 3 (0.2) 10 (0.6) 44 (2.7) 20 (1.2)
Other center-based 5,949 (7.3) 40 (0.7) 268 (4.5) 44 (0.7) 39 (0.7) 239 (4.0) 124 (2.1)

a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020. All values are number (percentage) unless otherwise indicated.

Return to your place in the text

Supplemental Table 2. Number of Chronic Diseases or Health Conditions, by Sociodemographic Characteristics, Among US Childcare Professionals, 2020a
Characteristic No. of chronic diseases or health conditions
0 1 2 ≥3
Total 49,099 (60.1) 21,398 (26.2) 7,962 (9.7) 3,239 (4.0)
Age, mean (SD), y 41.1 (13.9) 42.7 (14.1) 44.5 (13.8) 48.1 (13.7)
Race
American Indian/Alaska Native 863 (54.6) 421 (26.6) 181 (11.4) 117 (7.4)
Asian 2,221 (75.3) 538 (18.3) 138 (4.7) 51 (1.7)
Black/African American 6,718 (56.8) 3271 (27.6) 1,319 (11.1) 530 (4.5)
Multiracial 1,561 (53.0) 832 (28.3) 406 (13.8) 146 (4.9)
Native Hawaiian/Pacific Islander 305 (62.1) 113 (23.1) 48 (9.7) 25 (5.1)
Prefer to not answer 6,557 (67.4) 2,214 (22.8) 697 (7.2) 263 (2.7)
White 30,874 (59.2) 14,009 (26.9) 5,174 (9.9) 2,107 (4.0)
Hispanic
No 35,969 (58.2) 16,739 (27.1) 6,410 (10.4) 2,588 (4.3)
Yes 11,738 (66.1) 4,154 (23.4) 1,392 (7.8) 468 (2.6)
Prefer to not answer 1,392 (65.1) 505 (23.6) 160 (7.5) 82 (3.8)
Sex/gender
Female 47,227 (60.0) 20,662 (26.2) 7,709 (9.8) 3,127 (4.0)
Male 1,300 (64.0) 498 (24.5) 169 (8.3) 65 (3.2)
Nonbinary 88 (39.2) 80 (35.6) 33 (14.9) 23 (10.3)
Prefer to not answer 484 (67.7) 157 (21.9) 51 (7.1) 23 (3.3)
Health insurance
No 5,654 (64.2) 2,212 (25.1) 711 (8.1) 231 (2.6)
Yes 43,445 (59.6) 19,186 (26.3) 7,251 (9.9) 3,008 (4.1)
Program type
For-profit center 11,757 (58.9) 5,359 (26.8) 2,008 (10.1) 852 (4.3)
Home-based/family childcare 11,247 (62.2) 4,438 (24.5) 1,687 (9.3) 706 (3.9)
Nanny/home visiting 717 (64.3) 246 (22.1) 103 (9.3) 48 (4.3)
Nonprofit agency center 9,171 (57.8) 4,369 (27.5) 1,635 (10.3) 699 (4.4)
School-based 6,755 (63.7) 2,692 (25.4) 844 (8.0) 313 (3.0)
Head Start/Early Head Start 4,783 (56.2) 2,369 (27.0) 972 (11.4) 381 (4.5)
Drop-in center 1,053 (66.0) 374 (26.2) 126 (7.9) 43 (2.7)
Other center-based 3,617 (60.8) 1,549 (26.0) 586 (9.8) 197 (3.3)

a Data were collected from self-identifying childcare professionals through an online Qualtrics survey distributed from May 22, 2020, through June 8, 2020. All values are number (percentage) unless otherwise indicated.

Top

Return to your place in the text

Post-Test Information

To obtain credit, you should first read the journal article. After reading the article, you should be able to answer the following, related, multiple-choice questions. To complete the questions (with a minimum 75% passing score) and earn continuing medical education (CME) credit, please go to http://www.medscape.org/journal/pcd. Credit cannot be obtained for tests completed on paper, although you may use the worksheet below to keep a record of your answers.

You must be a registered user on http://www.medscape.org. If you are not registered on http://www.medscape.org, please click on the “Register” link on the right hand side of the website.

Only one answer is correct for each question. Once you successfully answer all post-test questions, you will be able to view and/or print your certificate. For questions regarding this activity, contact the accredited provider, CME@medscape.net. For technical assistance, contact CME@medscape.net. American Medical Association’s Physician’s Recognition Award (AMA PRA) credits are accepted in the US as evidence of participation in CME activities. For further information on this award, please go to https://www.ama-assn.org. The AMA has determined that physicians not licensed in the US who participate in this CME activity are eligible for AMA PRA Category 1 Credits™. Through agreements that the AMA has made with agencies in some countries, AMA PRA credit may be acceptable as evidence of participation in CME activities. If you are not licensed in the US, please complete the questions online, print the AMA PRA CME credit certificate, and present it to your national medical association for review.

Top

Return to your place in the text

Post-Test Questions

Study Title: Prevalence of Chronic Diseases, Depression, and Stress Among US Childcare Professionals During the COVID-19 Pandemic

CME Questions

  1. Which one of the following chronic illnesses was most common among childcare professionals in the current study?
    1. Diabetes
    2. Heart disease
    3. Asthma
    4. Hypothyroidism
  2. Which one of the following racial/ethnic groups experienced the highest rates of asthma and cardiac disease in the current study?
    1. Black/African American and Hispanic
    2. Hispanic and White
    3. Black/African American and Asian
    4. Black/African American and American Indian/Alaska Native
  3. What was the approximate rate of positive screening for depression among childcare professionals in the current study?
    1. 8%
    2. 15%
    3. 24%
    4. 46%
  4. Which one of the following variables had the strongest association with higher stress levels in the current study?
    1. Older age
    2. Black/African American race
    3. Being a woman
    4. Working in a Head Start program

Top

Error processing SSI file

The opinions expressed by authors contributing to this journal do not necessarily reflect the opinions of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors’ affiliated institutions.