key: cord-0785358-pinu7a84
authors: Daly, Michael; Sutin, Angelina; Robinson, Eric
title: Depression reported by US adults in 2017-2018 and March and April 2020
date: 2020-09-15
journal: J Affect Disord
DOI: 10.1016/j.jad.2020.09.065
sha: db7011a8cc03eb9d799bd72bb92ad508a946c43d
doc_id: 785358
cord_uid: pinu7a84

BACKGROUND: Coronavirus disease 2019 (COVID-19) and the associated social distancing and lockdown restrictions are expected to have substantial and enduring mental health effects. In this study, we aimed to assess depression levels before and during the COVID-19 pandemic in the United States. METHODS: We used the Patient Health Questionnaire-2 (PHQ-2) brief screening instrument to detect probable depression in two nationally representative surveys of US adults. Pre-pandemic levels of depression were assessed in a sample of 5,075 adults from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). Depression was assessed in March (N=6,819) and April, 2020 (N=5,428) in the Understanding America Study, a representative sample of the US population. RESULTS: The percentage of US adults with depression increased significantly from 8.7% (95% CI[7.6%-9.8%]) in 2017-2018 to 10.6% (95% CI[9.6%-11.6%) in March, 2020 and 14.4% (95% CI[13.1%-15.7%]) in April, 2020. Statistically significant increases in depression levels were observed for all population subgroups examined with the exception of those aged 65+ years and Black participants. Young adults (aged 18-34) experienced a marked increase in depression of 13.4 percentage points (95% CI [9.5%-17.2%]) that was larger than any other age group. Additional analyses of depression trends in NHANES from 2007/2008-2017/2018 showed that the substantial increase in depression in April, 2020 was unlikely to be due to typical year-to-year variation. CONCLUSIONS: Our findings suggest that depression levels have risen substantially during the COVID-19 pandemic and reinforce recent findings indicating that young adults may be particularly vulnerable to the mental health effects of the pandemic.

Coronavirus disease 2019 and the associated social distancing and lockdown restrictions are expected to have substantial and enduring mental health effects. In this study, we aimed to assess depression levels before and during the COVID-19 pandemic in the United States.

We used the Patient Health Questionnaire-2 (PHQ-2) brief screening instrument to detect probable depression in two nationally representative surveys of US adults. Pre-pandemic levels of depression were assessed in a sample of 5,075 adults from the 2017-2018 National Health and Nutrition Examination Survey (NHANES). Depression was assessed in March (N=6,819) and April, 2020 (N=5,428) in the Understanding America Study, a representative sample of the US population.

The percentage of US adults with depression increased significantly from 8.7% (95% CI[7.6%-9.8%]) in 2017-2018 to 10.6% (95% CI[9.6%-11.6%) in March, 2020 and 14.4% (95% CI[13.1%-15.7%]) in April, 2020. Statistically significant increases in depression levels were observed for all population subgroups examined with the exception of those aged 65+ years and Black participants. Young adults (aged 18-34) experienced a marked increase in depression of 13.4 percentage points (95% CI [9.5%-17.2%]) that was larger than any other age group. Additional analyses of depression trends in NHANES from 2007 NHANES from /2008 NHANES from -2017 NHANES from /2018 showed that the substantial increase in depression in April, 2020 was unlikely to be due to typical year-to-year variation.

The COVID-19 crisis has impacted daily life for much of the world's population and this may have adversely affected mental health (Holmes et al., 2020) . However, quantification of the impact that the COVID-19 crisis has had on mental health has been difficult as there has been an absence of large-scale nationally representative probability-based studies contrasting mental health before vs. during the COVID-19 pandemic (Pierce et al., 2020) .

In the US, on March 16 th the president requested that Americans limit non-essential travel, avoid bars and restaurants and gatherings of more than ten people, and recommended the closure of schools and universities. This was followed by announcements of mandatory stay-at-home orders from individual states commencing with California on March 19th and spreading to 73% (2,355 of 3,233) of counties across US states and territories by March 31st (Moreland et al., 2020) . During this period there was a rapid rise in COVID-19 cases from under 10,000 confirmed cases on March 19th to 164,620 by March 31st (OWID, 2020). We suggest that the surge in cases coupled with the commencement of social lockdown restrictions towards the end of March may have adversely impacted mental health by April, 2020.

Already a US study has utilized nationally representative samples to show that the prevalence of psychological distress was higher in April 2020 compared to (McGinty et al., 2020 and a similar increase in distress was observed in a longitudinal study of adults in the UK (Daly et al.,2020) . Studies sampling young adults in China (Li et al., 2020) and Switzerland Elmer et al., 2020) have also found an increase in depression during the early stages of the pandemic. In the current study, we examined two US probability-based samples to compare depression levels assessed in 2017-2018 with levels in April, 2020 when the 6 COVID-19 crisis was unfolding. We examined the magnitude of increases in depression during the pandemic and whether increases in depression varied across population subgroups.

The Understanding America Study (UAS) is a national probability-based longitudinal internet panel study. Participants were recruited via address-based sampling using the US Postal Service Computerized Delivery Sequence file covering almost 100% of US households (Alattar et al., 2018) . Those without internet access were provided with internetconnected tablets to ensure sample representativeness. In this study we conducted secondary analysis of the UAS anonymized microdata files which did not require institutional approval from the [removed for anonymity] Ethics Sub-Committee. Depression levels in the UAS were contrasted with levels in the National Health and Nutrition Examination Survey (NHANES) 2017-2018 wave (Chen et al., 2020) , a second nationally representative probability-based sample of the US population (N=5,075) including identical depression items. In addition, we examined recent trends in depression using six waves of NHANES data (2007/2008, 2009/2010, 2011/2012, 2013/2014, 2015/2016, 2017/2018) The NHANES and UAS samples were comparable on gender, household income, and Hispanic, White, and Black ethnicity. The NHANES sample included a larger portion of individuals classified as ‗other race/ethnicity' and was slightly younger and included a lower portion of college educated participants. These sample composition differences between NHANES and UAS were adjusted for in all analyses.

In both surveys, participants reported their age (grouped into 18-34, 35-54, 55-64, & 65+ for depression comparisons), sex (male, female), and race/ethnicity (White, Hispanic, Black, other race/ethnicity), and their education (college degree, no degree), and household income levels. In NHANES household income was assessed using income brackets ranging from 1 = $0-$4,999 to 12 = ≥$100,000 and in the UAS income brackets ranged from 1 = $0-$4,999 to 16 = ≥$150,000. To generate a comparable continuous household income variable across samples participants were assigned the value of each income bracket mid-point (e.g. $0-$4,999 assigned a value of $2,500) or the highest income level assessed if applicable.

Income data was missing for a notable portion of the NHANES sample (13.8%) and this group were assigned the mean income value and a dummy variable was included to adjust for differences in depression between those with/without available income data.

Depression was measured using the Patient Health Questionnaire-2 (PHQ-2) a reliable short screening tool for assessing depression levels in the general population (Kroenke et al., 2003) . Participants were asked -Over the last 2 weeks, how often have you been bothered by the following problems?‖ and responded to two items (-Feeling down, depressed, or hopeless‖ and -Little interest or pleasure in doing things‖) on a scale with the response options -not at all‖, -several days‖, -more than half the days‖, and -nearly every day‖, that are scored as 0,1,2, and 3, respectively. This gives a score from 0-6 and scores of ≥3 are the validated threshold for detecting probable cases of depression (Carey et al., 2016; Lowe et al., 2010; Kroenke et al., 2003) . This threshold has been shown to optimally balance sensitivity (.91) and specificity (.78) for identifying probable cases of depression (Carey et al., 2016) . A 2016 aggregate-data diagnostic meta-analysis examined the ≥3 cut-off in 19 studies and found a sensitivity level of .76 and specificity level of .87 (Manea et al., 2016) .

In NHANES 2017-2018 the PHQ-2 items formed the first two items of the PHQ-9 (Carey et al., 2016) . In this sample, 8.9% (95% CI[7.8%-10.1%]) of the sample were classified as experiencing depression using the PHQ-2 and 8.6% (95% CI[7.5%-9.7%]) when using the PHQ-9 with the recommended cut-off of ≥10 for moderate depression (Carey et al., 2016) . The correlation between the PHQ-2 and PHQ-9 total scores was very strong (r=0.83, 95% CI[.81-.84]), supporting the validity of the PHQ-2 as a measure of depression in this sample.

First, we examined the demographic characteristics and depression levels of the NHANES and UAS March and April 2020 samples. We then merged the NHANES and UAS datasets and used logistic regression analysis to estimate whether depression levels during the 9 pandemic were statistically different to baseline levels in 2017-2018 after adjustment for any differences in demographic characteristics between the samples. Estimates were calculated first for the entire sample and then for each population subgroup examined. To estimate differences in the predicted probability of depression across time-points and subgroups we used the Stata margins and lincom postestimation commands (Long & Freese, 2014) .

Predicted probabilities were multiplied by 100 to generate percentage point estimates.

Finally, to contextualize our estimates we drew on six waves of NHANES data (2007/2008, 2009/2010, 2011/2012, 2013/2014, 2015/2016, 2017/2018) 

An examination of the descriptive trends in the data showed that between 2017-2018 and April, 2020 the PHQ-2 total score increased by 0.4 points from 0.69 (SD=1.25) to 1.08 (SD=1.56) an increase of .32 standard deviations using 2017-2018 as a benchmark (see Table  1 ). The percentage of US adults who reported depression (based on the PHQ-2 cut-off of ≥3) was 8.9% in 2017-2018 and subsequently increased to 10.5% in March, 2020 and 14.2% in April 2020, as shown in Table 1 .

Our logistic regression analyses showed that after adjustment for differences in demographic characteristics between the two samples depression increased from 8.7% (95% CI[7.6%-9.8%]) in 2017-2018 to 10.6% (95% CI[9.6%-11.6%) in March, 2020 and 14.4% (95% CI[13.1%-15.7%]) in April, 2020 ( Table 2 ). The 1.9 percentage point (95% CI[0.3%-3.5%]) increase in depression from 2017-2018 to March, 2020 was statistically significant at the p<.05 level and the 5.7 percentage point (95% CI[3.9%-7.5%]) increase from 2017-2018 to April, 2020 was statistically significant at the p<.001 level.

April, 2020 were identified for all population subgroups examined with the exception of those aged 65 years and over and Black participants (see Table 2 ). Depression levels rose most sharply amongst younger adults aged 18-34 years increasing from a baseline of 8% (95% CI[6.2%-9.9%]) in 2017-2018 to 21.4% (95% CI[17.9%-24.8%]) in April 2020, a statistically significant difference of 13.4% (95% CI [9.5%-17.2%]) (see Table 2 ). Additional analyses showed that this substantial increase was significantly larger than the increase in depression experienced by other age groups (Table S1 ).

Other groups that experienced notable increases in depression were: Hispanic (8.3%, 95% CI[3.9-12.7]) and other ethnicity/race participants (10%, 95% CI[3.5-16.6), those with a college degree (8.6%, 95% CI[5.0-12.1), and females (6.1%, 95% CI[3.7-8.6]). However, the difference in the increase in depression between Hispanic and other ethnicity/race participants and White participants was not statistically significant, nor was the difference in the increase between males and females or those with a college degree and participants without a degree, as shown in Table S1 .

In NHANES depression varied little across previous waves and was lowest in (Table S2 ). These analyses indicated that estimates of the population prevalence of depression in the US as gauged using the PHQ-2 or PHQ-9 were highly stable in the years preceding the COVID-19 crisis.

Depression increased substantially from 2017-2018 to April 2020 following the emergence of the COVID-19 pandemic and rises in depression were particularly pronounced in younger adults, which corroborates other emerging studies (Daly et al., 2020; McGinty et al., 2020) .

The increase in depression observed among young adults in the present study are broadly comparable to that observed in studies of young adults in China and Switzerland (Li et al., 2020; Elmer et al., 2020) .

Young adults are also disproportionally more likely to work in sectors of the economy that were shut down during the pandemic (e.g. retail, restaurants, leisure facilities) (Joyce & Xu, 2020) . The associated financial insecurity and job loss experienced by many young people may have contributed to the sustained rise in depression levels observed in this study (Paul & Moser, 2009) . As many young adults may be experiencing mental health difficulties for the first time during the pandemic, both prevention and early treatment of mental health in the community remains important during the COVID-19 pandemic (Holmes et al., 2020) . In contrast, those aged 65+ and Black participants reported low levels of depression during the pandemic. A recent study (Czeisler, 2020) found a small increase in the likelihood of trauma and stress-related disorder associated with the pandemic among non-Hispanic Black groups compared to non-Hispanic Whites during the COVID-19 pandemic. In this study we identified a small decrease in depression among non-Hispanic Black participants from 2017-2018 to April, 2020. Further research examining the role of race/ethnicity and mental health during COVID-19 will be valuable to better understand such unexpected findings.

A strength is that we drew on nationally representative probability-based samples that included the same measure of depression at both time-points enabling meaningful estimates of population prevalence to be generated. In addition, we tested whether the pandemic is likely to have disproportionately affected specific population subgroups. By examining PHQ-2 scores from 2007-2018 we also demonstrate that variation in population depression levels is typically minimal and contrasts sharply with the large increase observed during the pandemic.

It is important to note that whilst both the NHANES and UAS utilize probabilitybased samples they differ in their sampling and mode of administration which may bias contrasts between cohorts. The UAS also included a larger portion of participants with a college degree and a smaller portion from ethnic/racial minority groups than the NHANES 13 sample. However, we were able to adjust for these differences in sample characteristics and also show that an increase in depression was evident from March to April, 2020 when the UAS sample alone was examined.

In addition, our analyses of prior depression trends suggest that the change in depression levels is atypical and unlikely to be explained fully by these differences. Whilst the PHQ-2 is a reliable and well-validated screening instrument for detecting probable depression, longer scales would yield insight into the robustness of the trends examined. It will also be important to understand mental health trends as the COVID-19 pandemic progresses and to understand how these trends are modified by differences in COVID-19 infection and mortality rates and differences in the timing of stay-at-home orders across US states. a Simple linear regression analysis was used to test for differences in age, income, and depression (mean levels) between study 2017-2018 and March/April, 2020. Binary and multinomial logistic regression analyses were used to test for differences in sex, race/ethnicity, education, and depression (%) between 2017 and March/April, 2020.

*p < .05. **p < .01. ***p < .001. Table 2 Regression estimates of depression levels in the NHANES 2017-2018 sample (N = 5,075) and the Understanding America Study March (N = 6,819) and April 2020 assessments (N = 5,428) and percentage point differences in depression between the study samples.

Year 

An introduction to the Understanding America Study Internet panel

Sampling and weighting the Understanding America Study

Validation of the PHQ-2 against the PHQ-9 for detecting depression in a large sample of Australian general practice patients

National Health and Nutrition Examination Survey

Mental health, substance use, and suicidal ideation during the COVID-19 pandemic -United States

Longitudinal changes in mental health and the COVID-19 pandemic: Evidence from the UK Household Longitudinal Study

Students under lockdown: Comparisons of students' social networks and mental health before and during the COVID-19 crisis in Switzerland

Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science

Sector shutdowns during the coronavirus crisis: which workers 16

The Patient Health Questionnaire-2: validity of a two-item depression screener

The psychological impacts of a COVID-19 outbreak on college students in China: A longitudinal study

Regression models for categorical dependent variables in Stata

A 4-item measure of depression and anxiety: validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population

Identifying depression with the PHQ-2: A diagnostic meta-analysis

Psychological distress and loneliness reported by US Adults

Timing of state and territorial COVID-19 stay-at-home orders and changes in population movement-United States

United States: What is the daily number of confirmed cases?

Unemployment impairs mental health: Meta-analyses

Says who? The significance of sampling in mental health surveys during COVID-19. Lancet Psychiat

Note: Estimates are from marginal effects calculated after logistic regression analysis adjusting for the covariates shown in the table. a Column displays the magnitude and statistical significance of the difference in depression levels between

The project described in this paper relies on data from survey(s) administered by the Understanding America Study, which is maintained by the Center for Economic and Social Aging. We are also grateful to the Centers for Disease Control and Prevention's (CDC) 14 National Center for Health Statistics (NCHS) for their management of the Nutrition Examination Surveys (NHANES) and making the data available. However, these organizations bear no responsibility for the analysis or interpretation of the data.

Our findings indicate that depression increased by over 60% from pre-pandemic levels of under 9% in 2017-2018 to over 14% in April 2020 among US adults, and provide further evidence that young adults may be most vulnerable to the mental health effects of the pandemic.