Highlights
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A large electronic health record study of smoking, alcohol use, and depression in community-based clinics was conducted.
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Smoking was associated with likelihood of alcohol use disorder and depression; it increased with COVID-19 public health emergency.
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There was a higher likelihood of alcohol use disorder in men and depression in women; the greatest impact was observed in the smoking cohort.
Keywords: COVID-19 pandemic, alcohol use disorder, depression, smoking, tobacco use, primary care, behavioral health
Abstract
Introduction
The clustering of smoking, alcohol use disorder, and depression is associated with increased health risks and mortality. The COVID-19 pandemic caused significant disruption, with unknown implications for alcohol use disorder and depression diagnoses among patients who smoke. This study assessed changes in the prevalence of alcohol use disorder and depression diagnoses in patients at community-based healthcare organizations before and during the COVID-19 public health emergency, by smoking status and sex.
Methods
A retrospective cohort study was conducted using electronic health record data from community-based primary care and behavioral health clinics (n=766 clinics in 19 states) in the U.S. Outcomes included the covariate-adjusted probability of alcohol use disorder diagnosis, depression diagnosis, and comorbid diagnoses in 2019 and 2022, stratified by smoking status and sex.
Results
In both years, alcohol use disorder and depression diagnoses were higher among patients who were smoking (n=57,351 patients) than among those who were not (n=304,405 patients). The likelihood of alcohol use disorder, depression, or co-occurring alcohol use disorder and depression diagnoses increased from 2019 to 2022 among both sexes and all smoking statuses, with larger increases seen among patients who were smoking. The largest change was in depression among currently smoking females, rising from 35.2% to 41.7% (absolute difference=6.4%, 95% CI=5.8%, 7.1%).
Conclusions
The COVID-19 pandemic was associated with a greater burden of alcohol use disorder and depression diagnoses among patients seen in community-based clinics, with larger differences among those who currently smoke than among those who do not. Males had the largest increase in alcohol use disorder diagnoses, and females had the largest increase in depression diagnoses. These results support the need for a coordinated, integrated healthcare approach addressing the clustering of smoking, alcohol use, and depression in populations already facing elevated social and health risks, particularly during times of high stress, such as pandemics and other public health emergencies.
INTRODUCTION
The clustering of smoking, alcohol use disorder (AUD), and depression is associated with increased health risks and mortality.1, 2, 3 Temporal patterns of development of these 3 conditions suggest that they coexist over time.4 Each condition has been shown to be associated with the others, such that the presence of one often coincides with both the current and future presence of the others. Likewise, resolution in one condition frequently aligns with improvements in the others.4 During the coronavirus disease 2019 (COVID-19) pandemic public health emergency (PHE), observed elevations of general stress and isolation could have exacerbated these conditions. Existing literature suggests that the pandemic impacted smoking5 and alcohol use behaviors6,7 as well as depressive symptoms.8 Specifically, increases in alcohol consumption and depressive symptoms were observed, with women experiencing more significant increases than men in some cases.7,9, 10, 11, 12 Many people who smoked tended to increase their smoking rate during the pandemic, especially those reporting high levels of stress.13,14 Furthermore, a recent national study found that people who smoked prior to the pandemic tended to smoke more cigarettes per day and were less likely to quit smoking during the pandemic.15
Current literature related to the impact of the COVID-19 pandemic on the associations between smoking and AUD or depression is limited. Existing studies are predominantly survey based, with small sample sizes limited to specific populations, generally early in the pandemic timeline.16, 17, 18 Schäfer et al.18 analyzed data from 2 population-based studies in Brazil and found that consumption of alcohol and cigarettes was higher among those with depressive symptoms, feelings of sadness, and self-reported stress during the first year of the COVID-19 pandemic. Stanton and colleagues16 analyzed survey data from 1,491 Australian adults and found that adverse changes in physical activity, sleep, smoking, and alcohol intake were associated with higher depression, anxiety, and stress symptoms in the first months of the pandemic. Habtemariam et al.17 found in a Midwest population that younger female participants with elevated financial and employment concerns during the pandemic were more likely to report increased alcohol or tobacco use during the pandemic.
These studies lack information on patients seen at community-based healthcare organizations in the U.S. Patients seen at community-based healthcare organizations represent a critical population in which to examine these relationships, and the authors are unaware of prior studies that have done so. Among this high-risk population, the relationship of smoking status and co-occurring AUD or depression and the impact of the COVID-19 pandemic on that relationship are unknown. Because assessment and treatment of AUD, depression, and tobacco cessation are commonly addressed in this setting, understanding changes in their prevalence and co-occurrence is especially important. Smoking is singled out for analysis because it may act as a behavioral marker or amplifier of vulnerability, given its strong associations with both AUD and depression and its higher prevalence in populations with greater socioeconomic disadvantage.1, 2, 3, 4,19 Furthermore, smoking status is documented for nearly all patients seen in the study clinics because it is routinely asked during the rooming process.
This study was undertaken to assess the changes in AUD and depression diagnoses before and during the COVID-19 PHE and how this differed by smoking status and sex among patients seen in community-based healthcare organizations using a large electronic health record (EHR) data source. The authors hypothesized that the prevalence of these diagnoses would increase during the COVID-19 PHE, with a more pronounced increase among patients who smoke compared with those who do not. The secondary hypothesis stated that there would be differences by sex in the probabilities of these disorders, with greater increases in AUD and depression among females than among males during the COVID-19 PHE.
METHODS
This study was conducted using EHR data from OCHIN Epic As a national nonprofit information technology consultancy, OCHIN provides a fully hosted and shared single instance of the OCHIN Epic EHR platform for a nationwide network of community-based healthcare organizations that is part of the ADVANCE (Accelerating Data Value Across a National Community Health Center Network) Clinical Research Network, which is led by OCHIN as a member of PCORnet. OCHIN’s EHR platform is shared by more than 33,000 providers to support connected, whole-patient care for more than 6 million people in rural and medically underserved communities nationwide. Community-based healthcare organizations in the OCHIN network include but are not limited to federally qualified health centers, rural health centers, behavioral health providers, and public health departments. This study was approved by the IRB of Oregon Health & Science University.
Study Population
The population included adult patients (aged ≥18 years) receiving care at OCHIN-affiliated clinics (including not-for-profit organizations, federally qualified health centers, rural health clinics, and county clinics) between January 1, 2019 and December 31, 2019 and between January 1, 2022 and December 31, 2022. Patients were eligible for inclusion if they had at least 1 ambulatory (in-person) or telehealth visit in 2019 (before pandemic) and at least 1 visit in 2022 (during the COVID-19 PHE) in a family practice, primary care, internal medicine, psychiatry, mental health, or behavioral health clinic with primary care or behavioral health clinical team members (e.g., MD, MA, DNP). Visits included those for primary care, defined using primary care evaluation and management billing codes and behavioral health billing codes, as defined in previous research using data from this network (Appendix Table 1, available online). To be included in the study cohort, patients had to have a documented smoking status in the EHR in both years.
Measures
Smoking status was used as a stratification variable to examine AUD and depression before and during the COVID-19 PHE. To determine the smoking versus nonsmoking cohorts, smoking status was derived from structured vital signs. Patients who had current smoking recorded in both 2019 and 2022 were included in the smoking cohort, whereas the nonsmoking cohort was comprised of patients with statuses of never or former smoker in both years.
The primary outcomes included the prevalence of (1) AUD, (2) depression, and (3) comorbid AUD and depression diagnoses in 2019, 2022, or both. AUD and depression were identified using ICD-10 diagnosis codes.
The main independent variable was a binary indicator for sex (male/female) for the main analysis. Other sex was included descriptively but was not included in the adjusted analyses because of the small sample size.
Patient-level EHR covariates included age (18–24, 25–34, 35–44, 45–54, 55–64, and ≥65 years), race (American Indian or Alaska Native, Asian, Black or African American, Native Hawaiian or Other Pacific Islander, White, multiple race, or unknown race), ethnicity (Hispanic, non-Hispanic, or unknown), insurance/payor (from the majority of visits if more than 1 type was used; Medicaid, Medicare, other public or private, or uninsured), household income as a percentage of the federal poverty level (ever above 138%, always below 138%, or always missing), chronic conditions identified by ICD-10 diagnostic codes from patients’ problem lists (cancer, chronic respiratory disease [i.e., chronic obstructive pulmonary disease or asthma], cardiovascular disease [chronic heart disease or chronic heart failure], and cardiovascular disease risk factors [diabetes, hyperlipidemia, or hypertension]), number of visits, state of the patient’s most visited clinic (listed in Table 1 notes), and clinic rurality. Rurality was defined using 2010 Rural-Urban Commuting Area codes associated with the patient’s most often visited clinic (urban [including metropolitan and micropolitan area cores], rural [including small towns and rural areas], or missing).20
Table 1.
Characteristics of Patients Receiving Primary and Mental/Behavioral Health Care in Both 2019 and 2022, Stratified by Smoking Status, Reported in 2019 and 2022 (N=361,756)
| Baseline year (2019) |
Final study year (2022) |
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|---|---|---|---|---|
| Characteristics | Not smoking | Smoking | Not smoking | Smoking |
| n | 304,405 | 57,351 | 304,405 | 57,351 |
| Sex | ||||
| Female | 199,949 (65.7) | 29,252 (51.0) | ||
| Male | 104,307 (34.3) | 28,069 (48.9) | ||
| Other (not in adjusted analysis) | 149 (0.0) | 30 (0.1) | ||
| Race | ||||
| American Indian or Alaska Native | 2,995 (1.0) | 677 (1.2) | ||
| Asian | 27,331 (9.0) | 2,339 (4.1) | ||
| Black or African American | 51,078 (16.8) | 14,709 (25.6) | ||
| Multiple race | 2,687 (0.9) | 749 (1.3) | ||
| Native Hawaiian or Other Pacific Islander | 908 (0.3) | 154 (0.3) | ||
| White | 193,382 (63.5) | 36,232 (63.2) | ||
| Unknown | 26,024 (8.5) | 2,491 (4.3) | ||
| Hispanic ethnicity | ||||
| No | 174,456 (57.3) | 47,214 (82.3) | ||
| Yes | 113,730 (37.4) | 7,370 (12.9) | ||
| Unknown | 16,219 (5.3) | 2,767 (4.8) | ||
| Variable characteristics | ||||
| Age category, years | ||||
| 18–24 | 24,922 (8.2) | 1,997 (3.5) | 14,918 (4.9) | 877 (1.5) |
| 25–34 | 44,749 (14.7) | 8,253 (14.4) | 40,594 (13.3) | 6,540 (11.4) |
| 35–44 | 54,241 (17.8) | 11,149 (19.4) | 51,844 (17.0) | 10,646 (18.6) |
| 45–54 | 60,886 (20.0) | 14,289 (24.9) | 59,346 (19.5) | 12,788 (22.3) |
| 55–64 | 63,064 (20.7) | 16,041 (28.0) | 63,825 (21.0) | 17,418 (30.4) |
| ≥65 | 56,543 (18.6) | 5,622 (9.8) | 73,878 (24.3) | 9,082 (15.8) |
| Insurance | ||||
| Medicaid | 12,2707 (40.3) | 30,807 (53.7) | 129,149 (42.4) | 30,554 (53.3) |
| Medicare | 61,328 (20.1) | 11,534 (20.1) | 74,944 (24.6) | 14,482 (25.3) |
| Other Public | 13,020 (4.3) | 783 (1.4) | 6,548 (2.2) | 372 (0.6) |
| Private | 65,671 (21.6) | 8,208 (14.3) | 61,670 (20.3) | 8,177 (14.3) |
| Uninsured | 41,679 (13.7) | 6,019 (10.5) | 32,094 (10.5) | 3,766 (6.6) |
| Income as percentage of FPL | ||||
| Always below 138 | 181,146 (59.5) | 36,854 (64.3) | 190,655 (62.6) | 37,608 (65.6) |
| Ever above 138 | 59,364 (19.5) | 9,093 (15.9) | 51,312 (16.9) | 10,340 (18.0) |
| Always missing | 63,895 (21.0) | 11,404 (19.9) | 62,438 (20.5) | 9,403 (16.4) |
| Urban/rural status of patient's primary clinic | ||||
| Rural | 60,685 (19.9) | 12,892 (22.5) | 60,954 (20.0) | 12,906 (22.5) |
| Urban | 238,797 (78.4) | 43,204 (75.3) | 238,406 (78.3) | 43,240 (75.4) |
| Missing | 4,923 (1.6) | 1,255 (2.2) | 5,045 (1.7) | 1,205 (2.1) |
| Ever had cancer | 11,923 (3.9) | 2,140 (3.7) | 11,923 (3.9) | 2,140 (3.7) |
| Ever had respiratory diseasea | 42,334 (13.9) | 16,849 (29.4) | 42,334 (13.9) | 16,849 (29.4) |
| Ever had cardiovascular diseaseb | 193,011 (63.4) | 37,967 (66.2) | 193,011 (63.4) | 37,967 (66.2) |
| Mean visits (SD) | 3.85 (4.32) | 5.08 (6.92) | 4.20 (4.69) | 5.20 (6.72) |
Note: Clinic states include Alaska, California, Colorado, Connecticut, Georgia, Idaho, Indiana, Louisiana, Massachusetts, Minnesota, Missouri, Montana, North Carolina, Ohio, Oregon, South Carolina, Texas, Washington, and Wisconsin.
Respiratory disease includes chronic obstructive pulmonary disease and asthma.
Cardiovascular disease includes chronic heart disease, chronic heart failure, diabetes, hyperlipidemia, and hypertension.
FPL, federal poverty level.
Statistical Analysis
Descriptive statistics were used to estimate the annual unadjusted prevalence of AUD, depression, and comorbid AUD and depression, stratified by smoking status and sex for each year. A difference-in-differences framework was used to evaluate changes in each of the 3 outcomes over time: (1) AUD, (2) depression, and (3) comorbid AUD and depression. Linear regression modeling was used to estimate the risk difference (RD) and corresponding 95% CI for each outcome between 2019 and 2022 (before and during the COVID-19 PHE) for females and males, with separate models for those identified as currently smoking and those not currently smoking. All models accounted for clustering by clinic using robust SEs. Adjusted probabilities are reported. Analyses were conducted using Stata, Version 17 (StataCorp LLC), with statistical significance defined as alpha <0.05.
RESULTS
The final analytic cohort comprised 361,756 unique adult patients who received care in study clinics in both 2019 and 2022 across 766 facilities in 19 states, contributing 3,040,470 ambulatory and telehealth encounters. Of the patient cohort, 57,351 (15.9%) were assessed as currently smoking in both years, and 304,405 (84.1%) were assessed as not smoking in both years. Among those who smoked, 51.0% were female, and 48.9% were male (Table 1). The smoking cohort had a higher proportion of Black patients (25.6% vs 16.8%) and a lower proportion of Asian (4.1% vs 9.0%) and Hispanic patients (12.9% vs 37.4%) than the nonsmoking cohort. The smoking cohort had a higher proportion of patients with incomes below 138% federal poverty level, more frequently received care at clinics in rural areas, had a higher prevalence of respiratory or cardiovascular disease, and had a higher mean visit count than the nonsmoking cohort.
Table 2 and Figure 1 show the unadjusted prevalence of AUD, depression, and comorbid AUD and depression by smoking status and sex before and during the COVID-19 PHE. AUD and depression were higher among people who smoked than among those who did not smoke. The unadjusted prevalence of AUD increased overall among those who were smoking (10.4% to 13.2%) and among those who were not smoking (2.1% to 2.7%). Among those who smoked, depression also increased overall, from 30.1% to 35.8%. Among those who were not smoking, the prevalence of depression increased overall from 18.2% to 22.3%, with increases seen among both sexes. Comorbid AUD and depression increased among those who were smoking (from 4.8% to 6.7% overall) and among those who were not smoking (from 0.9% to 1.2%).
Table 2.
Unadjusted Prevalence of Alcohol Use Disorder, Depression, and Both, Stratified by Smoking Status and Sex, Among All Patients Receiving Primary or Mental/Behavioral Care in Both 2019 and 2022
| Among people currently smoking in both years |
Among those who were not currently smoking in both years |
|||||||
|---|---|---|---|---|---|---|---|---|
| Diagnosis | Overall, n (%) |
Female, n (%) |
Male, n (%) |
Other, n (%) |
Overall, n (%) |
Female, n (%) |
Male, n (%) |
Other, n (%) |
| 2019 (n=57,351) | 2019 (n=304,405) | |||||||
| AUD prevalence | 5,893 (10.4) | 2,265 (7.7) | 3,716 (13.2) | <11 | 6,233 (2.1) | 2,031 (1.0) | 4,197 (4.0) | <11 |
| Depression prevalence | 17,252 (30.1) | 10,605 (36.3) | 6,637 (23.7) | <11 | 55,374 (18.2) | 40,338 (20.2) | 14,975 (14.4) | 61 (40.9) |
| Prevalence of both | 2,723 (4.8) | 1,221 (4.2) | 1,501 (5.4) | <11 | 2,608 (0.9) | 1,158 (0.6) | 1,446 (1.4) | <11 |
| 2022 (n=57,351) | 2022 (n=304,405) | |||||||
| AUD prevalence | 7,582 (13.2) | 2,913 (10.0) | 4,665 (16.6) | <11 | 8,144 (2.7) | 2,730 (1.4) | 5,407 (5.2) | <11 |
| Depression prevalence | 20,514 (35.8) | 12,508 (42.8) | 7,993 (28.5) | 13 (43.3) | 67,773 (22.3) | 49,217 (24.6) | 18,484 (17.7) | 72 (48.3) |
| Prevalence of both | 3,840 (6.7) | 1,735 (5.9) | 2,104 (7.5) | <11 | 3,769 (1.2) | 1,702 (0.9) | 2,061 (2.0) | <11 |
Note: Cells with counts of less than 11 are masked to protect patient privacy.
Figure 1.
Unadjusted prevalence of diagnosis before and after COVID-19 pandemic by sex and smoking status.
AUD, alcohol use disorder.
The adjusted probabilities of AUD, depression, and co-occurring AUD and depression in 2022 were higher than in 2019 among both sexes in smoking and nonsmoking cohorts (Table 3). For females in the smoking cohort, the adjusted probability of AUD increased from 7.5% to 9.5% (RD=2.0%, 95% CI=1.7%, 2.4%), compared with that for males in this cohort, who started at a higher adjusted prevalence of alcohol use of 13.7% and had a greater increase to 17.0% (RD=3.3%, 95% CI=2.9%, 3.8%). In the nonsmoking cohort, increases by sex were similar to those in the smoking cohort, but the estimates were lower.
Table 3.
Changes in Alcohol Use Disorder, Depression, and Comorbid Alcohol Use Disorder and Depression Before and During the COVID-19 Public Health Emergency
| Alcohol use disorder |
Depression |
Alcohol use disorder and depression |
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|---|---|---|---|---|---|---|
| Cohorts | 2019 | 2022 | 2019 | 2022 | 2019 | 2022 |
| Patients currently smoking in both periods | ||||||
| Sex | ||||||
| Female | ||||||
| Adjusted probability | 7.5% | 9.5% | 35.2% | 41.5% | 4.0% | 5.7% |
| 2019 versus 2022, risk difference (95% CI) | 2.0% (1.7%, 2.4%) | 6.4% (5.8%, 7.1%) | 1.7% (1.4%, 2.0%) | |||
| Male | ||||||
| Adjusted probability | 13.7% | 17.0% | 24.6% | 29.7% | 5.6% | 7.8% |
| 2019 versus 2022, risk difference (95% CI) | 3.3% (2.9%, 3.8%) | 5.1% (4.4%, 5.8%) | 2.2% (1.8%, 2.6%) | |||
| Patients not currently smoking in both periods | ||||||
| Sex | ||||||
| Female | ||||||
| Adjusted probability | 1.1% | 1.4% | 20.8% | 24.4% | 0.6% | 0.8% |
| 2019 versus 2022, risk difference (95% CI) | 0.2% (0.2%, 0.3%) | 3.6% (3.3%, 4.1%) | 0.2% (0.2%, 0.2%) | |||
| Male | ||||||
| Adjusted probability | 3.9% | 5.1% | 14.0% | 17.2% | 1.3% | 1.9% |
| 2019 versus 2022, risk difference (95% CI) | 1.1% (0.9%, 1.3%) | 3.1% (2.7%, 3.6%) | 0.6% (0.5%, 0.7%) | |||
Note: Difference-in-difference linear regression model adjusted for age, race, Hispanic ethnicity, insurance, income as a percentage of the federal poverty level, cancer, cardiovascular disease, respiratory conditions, number of clinic visits, clinic rurality, and clinic state, with clustering by patients most visited clinic.
In the smoking cohort, females had a higher adjusted probability of depression than males in both years. The adjusted probability of depression increased for both females and males, with a larger increase among females (from 35.2% to 41.7% [RD=6.4%, 95% CI=5.8%, 7.1%] and from 24.6% to 29.7% [RD=5.1%, 95% CI=4.4%, 5.8%], respectively). Among those who were not smoking, the estimates were lower than those in the smoking cohort but followed a similar pattern.
In the smoking cohort, females had a lower adjusted probability of co-occurring AUD and depression than males in both years. For both females and males, these probabilities increased over time (from 4.0% to 5.7% [RD=1.7%, 95% CI=1.4%, 2.0%] and from 5.6% to 7.8% [RD=2.2%, 95% CI=1.8%, 2.6%], respectively), with a slightly greater increase seen among males. Among those who were not smoking, the estimates of AUD plus depression were lower than those in the smoking cohort but followed a similar pattern.
DISCUSSION
Findings suggest that AUD and depression diagnoses increased during the COVID-19 PHE for patients seen in community-based primary care and behavioral health clinics (e.g., federally qualified health centers, rural health centers). Although the highest RD was 6% (depression diagnosis among females who smoke), even these seemingly modest increases are meaningful from a public health perspective.21 Increases in AUD and depression among those who smoked are consistent with prior literature reporting increased alcohol use and depression symptoms during the pandemic.6,7,12,22,23 This previous literature is survey based and focused on the immediate impacts of social isolation and other pandemic disruptions, whereas this is the first known study to examine these changes among a large population of patients seen in community-based primary care and behavioral health clinics and to investigate changes further into the COVID-19 PHE. This population has substantially higher levels of AUD and depression than the general U.S. adult population, for which the prevalence of AUD and depression has been reported at levels of 10.3% and 8.3%, respectively.24,25 Thus, it is imperative that patients in these community-based settings are screened for and have access to evidence-based treatment for these disorders.
Consistent with the literature on the syndemic of AUD, smoking, and depression,1, 2, 3 both male and female patients who were smoking in both years were more likely to have AUD and depression diagnoses both before and during the COVID-19 PHE than those who were not smoking. Furthermore and importantly, greater increases in the probability of these diagnoses during the COVID-19 PHE were seen among the smoking cohort than among the nonsmoking cohort. This is the first known study to examine these patterns of AUD and depression by smoking status and sex. By 2022, more than 4 in 10 females and nearly 3 in 10 males who smoked had received a diagnosis of depression in their health records compared with more than 2 in 10 females and nearly 2 in 10 males who did not smoke. These findings highlight the importance of screening for co-occurring alcohol use and depression, especially among those who smoke.
The secondary hypothesis, that females would have greater increases in AUD and depression during the COVID-19 PHE than males, was partially supported. There were impacts on both males and females, but with males more impacted by AUD and females more impacted by depression. Some previous studies exploring syndemic smoking, AUD, and depression included predominantly patients with HIV and largely male veteran populations.1, 2, 3, 4 Other survey-based early pandemic literature suggested that pandemic effects on alcohol use were particularly influential for females but relied on reported increases in quantities of alcohol consumed or drinking days rather than AUD diagnoses.6,7,12 This study expands on this inquiry in a community-based clinical setting and therefore explores variations by sex and by clinical diagnosis rather than only self-reported use. Documentation of AUD in the medical record requires alcohol use causing negative impacts on health and role fulfillment, which may continue to be more common among men.24 Future research is needed to determine whether males and females were screened at the same rate for AUD and depression.
Limitations
Despite including a large population of patients throughout the U.S., this study has some limitations. Although EHR data allow for a large sample size and tracking over time, the sample is limited to patients who are seeking care in community-based clinics. These patients may differ in significant ways from the general population with regard to health insurance, income, and other social determinants of health. In this analysis, patients had to be receiving care at a clinic using the OCHIN Epic EHR in both 2019 and 2022 and have the same recorded smoking status at those 2 time points. Thus, although this study provides insights into this population, future studies are needed to determine whether similar changes in AUD and depression are seen among patients who did not have continuity of care within the study clinics or who might have initiated, resumed, or quit smoking over time. Furthermore, it was not possible to assess whether AUD and depression were time limited for some patients, whereas these conditions might have persisted for others after pandemic. Future studies are warranted for a more nuanced examination of how these relationships persisted (or not) over time using more than 2 time points. Owing to the use of EHR data, the study was also limited to documentation of clinical diagnoses by medical or behavioral health providers. This may miss AUD or depression that were not asked about by the clinical team, were not reported by the patient, did not rise to the level of diagnostic criteria, or were not documented in the EHR.
CONCLUSIONS
This investigation found significant associations between smoking and an increased likelihood of AUD and depression among both male and female patients in community-based clinics, with an increased prevalence of these disorders during the COVID-19 PHE compared with that before the COVID-19 pandemic. Although the pandemic was unprecedented and had wide-ranging impacts, similar widespread stressors, such as a downturn in the economy, may also warrant more frequent assessments of AUD, depression, and smoking. Although all 3 conditions are associated with increased mortality, the key implication lies in applying lessons learned from the COVID-19 pandemic to develop stronger and more coordinated strategies for screening and treatment in future pandemics or public health emergencies.
Acknowledgments
ACKNOWLEDGMENTS
The authors acknowledge Heather Holderness, MPH, for her review of the manuscript.
Funding: Research reported in this publication was supported by the National Cancer Institute of the NIH under Award Numbers R01CA255016 (ClinicalTrials.gov Identifier: NCT04969978) and R01CA258464. The research reported in this work was powered by PCORnet. PCORnet has been developed with funding from the Patient-Centered Outcomes Research Institute and conducted with the ADVANCE (Accelerating Data Value Across a National Community Health Center Network) Clinical Research Network. ADVANCE is a Clinical Research Network in PCORnet led by OCHIN in partnership with Fenway Health, Health Choice Network, Oregon Health & Science University, and University of Washington. ADVANCE’s participation in PCORnet is funded through the Patient-Centered Outcomes Research Institute Award RI-OCHIN-01-MC.
Disclaimer: The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Declaration of interest: There are no declarations of interests to declare.
CRediT AUTHOR STATEMENT
AnnMarie Overholser: Investigation, Conceptualization, Methodology, Writing - original draft, Supervision, Writing - review & editing. Jennifer A. Lucas: Methodology, Data curation, Writing - original draft, Visualization, Formal analysis. Kristin Lyon-Scott: Software, Data curation, Writing - review & editing, Resources. Jennifer Hauschildt: Investigation, Writing - original draft, Visualization, Project administration, Writing - review & editing. Susan A. Flocke: Conceptualization, Methodology, Writing - review & editing. Hilary A. Tindle: Conceptualization, Methodology, Writing - review & editing. Jeremy Erroba: Investigation, Project administration. Miguel Marino: Methodology, Writing - review & editing. Steffani R. Bailey: Investigation, Funding acquisition, Conceptualization, Methodology, Writing - original draft, Supervision.
Footnotes
Supplementary material associated with this article can be found in the online version at doi:10.1016/j.focus.2026.100500.
Appendix. Supplementary materials
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