Purpose: To examine associations between state-level abortion restrictiveness and depression among female participants in a large, US sample surveyed from 1990 to 2015. Methods: Eligible participants were female respondents in the Monitoring the Future panel study followed from adolescence into adulthood (N = 19,881 female respondents with 50,995 unique observations). Depression symptoms were assessed using a four-item index. State-level restrictive abortion policy climate was quantified using an annual index of 18 policies, standardized across states and years. We modeled associations using log-binomial multilevel models, adjusting for individual (e.g., race/ethnicity, age, urbanicity) and state-level (e.g., unemployment, income inequality, political and legislative composition, demographic composition, gender wage gap) confounders. We conducted tests to assess robustness of findings, including using a negative control outcome (motor vehicle crashes), alternative populations (male respondents), and subgroup tests by religiosity. Results: A one-standard deviation increase in state abortion restrictiveness (equivalent to approximately 4 more restrictive laws) was associated with a 7% increase in depression symptoms among females (adjusted risk ratio [RR] = 1.07, 95% confidence interval [CI]: 1.02-1.11). As hypothesized, associations among our alternative sample were not statistically significant (males, RR = 1.03, 95% CI 0.99-1.08, though estimates did not statistically differ by sex) as were associations with our negative control outcome (motor vehicle crashes). As hypothesized, associations were most pronounced among female respondents reporting low religiosity (RR = 1.08, 95% CI: 1.01-1.15), and not significant among those reporting high religiosity. Conclusion: Restrictive abortion policies are associated with higher depression symptoms among women. Legal protections for reproductive health care may benefit mental health.

BACKGROUND:Large biobanks offer unprecedented data for psychiatric genomic research, but concerns exist about representativeness and generalizability. This study examined depression prevalence and polygenic risk score (PRS) associations in the All of Us data to assess potential impacts of nonrepresentative sampling. METHODS:Depression prevalence and correlates were analyzed in two subsamples: those with self-reported personal medical history (PMH) data (N = 185,232 overall; N = 114,739 with genetic data) and those with electronic health record (EHR) data (N = 287,015 overall; N = 206,175 with genetic data). PRS weights were estimated across ancestry groups. Associations of PRS with depression were examined by state and ancestry. RESULTS:Depression prevalence varied across states in both PMH (16.7-35.9%) and EHR (0.2-45.8%) data. Concordance between PMH and EHR diagnoses was low (kappa: 0.29, 95% CI: 0.30-0.30). Overall, one standard deviation increase in depression PRS was associated with lifetime depression based on PMH (odds ratio [OR] = 1.05, 95% confidence interval [CI]: 1.04-1.07) and EHR (OR = 1.05, 95% CI: 1.04-1.07). Results were generally consistent by ancestry, with the strongest signal for European ancestry (PMH: OR = 1.10, 95% CI: 1.08-1.12; EHR: OR = 1.07, 95% CI: 1.05-1.10). Associations between PRS and lifetime depression were largely consistent and significant associations varied minimally (ORs = 1.06-1.45) by state of residence in both subsamples. CONCLUSIONS:Recorded depression prevalence by state in All of Us demonstrates a wide range, likely reflecting recruitment differences, EHR data completeness, and true geographic variation; yet PRS associations remained relatively stable. As studies like All of Us expand, accounting for sample composition and measurement approaches will be crucial for generating actionable findings.

Study objective Even before the Dobbs Supreme Court decision, minors experienced a wide variety of barriers to abortion care in the United States, including legal, financial, cultural, transportation, and misinformation barriers as well as pressure from parents and partners. This scoping review summarizes the literature on barriers to abortion among minors in the United States prior to the Dobbs decision. Methods We conducted a database search to identify original research in the United States published between 2007 and 2022. We included quantitative and qualitative empirical articles and assessed their quality. We created categories for the barriers to abortion among minors identified in the articles. We screened 7584 records and included 70 articles in the scoping review. We charted study aims, study designs, data sources, analytic samples, and results. Results The articles explored factors related to abortion access and identified several categories of barriers to abortion among minors. These included legal barriers (41 articles found them to be a barrier), financial barriers (14 articles), cultural barriers (13 articles), transportation barriers (12 articles), pressure from parents (11 articles), misinformation (8 articles), and pressure from a partner (8 articles). Legal barriers, including laws that require minors to inform or get permission from an adult guardian, were the most commonly identified barrier. Conclusion These findings suggest that minors need policy and interpersonal support to overcome general and age-specific barriers to abortion care. Future research should examine if and how barriers for minors have intensified post-Dobbs, informing targeted policy responses.

STUDY OBJECTIVE:To describe patterns of postpartum contraception use among primiparous and multiparous adolescent mothers. METHODS:Cross-sectional data came from the Pregnancy Risk Assessment Monitoring System Phase 7 (2012-2015). The analytic sample included postpartum respondents ages 15-19 in 40 US states (N = 5535). Exposures included age, race, parity, intimate partner violence, psychosocial stressors, prenatal care utilization, postpartum home health visits, and insurance type. The primary outcome was postpartum use of effective contraception. The secondary outcome was reasons for not using postpartum contraception. RESULTS:Adolescents who attended postpartum check-ups (AOR = 2.12; 95% CI 1.58-2.84) or received home health visits (AOR = 1.37; 95% CI 1.06-1.77) were more likely to use effective contraception postpartum, whereas those experiencing more stressors were less likely (AOR = 0.93; 95% CI: 0.86-1.00). Non-Hispanic Black adolescents were less likely to use effective contraception (AOR = 0.69; 95% CI 0.50-0.94) compared to non-Hispanic White adolescents. Among those who did not use contraception postpartum, having a postpartum home health visit was associated with lower odds of endorsing contraceptive side effects (AOR = 0.33; 95% CI 0.18-0.60) or not wishing to use contraception (AOR = 0.43; 95% CI 0.22-0.86) as reasons for nonuse. CONCLUSION:Access to postpartum care via home health and postpartum clinic visits was associated with significantly higher likelihood of using effective contraception. However, disparities persisted among non-Hispanic Black adolescents and those experiencing high levels of psychosocial stress. For postpartum adolescents who do not desire a subsequent birth, increasing their ability to obtain effective contraceptives can be achieved through increased access to postpartum care, particularly for underserved populations.

PURPOSE:To determine the impact of abortion legislation on mental health during pregnancy and postpartum and assess whether pregnancy intention mediates associations. METHODS:We quantified associations between restrictive abortion laws and stress, depression symptoms during and after pregnancy, and depression diagnoses after pregnancy using longitudinal data from Nurses' Health Study 3 in 2010-2017 (4091 participants, 4988 pregnancies) using structural equation models with repeated measures, controlling for sociodemographics, prior depression, state economic and sociopolitical measures (unemployment rate, gender wage gap, Gini index, percentage of state legislatures who are women, Democratic governor). RESULTS:Restrictive abortion legislation was associated with unintended pregnancies (β = 0.127, p = 0.02). These were, in turn, associated with increased risks of stress and depression symptoms during pregnancy (total indirect effects β = 0.035, p = 0.03; β = 0.029, p = 0.03, respectively, corresponding <1% increase in probability), but not after pregnancy. CONCLUSIONS:Abortion restrictions are associated with higher proportions of unintended pregnancies, which are associated with increased risks of stress and depression during pregnancy.

This study estimates the association between Florida’s red flag law enactment and firearm and nonfirearm homicide and suicide rates.

Background The rate of suicide death has been increasing, making understanding risk factors of growing importance. While exposure to explicit suicide-related media, such as description of means in news reports or sensationalized fictional portrayal, is known to increase population suicide rates, it is not known whether prosuicide website forums, which often promote or facilitate information about fatal suicide means, are related to change in suicide deaths overall or by specific means. Objective This study aimed to estimate the association of the frequency of Google searches of known prosuicide web forums and content with death by suicide over time in the United States, by age, sex, and means of death. Methods National monthly Google search data for names of common prosuicide websites between January 2010 and December 2021 were extracted from Google Health Trends API (application programming interface). Suicide deaths were identified using the CDC (Centers for Disease Control and Prevention) National Vital Statistics System (NVSS), and 3 primary means of death were identified (poisoning, suffocation, and firearm). Distributed lag nonlinear models (DLNMs) were then used to estimate the lagged association between the number of Google searches on suicide mortality, stratified by age, sex, and means, and adjusted for month. Sensitivity analyses, including using autoregressive integrated moving average (ARIMA) modeling approaches, were also conducted. Results Months in the United States in which search rates for prosuicide websites increased had more documented deaths by intentional poisoning and suffocation among both adolescents and adults. For example, the risk of poisoning suicide among youth and young adults (age 10-24 years) was 1.79 (95% CI 1.06-3.03) times higher in months with 22 searches per 10 million as compared to 0 searches. The risk of poisoning suicide among adults aged 25-64 was 1.10 (95% CI 1.03-1.16) times higher 1 month after searches reached 9 per 10 million compared with 0 searches. We also observed that increased search rates were associated with fewer youth suicide deaths by firearms with a 3-month time lag for adolescents. These models were robust to sensitivity tests. Conclusions Although more analysis is needed, the findings are suggestive of an association between increased prosuicide website access and increased suicide deaths, specifically deaths by poisoning and suffocation. These findings emphasize the need to further investigate sites containing potentially dangerous information and their associations with deaths by suicide, as they may affect vulnerable individuals.

Suicide rates in the United States have increased over the past 15 years, with substantial geographic variation in these increases; yet there have been few attempts to cluster counties by the magnitude of suicide rate changes according to intercept and slope or to identify the economic precursors of increases. We used vital statistics data and growth mixture models to identify clusters of counties by their magnitude of suicide growth from 2008 to 2020 and examined associations with county economic and labor indices. Our models identified 5 clusters, each differentiated by intercept and slope magnitude, with the highest-rate cluster (4% of counties) being observed mainly in sparsely populated areas in the West and Alaska, starting the time series at 25.4 suicides per 100,000 population, and exhibiting the steepest increase in slope (0.69/100,000/year). There was no cluster for which the suicide rate was stable or declining. Counties in the highest-rate cluster were more likely to have agricultural and service economies and less likely to have urban professional economies. Given the increased burden of suicide, with no clusters of counties improving over time, additional policy and prevention efforts are needed, particularly targeted at rural areas in the West.

IntroductionResearch has established that suicide-related media can impact suicide rates both positively and negatively, supporting efforts to engage the media in the service of suicide prevention. The goal of the current study is to evaluate the impact of a suicide prevention media campaign implemented April 7-14, 2019 in Oregon.MethodsSeveral indices of help-seeking behavior and suicide risk were employed: suicide-related Google Health API searches, National Suicide Prevention Lifeline (Lifeline) (currently known as the 988 Suicide and Crisis Lifeline) call volume, and state suicide mortality data from April 7, 2016-May 6, 2019. Eight states with similar 2016-2018 average suicide rates were compared with Oregon. Bayesian structural time-series modeling in R was used to test intervention effects.ResultsDuring the 30 days following the start of the campaign, there was a significant increase in Lifeline calls from Oregon area codes (2488 observed vs. 2283 expected calls, p = 0.03). There were no significant changes in suicide mortality or suicide-related Google searches in Oregon.ConclusionsThe campaign appeared to increase help-seeking behavior in the form of Lifeline calls, without any indication of an iatrogenic suicide contagion effect. However, the campaign's potential to reduce suicide mortality was unmet.

Searches for “pro-suicide” websites in the United States peaked during the week a high-profile news story was published and remained elevated for 6 months afterward, highlighting the need to avoid mentioning specific sources of explicit suicide instructions in media publications.

Back to table of contents Previous article Next article Priority Data LetterNo AccessTrends in Suicide Among Black Women in the United States, 1999–2020Victoria A. Joseph, M.P.H., Gonzalo Martínez-Alés, M.D., Ph.D., Mark Olfson, M.P.H., M.D., Jeffrey Shaman, Ph.D., Madelyn S. Gould, M.P.H., Ph.D., Catherine Gimbrone, M.P.H., Katherine M. Keyes, M.P.H., Ph.D.Victoria A. Joseph, M.P.H., Gonzalo Martínez-Alés, M.D., Ph.D., Mark Olfson, M.P.H., M.D., Jeffrey Shaman, Ph.D., Madelyn S. Gould, M.P.H., Ph.D., Catherine Gimbrone, M.P.H., Katherine M. Keyes, M.P.H., Ph.D.Published Online:1 Dec 2023https://doi.org/10.1176/appi.ajp.20230254AboutSectionsView articleView Full TextSupplemental MaterialPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail View article Access content To read the fulltext, please use one of the options below to sign in or purchase access. Personal login Institutional Login Sign in via OpenAthens Register for access Purchase Save for later Item saved, go to cart PPV Articles - American Journal of Psychiatry $35.00 Add to cart PPV Articles - American Journal of Psychiatry Checkout Please login/register if you wish to pair your device and check access availability. Not a subscriber? Subscribe Now / Learn More PsychiatryOnline subscription options offer access to the DSM-5 library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development. Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.). FiguresReferencesCited byDetailsCited byA Mental Health Crisis and Call to Action: Increasing Trends in Suicide Among Black Women in the United StatesRuth S. Shim, M.D., M.P.H., Carolyn I. Rodriguez, M.D., Ph.D.1 December 2023 | American Journal of Psychiatry, Vol. 180, No. 12Adversity and Resilience, Postpartum Depression, Suicide, and Racial/Ethnic DisparitiesNed H. Kalin, M.D.1 December 2023 | American Journal of Psychiatry, Vol. 180, No. 12 Volume 180Issue 12 December 01, 2023Pages 914-917 Metrics KeywordsEpidemiologySuicide and Self-HarmWomenPDF download History Received 30 March 2023 Revised 9 June 2023 Accepted 24 July 2023 Published online 1 December 2023 Published in print 1 December 2023

This presentation will address recent research on emerging trends of using electronic health records (EHRs) to detect and identify trends in clinical psychiatric diagnoses among youth infected with the SARS-CoV-2 virus and during postacute SARS-CoV-2 infection. Drawing on recent findings of a study examining changes in clinical psychiatric diagnoses between March 2020 and August 2021 including 271,345 children from the New York City (NYC) metropolitan region, this study will highlight use of structured EHR data from Healthix to detect clinical psychiatric diagnoses in the context of the sequelae of the COVID-19 pandemic. Using a time series approach, trends were compared among individuals with and without recent pre–COVID-19 clinical psychiatric diagnoses noted in the EHRs up to 3 years before the first COVID-19 test. Of the 90,027 (33.1%) children with a recent psychiatric diagnosis, 46,578 (51.7%) tested positive (23,281 hospitalized vs 23,297 not hospitalized) and 43,449 (48.3%) tested negative. Across age groups, patients with recent pre–COVID-19 clinical psychiatric diagnoses, compared to those without, had greater percentages of anxiety disorders, mood disorders, and psychosis diagnoses, early in the pandemic in March 2020 in NYC. Anxiety and mood disorders were the most commonly diagnosed in the first year of the pandemic among COVID-19–positive patients with recent clinical psychiatric diagnoses. The greatest increases were anxiety disorders (378.7%) and mood disorders (269.0%) among COVID-19–positive nonhospitalized patients. Use of a large-scale health information exchange enabled data aggregation, detection, and tracking across varied health settings of children with psychiatric diagnoses during the COVID-19 pandemic. Mobilizing health information across communities may help support future research on long-term trends in clinical diagnosis during the aftermath of the pandemic.

BACKGROUND:Suicide is one of the leading causes of death in the USA and population risk prediction models can inform decisions on the type, location, and timing of public health interventions. We aimed to develop a prediction model to estimate county-level suicide risk in the USA using population characteristics. METHODS:We obtained data on all deaths by suicide reported to the National Vital Statistics System between Jan 1, 2005, and Dec 31, 2019, and age, sex, race, and county of residence of the decedents were extracted to calculate baseline risk. We also obtained county-level annual measures of socioeconomic predictors of suicide risk (unemployment, weekly wage, poverty prevalence, median household income, and population density) and state-level prevalence of major depressive disorder and firearm ownership from US public sources. We applied conditional autoregressive models, which account for spatiotemporal autocorrelation in response and predictors, to estimate county-level suicide risk. FINDINGS:Estimates derived from conditional autoregressive models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk and protective covariates further reduced errors. Suicide risk was estimated to increase with each SD increase in firearm ownership (2·8% [95% credible interval (CrI) 1·8 to 3·9]), prevalence of major depressive episode (1·0% [0·4 to 1·5]), and unemployment rate (2·8% [1·9 to 3·8]). Conversely, risk was estimated to decrease by 4·3% (-5·1 to -3·2) for each SD increase in median household income and by 4·3% (-5·8 to -2·5) for each SD increase in population density. An increase in the heterogeneity in county-specific suicide risk was also observed during the study period. INTERPRETATION:Area-level characteristics and the conditional autoregressive models can estimate population-level suicide risk. Availability of near real-time situational data are necessary for the translation of these models into a surveillance setting. Monitoring changes in population-level risk of suicide could help public health agencies select and deploy targeted interventions quickly. FUNDING:US National Institute of Mental Health.

Objective:After remaining stable for many years, the prevalence of depression among adolescents increased over the past decade, particularly among girls. In this study, we used longitudinal data from a cohort of high school students to characterize sex-specific trajectories of depressive symptoms during this period of increasing prevalence and widening gender gap in adolescent depression. Method:Using data from the Health and Happiness Cohort, a longitudinal 8-wave study of high school students residing in Los Angeles County from 2013 to 2017 (N = 3,393), we conducted a multiple-group, latent class growth analysis by sex to differentiate developmental trajectories in depressive symptoms scores measured by the Center for Epidemiological Studies- Depression (CES-D) scale (range, 0-60). Results:A 4-class solution provided the best model fit for both girls and boys. Trajectories among girls included low stable (35.1%), mild stable (42.8%), moderate decreasing (16.2%), and high arching (5.9%). Trajectories among boys included low stable (49.2%), mild increasing (34.7%), moderate decreasing (12.2%), and high increasing (3.9%). Average scores consistently exceeded or crossed the threshold for probable depression (≥16). Across comparable sex-specific trajectory groups, the average CES-D scores of girls were higher than those of boys, whose average scores increased over time. Conclusion:In a diverse cohort of students in Los Angeles County, depressive symptom trajectories were comparable to prior time periods but with a higher proportion of students in trajectories characterized by probable depression. Trajectories differed by sex, suggesting that future research should consider differential severity and onset of depression between boys and girls.

Violations of the positivity assumption (also called the common support condition) challenge health policy research and can result in significant bias, large variance, and invalid inference. We define positivity in the single- and multiple-timepoint (i.e., longitudinal) health policy evaluation setting, and discuss real-world threats to positivity. We show empirical evidence of the practical positivity violations that can result when attempting to estimate the effects of health policies (in this case, Naloxone Access Laws). In such scenarios, an alternative is to estimate the effect of a shift in law enactment (e.g., the effect if enactment had been delayed by some number of years). Such an effect corresponds to what is called a modified treatment policy, and dramatically weakens the required positivity assumption, thereby offering a means to estimate policy effects even in scenarios with serious positivity problems. We apply the approach to define and estimate the longitudinal effects of Naloxone Access Laws on opioid overdose rates.

Objectives: To examine recent age-period-cohort effects on suicide among foreign-born individuals, a particularly vulnerable sociodemographic group in Spain. Methods: Using 2000–2019 mortality data from Spain’s National Institute of Statistics, we estimated age-period-cohort effects on suicide mortality, stratified by foreign-born status (native- vs. foreign-born) and, among the foreign-born, by Spanish citizenship status, a proxy for greater socioeconomic stability. Results: Annual suicide mortality rates were lower among foreign- than native-born individuals. There was heterogeneity in age-period-cohort effects between study groups. After 2010, suicide mortality increased markedly among the foreign-born—especially for female cohorts born around 1950, and slightly among native-born women—especially among female cohorts born after the 1960s. Among native-born men, suicide increased linearly with age and remained stable over time. Increases in suicide among the foreign-born were driven by increases among individuals without Spanish citizenship—especially among cohorts born after 1975. Conclusion: After 2010, suicide in Spain increased markedly among foreign-born individuals and slightly among native-born women, suggesting an association between the downstream effects of the 2008 economic recession and increases in suicide mortality among socioeconomically vulnerable populations.

Background Suicide is one of the leading causes of death in the United States and population risk prediction models can inform the type, location, and timing of public health interventions. Here, we report the development of a prediction model of suicide risk using population characteristics. Methods All suicide deaths reported to the Nation Vital Statistics System between 2005-2019 were identified, and age, sex, race, and county-of-residence of the decedents were extracted to calculate baseline risk. County-wise annual measures of socioeconomic predictors of suicide risk — unemployment, weekly wage, poverty prevalence, median household income, and population density — along with two state-wise measures of prevalence of major depressive disorder and firearm ownership were compiled from public sources. Conditional autoregressive (CAR) models, which account for spatiotemporal autocorrelation in response and predictors, were used to estimate county-level risk. Results Estimates derived from CAR models were more accurate than from models not adjusted for spatiotemporal autocorrelation. Inclusion of suicide risk/protective covariates further reduced errors. Suicide risk was estimated to increase with each standard deviation increase in firearm ownership (2.8%), prevalence of major depressive episode (1%) and unemployment (2.8%). Conversely, risk was estimated to decrease by 4.3% for each standard deviation increase in both median household income and population density. Increased heterogeneity of risk across counties was also noted. Conclusions Area-level characteristics and the CAR model structure can estimate population-level suicide risk and thus inform decisions on resource allocation and focused interventions during outbreaks.

Objective: Deaths by suicide correlate both spatially and temporally, leading to suicide clusters. This study aimed to estimate racial patterns in suicide clusters since 2000. Method: Data from the US National Vital Statistics System included all International Classification of Diseases, Tenth Revision (ICD-10)-coded suicide cases from 2000-2019 among American Indian/Alaska Native (AI/AN), Asian/Pacific Islander (A/PI), Black, or White youth and young adults, aged 5-34 years. We estimated age, period, and cohort (APC) trends and identified spatiotemporal clusters using the SaTScan space-time statistic, which identified lower- and higher-than-expected suicide rates (cold and hot clusters) in a prespecified area (150 km) and time interval (15 months). We also calculated the average proportion of deaths by suicide contained in clusters, to quantify the relative importance of spatiotemporal patterning as a driver of overall suicide rates. Results: From 2010-2019, suicide rates increased from between 37% among AI/AN (95% CI = 1.22, 1.55) to 81% among A/PI (95% CI = 1.65, 2.01) groups. Suicide clusters accounted for 0.8%-10.3% of all suicide deaths, across racial groups. Since 2000, the likelihood of detecting cluster increased over time, with considerable differences in the number of clusters in each racial group (4 among AI/AN to 72 among White youth). Among Black youth and young adults, 27 total clusters were identified. Hot clusters were concentrated in southeastern and mid-Atlantic counties. Conclusion: Suicide rates and clusters in youth and young adults have increased in the past 2 decades, requiring attention from policy makers, clinicians, and caretakers. Racially distinct patterns highlight opportunities to tailor individual- and population-level prevention efforts to prevent suicide deaths in emerging high-risk groups.

Determining emerging trends of clinical psychiatric diagnoses among patients infected with the SARS-CoV-2 virus is important to understand post-acute sequelae of SARS-CoV-2 infection or long COVID. However, published reports accounting for pre-COVID psychiatric diagnoses have usually relied on self-report rather than clinical diagnoses. Using electronic health records (EHRs) among 2,358,318 patients from the New York City (NYC) metropolitan region, this time series study examined changes in clinical psychiatric diagnoses between March 2020 and August 2021 with month as the unit of analysis. We compared trends in patients with and without recent pre-COVID clinical psychiatric diagnoses noted in the EHRs up to 3 years before the first COVID-19 test. Patients with recent clinical psychiatric diagnoses, as compared to those without, had more subsequent anxiety disorders, mood disorders, and psychosis throughout the study period. Substance use disorders were greater between March and August 2020 among patients without any recent clinical psychiatric diagnoses than those with. COVID-19 positive patients (both hospitalized and non-hospitalized) had greater post-COVID psychiatric diagnoses than COVID-19 negative patients. Among patients with recent clinical psychiatric diagnoses, psychiatric diagnoses have decreased since January 2021, regardless of COVID-19 infection/hospitalization. However, among patients without recent clinical psychiatric diagnoses, new anxiety disorders, mood disorders, and psychosis diagnoses increased between February and August 2021 among all patients (COVID-19 positive and negative). The greatest increases were anxiety disorders (378.7%) and mood disorders (269.0%) among COVID-19 positive non-hospitalized patients. New clinical psychosis diagnoses increased by 242.5% among COVID-19 negative patients. This study is the first to delineate the impact of COVID-19 on different clinical psychiatric diagnoses by pre-COVID psychiatric diagnoses and COVID-19 infections and hospitalizations across NYC, one of the hardest-hit US cities in the early pandemic. Our findings suggest the need for tailoring treatment and policies to meet the needs of individuals with pre-COVID psychiatric diagnoses.