A survey of college students in the United States in 2023-2024 found that around 38 percent had symptoms of depression. Symptoms of depression vary in severity and can include a loss of interest/pleasure in things once found enjoyable, feelings of sadness and hopelessness, fatigue, changes in sleep, and thoughts of death or suicide. Mental health among college students Due to the life changes and stress that often come with attending college, mental health problems are not unusual among college students. The most common mental health problems college students have been diagnosed with are anxiety disorders and depression. Fortunately, these are two of the most treatable forms of mental illness, with psychotherapy and/or medications the most frequent means of treatment. However, barriers to access mental health services persist, with around 22 percent of college students stating that in the past year financial reasons caused them to receive fewer services for their mental or emotional health than they would have otherwise received. Depression in the United States Depression is not only a problem among college students but affects people of all ages. In 2021, around ten percent of those aged 26 to 49 years in the United States reported a major depressive episode in the past year. Depression in the United States is more prevalent among females than males, but suicide is almost four times more common among males than females. Death rates due to suicide in the U.S. have increased for both genders in the past few years, highlighting the issue of depression and other mental health disorders and the need for easy access to mental health services.

This dataset contains county-level information for U.S. counties from 2020 to 2022, aiming to explore the potential relationship between COVID-19 vaccination coverage and the prevalence of severe depression. It integrates multiple data sources, including public health statistics, socioeconomic indicators, environmental variables, and demographic characteristics. The dataset is structured to support spatial, temporal, and statistical analysis.Key Variables Include:Mental Health: Severe depression rates per 100,000 population for 2021 and 2022COVID-19 Metrics: Case rates per 100,000 (2021, 2022), and vaccination rates (2-dose complete, 5+ population)Socioeconomic Data: Unemployment rates, median household income, percent of adults with bachelor's degree or higherEnvironmental Factors: Average daily sunlight (KJ/m²), cooling degree daysDemographics: Population size, gender distribution, age distribution, urbanization rateHealth Behavior Indicators: Rates of smoking, obesity, physical inactivity, and excessive drinkingLog-transformed versions of several variables are also included to support regression modeling and machine learning tasks.Purpose:The dataset is curated for research that investigates the interplay between COVID-19 vaccination campaigns and mental health outcomes, with potential applications in spatial epidemiology, public health policy, and social determinants of health research.Temporal Coverage: 2020–2022Geographic Scope: U.S. counties (N ≈ 3,000+)Data Format: XlsxSuggested Citation: Wencong Cui, Yuqing Wang, "COVID-19 Vaccination and Depression: U.S. County-Level Dataset (2020–2022)", Figshare, 2025. DOI: 10.6084/m9.figshare.29451644

• Excluded for meta-analysis due to different items/cut-points;** Excluded for meta-analysis due to duplicate database; BDI: Beck Depression Inventory; CESD: Center for Epidemiologic Studies of Depression; HDI: Hamilton Depression Inventory; PDSS: Postpartum Depression Screening Scale; WMH-CIDI: World Mental Health Organization Composite International Diagnostic Interview; UM-CIDI: University of Michigan’s version of CIDI; PHQ: Patient Health Questionnaire; GDS: Geriatric Depression Scale; HSCL: Hopkins Symptom Checklist; MDD: Major Depressive Disorder; MDE: Major Depressive Episode; NLAAS: National Latino and Asian American Study; CPES: Collaborative Psychiatric Epidemiology Surveys, the CPES includes the National Comorbidity Survey-Replication, the NLAAS and the National Survey of American Life.Review of prevalence studies of depression in Asian-Americans.

The World Health Organization estimates that almost 300 million people suffer from depression worldwide. Depression is the most common mental health disorder and shows racial disparities in disease prevalence, age of onset, severity of symptoms, frequency of diagnosis, and treatment utilization across the United States. Since depression has both social and genetic risk factors, we propose a conceptual model wherein social stressors are primary risk factors for depression, but genetic variants increase or decrease individual susceptibility to the effects of the social stressors. Our research strategy incorporates both social and genetic data to investigate variation in symptoms of depression (CES-D scores). We collected data on financial strain (difficulty paying bills) and personal social networks (a model of an individual’s social environment), and we genotyped genetic variants in five genes involved in stress reactivity (HTR1a, BDNF, GNB3, SLC6A4, and FKBP5) in 135 African Americans residing in Tallahassee, Florida. We found that high financial strain and a high percentage of people in one’s social network who are a source of stress or worry were significantly associated with higher CES-D scores and explained more variation in CES-D scores than did genetic factors. Only one genetic variant (rs1360780 in FKBP5) was significantly associated with CES-D scores and only when the social stressors were included in the model. Interestingly, the effect of FKPB5 appeared to be strongest in individuals with high financial strain such that participants with a T allele at rs1360780 in FKBP5 and high financial strain had the highest mean CES-D scores in our study population. These results suggest that material disadvantage and a stressful social environment increases the risk of depression, but that individual-level genetic variation may increase susceptibility to the adverse health consequences of social stressors.

As the tagline of ‘American Association of Suicidology’ says I strongly believe that suicide prevention is everyone’s business. The act of ending one’s own life stating the reasons to be depression, alcoholism or any other mental disorders for that matter is not a considerable idea keeping in mind that anything can be overcome with reliable help and lifestyle. We can choose to stand together in the face of a society which may often feel like a lonely and disconnected place, and we can choose to make a difference by making lives more livable for those who struggle to cope. Through this project, I am hoping to identify the trends of suicidal rates by country, gender, age and ethnicity. And relate the trends to the possible reasons that leads to the drastic decision, which might help us to curb the thought in the very beginning.

What's inside is more than just rows and columns. Make it easy for others to get started by describing how you acquired the data and what time period it represents, too. Data on suicides is deficient for two reasons, first of all, there is a problem with the frequency and reliability of vital registration data in many countries – an issue that undermine the quality of mortality estimates in general, not just suicide. Secondly, there are problems with the accuracy of the official figures made available, since suicide registration is a complicated process involving several responsible authorities with medical and legal concerns. Moreover, the illegality of suicidal behavior in some countries contributes to under reporting and misclassification. I was lucky enough to obtain enough data from different reliable resources. I will be starting off the project with the most reliable datasets available for us on suicide.

•World Health Organization (WHO) dataset which contains entity wise suicide rates, crude suicide rates per gender and country which are age standardized which has a geographical coverage of 198 countries. The time spanning from 1950-2011.

•Samaritans statistics report 2017 including data for 2013-2015, in order to reduce the time, it takes to register deaths, the maximum time between a death and registration is eight days.

•American Association of Suicidology facts and statistics which are categorized by age, gender, region and ethnicity.

Inspiration: To visualize the trends and patterns by merging different datasets available regarding the subject matter from different organizations, deriving the major causes for the drastic stride. And also observing the changes in patterns over the years by country, sex and ethnicity

Understanding the data: It is always tricky to understand the suicide statistics as they may not be so straight forward as they appear to be. Generally, the rate is per 100,000. It is done this way to adjust the underlying population size. ‘Age-standardized’ rates have been standardized to the world population to increase the confidence while making the comparisons. On the other hand, ‘Crude rates’ have not been standardized like the prior, so they are just the basic calculation of number of deaths divided by the population (x100,000). The size of the population and specific cohort is also to be taken into account as smaller groups often produce less reliable rates per 100,000. When examining the suicide trends over a period of time it is also important to look over a relatively long period. Increases and decreases for a year at a time should not be considered in isolation.

This table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.

Hermaphroditic plants can potentially self-fertilise, but most possess adaptations that promote outcrossing. However, evolutionary transitions to higher selfing rates are frequent. Selfing comes with a transmission advantage over outcrossing, but self-progeny may suffer from inbreeding depression, which forms the main barrier to the evolution of higher selfing rates. Here, we assessed inbreeding depression in the North American herb Arabidopsis lyrata, which is normally self-incompatible, with a low frequency of self-compatible plants. However, a few populations have become fixed for self-compatibility and have high selfing rates. Under greenhouse conditions, we estimated mean inbreeding depression per seed (based on cumulative vegetative performance calculated as the product of germination, survival and aboveground biomass) to be 0.34 for six outcrossing populations, and 0.26 for five selfing populations. Exposing plants to drought and inducing defenses with jasmonic acid did not magnify these estimates. For outcrossing populations, however, inbreeding depression per seed may underestimate true levels of inbreeding depression, because self-incompatible plants showed strong reductions in seed set after (enforced) selfing. Inbreeding-depression estimates incorporating seed set averaged 0.63 for outcrossing populations (compared to 0.30 for selfing populations). However, this is likely an overestimate because exposing plants to 5% CO2 to circumvent self-incompatibility to produce selfed seed might leave residual effects of self-incompatibility that contribute to reduced seed set. Nevertheless, our estimates of inbreeding depression were clearly lower than previous estimates based on the same performance traits in outcrossing European populations of A. lyrata, which may help explain why selfing could evolve in North American A. lyrata.

Characteristics of participating providers.

Results of regression analyses for evaluating the three hypotheses for three outcomes.

Descriptive results for the three outcome measures by arm.

Psychosocial aspects of the men surveyed and association with sexualized drug use (SDU), in total sample and each country participating in LAMIS-2018 (part two).