Social Determinants of Health and Depression among African American Adults: A Scoping Review of Current Research

Cumulative inequality in social determinants of health in relation to depression symptom: An analysis of nationwide cross-sectional data from U.S. NHANES 2005-2018

Social determinants of health (SDoH) have been linked to a higher likelihood of experiencing mental health problems. This study aimed to investigate whether the accumulation of unfavorable SDoH is associated with depression symptom. Data was gathered from a representative population participating in the U.S. National Health and Nutrition Examination Survey spanning from 2005 to 2018. Self-reported SDoH were operationalized according to the criteria outlined in Healthy People 2030, with a cumulative measure of unfavorable SDoH calculated for analysis. The presence of depression symptom was identified using the Patient Health Questionnaire in a representative sample of 30,762 participants (49.2 % males) representing 1,392 million non-institutionalized U.S. adults, with 2,675 (8.7 %) participants showing depression symptom. Unfavorable SDoH were found to be significantly and independently associated with depression symptom. Individuals facing multiple unfavorable SDoHs were more likely to experience depression symptom (P for trend < 0.001). For instance, a positive association was observed in participants exposed to six or more unfavorable SDoHs with depression symptom (AOR = 3.537, 95 % CI: 1.781, 7.075, P-value < 0.001). The findings emphasize that the likelihood of developing depression symptom significantly increases when multiple SDoHs are present, compared to just a single SDoH.

Prediction of Positive Patient Health Questionnaire-2 Screening Using Area Deprivation Index in Primary Care

Depression is recognized as a significant public health issue in the United States. The National Survey on Drug Use and Health reports that 21.0 million adults aged 18 or older had major depressive disorder in 2020, including 14.8 million experiencing a major depressive episode with severe impairment. The aim is to predict the positivity of Patient Health Questionnaire-2 (PHQ-2) outcomes among patients in primary care settings by analyzing a range of variables, including socioeconomic status, demographic characteristics, and health behaviors, thereby identifying those at increased risk for depression. Employing a machine learning approach, the study utilizes retrospective data from electronic health records across 15 primary care clinics in South Florida to explore the relationship between social determinants of health (SDoH), including area of deprivation index (ADI) and PHQ-2 positivity. The study encompasses 15 primary care clinics located in South Florida, where a diverse patient population receives care. Analysis included 94,572 patient visits; 74,636 records were included in the study. If a zip+4 was not available or an ADI score did not exist, the visit was not included in the final analysis. Screening involved the PHQ-2, assessing depressed mood and anhedonia, with a cutoff >2 indicating positive screening. ADI was used to assess SDoH by matching patients' residential postal codes to ADI national percentiles. Demographics, sexual history, tobacco use, caffeine intake, and community involvement were also evaluated in the study. Over 40 machine learning algorithms were explored for their accuracy in predicting PHQ-2 outcomes, using software tools including Scikit-learn and stats models in Python. Variables were normalized, scored, and then subjected to predictive regression models, with Random Forest showing outstanding performance. Feature engineering and correlation analysis identified ADI, age, education, visit type, coffee intake, and marital status as significant predictors of PHQ-2 positivity. The area under the curve and model accuracies varied across clinics, with specific clinics showing higher predictive accuracy and others (p > .05). The study concludes that the ADI, as a proxy for SDoH, alongside other individual factors, can predict PHQ-2 positivity. Health organizations can use this information to anticipate health needs and resource allocation.

Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by Natural Language Processing

PURPOSE

This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language processing (NLP) and machine learning (ML) techniques on race-related spatiotemporal social media text data. Specifically, this study establishes the extent to which Latent Dirichlet Allocation (LDA) and Gibbs Sampling Dirichlet Multinomial Mixture (GSDMM)-based topic modeling determines social determinants of health (SDOH) categories, and how adequately custom named-entity recognition (NER) detects key SDOH factors from a race/ethnicity-related Reddit data corpus.

METHODS

In this study, we collected race/ethnicity-specific data from 5 location subreddits including New York City, NY; Los Angeles, CA; Chicago, IL; Philadelphia, PA; and Houston, TX from March to December 2019 (before COVID-19 pandemic) and from March to December 2020 (during COVID-19 pandemic). Next, we applied methods from natural language processing and machine learning to analyze SDOH issues from extracted Reddit comments and conversation threads using feature engineering, topic modeling, and custom named-entity recognition (NER).

RESULTS

Topic modeling identified 35 SDOH-related topics. The SDOH-based custom NER analyses revealed that the COVID-19 pandemic significantly impacted SDOH issues of marginalized Black and Asian communities. On average, the Social and Community Context (SCC) category of SDOH had the highest percent increase (366%) from the pre-pandemic period to the pandemic period across all locations and population groups. Some of the detected SCC issues were racism, protests, arrests, immigration, police brutality, hate crime, white supremacy, and discrimination.

CONCLUSION

Reddit social media platform can be an alternative source to assess the SDOH issues of marginalized Black and Asian communities during the COVID-19 pandemic. By employing NLP/ML techniques such as LDA/GSDMM-based topic modeling and custom NER on a race/ethnicity-specific Reddit corpus, we uncovered various SDOH issues affecting marginalized Black and Asian communities that were significantly worsened during the COVID-19 pandemic. As a result of conducting this research, we recommend that researchers, healthcare providers, and governments utilize social media and collaboratively formulate responses and policies that will address SDOH issues during public health crises.

Genetic and environmental influence on alcohol intent and alcohol sips among U.S. children-Effects across sex, race, and ethnicity

INTRODUCTION

Alcohol intent (the susceptibility to initiating alcohol use) and alcohol sips (the initiation of alcohol) in youth are a multifactorial puzzle with many components. This research aims to examine the connection between genetic and environmental factors across sex, race and ethnicity.

METHODS

Data was obtained from the twin hub of the Adolescent Brain Cognitive Development (ABCD) study at baseline (2016-2018). Variance component models were conducted to dissect the additive genetic (A), common (C) and unique environmental (E) effects on alcohol traits. The proportion of the total alcohol phenotypic variation attributable to additive genetic factors is reported as heritability (h2).

RESULTS

The sample (n = 1,772) included an approximately equal male-female distribution. The 886 same-sex twin pairs were 60.4% dizygotic (DZ), 39.6% monozygotic (MZ), 65.4% non-Hispanic Whites, 13.9% non-Hispanic Blacks, 10.8% of Hispanics with a mean age of 121.2 months. Overall, genetic predisposition was moderate for alcohol intent (h2 = 28%, p = .006) and low for alcohol initiation (h2 = 4%, p = 0.83). Hispanics (h2 = 53%, p < .0001) and Blacks (h2 = 48%, p < .0001) demonstrated higher alcohol intent due to additive genetic factors than Whites (h2 = 34%, p < .0001). Common environmental factors explained more variation in alcohol sips in females (c2 = 63%, p = .001) than in males (c2 = 55%, p = .003). Unique environmental factors largely attributed to alcohol intent, while common environmental factors explained the substantial variation in alcohol initiation.

CONCLUSION

Sex and racial/ethnic disparities in genetic and environmental risk factors for susceptibility to alcohol initiation can lead to significant health disparities. Certain populations may be at greater risk for alcohol use due to their genetic and ecological factors at an early age.

Analysis of social determinants of health and individual factors found in health equity frameworks: Applications to injury research

INTRODUCTION

This research evaluated existing health equity frameworks as they relate to social determinants of health (SDOHs) and individual factors that may impact injury outcomes and identify gaps in coverage using the Healthy People (HP) 2030 key domains.

METHODS

The study used a list of health equity frameworks sourced from previous literature. SDOHs and individual factors from each framework were identified and categorized into the Healthy People 2030 domains. Five injury topic areas were used as examples for how SDOHs and individual factors can be compared to injury topic-specific health disparities to identify health equity frameworks to apply to injury research.

RESULTS

The study identified 59 SDOHs and individual factors from the list of 33 health equity frameworks. The number of SDOHs and individual factors identified varied by Healthy People 2030 domain: Neighborhood and Built Environment contained 16 (27.1%) SDOHs and individual actors, Social and Community Context contained 22 (37.3%), Economic Stability contained 10 (16.9%), Healthcare Access and Quality contained 10 (16.9%), and Education Access and Quality contained one (1.7%). Twenty-three (39.0%) SDOHs/individual factors related to traumatic brain injury, thirteen (22.0%) related to motor vehicle crashes and suicide, 11 (18.6%) related to drowning and older adult falls. Eight frameworks (24.2%) covered all HP 2030 key domains and may be applicable to injury topics.

CONCLUSIONS

Incorporating health equity into research is critical. Health equity frameworks can provide a way to systematically incorporate health equity into research. The findings from this study may be useful to health equity research by providing a resource to injury and other public health fields.

PRACTICAL APPLICATIONS

Health equity frameworks are a practical tool to guide injury research, translation, evaluation, and program implementation. The findings from this study can be used to guide the application of health equity frameworks in injury research for specific topic areas.

Plasma metabolomics profiles in Black and White participants of the Adventist Health Study-2 cohort

BACKGROUND

Black Americans suffer disparities in risk for cardiometabolic and other chronic diseases. Findings from the Adventist Health Study-2 (AHS-2) cohort have shown associations of plant-based dietary patterns and healthy lifestyle factors with prevention of such diseases. Hence, it is likely that racial differences in metabolic profiles correlating with disparities in chronic diseases are explained largely by diet and lifestyle, besides social determinants of health.

METHODS

Untargeted plasma metabolomics screening was performed on plasma samples from 350 participants of the AHS-2, including 171 Black and 179 White participants, using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and a global platform of 892 metabolites. Differences in metabolites or biochemical subclasses by race were analyzed using linear regression, considering various models adjusted for known confounders, dietary and/or other lifestyle behaviors, social vulnerability, and psychosocial stress. The Storey permutation approach was used to adjust for false discovery at FDR < 0.05.

RESULTS

Linear regression revealed differential abundance of over 40% of individual metabolites or biochemical subclasses when comparing Black with White participants after adjustment for false discovery (FDR < 0.05), with the vast majority showing lower abundance in Blacks. Associations were not appreciably altered with adjustment for dietary patterns and socioeconomic or psychosocial stress. Metabolite subclasses showing consistently lower abundance in Black participants included various lipids, such as lysophospholipids, phosphatidylethanolamines, monoacylglycerols, diacylglycerols, and long-chain monounsaturated fatty acids, among other subclasses or lipid categories. Among all biochemical subclasses, creatine metabolism exclusively showed higher abundance in Black participants, although among metabolites within this subclass, only creatine showed differential abundance after adjustment for glomerular filtration rate. Notable metabolites in higher abundance in Black participants included methyl and propyl paraben sulfates, piperine metabolites, and a considerable proportion of acetylated amino acids, including many previously found associated with glomerular filtration rate.

CONCLUSIONS

Differences in metabolic profiles were evident when comparing Black and White participants of the AHS-2 cohort. These differences are likely attributed in part to dietary behaviors not adequately explained by dietary pattern covariates, besides other environmental or genetic factors. Alterations in these metabolites and associated subclasses may have implications for the prevention of chronic diseases in Black Americans.

Racial differences in the major clinical symptom domains of bipolar disorder

BACKGROUND

Across clinical settings, black individuals are disproportionately less likely to be diagnosed with bipolar disorder compared to schizophrenia, a traditionally more severe and chronic disorder with lower expectations for remission. The causes of this disparity are likely multifactorial, ranging from the effects of implicit bias, to developmental and lifelong effects of structural racism, to differing cultural manifestations of psychiatric symptoms and distress. While prior studies examining differences have found a greater preponderance of specific psychotic symptoms (such as persecutory delusions and hallucinations) and a more dysphoric/mixed mania presentation in Black individuals, these studies have been limited by a lack of systematic phenotypic assessment and small sample sizes. In the current report, we have combined data from two large multi-ethnic studies of bipolar disorder with comparable semi-structured interviews to investigate differences in symptoms presentation across the major clinical symptom domains of bipolar disorder.

RESULTS

In the combined meta-analysis, there were 4423 patients diagnosed with bipolar disorder type I, including 775 of self-reported as Black race. When symptom presentations were compared in Black versus White individuals, differences were found across all the major clinical symptom domains of bipolar disorder. Psychotic symptoms, particularly persecutory hallucinations and both persecutory and mood-incongruent delusions, were more prevalent in Black individuals with bipolar disorder type I (ORs = 1.26 to 2.45). In contrast, Black individuals endorsed fewer prototypical manic symptoms, with a notably decreased likelihood of endorsing abnormally elevated mood (OR = 0.44). Within depression associated symptoms, we found similar rates of mood or cognitive related mood symptoms but higher rates of decreased appetite (OR = 1.32) and weight loss (OR = 1.40), as well as increased endorsement of initial, middle, and early-morning insomnia (ORs = 1.73 to 1.82). Concurrently, we found that black individuals with BP-1 were much less likely to be treated with mood stabilizers, such as lithium (OR = 0.45), carbamazepine (OR = 0.37) and lamotrigine (OR = 0.34), and moderately more likely to be on antipsychotic medications (OR = 1.25).

CONCLUSIONS

In two large studies spanning over a decade, we found highly consistent and enduring differences in symptoms across the major clinical symptom domains of bipolar disorder. These differences were marked by a greater burden of mood-incongruent psychotic symptoms, insomnia and irritability, and fewer prototypical symptoms of mania. While such symptoms warrant better recognition to reduce diagnostic disparities, they may also represent potential targets of treatment that can be addressed to mitigate persistent disparities in outcome.

Ethnoracial discrimination and the development of suspiciousness symptoms in individuals at clinical high-risk for psychosis

BACKGROUND AND HYPOTHESIS

While individuals at clinical high-risk (CHR) for psychosis experience higher levels of discrimination than healthy controls, it is unclear how these experiences contribute to the etiology of attenuated positive symptoms. The present study examined the association of perceived discrimination with positive symptoms in a cohort from the North American Prodrome Longitudinal Study (NAPLS2). It predicted that CHR individuals will report higher levels of lifetime and past year perceived discrimination related to their race and ethnicity (ethnoracial discrimination) and that this form of discrimination will be significantly associated with baseline positive symptoms.

STUDY DESIGN

Participants included 686 CHR and 252 healthy controls. The present study examined data from the perceived discrimination (PD) scale, the Brief Core Schema Scale, and the Scale for the Psychosis-Risk Symptoms. Structural equation modeling was employed to examine whether negative schema of self and others mediated the relation of past year ethnoracial PD to baseline suspiciousness symptoms.

RESULTS

CHR individuals report higher levels of past year and lifetime PD compared to healthy controls. Lifetime ethnoracial PD was associated with suspiciousness and total positive symptoms. Negative schema of self and others scores partially mediated the relation of past year ethnoracial PD to suspiciousness, one of five positive symptom criteria for CHR.

CONCLUSIONS

For CHR individuals, past year ethnoracial discrimination was associated with negative beliefs about themselves and others, which was associated with suspiciousness. These findings contribute to an emerging literature characterizing the mechanisms by which discrimination contributes to the positive symptoms characterizing the CHR syndrome.

The Social Determinants of Mental Illness: A Rapid Review of Systematic Reviews

Previous research agendas have prioritised the role of biological determinants in mental illness aetiology. This is of particular concern, as endorsing biological determinants has been shown to promote negative attitudes towards people with mental illness. The aim of this review was to provide an overview of high-quality evidence of the social determinants of mental illness. A rapid review of systematic reviews was conducted. Five databases were searched: Embase, Medline, Academic Search Complete, CINAHL Plus, and PsycINFO. Systematic reviews or meta-analyses that described any social determinant of mental illness, were published in peer-review journals in English, and focussed on human participants were included. The Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines were applied for the selection procedure. Thirty-seven systematic reviews were deemed eligible for review and narrative synthesis. Determinants identified included conflict, violence and maltreatment, life events and experiences, racism and discrimination, culture and migration, social interaction and support, structural policies and inequality, financial factors, employment factors, housing and living conditions, and demographic factors. We recommend that mental health nurses ensure adequate support be provided to those affected by the evidenced social determinants of mental illness.

Mental Health Service Utilization and Disparities in the U.S: Observation of the First Year into the COVID Pandemic

This study examined mental health service utilization and disparities during the first year of COVID. We analyzed data from all adult respondents with any mental illness in the past year (n = 6967) in the 2020 National Survey on Drug Use and Health to evaluate if mental health service utilization differed by geographic areas, race/ethnicity, and age groups. Only 46% of individuals with any mental illness had received mental health treatment. Compared to non-Hispanic Whites, Asian and Hispanics were less likely to receive outpatient services and prescription medicine. Rural residents received less outpatient treatment compared to large metropolitan residents. No difference was found in telemedicine utilization across area types and race/ethnicity groups. Older individuals were less likely to utilize telemedicine services. Our findings highlighted continued mental health treatment disparities among race/ethnic minorities and other sub-populations during COVID. Targeted strategies are warranted to allow older populations to benefit from telemedicine.

Biological Role of Nutrients, Food and Dietary Patterns in the Prevention and Clinical Management of Major Depressive Disorder

Major Depressive Disorder (MDD) is a growing disabling condition affecting around 280 million people worldwide. This complex entity is the result of the interplay between biological, psychological, and sociocultural factors, and compelling evidence suggests that MDD can be considered a disease that occurs as a consequence of an evolutionary mismatch and unhealthy lifestyle habits. In this context, diet is one of the core pillars of health, influencing multiple biological processes in the brain and the entire body. It seems that there is a bidirectional relationship between MDD and malnutrition, and depressed individuals often lack certain critical nutrients along with an aberrant dietary pattern. Thus, dietary interventions are one of the most promising tools to explore in the field of MDD, as there are a specific group of nutrients (i.e., omega 3, vitamins, polyphenols, and caffeine), foods (fish, nuts, seeds fruits, vegetables, coffee/tea, and fermented products) or dietary supplements (such as S-adenosylmethionine, acetyl carnitine, creatine, amino acids, etc.), which are being currently studied. Likewise, the entire nutritional context and the dietary pattern seem to be another potential area of study, and some strategies such as the Mediterranean diet have demonstrated some relevant benefits in patients with MDD; although, further efforts are still needed. In the present work, we will explore the state-of-the-art diet in the prevention and clinical support of MDD, focusing on the biological properties of its main nutrients, foods, and dietary patterns and their possible implications for these patients.

Examining Social Determinants of Health During a Pandemic: Clinical Application of Z Codes Before and During COVID-19

Recognition of the impact of social determinants of health (SDoH) on healthcare outcomes, healthcare service utilization, and population health has prompted a global shift in focus to patient social needs and lived experiences in assessment and treatment. The International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) provides a list of non-billable “Z codes” specific to SDoH for use in electronic health records. Using population-level analysis, this study aims to examine clinical application of Z codes in South Carolina before and during the COVID-19 pandemic. The study population consists of South Carolina residents who had a healthcare visit and had their COVID-19 test result reported to the state's Department of Health and Environmental Control before January 14, 2021. Of the 1,190,531 individuals in the overall sample, Z codes were used only for 14,665 (1.23%) of the patients, including 2,536 (0.97%) COVID-positive patients and 12,129 (1.30%) COVID-negative patients. Compared with hospitals that did not use Z codes, those that did were significantly more likely to have higher bed capacity (p = 0.017) and to be teaching hospitals (p = 0.03), although this was significant only among COVID-19 positive individuals. Those at inpatient visits were most likely to receive Z codes (OR: 5.26; 95% CI: 5.14, 5.38; p < 0.0001) compared to those at outpatient visits (OR: 0.07; 95%CI: 0.06, 0.07; p < 0.0001). There was a slight increase of Z code use from 2019 to 2020 (OR: 1.33, 95% CI: 1.30, 1.36; p < 0.0001), which was still significant when stratified by facility type across time. As one of the first studies to examine Z code use among a large patient population, findings clearly indicate underutilization by providers. Additional study is needed to understand the potentially long-lasting health effects related to SDoH among underserved populations.