Prevalence of depressive symptoms among Hispanic/Latino ethnic subgroups during the COVID-19 pandemic.

Hispanic/Latino populations experienced disproportionate exposure to depression risk factors during the COVID-19 pandemic. While aggregated data confirm the risks of depressive symptoms among Hispanic/Latino individuals, little research uses disaggregated data to investigate these risks based on ethnic subgroups. Using the "Understanding the Impact of the Novel Coronavirus (COVID-19) and Social Distancing on Physical and Psychosocial (Mental) Health and Chronic Diseases" survey, which was distributed nationally between May 13, 2021, and January 9, 2022 (N = 5413), we estimated the prevalence of depressive symptoms among Hispanic/Latino ethnic subgroups during the pandemic. We performed descriptive analysis on a 116-item survey, which collected disaggregated data from Hispanic/Latino individuals aged ≥ 18 years (n = 1181). About one-third of the participants reported depressive symptoms (31.3%), with those who self-identified as other Hispanic/Latino/Spanish origin (40.2%) reporting the highest depressive symptom prevalence. Among participants who reported depression treatment before the pandemic, the highest reports of treatment were among Puerto Rican (81.8%) participants. More than one-third of participants receiving prior depression treatment (38.7%) reported treatment interference by the pandemic, mostly among Central American individuals (50.0%). This study highlights the need for integrating more disaggregated data into public health approaches which seek to target population subgroups and reduce racial/ethnic mental health disparities.

A multivariable model of barriers to COVID-19 vaccination: Using cross sectional data from a nationally distributed survey in the United States.

OBJECTIVE: Discrimination has had longstanding effects on mental and physiological health, which became more evident and synergized during the COVID-19 pandemic. The role of discrimination on vaccination for COVID-19 during the pandemic, however, is not well understood. As such, we examined the relationship of everyday discrimination on COVID-19 vaccination. METHODS: Using a multivariate logistic regression on data collected from a nationally distributed survey in the United States (US), we examined the relationship of discrimination measured by the Everyday Discrimination Scale on self-reported COVID-19 vaccination while adjusting for US nativity, as well as sociodemographic (i.e., age; gender; sexual orientation; race, and ethnicity) and socioeconomic (i.e., educational attainment; employment status; household income) factors. RESULTS: We found that participants reporting monthly to weekly discrimination and multiple times a week to daily discrimination had decreased odds of reporting COVID-19 vaccination (adjusted odds ratio [AOR] = 0.78, 95% confidence interval [CI]:0.68-0.90; and AOR = 0.75, 95% CI = 0.62-0.91, respectively) compared to those that reported no discrimination experienced. Educational attainment of high school equivalent or above, employment as an essential worker, and household-annual income of $50,000 or greater were significant socioeconomic factors. Age, sexual orientation, and race/ethnicity had mixed associations with COVID-19 vaccination. CONCLUSIONS: Discrimination overall remained a significant barrier to vaccination, while nativity was not significant when accounting for socioeconomic and sociodemographic factors. Discrimination must become a public health priority in addressing disparities in health and access and barriers that may affect preventive behaviors.

Capturing the bigger picture: A gestalt of general and alcohol-specific social media usage during the transition to college as a predictor of first-year alcohol use and consequences.

Previous research has shown a reliable association between social media (SM) use and drinking among college students. However, most studies have investigated SM behaviors (e.g., time spent on a platform, posting frequency) in isolation and on a single site. While some have studied multiple SM behaviors across platforms using person-centered approaches (e.g., latent profile analysis [LPA]), these studies have failed to take alcohol-related SM behaviors into account. This longitudinal study addressed this gap in the literature by using LPA to identify subpopulations of SM users during the college transition (N = 319; 62.1% female) using general (frequency of checking, time spent on, and frequency of posting to Instagram/Facebook/Snapchat; Finstagram ownership) and alcohol-related SM behaviors (posting alcohol, partying, and marijuana content). LPA results revealed three SM user profiles at baseline: low general use with low alcohol-related posting (LGU + LAP), high general use with low alcohol-related posting (HGU + LAP), and high general use with high alcohol-related posting (HGU + HAP). Prospective analyses revealed that HGU + HAP membership was associated with greater descriptive peer drinking norms, alcohol use, and consequences relative to HGU + LAP and LGU + LAP membership. Results suggest that there are distinct patterns of general and alcohol-related SM use during the college transition associated with risky drinking that can inform interventions combating SM-related alcohol risks. These findings illustrate the importance of investigating SM use holistically and suggests studying alcohol-related SM behaviors may reveal differences in individuals' alcohol risk that general SM behaviors might not capture.

Household profiles of neglected tropical disease symptoms among children: A latent class analysis of built-environment features of Tanzanian households using the Demographic and Health Survey.

Background: While malaria and neglected tropical disease (NTD) morbidity and mortality rates among children <5 years old have decreased through public health efforts in the United Republic of Tanzania, associations between household environments and disease outcomes are relatively unknown. Methods: We conducted latent class analysis (LCA) on 2015-2016 Tanzania Demographic Health Survey data from mothers with children <5 years old (N = 10 233) to identify NTD household risk profiles. The outcome of child NTD was assessed by mothers' reports of recent diarrhoea, cough, treatment for enteric parasites, and fever symptoms. Household-built environment indicators included urban/rural designation, electricity access, water source, cooking fuel, flooring, wall, and roofing materials. External environmental covariates were considered to further differentiate profiles. Results: Five profiles were identified in the sample: rural finished walls households (40.2%) with the lowest NTD risk; rural rudimentary households (20.9%) with intermediate-low NTD risk; finished material households (22.5%) with intermediate NTD risk; urban households (14.4%) with intermediate-high NTD risk and high likelihood of enteric parasites; rural finished roof/walls households (2.1%) with the highest overall NTD risk. Conclusions: This study is among the first to use LCA to examine household environment characteristics to assess child NTD risk in Tanzania. This paper serves as a framework for community-level rapid NTD risk assessment for targeted health promotion interventions.

Acculturation Profiles of Weight Perception Status among US Foreign-Born Hispanic/Latino Adults: A Mixture Model Approach.

The objective of this study was to identify profiles of acculturation and weight-by-weight perception status among United States (US) foreign-born Hispanic/Latino adults using a person-centered approach. We conducted a latent class analysis (LCA) on 1999-2004 National Health and Nutrition Examination Survey (NHANES) data from US foreign-born Hispanic/Latino adults 18 years and older (N = 4944). Acculturation was assessed by self-reported linguistic acculturation questions from the Short Acculturation Scale for Hispanics. Weight was assessed by body mass index (BMI). Covariates included weight perception and sociodemographic factors to compare and further differentiate profiles. Three profiles were identified: bicultural (15% of sample), low acculturation (84%), and non-integrated (1%). All the profiles had a BMI that was considered overweight or obese. The low acculturated profile was less likely (odds ratio (OR): 0.62, 95% confidence interval (CI): 0.43-0.91) to perceive themselves as overweight relative to the bicultural class. The low accultured profile was also more likely to be female and a US citizen (OR: 1.45, 95% CI: 1.09-1.92 and OR: 2.29, 95% CI: 1.57-3.34) in comparison to the bicultural class. Our study is among the first to use LCA to examine weight perception on acculturation status and weight profiles among US foreign-born Hispanic/Latino adults. The findings of our study are a step towards building a foundation to mitigate weight disparities among underserved/underrepresented US foreign-born individuals, especially Hispanics/Latinos. Our results can also inform the development of tailored interventions.

Hypertension and Diabetes Status by Patterns of Stress in Older Adults From the US Health and Retirement Study: A Latent Class Analysis.

Background Hypertension and diabetes disproportionately affect older non-Hispanic Black and Hispanic adults in the United States. Chronic stress may partially explain these disparities. This study identified underlying stress profiles of older US adults, analyzed stress profiles in relation to hypertension and diabetes, examined the distribution of stress profiles by race and ethnicity, and assessed patterns of change in latent classes of stress over time. Methods and Results Latent class analysis was conducted with a nationally representative sample of older US adults who completed 3 waves of the HRS (Health and Retirement Study) (ie, 2010 [n=6863], 2014 [n=4995], and 2018 [n=3089]). Latent classes of stress in 2010 (ie, stress profiles) were identified using 15 indicators of unmet needs within 5 categories (ie, physiological, safety/security, belonging, esteem, and self-fulfillment). Hypertension and diabetes status were examined as outcomes of latent class membership at 3 time points, and race and ethnicity were examined in association with class membership, adjusting for sociodemographic covariates. Finally, a latent transition analysis examined the stability of latent class membership and racial and ethnic differences in the patterns of stress profiles experienced from 2010 to 2018. Five classes were identified: Generally Unmet Needs (13% of sample), Generally Met Needs (42% of sample), Unmet Self-Efficacy/Goal Needs (12% of sample), Unmet Financial Needs (20% of sample), and Unmet Social Belonging Needs (13% of sample). Compared with the Generally Met Needs class, the Generally Unmet Needs class had higher odds of hypertension (odds ratio [OR], 1.80; [95% CI, 1.35-2.39]) and diabetes (OR, 1.94; [95% CI, 1.45-2.59]), and the Unmet Financial Needs class had higher odds of diabetes (OR, 1.50; [95% CI, 1.10-2.05]). Non-Hispanic Black participants compared with non-Hispanic White participants had higher odds of being members of the Generally Unmet Needs, Unmet Self-Efficacy/Goal Needs, and Unmet Financial Needs classes (OR, 2.70; [95% CI, 1.59-4.58]; OR, 1.99; [95% CI, 1.15-3.43]; and OR, 4.74; [95% CI, 3.32-6.76], respectively). Class membership remained relatively stable over time, with 93% of participants remaining in Generally Met Needs and 78% of participants remaining in Generally Unmet Needs across time points. Compared with non-Hispanic White participants, non-Hispanic Black participants had lower odds of Generally Met Needs class membership at any time point (OR, 0.60; [95% CI, 0.42-0.84]) and had lower odds of moving into the Generally Met Needs class and higher odds of moving into the Unmet Financial Needs class from 2010 to 2014 (OR, 0.33; [95% CI, 0.13-0.86]; and OR, 3.02; [95% CI, 1.16-7.87], respectively). Conclusions Underlying classes of stress based on unmet needs were associated with hypertension and diabetes status. Racial and ethnic differences were observed for both latent class membership and transitions between classes over time. Latent classes of stress associated with unmet needs, hypertension, and diabetes and the ability to transition between classes may explain the perpetuation of racial and ethnic disparities in cardiovascular health. Interventions targeting unmet needs may be used to confront these disparities.

A Socioecological Mixture Model of Asthma Prevalence Among Sexual Minority Adults in the United States.

Purpose: Sexual minority (SM) identity as well as sociodemographic and socioeconomic factors are associated with asthma prevalence. A syndemics framework analyzes disease conditions in a population and the social, economic, and environmental contexts in which they are found. We used a syndemic model of individual-level socioecological factors to identify profiles of asthma prevalence among SM adults. Methods: Latent class analysis (LCA) was conducted on a subpopulation of SM adults aged 18-59 years from the 2001 to 2016 National Health and Nutrition Examination Survey. Indicators in the LCA model included current asthma, gender, sexual identity, poverty-income ratio, education, and serum cotinine level. Multinomial logistic regression analyzed the effects of covariates (race/ethnicity, nativity, age, marital status, body mass index, lifetime smoking, and mental health care seeking) on identified profiles. Results: Four classes were identified among our sample of n = 1097 SM adults. Classes 1 and 2 had 19% and 18% conditional probabilities of current asthma, respectively, and were primarily female and bisexual. Classes 3 and 4 had 5% and 2% conditional probabilities of asthma, respectively, and were primarily male and gay. Classes 1 and 3 also had conditional probabilities of high income and educational attainment. Black individuals had higher odds than White individuals of being in Class 1 (odds ratio [OR] = 4.46, 95% confidence interval [CI] = 1.43-13.93), Class 2 (OR = 21.66, 95% CI = 7.50-62.60), and Class 4 (OR = 7.41, 95% CI = 2.05-26.71), relative to Class 3. Conclusion: Findings extend past literature that suggests within-group asthma disparities among SM adults. Informational campaigns on asthma management should target this community to avoid severe disease exacerbations.

Profiles of Sleep Duration and Psychological Distress among Puerto Ricans Living in the United States: A Cross-Sectional Survey and Latent Class Analysis.

Sleep duration affects physiological functioning and mental health outcomes among Hispanics/Latinos. The limited research reports that Hispanic/Latino subpopulations like Puerto Ricans carry a disproportionate burden. To understand this burden, we identified profiles of sleep duration by psychological distress among Puerto Rican adults (N = 4443) using latent class analysis on 2010-2019 National Health Interview Survey data. The outcome of sleep was constructed from self-reports of sleep duration and difficulties falling and staying asleep. Sleep duration was categorized as short sleep (≤6 h), normal sleep (7 to 8 h), and long sleep (≥9 h). Mental health indicators included psychological distress items from the Kessler-6 scale. Health behaviors (nicotine and alcohol use), weight (calculated body mass index), food security, acculturative factors (language use), and socio-economic/socio-demographic covariates were considered to further differentiate profiles. Six profiles were identified: troubled shortest sleep (5.0% of sample) with high psychological distress; highly troubled short sleep (8.0%) with little psychological distress; some disturbed and shortened sleep (10.0%) with moderate psychological distress; undisturbed and shortened sleep (28.0%) with little psychological distress; normal/average sleep (49.0%); and long sleep (1.0%) with moderate psychological distress. While our study is among the first to identify profiles that are at the highest mental health risk due to sleep issues, the findings and approach help examine the complex disparity among Puerto Ricans to then leverage complex survey data for interventional designs.

Sociodemographic Factors and Health Insurance Coverage Are Associated with Invasive Breast Cancer in Tennessee: Appalachian and Non-Appalachian County Comparison.

Background: Tennessean women experience the 12th highest breast cancer (BC) mortality in the United States. Yet, few studies have examined BC outcomes among Tennessean women in and outside of Appalachia. We examined whether sociodemographic factors and health insurance status were associated with invasive BC in Tennessee by Appalachian and non-Appalachian county designation. Materials and Methods: Using the Tennessee Cancer Registry, we identified 52,187 women, aged ≥18, diagnosed with BC between 2005 and 2015. Multivariable logistic regression was performed to examine associations between invasive BC and sociodemographic characteristics, health insurance coverage, and county designation (Appalachian/non-Appalachian). Regression analyses stratified by county designation were subsequently performed. Results: In Tennessee, younger women had lower odds of invasive BC diagnosis (<45: odds ratio [OR] = 0.74, 95% confidence interval [CI] = 0.67-0.81; 55-64: OR = 0.91, 95% CI = 0.84-0.97) compared to women ≥65. Married Tennessean women had 12% (95% CI = 1.04-1.21) higher odds of invasive BC than single women. Further, both public (OR = 1.81, 95% CI = 1.41-2.33) and private (OR = 1.36, 95% CI = 1.06-1.76) health insurance were found to increase odds of invasive BC compared to no insurance/self-pay. Results from the subpopulation analyses were largely consistent with overall findings. In Appalachian counties, women on public health insurance had increased odds (OR = 1.42, 95% CI = 1.00-2.03) of invasive BC compared to uninsured/self-pay women, while in non-Appalachian counties, women insured both publicly (OR = 2.25, 95% CI = 1.57-3.24) and privately (OR = 1.68, 95% CI = 1.16-2.24) had increased odds of invasive BC. Conclusions: The results identify risk factors for Tennessean women in Appalachian and non-Appalachian counties whose malignancies evaded early detection, increasing risk of mortality.

Breast cancer screening among Hispanic and non-Hispanic White women by birthplace in the Sister Study.

BACKGROUND: Hispanic/Latina women are less likely to be diagnosed with local stage breast cancer than White women. Additionally, foreign-born women have lower mammography rates than US-born women. We evaluated the combined effect of birthplace and race/ethnicity on screening habits of women at higher-than-average risk of breast cancer. METHODS: Multinomial logistic regression was used to evaluate breast cancer screening in 44,524 women in the Sister Study cohort. Screening methods ascertained at enrollment (2003-2009) included mammography, ultrasound, and magnetic resonance imaging. Timing of screening was assessed as recently (≤2 years ago), formerly (>2 years ago), and never screened. Adjustments included sociodemographic, socioeconomic, and health variables. RESULTS: Most women in the sample were US-born non-Hispanic/Latina White (92%), were ≥50 years old (73%), had one first-degree female relative with breast cancer (73%), and were screened in the past two years (97%). US-born Hispanic/Latina women had higher odds (odds ratio [OR] = 1.47, 95% confidence interval [CI] = 1.08-2.00) than US-born non-Hispanic/Latina White women of not having received a breast cancer screening in the past 2 years, relative to a recent screening. Similarly, foreign-born Hispanic/Latina women had higher odds (OR = 1.63, 95% CI = 1.10-2.41) than US-born non-Hispanic/Latina White women of never having received a breast cancer screening. CONCLUSION: We observed that Hispanic/Latina women have higher odds of never and dated breast cancer screenings compared to US-born White women. Birthplace and race/ethnicity each contribute to disparities in who receives preventative health care in the United States. It is critical to include birthplace when evaluating health behaviors in minority groups.

Maladaptive coping among military-connected adolescents: Examining combined risk using QCA.

Introduction: Military-connected students in public schools face a unique set of stressors that may impact their wellbeing and academic functioning. Methods: Twenty-four youth in the 7th to 12th grades who had an active-duty parent (mother or father) serving in the U.S. Armed Forces were interviewed. Participants completed a qualitative interview while actively completing a Life History Calendar (LHC) to mark deployment and family military service milestones and discuss how they impacted the youth respondent. This study used Qualitative Comparative Analysis (QCA) to explore the interplay and combination of specific stressors related to relocation and deployment experiences among adolescents, and to determine key factors associated with maladaptive outcomes. Results: The results of the QCA analysis identified bullying experiences and negative experiences with other military-connected youth as conditions that are associated with maladaptive coping. Discussion: Chronic and acute stressors in adolescence are established risk factors for mental, emotional, and behavioral problems in the short and long-term including suicidality, substance use and abuse, and substance use disorders. Through qualitative inquiry we were able to identify specific contextual details related to maladaptive coping that can be used to further refine areas of focus for research, prevention, and interventions for military-connected adolescents.

Intimate partner violence and HIV testing during antenatal care: A latent class analysis to identify risk factors for HIV infection in mothers and their children in the United Republic of Tanzania.

Intimate partner violence has adverse effects on mother's overall health and prevention of mother to child HIV transmission. To identify and examine subgroups of mothers experiencing intimate partner violence and the likelihood of HIV testing during antenatal care, we conducted a latent class analysis using data from the Tanzania Demographic and Health Survey 2010 (N = 2,809). Intimate partner violence included mother's experiences with partners' controlling behaviors, as well as emotional, physical, and sexual violence. The outcome was mother's accepting HIV testing offered during their antenatal care visit. Covariates included mother's level of education, rural/urban residence, and prevention of mother to child HIV transmission talk during antenatal care visit. The latent class analysis indicated a three-class solution was the best model and identified the following profiles: mothers with no experience of intimate partner violence (61% of sample) with a 90.5% likelihood of HIV testing; mothers with moderate levels of intimate partner violence (26%) with an 84.7% likelihood of testing; and mothers with extreme levels of intimate partner violence (13%) with an 82% likelihood of testing. An auxiliary multinomial logistic regression with selected covariates was conducted to further differentiate IPV profiles, where mothers with extreme levels of intimate partner violence had 57% increased odds [95%CI:1.06-2.33, p = .023] of living in rural areas compared to mothers with no experience of intimate partner violence. Our person-centered methodological approach provided a novel model to understand the impact of multiple intimate partner violence risk factors on antenatal care HIV testing to identify mothers in need of interventions and their children at highest for parent to child HIV transmission. Our model allows person-centered interventional designs tailored for the most at-risk subgroups within a population.

Applying Latent Class Analysis on Cancer Registry Data to Identify and Compare Health Disparity Profiles in Colorectal Cancer Surgical Treatment Delay.

CONTEXT: Colorectal cancer (CRC) surgical treatment delay (TD) has been associated with mortality and morbidity; however, disparities by TD profiles are unknown. OBJECTIVES: This study aimed to identify CRC patient profiles of surgical TD while accounting for differences in sociodemographic, health insurance, and geographic characteristics. DESIGN: We used latent class analysis (LCA) on 2005-2015 Tennessee Cancer Registry data of CRC patients and observed indicators that included sex/gender, age at diagnosis, marital status (single/married/divorced/widowed), race (White/Black/other), health insurance type, and geographic residence (non-Appalachian/Appalachian). SETTING: The state of Tennessee in the United States that included both Appalachian and non-Appalachian counties. PARTICIPANTS: Adult (18 years or older) CRC patients (N = 35 412) who were diagnosed and surgically treated for in situ (n = 1286) and malignant CRC (n = 34 126). MAIN OUTCOME MEASURE: The distal outcome of TD was categorized as 30 days or less and more than 30 days from diagnosis to surgical treatment. RESULTS: Our LCA identified a 4-class solution and a 3-class solution for in situ and malignant profiles, respectively. The highest in situ CRC patient risk profile was female, White, aged 75 to 84 years, widowed, and used public health insurance when compared with respective profiles. The highest malignant CRC patient risk profile was male, Black, both single/never married and divorced/separated, resided in non-Appalachian county, and used public health insurance when compared with respective profiles. The highest risk profiles of in situ and malignant patients had a TD likelihood of 19.3% and 29.4%, respectively. CONCLUSIONS: While our findings are not meant for diagnostic purposes, we found that Blacks had lower TD with in situ CRC. The opposite was found in the malignant profiles where Blacks had the highest TD. Although TD is not a definitive marker of survival, we observed that non-Appalachian underserved/underrepresented groups were overrepresented in the highest TD profiles. The observed disparities could be indicative of intervenable risk.

Sociodemographic and Geographic Disparities of Prostate Cancer Treatment Delay in Tennessee: A Population-Based Study.

The relationship of social determinants of health, Appalachian residence, and prostate cancer treatment delay among Tennessee adults is relatively unknown. We used multivariate logistic regression on 2005-2015 Tennessee Cancer Registry data of adults aged ≥18 diagnosed with prostate cancer. The outcome of treatment delay was more than 90 days without surgical or nonsurgical intervention from date of diagnosis. Social determinants in the population-based registry were race (White, Black, Other) and marital status (single, married, divorced/separated, widow/widower). Tennessee residence was classified as Appalachian versus non-Appalachian (urban/rural). Covariates include age at diagnosis (18-54, 54-69, ≥70), health insurance type (none, public, private), derived staging of cancer (localized, regional, distant), and treatment type (non-surgical/surgical). We found that Black and divorced/separated patients had 32% (95% confidence interval [CI]: 1.22-1.42) and 15% (95% CI: 1.01-1.31) increased odds to delay prostate cancer treatment. Patients were at decreased odds of treatment delay when living in an Appalachian county, both urban (odds ratio [OR] = 0.89, 95% CI: 0.82-0.95) and rural (OR = 0.83, 95% CI: 0.78-0.89), diagnosed at ≥70 (OR = 0.59, 95% CI: 0.53-0.66), and received surgical intervention (OR = 0.72, 95% CI: 0.68-0.76). Our study was among the first to comprehensively examine prostate cancer treatment delay in Tennessee, and while we do not make clinical recommendations, there is a critical need to further explore the unique factors that may propagate disparities. Prostate cancer treatment delay in Black patients may be indicative of ongoing health and access disparities in Tennessee, which may further affect quality of life and survivorship among this racial group. Divorced/separated patients may need tailored interventions to improve social support.

A National Study of Colorectal Cancer Survivorship Disparities: A Latent Class Analysis Using SEER (Surveillance, Epidemiology, and End Results) Registries.

Introduction: Long-standing disparities in colorectal cancer (CRC) outcomes and survival between Whites and Blacks have been observed. A person-centered approach using latent class analysis (LCA) is a novel methodology to assess and address CRC health disparities. LCA can overcome statistical challenges from subgroup analyses that would normally impede variable-centered analyses like regression. Aim was to identify risk profiles and differences in malignant CRC survivorship outcomes. Methods: We conducted an LCA on the Surveillance, Epidemiology, and End Results data from 1975 to 2016 for adults ≥18 (N = 525,245). Sociodemographics used were age, sex/gender, marital status, race, and ethnicity (Hispanic/Latinos) and stage at diagnosis. To select the best fitting model, we employed a comparative approach comparing sample-size adjusted BIC and entropy; which indicates a good separation of classes. Results: A four-class solution with an entropy of 0.72 was identified as: lowest survivorship, medium-low, medium-high, and highest survivorship. The lowest survivorship class (26% of sample) with a mean survival rate of 53 months had the highest conditional probabilities of being 76-85 years-old at diagnosis, female, widowed, and non-Hispanic White, with a high likelihood with localized staging. The highest survivorship class (53% of sample) with a mean survival rate of 92 months had the highest likelihood of being married, male with localized staging, and a high likelihood of being non-Hispanic White. Conclusion: The use of a person-centered measure with population-based cancer registries data can help better detect cancer risk subgroups that may otherwise be overlooked.

Polytobacco use among a nationally-representative sample of black high school students.

BACKGROUND: Studies of the patterns of polytobacco use have increased. However, understanding the patterns of using multiple tobacco products among Black adolescents is minimal. This study identified the patterns of polytobacco use among U.S. Black adolescents. METHODS: Latent class analysis (LCA) was used to identify patterns of adolescent polytobacco use among a representative sample of Black youth from the 2017 Youth Risk Behavior Survey (n = 2782). Ever and recent (past 30 day) use of cigarettes, electronic cigarettes, cigars, and dip or chewing tobacco were used as latent class indicators. Multinomial regression was conducted to identify the association if smoking adjusting for sex, age, grade, and marijuana use. RESULTS: Most students were in the 9th grade (29%), e-cigarette users (21%) and were current marijuana users (25%). Three profiles of tobacco use were identified: Class 1: Non-smokers (81%), Class 2: E-cigarette Users (14%), and Class 3: Polytobacco Users (5%). Black adolescent Polytobacco users were the smallest class, but had the highest conditional probabilities of recent cigarette use, e-cigarette use, ever smoking cigars or chewing tobacco. Ever and current use of marijuana were associated with increased odds of being in the e-cigarette user versus non-smoker group, and current marijuana use was associated with increased odds of polytobacco use (aOR = 24.61, CI = 6.95-87.11). CONCLUSIONS: Findings suggests the need for targeted interventions for reducing tobacco use and examining the unique effects of polytobacco use on Black adolescents. Findings confirm a significant association of marijuana use with tobacco use.

Identifying Risk Profiles of Malignant Prostate Cancer Surgical Delay Using a Person-Centered Approach to Understand Prostate Cancer Disparities: The Constellation of Health Determinants Using Latent Class Analysis on Cancer Registry Data.

Surgical prostate cancer (PCa) treatment delay (TD) may increase the likelihood of recurrence of disease, and influence quality of life as well as survival disparities between Black and White men. We used latent class analysis (LCA) to identify risk profiles in localized, malignant PCa surgical treatment delays while assessing co-occurring social determinants of health. Profiles were identified by age, marital status, race, county of residence (non-Appalachian or Appalachian), and health insurance type (none/self-pay, public, or private) reported in the Tennessee Department of Health cancer registry from 2005 to 2015 for adults ≥18 years (N = 18,088). We identified three risk profiles. The highest surgical delay profile (11% of the sample) with a 30% likelihood of delaying surgery >90 days were young Black men, <55 years old, living in a non-Appalachian county, and single/never married, with a high probability of having private health insurance. The medium surgical delay profile (46% of the sample) with a 21% likelihood of delay were 55-69 years old, White, married, and having private health insurance. The lowest surgical delay profile (42% of the sample) with a 14% likelihood of delay were ≥70 years with public health insurance as well as had a high probability of being White and married. We identified that even with health insurance coverage, Blacks living in non-Appalachian counties had the highest surgical delay, which was almost double that of Whites in the lowest delay profile. These disparities in PCa surgical delay may explain differences in health outcomes in Blacks who are most at-risk.

A comprehensive multivariate model of biopsychosocial factors associated with opioid misuse and use disorder in a 2017-2018 United States national survey.

BACKGROUND: Few studies have comprehensively and contextually examined the relationship of variables associated with opioid use. Our purpose was to fill a critical gap in comprehensive risk models of opioid misuse and use disorder in the United States by identifying the most salient predictors. METHODS: A multivariate logistic regression was used on the 2017 and 2018 National Survey on Drug Use and Health, which included all 50 states and the District of Columbia of the United States. The sample included all noninstitutionalized civilian adults aged 18 and older (N = 85,580; weighted N = 248,008,986). The outcome of opioid misuse and/or use disorder was based on reported prescription pain reliever and/or heroin use dependence, abuse, or misuse. Biopsychosocial predictors of opioid misuse and use disorder in addition to sociodemographic characteristics and other substance dependence or abuse were examined in our comprehensive model. Biopsychosocial characteristics included socioecological and health indicators. Criminality was the socioecological indicator. Health indicators included self-reported health, private health insurance, psychological distress, and suicidality. Sociodemographic variables included age, sex/gender, race/ethnicity, sexual identity, education, residence, income, and employment status. Substance dependence or abuse included both licit and illicit substances (i.e., nicotine, alcohol, marijuana, cocaine, inhalants, methamphetamine, tranquilizers, stimulants, sedatives). RESULTS: The comprehensive model found that criminality (adjusted odds ratio [AOR] = 2.58, 95% confidence interval [CI] = 1.98-3.37, p < 0.001), self-reported health (i.e., excellent compared to fair/poor [AOR = 3.71, 95% CI = 2.19-6.29, p < 0.001], good [AOR = 3.43, 95% CI = 2.20-5.34, p < 0.001], and very good [AOR = 2.75, 95% CI = 1.90-3.98, p < 0.001]), no private health insurance (AOR = 2.12, 95% CI = 1.55-2.89, p < 0.001), serious psychological distress (AOR = 2.12, 95% CI = 1.55-2.89, p < 0.001), suicidality (AOR = 1.58, 95% CI = 1.17-2.14, p = 0.004), and other substance dependence or abuse were significant predictors of opioid misuse and/or use disorder. Substances associated were nicotine (AOR = 3.01, 95% CI = 2.30-3.93, p < 0.001), alcohol (AOR = 1.40, 95% CI = 1.02-1.92, p = 0.038), marijuana (AOR = 2.24, 95% CI = 1.40-3.58, p = 0.001), cocaine (AOR = 3.92, 95% CI = 2.14-7.17, p < 0.001), methamphetamine (AOR = 3.32, 95% CI = 1.96-5.64, p < 0.001), tranquilizers (AOR = 16.72, 95% CI = 9.75-28.65, p < 0.001), and stimulants (AOR = 2.45, 95% CI = 1.03-5.87, p = 0.044). CONCLUSIONS: Biopsychosocial characteristics such as socioecological and health indicators, as well as other substance dependence or abuse were stronger predictors of opioid misuse and use disorder than sociodemographic characteristics.

Finding the Hidden Risk Profiles of the United States Opioid Epidemic: Using a Person-Centered Approach on a National Dataset of Noninstitutionalized Adults Reporting Opioid Misuse.

Opioid misuse can lead to use disorder and other adverse outcomes. Identifying sociodemographic risk profiles and understanding misuse patterns in combination with health indicators can inform prevention science and clinical practice. A latent class analysis of opioid misuse was conducted on noninstitutionalized United States civilians aged 18 and older that reported opioid dependence or abuse in the 2017 National Survey of Drug Use and Health (n = 476; weighted n = 2,018,922). Opioid misuse was based on heroin and/or prescription pain reliever use, and associated determinants of health and mental health indicators. Five misuse profiles were identified: (1) single heroin or prescription misuse with high-income; (2) female prescription pain reliever misuse with psychological distress and suicidality; (3) younger polyopioid misuse with the highest proportion of Hispanics and heroin use; (4) older polyopioid misuse with the highest proportion of non-Hispanic blacks and disability; and (5) older non-Hispanic white male exclusive dual heroin and/or prescription misuse (27%, 20%, 38%, 10%, and 5% of sample, respectively). The identified risk profiles can inform public health practice to develop interventions for acute and immediate response by providing etiological evidence and to inform prevention and intervention efforts along the continuum from opioid initiation to use disorder.