Inclusion of marginalized populations in HPV vaccine modeling: A systematic review.

OBJECTIVE: Models simulating the potential impacts of Human Papillomavirus (HPV) vaccine have been used globally to guide vaccination policies and programs. We sought to understand how and why marginalized populations have been incorporated into HPV vaccine simulation models. METHODS: We conducted a systematic search of PubMed, CINAHL, Scopus, and Embase to identify studies using simulation models of HPV vaccination incorporating one or more marginalized population through stratification or subgroup analysis. We extracted data on study characteristics and described these overall and by included marginalized groups. RESULTS: We identified 36 studies that met inclusion criteria, which modeled vaccination in 21 countries. Models included men who have sex with men (MSM; k = 16), stratification by HIV status (k = 9), race/ethnicity (k = 6), poverty (k = 5), rurality (k = 4), and female sex workers (k = 1). When evaluating for a marginalized group (k = 10), HPV vaccination was generally found to be cost-effective, including for MSM, individuals living with HIV, and rural populations. In studies evaluating equity in cancer prevention (k = 9), HPV vaccination generally advanced equity, but this was sensitive to differences in HPV vaccine uptake and use of absolute or relative measures of inequities. Only one study assessed the impact of an intervention promoting HPV vaccine uptake. DISCUSSION: Incorporating marginalized populations into decision models can provide valuable insights to guide decision making and improve equity in cancer prevention. More research is needed to understand the equity impact of HPV vaccination on cancer outcomes among marginalized groups. Research should emphasize implementation - including identifying and evaluating specific interventions to increase HPV vaccine uptake.

The Impact of Menthol Cigarette Bans: A Systematic Review and Meta-Analysis.

INTRODUCTION: This review investigates the impacts of banning the sale of menthol cigarettes at stores. METHODS: A systematic search of studies published in English up to November 2022 was conducted. The following databases were searched: PubMed/Medline, CINAHL, PsycINFO, Web of Science, and Embase, as well as a non-indexed journal. Studies evaluating either the impact of real-world or hypothesized menthol cigarette bans were included. Primary outcomes include tobacco use behaviors. Secondary outcomes include cigarette sales, retailer compliance, and the tobacco industry's response to a menthol ban. Data on tobacco use behavior after a menthol ban were pooled using random-effects models. Two pairs of reviewers independently extracted data and assessed study quality. RESULTS: Of the 964 articles that were identified during the initial search, 78 were included in the review and 16 were included in the meta-analysis. Cessation rates among menthol cigarette smokers were high after a menthol ban. Pooled results show that 24% (95% confidence interval [95% CI]: 20%, 28%) of menthol cigarette smokers quit smoking after a menthol ban, 50% (95% CI: 31%, 68%) switched to non-menthol cigarettes, 12% (95% CI: 3%, 20%) switched to other flavored tobacco products, and 24% (95% CI: 17%, 31%) continued smoking menthol cigarettes. Hypothesized quitting and switching rates were fairly close to real-world rates. Studies found the tobacco industry attempts to undermine menthol bans. National menthol bans appear more effective than local or state menthol bans. CONCLUSIONS: Menthol cigarette bans promote smoking cessation suggesting their potential to improve public health. IMPLICATIONS: Findings from this review suggest that menthol cigarette bans promote smoking cessation among menthol cigarette smokers and have the potential to improve public health.

Improving Prediction of Tobacco Use Over Time: Findings from Waves 1-4 of the Population Assessment of Tobacco and Health Study.

INTRODUCTION: First-order Markov models assume future tobacco use behavior is dependent on current tobacco use and are often used to characterize patterns of tobacco use over time. Higher-order Markov models that assume future behavior is dependent on current and prior tobacco use may better estimate patterns of tobacco use. AIMS AND METHODS: This study compared Markov models of different orders to examine whether incorporating information about tobacco use history improves model estimation of tobacco use and estimated tobacco use transition probabilities. We used data from four waves of the Population Assessment of Tobacco and Health Study. In each Wave, a participant was categorized into one of the following tobacco use states: never smoker, former smoker, menthol cigarette smoker, non-menthol cigarette smoker, or e-cigarette/dual user. We compared first-, second-, and third-order Markov models using multinomial logistic regression and estimated transition probabilities between tobacco use states. `RESULTS: The third-order model was the best fit for the data. The percentage of former smokers, menthol cigarette smokers, non-menthol cigarette smokers, and e-cigarette/dual users in Wave 3 that remained in the same tobacco use state in Wave 4 ranged from 63.4% to 97.2%, 29.2% to 89.8%, 34.8% to 89.7%, and 20.5% to 80.0%, respectively, dependent on tobacco use history. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit. CONCLUSIONS: Transition probabilities between tobacco use states varied widely depending on tobacco use history. Higher-order Markov models improve estimation of tobacco use over time and can inform understanding of trajectories of tobacco use behavior. IMPLICATIONS: Findings from this study suggest that transition probabilities between tobacco use states vary widely depending on tobacco use history. Tobacco product users (cigarette or e-cigarette/dual users) who were in the same tobacco use state in the prior two years were least likely to quit. Individuals who were current tobacco users, but former smokers in the prior two years, were most likely to quit. Quitting smoking for at least two years is an important milestone in the process of cessation.

Multi-level predictors of being up-to-date with colorectal cancer screening.

PURPOSE: Assessing factors associated with being up-to-date with colorectal cancer (CRC) screening is important for identifying populations for which targeted interventions may be needed. METHODS: This study used Medicare and private insurance claims data for residents of North Carolina to identify up-to-date status in the 10th year of continuous enrollment in the claims data and in available subsequent years. USPSTF guidelines were used to define up-to-date status for multiple recommended modalities. Area Health Resources Files provided geographic and health care service provider data at the county level. A generalized estimating equation logistic regression model was used to examine the association between individual- and county-level characteristics and being up-to-date with CRC screening. RESULTS: From 2012-2016, 75% of the sample (n = 274,660) age 59-75 was up-to-date. We identified several individual- (e.g., sex, age, insurance type, recent visit with a primary care provider, distance to nearest endoscopy facility, insurance type) and county-level (e.g., percentage of residents with a high school education, without insurance, and unemployed) predictors of being up-to-date. For example, individuals had higher odds of being up-to-date if they were age 73-75 as compared to age 59 [OR: 1.12 (1.09, 1.15)], and if living in counties with more primary care physicians [OR: 1.03 (1.01, 1.06)]. CONCLUSION: This study identified 12 individual- and county-level demographic characteristics related to being up-to-date with screening to inform how interventions may optimally be targeted.

Using systems science to advance health equity in tobacco control: a causal loop diagram of smoking.

OBJECTIVES: Develop and use a causal loop diagram (CLD) of smoking among racial/ethnic minority and lower-income groups to anticipate the intended and unintended effects of tobacco control policies. METHODS: We developed a CLD to elucidate connections between individual, environmental and structural causes of racial/ethnic and socioeconomic disparities in smoking. The CLD was informed by a review of conceptual and empirical models of smoking, fundamental cause and social stress theories and 19 qualitative interviews with tobacco control stakeholders. The CLD was then used to examine the potential impacts of three tobacco control policies. RESULTS: The CLD includes 24 constructs encompassing individual (eg, risk perceptions), environmental (eg, marketing) and structural (eg, systemic racism) factors associated with smoking. Evaluations of tobacco control policies using the CLD identified potential unintended consequences that may maintain smoking disparities. For example, the intent of a smoke-free policy for public housing is to reduce smoking among residents. Our CLD suggests that the policy may reduce smoking among residents by reducing smoking among family/friends, which subsequently reduces pro-smoking norms and perceptions of tobacco use as low risk. On the other hand, some residents who smoke may violate the policy. Policy violations may result in financial strain and/or housing instability, which increases stress and reduces feelings of control, thus having the unintended consequence of increasing smoking. CONCLUSIONS: The CLD may be used to support stakeholder engagement in action planning and to identify non-traditional partners and approaches for tobacco control.

Community Engagement in Implementation Science: the Impact of Community Engagement Activities in the DECIPHeR Alliance.

Background: The translation of evidence-based interventions into practice settings remains challenging. Implementation science aims to bridge the evidence-to-practice gap by understanding multilevel contexts and tailoring evidence-based interventions accordingly. Engaging community partners who possess timely, local knowledge is crucial for this process to be successful. The Disparities Elimination through Coordinated Interventions to Prevent and Control Heart and Lung Disease Risk (DECIPHeR) Alliance aims to address cardiopulmonary health disparities by engaging diverse community partners to improve the implementation of evidence-based interventions. The goal of the Community Engagement Subcommittee is to strengthen community engagement practice across DECIPHeR. This paper presents the subcommittee's "Why We Engage Communities" statement that outlines why community engagement is critical for implementation science. The paper also provides case examples of DECIPHeR community engagement activities. Methods: To develop the "Why We Engage Communities" statement, we conducted a literature review, surveyed subcommittee members to assess the importance of community engagement in their work, and integrated community partner feedback. We synthesize the findings into three key themes and present examples of community engagement activities and their impact across DECIPHeR projects. Results: The statement presents three themes that illustrate why community engagement increases the impact of implementation and health equity research. Community engagement (1) engages local knowledge and expertise, (2) promotes authentic relationships, and (3) builds community and researcher capacity. The statement provides a guiding framework for strengthening DECIPHeR research and enhancing community partnerships. Conclusion: Community engagement can improve the implementation of evidence-based interventions across diverse settings, improving intervention effectiveness in underserved communities and furthering health equity.

Recommendations to advance equity in tobacco control.

Reducing racial and socioeconomic inequities in smoking has been declared a priority for tobacco control in the USA for several decades. Yet despite the rhetoric, these inequities persist and some have actually worsened over time. Although tobacco companies have targeted racially and ethnically diverse and lower-income tobacco users, which substantially contributes to these disparities, less attention has been given to the role of individuals and organisations within the tobacco control movement who have allowed progress in eliminating disparities to stagnate. We examine the failure of tobacco control professionals to ensure the widespread adoption of equity-focused tobacco control strategies. Review of major US tobacco control reports found that the focus on equity often stops after describing inequities in tobacco use. We suggest ways to advance equity in tobacco control in the USA. These recommendations fall across five categories: surveillance, interventions, funding, accountability and addressing root causes. Policy interventions that will have a pro-equity impact on smoking and related disease should be prioritised. Funding should be designated to tobacco control activities focused on eliminating racial and socioeconomic inequities in smoking, and tobacco control programmes should be held accountable for meeting equity-related goals.

Evidence-Based Point-of-Sale Policies to Reduce Youth Tobacco Use in North Carolina.

Many states and localities in the United States are implementing evidence-based tobacco control policies at the retail level, including Tobacco 21 laws, tobacco retailer licensing, restrictions on point-of-sale promotions, and bans on flavored tobacco products. With the passage of new point-of-sale tobacco control policies, North Carolina could reduce youth tobacco use rates.

When History and Heterogeneity Matter: A Tutorial on the Impact of Markov Model Specifications in the Context of Colorectal Cancer Screening.

BACKGROUND: Markov models are used in health research to simulate health care utilization and disease states over time. Health phenomena, however, are complex, and the memoryless assumption of Markov models may not appropriately represent reality. This tutorial provides guidance on the use of Markov models of different orders and stratification levels in health decision-analytic modeling. Colorectal cancer (CRC) screening is used as a case example to examine the impact of using different Markov modeling approaches on CRC outcomes. METHODS: This study used insurance claims data from commercially insured individuals in Oregon to estimate transition probabilities between CRC screening states (no screen, colonoscopy, fecal immunochemical test or fecal occult blood test). First-order, first-order stratified by sex and geography, and third-order Markov models were compared. Screening trajectories produced from the different Markov models were incorporated into a microsimulation model that simulated the natural history of CRC disease progression. Simulation outcomes (e.g., future screening choices, CRC incidence, deaths due to CRC) were compared across models. RESULTS: Simulated CRC screening trajectories and resulting CRC outcomes varied depending on the Markov modeling approach used. For example, when using the first-order, first-order stratified, and third-order Markov models, 30%, 31%, and 44% of individuals used colonoscopy as their only screening modality, respectively. Screening trajectories based on the third-order Markov model predicted that a higher percentage of individuals were up-to-date with CRC screening as compared with the other Markov models. LIMITATIONS: The study was limited to insurance claims data spanning 5 y. It was not possible to validate which Markov model better predicts long-term screening behavior and outcomes. CONCLUSIONS: Findings demonstrate the impact that different order and stratification assumptions can have in decision-analytic models. HIGHLIGHTS: This tutorial uses colorectal cancer screening as a case example to provide guidance on the use of Markov models of different orders and stratification levels in health decision-analytic models.Colorectal cancer screening trajectories and projected health outcomes were sensitive to the use of alternate Markov model specifications.Although data limitations precluded the assessment of model accuracy beyond a 5-y period, within the 5-y period, the third-order Markov model was slightly more accurate in predicting the fifth colorectal cancer screening action than the first-order Markov model.Findings from this tutorial demonstrate the importance of examining the memoryless assumption of the first-order Markov model when simulating health care utilization over time.

Sociodemographic Disparities in Tobacco Retailer Density in the United States, 2000-2017.

INTRODUCTION: Studies find differences in tobacco retailer density according to neighborhood sociodemographic characteristics, raising issues of social justice, but not all research is consistent. AIMS AND METHODS: This study examined associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints (2000, 2007, 2012, and 2017) and investigated if associations remained stable over time. Data on tobacco retailers came from the National Establishment Time-Series Database. Adjusted log-linear models examined the relationship between retailer density and census tract sociodemographic characteristics (% non-Hispanic Black [Black], % Hispanic, % vacant housing units, median household income), controlling for percentage of youth, urbanicity, and US region. To examine whether the relationship between density and sociodemographic characteristics changed over time, additional models were estimated with interaction terms between each sociodemographic characteristic and year. RESULTS: Tobacco retailer density ranged from 1.22 to 1.44 retailers/1000 persons from 2000 to 2017. There were significant, positive relationships between tobacco retailer density and the percentage of Black (standardized exp(b) = 1.05 [95% CI: 1.04% to 1.07%]) and Hispanic (standardized exp(b) = 1.06 [95% CI: 1.05% to 1.08%]) residents and the percentage of vacant housing units (standardized exp(b) =1.08 [95% CI: 1.07% to 1.10%]) in a census tract. Retailer density was negatively associated with income (standardized exp(b) = 0.84 [95% CI: 0.82% to 0.86%]). From 2000 to 2017, the relationship between retailer density and income and vacant housing units became weaker. CONCLUSIONS: Despite the weakening of some associations, there are sociodemographic disparities in tobacco retailer density from 2000 to 2017, which research has shown may contribute to inequities in smoking. IMPLICATIONS: This study examines associations between tobacco retailer density and neighborhood sociodemographic characteristics in the United States at four timepoints from 2000 to 2017. Although some associations weakened, there are sociodemographic disparities in tobacco retailer density over the study period. Research suggests that sociodemographic disparities in retailer density may contribute to inequities in smoking. Findings from this study may help identify which communities should be prioritized for policy intervention and regulation.

Beliefs About the Health Effects of Smoking Among Adults in the United States.

The majority of U.S. adults believe that smoking is a cause of lung cancer, but research suggests that the percentage of adults who believe smoking causes other types of cancers and chronic disease is lower. This study examines the correlates of beliefs about several established health effects of smoking in a nationally representative sample of U.S. adults. Data for this study come from Wave 4 of the Population Assessment of Tobacco and Health Study conducted from December 2016 to January 2018. Participants responded to questions assessing their beliefs about the health effects of smoking. Logistic regression models were used to examine the relationship between beliefs about the health effects of smoking and sociodemographic characteristics (smoker status, age, sex, education, race/ethnicity), exposure to antitobacco campaigns, smokers' health, and nicotine dependence. The percentage of U.S. adults who endorsed a health effect can be caused from smoking ranged from 56.4% for blindness to 97.4% for lung disease. Respondents who were older, less educated, current or former smokers, and had less exposure to antitobacco campaigns were generally less likely (p < .05) to endorse that an established health effect was caused by smoking. Smokers with lower nicotine dependence and worse health were generally more likely (p < .05) to endorse that an established health effect was caused by smoking. In summary, knowledge about the health effects of smoking varies across health conditions. Public health would benefit from campaigns targeting segments of the population with less knowledge about the health effects of smoking.

Assessing Sex, Gender Identity, Sexual Orientation, Race, Ethnicity, Socioeconomic Status, and Mental Health Concerns in Tobacco Use Disorder Treatment Research: Measurement Challenges and Recommendations From a Society for Research on Nicotine and Tobacco Pre-conference Workshop.

This paper reports on topics discussed at a Society for Research on Nicotine and Tobacco pre-conference workshop at the 2019 annual Society for Research on Nicotine and Tobacco meeting. The goal of the pre-conference workshop was to help develop a shared understanding of the importance of several tobacco-related priority groups in tobacco use disorder (TUD) treatment research and to highlight challenges in measurement related to these groups. The workshop focused on persons with minoritized sex, gender identity, and sexual orientation identities; persons with minoritized racial and ethnic backgrounds; persons with lower socioeconomic status (SES); and persons with mental health concerns. In addition to experiencing commercial tobacco-related health disparities, these groups are also underrepresented in tobacco research, including TUD treatment studies. Importantly, there is wide variation in how and whether researchers are identifying variation within these priority groups. Best practices for measuring and reporting sex, gender identity, sexual orientation, race, ethnicity, SES, and mental health concerns in TUD treatment research are needed. This paper provides information about measurement challenges when including these groups in TUD treatment research and specific recommendations about how to measure these groups and assess potential disparities in outcomes. The goal of this paper is to encourage TUD treatment researchers to use measurement best practices in these priority groups in an effort to conduct meaningful and equity-promoting research. Increasing the inclusion and visibility of these groups in TUD treatment research will help to move the field forward in decreasing tobacco-related health disparities. Implications: Tobacco-related disparities exist for a number of priority groups including, among others, women, individuals with minoritized sexual and gender identities, individuals with minoritized racial and ethnic backgrounds, individuals with lower SES, and individuals with mental health concerns. Research on TUD treatments for many of these subgroups is lacking. Accurate assessment and consideration of these subgroups will provide needed information about efficacious and effective TUD treatments, about potential mediators and moderators, and for accurately describing study samples, all critical elements for reducing tobacco-related disparities, and improving diversity, equity, and inclusion in TUD treatment research.

State-Level Patterns and Trends in Cigarette Smoking Across Racial and Ethnic Groups in the United States, 2011-2018.

INTRODUCTION: Reducing racial/ethnic disparities in smoking is a priority for state tobacco control programs. We investigated disparities in cigarette use by race/ethnicity, as well as trends in cigarette use across racial/ethnic groups from 2011 to 2018 in 50 US states and the District of Columbia. METHODS: We used data from the Behavioral Risk Factor Surveillance System. In each state, smoking prevalence and corresponding 95% CIs were estimated for each racial/ethnic group in 2011, 2014, and 2018. We used logistic regression models to examine state-specific linear and quadratic time trends in smoking prevalence from 2011 to 2018. RESULTS: Racial/ethnic disparities in smoking prevalence varied across states. From 2011 to 2018, compared with White adults, the odds of smoking were lower among Black adults in 14 states (odds ratio [OR] range, 0.58-0.91) and were higher in 9 states (OR range, 1.10-1.98); no differences were found in the odds of smoking in 13 states. Compared with White adults, the odds of smoking were lower among Hispanic adults in most states (OR range, 0.33-0.84) and were typically higher among Other adults (OR range, 1.19-2.44). Significant interactions between year and race/ethnicity were found in 4 states, indicating that time trends varied across racial/ethnic groups. In states with differential time trends, the decline in the odds of smoking was typically greater among Black, Hispanic, and Other adults compared with White adults. CONCLUSION: Some progress in reducing racial/ethnic disparities in smoking has been made, but additional efforts are needed to eliminate racial/ethnic disparities in smoking.

The African American Tobacco Control Leadership Council: Advocating for a menthol cigarette ban in San Francisco, California.

The African American Tobacco Control Leadership Council (AATCLC) is an advocacy group that works to inform the direction of tobacco control policy and priorities in the USA. This article narrates the AATCLC's work advocating for a comprehensive, flavoured tobacco product sales ban in San Francisco, California. Recommendations for tobacco control advocates and lessons learned from their work are provided. The article concludes by discussing conditions necessary to enact the policy. These include having a dedicated advocacy team, community support, a policy sponsor, and clear and repeated messaging that is responsive to community concerns.

The Relationship Between Menthol Cigarette Use, Smoking Cessation, and Relapse: Findings From Waves 1 to 4 of the Population Assessment of Tobacco and Health Study.

INTRODUCTION: Some, but not all, studies suggest that menthol cigarette smokers have more difficulty quitting than non-menthol cigarette smokers. Inconsistent findings may be a result of differences in smoker characteristics (eg, daily vs. non-daily smokers) across studies. This study examines the relationship between menthol cigarette use, cessation, and relapse in a longitudinal, nationally representative study of tobacco use in the United States. AIMS AND METHODS: Data come from four waves of the Population Assessment of Tobacco and Health Study. Waves 1-4 were conducted approximately annually from September 2013 to January 2018. Generalized estimating equation models were used to prospectively examine the relationship between menthol cigarette use, cessation, and relapse in non-daily and daily adult (18+) smokers. Cessation was defined as smokers who had not used cigarettes within the past 30 days at their subsequent assessment. Relapse was defined as cessation followed by past 30-day smoking in the next assessment. RESULTS: Among daily smokers (n = 13 710), 4.0% and 5.3% of menthol and non-menthol smokers quit after 1 year, respectively. In an adjusted model, menthol smokers were less likely to quit compared with non-menthol smokers (odds ratio [OR] = 0.76 [0.63, 0.91]). When the sample was stratified by race/ethnicity, African American (OR = 0.47 [0.24, 0.91]) and White (OR = 0.78 [0.63, 0.97]) daily menthol users were less likely to have quit. Among non-daily smokers (n = 3608), there were no significant differences in quit rates. Among daily and non-daily former smokers, there were also no differences in relapse rates between menthol and non-menthol smokers. CONCLUSIONS: Menthol cigarette use is associated with lower odds of cessation. IMPLICATIONS: Findings from this study suggest that menthol cigarette use is associated with lower odds of cessation, but not relapse. Removing menthol cigarettes from the market may improve cessation rates.

The Eleventh Judicial Circuit Criminal Mental Health Project: Improving Access to Mental Health Treatment in Miami-Dade County.

The Eleventh Judicial Circuit Criminal Mental Health Project (CMHP), a court-based jail diversion program, was established to divert individuals with serious mental illness from the criminal justice system into treatment and support services. The CMHP's success is built on collaboration among a diverse array of community stakeholders. This column describes the establishment and maintenance of these partnerships. CMHP's success is the result of several factors, including motivated local champions, acquisition of grant funding, formalized communication support, and use of the sequential intercept model. As the CMHP grows, system science methods will be useful for supporting optimization and sustainment.

Are state-level income-based disparities in adult smoking declining?

The United States (US) has identified income-based disparities in smoking as a critical public health issue, but the extent to which these disparities are changing over time within states is not well documented. This study examined recent trends in current cigarette smoking in each state and the District of Columbia by self-reported annual household income. Data came from the Behavioral Risk Factor Surveillance System, a state-representative survey of US adults. Sample sizes for each state and year ranged from 2914 to 36,955 participants. We fit logistic regression models to examine linear time trends in cigarette smoking status in each state between 2011 and 2017. In every state, the odds of smoking were 1.4 to 3.0 times greater in the lower-income group as compared to the higher-income group in 2017. Among 47 states, linear time trends in smoking did not significantly differ by income group, suggesting no change in income-based disparities. In three states (Florida, Maine, West Virginia) disparities widened, primarily because smoking prevalence only dropped among higher-income groups. Disparities declined in only one state. In New York, smoking prevalence declined more for lower-income groups compared to higher-income groups. Findings from this study suggest that little progress has been made toward reducing income-based differences in smoking and additional policy and tobacco control efforts may be required to meet national disparity reduction goals.

Validity and correlates of the Brief Satisfaction With Appearance Scale for patients with limited and diffuse systemic sclerosis: Analysis from the University of California, Los Angeles Scleroderma Quality of Life Study.

Objective: The Brief Satisfaction With Appearance Scale measures two dimensions (Dissatisfaction with Appearance and Social Discomfort) of body image dissatisfaction in systemic sclerosis. This study examined the structural validity of the Brief Satisfaction With Appearance Scale across limited and diffuse systemic sclerosis subtypes, compared body image dissatisfaction by systemic sclerosis subtype, and identified the significant sociodemographic and medical correlates of body image dissatisfaction and whether they differed by subtype. Methods: Participants were 183 adults participating in the University of California, Los Angeles Scleroderma Quality of Life Study with limited cutaneous (n = 101) or diffuse cutaneous (n = 82) systemic sclerosis who received clinical examinations and completed questionnaires. Multiple-group confirmatory factor analysis, multivariate analysis of variance, and structural equation modeling were used. Results: The Brief Satisfaction With Appearance Scale's two-factor structure fit well for both subtypes. Patients with diffuse systemic sclerosis reported greater body image dissatisfaction on both factors than patients with limited disease. Greater Dissatisfaction with Appearance was associated with younger age and being unmarried for limited patients, and with younger age and increased finger/hand skin involvement for diffuse patients. Greater Social Discomfort was associated with younger age and being unmarried for both subtypes. Conclusion: The Brief Satisfaction With Appearance Scale scores can be meaningfully compared across limited and diffuse systemic sclerosis. Patients with diffuse disease reported more body image dissatisfaction than those with limited disease. Findings demonstrate that both medical and sociodemographic variables are associated with body image dissatisfaction in systemic sclerosis and can be used to identify which patients may be at increased risk for body image dissatisfaction.

Psychosocial and neighborhood correlates of health-related quality of life: A multi-level study among Hispanic adults.

OBJECTIVE: Improvement in health-related quality of life (HRQoL) is a public health goal of Healthy People 2020. Hispanics living in the United States are at risk for poor HRQoL, but the causes and correlates of this risk are not well understood. Thus, the present study examined individual-level psychosocial and neighborhood-level built environment correlates of physical and mental HRQoL among Hispanic adults. METHOD: A community sample of Hispanic adults (N = 383) completed self-report health-related questionnaires, and census tract was used to collect data on neighborhood-level built environment variables. Multilevel modeling was used to examine individual-level psychosocial (language preference, religiosity, subjective social status, discrimination, and number of years lived in the United States) and neighborhood-level built-environment (the retail food environment, proximity to alcohol retailers, and tobacco retailer density) correlates of physical and mental HRQoL. RESULTS: Higher subjective social status was significantly associated with better HRQoL, and more experiences with discrimination were significantly associated with lower HRQoL. For physical HRQoL, these relationships were stronger in neighborhoods with a higher density of tobacco retail outlets. CONCLUSIONS: Findings from this study suggest that subjective social status and discrimination play important roles in HRQoL among Hispanics, in particular in neighborhoods with a higher density of tobacco retail outlets. This study highlights the importance of considering neighborhood context, and in particular neighborhood disadvantage, when examining the relationship between social status, discrimination and HRQoL among Hispanics. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Sleep disturbance and cancer-related fatigue symptom cluster in breast cancer patients undergoing chemotherapy.

PURPOSE: Sleep disturbance and cancer-related fatigue (CRF) are among the most commonly reported symptoms associated with breast cancer and its treatment. This study identified symptom cluster groups of breast cancer patients based on multidimensional assessment of sleep disturbance and CRF prior to and during chemotherapy. METHODS: Participants were 152 women with stage I-IIIA breast cancer. Data were collected before chemotherapy (T1) and during the final week of the fourth chemotherapy cycle (T2). Latent profile analysis was used to derive groups of patients at each timepoint who scored similarly on percent of the day/night asleep per actigraphy, the Pittsburgh Sleep Quality Index global score, and the five subscales of the Multidimensional Fatigue Symptom Inventory-Short Form. Bivariate logistic regression evaluated if sociodemographic/medical characteristics at T1 were associated with group membership at each timepoint. RESULTS: Three groups (Fatigued with sleep complaints, Average, Minimal symptoms) were identified at T1, and five groups (Severely fatigued with poor sleep, Emotionally fatigued with average sleep, Physically fatigued with average sleep, Average, Minimal symptoms) at T2. The majority of individuals in a group characterized by more severe symptoms at T1 were also in a more severe symptom group at T2. Sociodemographic/medical variables at T1 were significantly associated with group membership at T1 and T2. CONCLUSIONS: This study identified groups of breast cancer patients with differentially severe sleep disturbance and CRF symptom profiles prior to and during chemotherapy. Identifying groups with different symptom management needs and distinguishing groups by baseline sociodemographic/medical variables can identify patients at risk for greater symptom burden.