Search results

Abstract Purpose: The purpose of this study was to identify subgroups of sexual and gender minority (SGM) youth who are most vulnerable to tobacco use. Methods: We analyzed data from a national nonprobability sample of 11,192 SGM youth (ages 13–17). Age of cigarette initiation and current use were modeled using Cox proportional hazard and binomial regression. Sexual and gender identities were explanatory variables and the models were adjusted for ethnoracial identity and age. Results: Approximately 7\% of the sample reported current smoking. Cisgender and transgender boys had higher odds of current smoking compared with cisgender and transgender girls (adjusted odds ratio [AOR] = 1.86; 95\% confidence interval [CI]: 1.56–2.21). Pansexual-identified youth had higher odds of smoking (AOR = 1.33; 95\% CI: 1.05–1.70) compared with gay/lesbian youth independent of gender identity. Pansexual-identified cisgender boys had the highest smoking prevalence (21.6\%). Predicted probabilities were higher among transgender boys across all sexual identities, except asexual. The hazard of smoking at a younger age was greater for transgender boys compared with cisgender boys (adjusted hazard ratio [AHR] = 1.67; 95\% CI: 1.43–1.94) as well as for bisexual (AHR = 1.12; 95\% CI: 1.01–1.24) and pansexual (AHR = 1.17; 95\% CI: 1.03–1.33) youth compared with those who identified as gay or lesbian. Conclusions: These findings suggest that transgender boys may be at higher risk for early and current cigarette use regardless of their sexual identity, whereas smoking varied more widely for youth across different sexual identities. The findings suggest that specific subgroups of SGM youth require focused attention in tobacco control research and practice.

BACKGROUND: Using a population-based sample of youth, we examined rates of cigarette use and trends in cigarette use disparities between heterosexual youth and 3 subgroups of sexual minority youth (SMY) (ie, lesbian or gay, bisexual, and unsure) from 2005 to 2015. METHODS: Data are from 6 cohorts of the Youth Risk Behavior Survey, a national, biennial, school-based survey of ninth- to 12th-grade students in the United States (n = 404 583). Sex-stratified analyses conducted in 2017 examined trends in 2 cigarette-related behaviors: lifetime cigarette use and heavy cigarette use (20+ days in the past 30). RESULTS: Disparities in lifetime cigarette use between lesbian and heterosexual girls were statistically smaller in 2015 relative to 2005 (adjusted odds ratio [aOR] 0.29; 95% confidence interval [CI] 0.12–0.75; P = .011). Sexual orientation disparities in heavy use were narrower for bisexual boys in 2015 compared with 2005 (aOR 0.39; 95% CI 0.17–0.90; P = .028). Girls and boys unsure of their sexual identity had wider disparities in heavy use in 2015 (aOR 3.85; 95% CI 1.39–11.10; P = .009) relative to 2005 (aOR 2.44; 95% CI 1.22–5.00; P = .012). CONCLUSIONS: SMY remain at greater risk for cigarette-related behaviors despite greater acceptance of lesbian, gay, and bisexual people in the United States. Focused policies and programs aimed at reducing rates of SMY cigarette use are warranted, particularly for youth questioning their sexual identity.

PrEP Up!: a mixed methods study of stigma and pre-exposure prophylaxis use in Guatemala

COVID-19 and unintentional injury deaths are cited as major contributors of this shift

Bloomberg News article examines family and employment impacts

Scientific evidence regarding sexual minority populations has generally come from studies based on two types of samples: community-derived samples and probability samples. Probability samples are lauded as the gold standard of population research for their ability to represent the population of interest. However, while studies using community samples lack generalizability, they are often better able to assess population-specific concerns (e.g., minority stress) and are collected more rapidly, allowing them to be more responsive to changing population dynamics. Given these advantages, many sexual minority population studies rely on community samples. To identify how probability and community samples of sexual minorities are similar and different, we compared participant characteristics from two companion samples from the  Generations Study , each designed with the same demographic profile of U.S. sexual minority adults in mind. The first sample was recruited for a national probability survey, whereas the second was recruited for a multicommunity sample from four U.S. cities. We examined sociodemographic differences between the samples. Although there were several statistical differences between samples, the effect sizes were small for sociodemographic characteristics that defined the sample inclusion criteria: sex assigned at birth, race/ethnicity, and age cohort. The samples differed across other characteristics: bisexual respondents, respondents with less education, and those living in non-urban areas were underrepresented in the community sample. Our findings offer insights for recruiting community samples of sexual minority populations and for measuring sexual identity on probability surveys. They also bolster confidence in well-designed community samples as sources for data on sexual minority populations.

Commentary by Devon Payne-Sturges and others presents recommendations for a path toward eliminating racial inequities

MPRC Special Workshop

Abstract: Public health and built environment design have a long-intertwined history of promoting a healthy quality of life. They emerged with the common goal of preventing infectious disease outbreaks in urban areas and improving occupants’ living conditions. In recent years, however, the two disciplines have become less engaged and with each developing a distinct focus. To respond to this disconnection, a systematic review was conducted to identify the connection and divergence between public health and built environment design and planning. This paper aims to establish a context for understanding the connections, synergies, and divergence between public health and built environment design disciplines. Further, the four main health factors in the built environment are identified and explained: physical, physiological, biological, and psychological factors. Finally, future trends to reconnect public health with build environment design are then outlined.

Traditional Institutions in Modern Times: Dowries as Pensions When Sons Migrate