Introduction: Achieving optimal HIV outcomes, as measured by global 90‐90‐90 targets, that is awareness of HIV‐positive status, receipt of antiretroviral (ARV) therapy among aware and viral load (VL) suppression among those on ARVs, respectively, is critical. However, few data from sub‐Saharan Africa (SSA) are available on older people (50+) living with HIV (OPLWH). We examined 90‐90‐90 progress by age, 15–49 (as a comparison) and 50+ years, with further analyses among 50+ (55–59, 60–64, 65+ vs. 50–54), in 13 countries (Cameroon, Cote d'Ivoire, Eswatini, Ethiopia, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia and Zimbabwe).Methods: Using data from nationally representative Population‐based HIV Impact Assessments, conducted between 2015and 2019, participants from randomly selected households provided demographic and clinical information and whole blood specimens for HIV serology, VL and ARV testing. Survey weighted outcomes were estimated for 90‐90‐90 targets. Country‐specific Poisson regression models examined 90‐90‐90 variation among OPLWH age strata.Results: Analyses included 24,826 HIV‐positive individuals (15–49 years: 20,170; 50+ years: 4656). The first, second and third 90 outcomes were achieved in 1, 10 and 5 countries, respectively, by those aged 15–49, while OPLWH achieved outcomes in 3, 13 and 12 countries, respectively. Among those aged 15–49, women were more likely to achieve 90‐90‐90 targets than men; however, among OPLWH, men were more likely to achieve first and third 90 targets than women, with second 90 achievement being equivalent. Country‐specific 90‐90‐90 regression models among OPLWH demonstrated minimal variation by age stratum across 13 countries. Among OLPWH, no first 90 target differences were noted by age strata; three countries varied in the second 90 by older age strata but not in a consistent direction; one country showed higher achievement of the third 90 in an older age stratum.Conclusions: While OPLWH in these 13 countries were slightly more likely than younger people to be aware of their HIV‐positive status (first 90), this target was not achieved in most countries. However, OPLWH achieved treatment (second 90) and VL suppression (third 90) targets in more countries than PLWH <50. Findings support expanded HIV testing, prevention and treatment services to meet ongoing OPLWH health needs in SSA.

Researchers have identified associations between neighborhood-level factors (eg, income level, tobacco retailer density) and smoking behavior, but few studies have assessed these factors in urban environments. We explored the effect of tobacco retailer density, neighborhood poverty, and housing type (multiunit and public) on smoking in a large urban environment (New York City). We used data on smoking prevalence and individual sociodemographic characteristics from the 2011-2013 New York City Community Health Survey, data on tobacco retailers from the 2012 New York City Department of Consumer Affairs, data on neighborhood sociodemographic characteristics and population density from the 2009-2013 American Community Survey, and data on multiunit and public housing from the 2012 New York City Primary Land Use Tax Lot Output data set. We used aggregate neighborhood-level variables and ordinary least squares regression, geographic weighted regression, and multilevel models to assess the effects of tobacco retailer density and neighborhood poverty on smoking prevalence, adjusting for sociodemographic characteristics (age, sex, race/ethnicity, and education) and neighborhood population density. We also assessed interactions between tobacco retailer density and poverty and each housing type on smoking. Neighborhood poverty positively and significantly modified the association between tobacco retailer density and prevalence of neighborhood smoking (β = 0.003, P = .01) when we controlled for population density, sociodemographic characteristics, and types of housing. Neighborhood poverty was positively associated with the prevalence of individual smoking (β = 0.0099, P < .001) when we adjusted for population density, sociodemographic characteristics, and type of housing. More research is needed to determine all the environmental factors associated with smoking prevalence in a densely populated urban environment.

Introduction: Teen use of flavored tobacco products is a concern. Menthol cigarettes have been found to influence teen smoking; however, less is known about the association between teen use of other flavored tobacco products, such as cigars and dip, and cigarette smoking. Methods: The New York City 2010 Special Communities Putting Prevention to Work Youth Risk Behavior Survey data (N = 1,800 aged 13–17 years) were analyzed to examine the association between ever trying flavored tobacco products and current smoking, after we adjusted for demographics and ever-use of menthol cigarettes. Results: Twenty percent of teens reported ever trying flavored tobacco products; youth who were current smokers (58%) were more likely to have tried flavored tobacco products than youth who were not current smokers (16%). Controlling for menthol cigarette use, teens who had ever tried flavored tobacco products were nearly 3 times more likely to be current smokers than those who had never tried flavored tobacco products (odds ratio = 2.70, 95% confidence interval = 1.47–4.98). Conclusions: Ever trying flavored tobacco products was strongly associated with current smoking among teens. The findings from this study suggest that regulations prohibiting sales of flavored tobacco products could decrease youth smoking.

From 2010 through 2012, the New York City Department of Health and Mental Hygiene engaged in multiple smoke-free-air activities in collaboration with community, institution, and government partners. These included implementing a law prohibiting smoking in all parks and beaches as well as working to increase compliance with existing Smoke-free Air Act provisions. We investigated trends in awareness of existing smoke-free rules publicized with new signage and public support for new smoke-free air strategies by using 3 waves of survey data from population-based samples of smoking and nonsmoking adults in New York City (2010-2012). Analyses adjusted for the influence of sociodemographic characteristics. Among both smokers and nonsmokers, we observed increased awareness of smoke-free regulations in outdoor areas around hospital entrances and grounds and in lines in outdoor waiting areas for buses and taxis. Regardless of smoking status, women, racial/ethnic minorities, and adults aged 25 to 44 years were more likely than men, non-Hispanic whites, and adults aged 65 years or older to support smoke-free air strategies. New signage was successful in increasing population-wide awareness of rules. Our analysis of the association between demographic characteristics and support for tobacco control over time provide important contextual information for community education efforts on secondhand smoke and smoke-free air strategies.