Purchasing behavior and calorie information at fast-food chains in New York City, 2007

We surveyed 7318 customers from 275 randomly selected restaurants of 11 fast food chains. Participants purchased a mean of 827 calories, with 34% purchasing 1000 calories or more. Unlike other chains, Subway posted calorie information at point of purchase and its patrons more often reported seeing calorie information than patrons of other chains (32% vs 4%; P<.001); Subway patrons who saw calorie information purchased 52 fewer calories than did other Subway patrons (P<.01). Fast-food chains should display calorie information prominently at point of purchase, where it can be seen and used to inform purchases.     

Psychosocial interventions for improving engagement in care and health and behavioural outcomes for adolescents and young people living with HIV: a systematic review and meta‐analysis

IntroductionAdolescents and young people comprise a growing proportion of new HIV infections globally, yet current approaches do not effectively engage this group, and adolescent HIV‐related outcomes are the poorest among all age groups. Providing psychosocial interventions incorporating psychological, social, and/or behavioural approaches offer a potential pathway to improve engagement in care and health and behavioural outcomes among adolescents and young people living with HIV (AYPLHIV).MethodsA systematic search of all peer‐reviewed papers published between January 2000 and July 2020 was conducted through four electronic databases (Cochrane Library, PsycINFO, PubMed and Scopus). We included randomized controlled trials evaluating psychosocial interventions aimed at improving engagement in care and health and behavioural outcomes of AYPLHIV aged 10 to 24 years.Results and discussionThirty relevant studies were identified. Studies took place in the United States (n = 18, 60%), sub‐Saharan Africa (Nigeria, South Africa, Uganda, Zambia, Zimbabwe) and Southeast Asia (Thailand). Outcomes of interest included adherence to antiretroviral therapy (ART), ART knowledge, viral load data, sexual risk behaviours, sexual risk knowledge, retention in care and linkage to care. Overall, psychosocial interventions for AYPLHIV showed important, small‐to‐moderate effects on adherence to ART (SMD = 0.3907, 95% CI: 0.1059 to 0.6754, 21 studies, n = 2647) and viral load (SMD = −0.2607, 95% CI −04518 to −0.0696, 12 studies, n = 1566). The psychosocial interventions reviewed did not demonstrate significant impacts on retention in care (n = 8), sexual risk behaviours and knowledge (n = 13), viral suppression (n = 4), undetectable viral load (n = 5) or linkage to care (n = 1) among AYPLHIV. No studies measured transition to adult services. Effective interventions employed various approaches, including digital and lay health worker delivery, which hold promise for scaling interventions in the context of COVID‐19.ConclusionsThis review highlights the potential of psychosocial interventions in improving health outcomes in AYPLHIV. However, more research needs to be conducted on interventions that can effectively reduce sexual risk behaviours of AYPLHIV, as well as those that can strengthen engagement in care. Further investment is needed to ensure that these interventions are cost‐effective, sustainable and resilient in the face of resource constraints and global challenges such as the COVID‐19 pandemic.     

Socioeconomic status in health research: one size does not fit all

Paula A. Braveman, MD, MPH; Catherine Cubbin, PhD; Susan Egerter, PhD; Sekai Chideya, MD, MPH; Kristen S. Marchi, MPH; Marilyn Metzler, RN; Samuel Posner, PhD

JAMA. 2005;294:2879-2888.

Problems with measuring socioeconomic status (SES)—frequently included in clinical and public health studies as a control variable and less frequently as the variable(s) of main interest—could affect research findings and conclusions, with implications for practice and policy. We critically examine standard SES measurement approaches, illustrating problems with examples from new analyses and the literature. For example, marked racial/ethnic differences in income at a given educational level and in wealth at a given income level raise questions about the socioeconomic comparability of individuals who are similar on education or income alone. Evidence also shows that conclusions about nonsocioeconomic causes of racial/ethnic differences in health may depend on the measure—eg, income, wealth, education, occupation, neighborhood socioeconomic characteristics, or past socioeconomic experiences—used to "control for SES," suggesting that findings from studies that have measured limited aspects of SES should be reassessed. We recommend an outcome- and social group–specific approach to SES measurement that involves (1) considering plausible explanatory pathways and mechanisms, (2) measuring as much relevant socioeconomic information as possible, (3) specifying the particular socioeconomic factors measured (rather than SES overall), and (4) systematically considering how potentially important unmeasured socioeconomic factors may affect conclusions. Better SES measures are needed in data sources, but improvements could be made by using existing information more thoughtfully and acknowledging its limitations.

     

Should Health Studies Measure Wealth? : A Systematic Review

BACKGROUND: Health researchers rarely measure accumulated wealth to reflect socioeconomic status/position (SES). In order to determine whether health research should more frequently include measures of wealth, this study assessed the relationship between wealth and health. METHODS: Studies published between 1990 to 2006 were systematically reviewed. Included studies used wealth and at least one other SES measure as independent variables, and a health-related dependent variable. RESULTS: Twenty-nine studies met inclusion criteria. Measures of wealth varied greatly. In most studies, greater wealth was associated with better health, even after adjusting for other SES measures. The findings appeared most consistent when using detailed wealth measures on specific assets and debts, rather than a single question. Adjusting for wealth generally decreased observed racial/ethnic disparities in health. CONCLUSIONS: Health studies should include wealth as an important SES indicator. Failure to measure wealth may result in under-estimating the contribution of SES to health, such as when studying the etiology of racial/ethnic disparities. Validation is needed for simpler approaches to measuring wealth that would be feasible in health studies.