Minority populations are hard to reach with prevention interventions because of cultural and logistical barriers to recruitment. Understanding how to overcome these barriers is pertinent to reducing the elevated burden of obesity within these underserved communities. To inform this literature gap, we explore the processes and outcomes of recruitment for Live Well-a randomized controlled obesity prevention intervention targeting new immigrant mothers and children from Brazil, Latin America, and Haiti who were residing in the greater Somerville, MA area. We employed community-based participatory research principles to develop and implement five culturally-adapted recruitment activities (posters and flyers, media announcements, church outreach, participant referrals, and community organization partnerships) and tracked enrollment for the total and stratified samples of 406 dyads (37% Brazilian, 29% Latino, 33% Haitian). We describe how strategic partnerships were built and sustained within the intervention community, and detail the key adjustments that contributed to our success. Ultimately, community organization partnerships and participant referrals enrolled a collective majority of participants (34% and 25%, respectively); however, stratified analyses revealed variation by ethnicity: Haitian immigrants responded best to ethnic-based media announcements (44%), whereas Latino and Brazilian immigrants were most responsive to community organization outreach (45% and 38%, respectively). Implications from our findings enhance the literature on recruiting hard-to-reach communities into prevention research: some less integrated communities may respond more to grassroots activities with direct engagement, whereas communities with more social capital may be more responsive to top-down, community-wide collaborations. Furthermore, we suggest that strategic and trusting partnerships are key facilitators of recruitment, and future researchers must understand communities' culture and social networks when building relationships. Our analyses provide rare insight into best practices to overcome specific cultural barriers to recruitment which future investigators can use to better reach underserved communities with prevention research.

Background Dietary carbohydrate type may influence cardiometabolic risk through alterations in the gut microbiome and microbial-derived metabolites, but evidence is limited. Objectives We explored the relative effects of an isocaloric exchange of dietary simple, refined, and unrefined carbohydrate on gut microbiota composition/function, and selected microbial metabolite concentrations. Methods Participants [n = 11; age: 65 ± 8 y; BMI (in kg/m2): 29.8 ± 3.2] were provided with each of 3 diets for 4.5 wk with 2-wk washout, according to a randomized, crossover design. Diets [60% of energy (%E) carbohydrate, 15%E protein, and 25%E fat] differed in type of carbohydrate. Fecal microbial composition, metatranscriptomics, and microbial-derived SCFA and secondary bile acid (SBA) concentrations were assessed at the end of each phase and associated with cardiometabolic risk factors (CMRFs). Results Roseburia abundance was higher (11% compared with 5%) and fecal SBA concentrations were lower (lithocolic acid –50% and deoxycholic acid –64%) after consumption of the unrefined carbohydrate diet relative to the simple carbohydrate diet [false discovery rate (FDR): all P < 0.05), whereas Anaerostipes abundance was higher (0.35% compared with 0.12%; FDR: P = 0.04) after the simple carbohydrate diet relative to the refined carbohydrate diet. Metatranscriptomics indicated upregulation of 2 cellular stress genes (FDR: P < 0.1) after the unrefined carbohydrate diet compared with the simple carbohydrate or refined carbohydrate diets. The microbial expression of 3 cellular/oxidative stress and immune response genes was higher (FDR: P < 0.1) after the simple carbohydrate diet relative to the refined carbohydrate diet. No significant diet effect was observed in fecal SCFA concentrations. Independent of diet, we observed 16 associations (all FDR: P < 0.1) of taxon abundance (15 phylum and 1 genera) with serum inflammatory markers and also with fecal SCFA and SBA concentrations. Conclusions Consuming an unrefined carbohydrate–rich diet had a modest effect on the gut microbiome and SBAs, resulting in favorable associations with selected CMRFs. Simple carbohydrate– and refined carbohydrate–rich diets have distinctive effects on the gut microbiome, suggesting differential mechanisms mediate their effects on cardiometabolic health. This trial was registered at clinicaltrials.gov as NCT01610661.

Background Current approaches to studying relations between taste perception and diet quality typically consider each taste—sweet, salt, sour, bitter, umami—separately or aggregately, as total taste scores. Consistent with studying dietary patterns rather than single foods or total energy, an additional approach may be to study all 5 tastes collectively as “taste perception profiles.” Objective We developed a data-driven clustering approach to derive taste perception profiles from taste perception scores and examined whether profiles outperformed total taste scores for capturing individual variability in taste perception. Methods The cohort included 367 community-dwelling adults [55–75 y; 55% female; BMI (kg/m2): 32.2 ± 3.6] with metabolic syndrome from PREDIMED-Plus, Valencia. Cluster analysis identified subgroups of individuals with similar patterns in taste perception (taste perception profiles); quantitative criteria were used to select the cluster algorithm, determine the optimal number of clusters, and assess the profiles’ validity and stability. Goodness-of-fit parameters from adjusted linear regression evaluated the individual variability captured by each approach. Results A k-means algorithm with 6 clusters best fit the data and identified the following taste perception profiles: Low All, High Bitter, High Umami, Low Bitter & Umami, High All But Bitter and High All But Umami. All profiles were valid and stable. Compared with total taste scores, taste perception profiles explained more variability in bitter and umami perception (adjusted R2: 0.19 vs. 0.63, respectively; 0.40 vs. 0.65, respectively) and were comparable for sweet, salt, and sour. In addition, taste perception profiles captured differential perceptions of each taste within individuals, whereas these patterns were lost with total taste scores. Conclusions Among older adults with metabolic syndrome, taste perception profiles derived via data-driven clustering may provide a valuable approach to capture individual variability in perception of all 5 tastes and their collective influence on diet quality. This trial was registered at https://www.isrctn.com/ as ISRCTN89898870.