Challenges and Lessons Learned from Multi-Level Multi-Component Interventions to Prevent and Reduce Childhood Obesity

Multi-level multi-component (MLMC) strategies have been recommended to prevent and reduce childhood obesity, but results of such trials have been mixed. The present work discusses lessons learned from three recently completed MLMC interventions to inform future research and policy addressing childhood obesity. B’more Healthy Communities for Kids (BHCK), Children’s Healthy Living (CHL), and Health and Local Community (SoL) trials had distinct cultural contexts, global regions, and study designs, but intervened at multiple levels of the socioecological model with strategies that address multiple components of complex food and physical activity environments to prevent childhood obesity. We discuss four common themes: (i) How to engage with community partners and involve them in development of intervention and study design; (ii) build and maintain intervention intensity by creating mutual promotion and reinforcement of the intervention activities across the multiple levels and components; (iii) conduct process evaluation for monitoring, midcourse corrections, and to engage stakeholder groups; and (iv) sustaining MLMC interventions and its effect by developing enduring and systems focused collaborations. The paper expands on each of these themes with specific lessons learned and presents future directions for MLMC trials

Exposure to a multi-level multi-component childhood obesity prevention community-randomized controlled trial: patterns, determinants, and implications

Abstract Background For community interventions to be effective in real-world conditions, participants need to have sufficient exposure to the intervention. It is unclear how the dose and intensity of the intervention differ among study participants in low-income areas. We aimed to understand patterns of exposure to different components of a multi-level multi-component obesity prevention program to inform our future impact analyses. Methods B’more Healthy Communities for Kids (BHCK) was a community-randomized controlled trial implemented in 28 low-income zones in Baltimore in two rounds (waves). Exposure to three different intervention components (corner store/carryout restaurants, social media/text messaging, and youth-led nutrition education) was assessed via post-intervention interviews with 385 low-income urban youths and their caregivers. Exposure scores were generated based on self-reported viewing of BHCK materials (posters, handouts, educational displays, and social media posts) and participating in activities, including taste tests during the intervention. For each intervention component, points were assigned for exposure to study materials and activities, then scaled (0–1 range), yielding an overall BHCK exposure score [youths: mean 1.1 (range 0–7.6 points); caregivers: 1.1 (0–6.7), possible highest score: 13]. Ordered logit regression analyses were used to investigate correlates of youths’ and caregivers’ exposure level (quartile of exposure). Results Mean intervention exposure scores were significantly higher for intervention than comparison youths (mean 1.6 vs 0.5, p < 0.001) and caregivers (mean 1.6 vs 0.6, p < 0.001). However, exposure scores were low in both groups and 10% of the comparison group was moderately exposed to the intervention. For each 1-year increase in age, there was a 33% lower odds of being highly exposed to the intervention (odds ratio 0.77, 95% confidence interval 0.69; 0.88) in the unadjusted and adjusted model controlling for youths’ sex and household income. Conclusion Treatment effects may be attenuated in community-based trials, as participants may be differentially exposed to intervention components and the comparison group may also be exposed. Exposure should be measured to provide context to impact evaluations in multi-level trials. Future analyses linking exposure scores to the outcome should control for potential confounders in the treatment-on-the-treated approach, while recognizing that confounding and selection bias may exist affecting causal inference. Trial Registration ClinicalTrials.gov, NCT02181010. Retrospectively registered on 2 July 2014

Household, psychosocial, and individual-level factors associated with fruit, vegetable, and fiber intake among low-income urban African American youth

Abstract Background Childhood obesity, one of the greatest challenges to public health, disproportionately affects low-income urban minority populations. Fruits and vegetables (FV) are nutrient dense foods that may be inversely associated with excessive weight gain. We aimed to identify the individual characteristic, psychosocial, and household factors influencing FV and fiber consumption in low-income African-American (AA) youth in Baltimore, MD. Methods Cross-sectional analysis of data collected from 285 low-income AA caregiver-youth (age range: 10–14 y) dyads participating in the baseline evaluation of the B’More Healthy Communities for Kids obesity prevention trial. The Kid's Block FFQ was used to estimate daily intakes of FV (including 100 % fruit juice) and dietary fiber. Questionnaires were used to assess household socio-demographics, caregiver and youth food purchasing and preparation behavior, and youth psychosocial information. Ordered logit regression analyses were conducted to examine psychosocial and food-related behavior associated with FV and dietary fiber intake (quartile of intake) controlling for youth age, sex, BMI percentile, total calorie intake and household income. Results On average, youth consumed 1.5 ± 1.1 (M ± SD) servings of fruit, 1.8 ± 1.7 serving of vegetables, and 15.3 ± 10.9 g of fiber/day. There were no differences by gender, age or household income. Greater youth’s healthy eating intentions and self-efficacy scores were associated with greater odds ratio for higher intake of FV and fiber (Intention: ORfruit 1.22; 95 % CI: 1.06–1.41, ORvegetable 1.31; 1.15–1.51 and ORfiber 1.46; 1.23–1.74, Self-efficacy: ORfruit 1.07; 1.03–1.12, ORvegetable 1.04; 1.01–1.09, ORfiber 1.10; 1.04–1.16). Youth receiving free/low-cost breakfast were more than twice as likely to have higher fiber intake than those who did not receive free breakfast (OR 2.7; 1.10; 6.9). In addition, youth shopping more frequently at supermarkets were more likely to have greater vegetable and fiber intake (OR 1.26; 1.06–1.50; OR 1.28; 1.03–1.58, respectively). Also, youth with parents who shopped more frequently at fast-food stores had 7 % lower odds for higher vegetable intake (95 % CI: 0.88–0.99). Conclusion In this study, both, youth and household factors were associated with youth FV and fiber intake, underscoring the need for a multi-level approach to increasing youths’ diet quality. These results will inform and shape an effective intervention program for improving youth dietary intakes

Waking up to sleep\u27s role in obesity and blood pressure among Black adolescent girls in low-income, US urban communities: A longitudinal analysis

Objective: To identify longitudinal bidirectional associations between unique sleep trajectories and obesity and hypertension among Black, adolescent girls. Design, setting, and participants: Longitudinal data were from a randomized controlled trial (2009-2013) implemented in schools serving low-income communities aimed at preventing obesity among adolescent girls (mean age = 12.2 years (standard deviation ± 0.72). Measures: Nocturnal sleep data were extracted from accelerometers at T1 (enrollment, n = 470), T2 (6-month, n = 348), and T3 (18-month follow-up, n = 277); height and weight were measured at T1-T3; and systolic/diastolic blood pressure at T1 and T3 using an oscillometric monitor. Multilevel models examined longitudinal associations. Finite mixture models identified sleep trajectory groups. Structural equation models examined whether T1 chronic disease risk predicted sleep profiles, and conversely, if sleep trajectories predicted T3 chronic disease risk. Data were analyzed in 2021. Results: For each additional hour of sleep and 1% increase in efficiency there was a 7% lower risk of overweight/obesity at T1 and 6% lower risk at T2, but not at T3. Four sleep trajectories emerged: Worsened, Irregular, Improved, and Regular, with no demographic or metabolic differences between the trajectories. Improved sleep trajectory predicted lower diastolic percentile at T3 (b = −8.81 [95% confidence interval −16.23, −1.40]). Conclusions: Group-based trajectories of sleep duration and quality provide information on modifiable factors that can be targeted in interventions to evaluate their impact on reducing chronic diseases and addressing disparities. Additional research is needed on samples beyond those recruited in the context of an intervention study