Adult weight management across the community: population‐level impact of the LOSE IT to WIN IT challenge

Abstract

SummaryObjectiveExcess body weight negatively impacts health, but there are few evaluations of low‐intensity weight management challenge programs in defined populations. This study examined weight change in adults who participated in the LOSE IT to WIN IT (LIWI) health challenge in a US community. The community‐level impact on body mass index was also explored.MethodsBody weight was analysed over 1 year in the cohort of LIWI enrolees, stratified by participants who were healthy weight or overweight/obese at baseline. Secondarily, a multiple cross‐sectional analysis compared the 2.5‐year trends in body mass index between community adults who did vs. did not participate in LIWI.ResultsLOSE IT to WIN IT participants who were overweight/obese lost a mean (95% confidence interval) 1.6 (1.2, 2.0) kg (~2%) over 1 year (p < 0.001), whereas healthy weight participants lost 0.7 (0.3, 1.1) kg. Across the community, LIWI participants and non‐participants both gained 0.4 kg m−2 over the 2.5‐year study period (p = 0.884).ConclusionsLOSE IT to WIN IT was modestly effective among enrolees, resulting in a small weight loss of 2% over 1 year among those who were overweight/obese. However, LIWI did not impact weight gain in the community. To slow such community‐level weight gain trends, weight management challenges must reach larger fractions of the populations that they target.

Population-Level Reach of Cardiovascular Disease Prevention Interventions in a Rural Community: Findings from the Heart of New Ulm Project

“…LOSE IT to WIN IT, 30 the year-long weight management challenge, was the intervention with the second highest engagement level with 12% of community adults enrolling. Community health challenges (CHCs) had the third highest engagement level with 10% of adult residents participating in at least 1 CHC.…”

“…The focus of this paper is to understand participation rates of individual-level programs. These include heart health screenings, 23 community health challenges (6- to 8-week behavior change challenges implemented twice a year; one with a specific theme and one annual challenge called “Holiday Trimmings”), a year-long community-wide weight loss challenge, 30 a primary prevention phone coaching program for residents at high risk for CVD, 27 , 31 grocery store tours, cooking shows, and worksite behavior change interventions. Overall, most intervention offerings were available to all adult community residents.…”

“…4 Evidence to date supports CVD risk factor improvement for individual interventions and the comprehensive package of interventions. 24,[28][29][30][31] Project priorities were identified from a community assessment that identified the most prevalent risk factors as overweight/obesity, metabolic syndrome, low fruit and vegetable consumption, and low use of preventive medication among those with elevated risk for CVD. 23 Interventions were designed to fill gaps where other options did not exist in the community.…”

Connectedness: How Technology and Social Networks Are Advancing Diabetes Nutrition Care

“…As part of our mission to change the New Ulm environment and to increase access to programs and tools to support health behavior change throughout the community, we developed a lower-intensity intervention integrating EHR information, social media, community-based weighing kiosks, and incentives. Through the LOSE IT to WIN IT challenge, nearly 2,000 participating residents lost a mean 2% of their body weight over 1 year, earning small individual prizes such as gift cards, T-shirts, and gasoline discounts and a large community reward designed to benefit everyone—more than $59,000 for exercise equipment in local parks ( 9 ). Although the program yielded weight loss that, while statistically significant, was of limited clinical significance, it did give people opportunities to connect, share, and support each other and generated enthusiasm within the community.…”

Lifestyle behaviours or socioeconomic characteristics? Gender differences in covariates of BMI in Hungary

“…There is a substantial overlap between the variables recognized as key health lifestyle behaviours, that is dietary habits, physical activity, smoking, and drinking alcohol , and behaviours having a major impact on an individual's BMI, that is food choices and eating practices, physical activity, TV viewing, and sleep . Health lifestyle theories argue that focusing on a single or a small subset of behaviours does not sufficiently reflect the diversity of the social forces behind them .…”