Preventing Weight Gain in Women in Rural Communities: A Cluster Randomised Controlled Trial

Abstract

BackgroundObesity is reaching epidemic proportions in both developed and developing countries. Even modest weight gain increases the risk for chronic illness, yet evidence-based interventions to prevent weight gain are rare. This trial will determine if a simple low-intensity intervention can prevent weight gain in women compared to general health information.Methods and FindingsWe conducted a 1-yr pragmatic, cluster randomised controlled trial in 41 Australian towns (clusters) randomised using a computer-generated randomisation list for intervention (n = 21) or control (n = 20). Women aged 18 to 50 yr were recruited from the general population to receive a 1-yr self-management lifestyle intervention (HeLP-her) consisting of one group session, monthly SMS text messages, one phone coaching session, and a program manual, or to a control group receiving one general women’s health education session. From October 2012 to April 2014 we studied 649 women, mean age 39.6 yr (+/− SD 6.7) and BMI of 28.8 kg/m2 (+/− SD 6.9) with the primary outcome weight change between groups at 1 yr. The mean change in the control was +0.44 kg (95% CI −0.09 to 0.97) and in the intervention group −0.48kg (95% CI −0.99 to 0.03) with an unadjusted between group difference of −0.92 kg (95% CI −1.67 to −0.16) or −0.87 kg (95% CI −1.62 to −0.13) adjusted for baseline values and clustering. Secondary outcomes included improved diet quality and greater self-management behaviours. The intervention appeared to be equally efficacious across all age, BMI, income, and education subgroups. Loss to follow-up included 23.8% in the intervention group and 21.8% in the control group and was within the anticipated range. Limitations include lack of sensitive tools to measure the small changes to energy intake and physical activity. Those who gained weight may have been less inclined to return for 1 yr weight measures.ConclusionsA low intensity lifestyle program can prevent the persistent weight gain observed in women. Key features included community integration, nonprescriptive simple health messages, small changes to behaviour, low participant burden, self-weighing, and delivery including a mix of group, phone, and SMS text reminders. The findings support population strategies to halt the rise in obesity prevalence.

Effectiveness of lifestyle interventions for preventing harmful weight gain among young adults from lower socioeconomic status and ethnically diverse backgrounds: a systematic review

“…However, this study did not include a subgroup analysis to establish if weight gain was prevented in this population. There have also been other interventions carried out in priority populations such as rural communities, which have leveraged relative success . One intervention was able to elicit significant weight change in Australian women across 41 rural towns .…”

Evaluation of a large healthy lifestyle program: informing program implementation and scale-up in the prevention of obesity

“…As previously reported, HeLP-her Rural prevented weight gain at 1 year with the mean weight change from baseline in the control group at +0.44 kg (95% CI −0.09 to 0.97) and the intervention group at −0.48 kg (95% CI −0.99 to 0.03), with a between-group difference of −0.92 kg (95% CI −1.67 to −0.16) or −0.88 kg (95% CI −1.62 to −0.13) adjusted for baseline values and clustering [49]. …”

“…The HeLP-her, low-intensity healthy lifestyle program has now been delivered in a range of settings and populations in a series of RCT’s where it effectively improves lifestyle and prevents weight gain [4, 17, 49]. The HeLP-her Rural program achieved broad program reach across 41 rural townships with most participants reporting influencing some of the health behaviors of their families.…”

“…1) [49]. Participant recruitment strategies were underpinned by a comprehensive communication and engagement plan and were deliberately simple and low cost to reflect community practice.…”

“…The statistical analysis plan has been previously reported as has statistical methods applied [42, 49]. Data analysis was conducted using STATA and SPSS version 19.0 for Windows.…”