BackgroundExcessive gestational weight gain (GWG) is common and contributes to the development of obesity in women and their offspring. Electronic or e-health interventions have the potential to reach large groups of women and prevent excessive GWG, but their effectiveness has not been demonstrated. The purpose of this study was to evaluate, in a real-world setting, the effectiveness of a self-directed, integrated online and mobile phone behavioral intervention in preventing excessive GWG.MethodsThis effectiveness trial was a double-blind, three-arm trial with a parallel group design. Two arms received the same e-health intervention during pregnancy with the third arm serving as the placebo control. The intervention was based on a previously efficacious non-digital intervention that was adapted to electronic format. It included three behavior change tools: a weight gain tracker, and separate diet and physical activity goal-setting and self-monitoring tools. Both treatment conditions received access to informational tools, event reminders, and a blogging feature. Healthy pregnant women age 18-35 years with body mass indexes (BMI) ≥18.5 and < 35, at ≤20 weeks gestation, and an e-mail address were eligible. The proportion of women with excessive total GWG, as defined by the Institute of Medicine (IOM), was the primary outcome. 1689 randomized women were analyzed in the intent-to-treat (ITT) analysis. The study was designed to have 87% power to detect a 10 percentage point reduction from a control rate of 55% with a sample of 1641 (p = 0.0167, two-sided).ResultsIn the ITT sample, 48.1% (SD = 2.0%) gained excessively in the intervention group as did 46.2% (SD = 2.4%) in the placebo control group. These proportions were not significantly different (RR 1.09; 95% CI 0.98, 1.20, p = 0.12). The results were not altered in several sensitivity analyses.ConclusionThe addition of three behavior change tools to an informational placebo control did not result in a difference in the proportion of women with excessive total GWG compared to the placebo control in this effectiveness trial of an online, self-directed intervention. The similarity of intervention and control treatments and low usage of the behavior change tools in the intervention group are possible explanations.Trial registrationNCT01331564, ClinicalTrials.gov.Electronic supplementary materialThe online version of this article (10.1186/s12884-018-1767-4) contains supplementary material, which is available to authorized users.

Objectives To gain an in-depth understanding of issues related to gestational weight gain (GWG) including general health, diet, and physical activity among high- and low-income women and to elucidate socio-ecological and psychosocial risk factors that increase risk for excessive gestational weight gain. Methods We conducted 9 focus groups with high (n=4 groups) and low (n=5 groups) income pregnant women aged 18-35 years to discuss health, GWG, diet and physical activity following a discussion guide. The constant comparative method was used to code focus group notes and to identify emergent themes. Themes were categorized within the integrative model of behavioral prediction. Results Low income women, in contrast to high income women, had higher BMIs, had more children, and were African American. Diet and physical activity behaviors reported by low income women were more likely to promote positive energy balance than were those of high income women. The underlying behavioral, efficacy, and normative beliefs described by both groups of women explained most of these behaviors. Experiencing multiple risk factors may lead to 1) engaging in several behavior changes during pregnancy unrelated to weight and 2) holding more weight gain-promoting beliefs than weight maintaining beliefs. These factors could inhibit diet and physical activity behaviors and/or behavior changes that promote energy balance and in combination, result in excessive GWG. Conclusions Low income women experience multiple risk factors for excessive GWG and successful interventions to prevent excessive GWG and pregnancy related weight gain will need to recognize the complex web of influences.

No abstract

Purpose Social environments exert an important influence on health behaviors, yet evidence from rural‐specific contexts is limited. This study explored how social relationships influence health‐related behaviors among midlife and older rural adults at increased risk of chronic disease. Methods Seventeen focus groups were conducted with 125 sedentary, overweight/obese adults (aged 40‐91 years) residing in “medically underserved” rural Montana towns in 2014. Groups were stratified by age (40‐64 and ≥65) and gender. Transcripts were examined thematically using NVivo software according to social influences on diet, physical activity, and tobacco use. Analyses were conducted in 2015‐2016. Results Attitudes and actions of family members and friends were key influences on health behaviors, in both health‐promoting and health‐damaging ways. In these small, isolated communities, support from and accountability to family and friends were common facilitators of behavior change and maintenance. However, expectations to conform to social norms and traditional gender roles (eg, caregiving duties) often hindered healthy lifestyle changes. Conclusions These findings suggest that health behavior interventions targeting adults in rural settings need to consider and, if possible, integrate strategies to address the impact of social relationships in both supporting and sabotaging behavior change and maintenance.

Objective To evaluate a multilevel cardiovascular disease (CVD) prevention program for rural women. Methods This six-month community-based randomized trial enrolled 194 sedentary rural women aged 40 or older, with a BMI ≥ 25 kg/m2. Intervention participants attended six months of twice-weekly exercise, nutrition, and heart health classes (48 total) that included individual-, social-, and environment-level components. An education-only control program included didactic healthy lifestyle classes once a month (6 total). The primary outcome measures were change in BMI and weight. Results Within group and between group multivariate analyses revealed that only intervention participants decreased BMI (−0.85 units; 95% CI 1.32, −0.39; p=0.001) and weight (−2.24 kg; −3.49, −0.99; p=0.002); compared to controls, intervention participants decreased BMI and weight (difference: −0.71 units; −1.35, −0.08; p=0.03 and 1.85 kg; −3.55, −0.16; p=0.03, respectively) and improved C-reactive protein (difference: −1.15; −2.16, −0.15; p=0.03) and Simple 7, a composite CVD risk score (difference=0.67; 0.14, 1.21; p=0.01). Cholesterol decreased in controls but increased among intervention (−7.85 versus 3.92; difference=11.77; 0.57, 22.96; p=0.04). Conclusions The multilevel intervention demonstrated modest but superior and meaningful improvements in BMI and other CVD risk factors compared to the control program.