Dataset Information

Does Usage of an eHealth Intervention Reduce the Risk of Excessive Gestational Weight Gain? Secondary Analysis From a Randomized Controlled Trial.

ABSTRACT: BACKGROUND:Excessive gestational weight gain (GWG) contributes to the development of obesity in mother and child. Internet-based interventions have the potential for delivering innovative and interactive options for prevention of excessive GWG to large numbers of people. OBJECTIVE:The objective of this study was to create a novel measure of Internet-based intervention usage patterns and examine whether usage of an Internet-based intervention is associated with reduced risk of excessive GWG. METHODS:The website featured blogs, local resources, articles, frequently asked questions (FAQs), and events that were available to women in both the intervention and control arm. Weekly reminders to use the website and to highlight new content were emailed to participants in both arms. Only intervention arm participants had access to the weight gain tracker and diet and physical activity goal-setting tools. A total of 1335 (898 intervention and 437 control) relatively diverse and healthy pregnant women were randomly assigned to the intervention arm or control arm. Usage patterns were examined for both intervention and control arm participants using latent class analysis. Regression analyses were used to estimate the association between usage patterns and three GWG outcomes: excessive total GWG, excessive GWG rate, and GWG. RESULTS:Five usage patterns best characterized the usage of the intervention by intervention arm participants. Three usage patterns best characterized control arm participants' usage. Control arm usage patterns were not associated with excessive GWG, whereas intervention arm usage patterns were associated with excessive GWG. CONCLUSIONS:The control and intervention arm usage pattern characterization is a unique methodological contribution to process evaluations for self-directed Internet-based interventions. In the intervention arm some usage patterns were associated with GWG outcomes. CLINICALTRIAL:ClinicalTrials.gov; Clinical Trials Number: NCT01331564; https://clinicaltrials.gov/ct2/show/NCT01331564 (Archived by WebCite at http://www.webcitation/6nI9LuX9w).

SUBMITTER: Graham ML

PROVIDER: S-EPMC5259588 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Does Usage of an eHealth Intervention Reduce the Risk of Excessive Gestational Weight Gain? Secondary Analysis From a Randomized Controlled Trial.

Graham Meredith Leigh ML Strawderman Myla S MS Demment Margaret M Olson Christine Marie CM

Journal of medical Internet research 20170109 1

<h4>Background</h4>Excessive gestational weight gain (GWG) contributes to the development of obesity in mother and child. Internet-based interventions have the potential for delivering innovative and interactive options for prevention of excessive GWG to large numbers of people.<h4>Objective</h4>The objective of this study was to create a novel measure of Internet-based intervention usage patterns and examine whether usage of an Internet-based intervention is associated with reduced risk of exce ...[more]

PMID: 28069560

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Project description:BackgroundBehavioral lifestyle interventions during pregnancy can prevent excessive gestational weight gain (GWG) in women with normal weight; however, effective interventions to reduce GWG in ethnically diverse women with obesity are lacking.ObjectiveA randomized controlled trial was conducted to test whether a behavioral lifestyle intervention with partial meal replacement reduces GWG rate in Hispanic and non-Hispanic women with overweight or obesity relative to enhanced usual care.DesignParticipants (n = 257) were recruited in San Luis Obispo, California, and Providence, Rhode Island, between November 2012 and May 2016. Participants were pregnant (mean ± SD: 13.6 ± 1.8 wk of gestation) with overweight or obesity and had a mean age of 30.3 y; 41.6% of participants were Hispanic. Women were randomly assigned within site and by ethnicity to enhanced usual care (n = 128) or to a behavioral lifestyle intervention with partial meal replacement (n = 129). The primary outcome was GWG per week of observation. Secondary outcomes were proportions exceeding Institute of Medicine (IOM) guidelines for total GWG, changes in weight-control behaviors and cardiovascular disease risk factors, and incidence of pregnancy complications. Study retention was 99.6% (256 of 257).ResultsThe intervention compared with usual care resulted in less mean ± SD weekly GWG (0.33 ± 0.25 compared with 0.39 ± 0.23 kg/wk; P = 0.02) and total GWG (9.4 ± 6.9 compared with 11.2 ± 7.0 kg; P = 0.03) and reduced the proportion of women who exceeded IOM guidelines for total GWG (41.1% compared with 53.9%; P = 0.03). No significant group × time × demographic subgroup (ethnicity, BMI, age, parity, and income) interactions were observed. Among intervention participants, greater meal replacement intake was related to reduced GWG rate (β = -0.07; 95% CI:-0.12, -0.03; P = 0.002). The intervention compared with usual care increased weight-control strategies (P < 0.0001) and cognitive restraint (P < 0.0001) and reduced triglycerides (P = 0.03).ConclusionPrenatal behavioral intervention with partial meal replacement significantly reduced GWG in Hispanic and non-Hispanic women with overweight or obesity. This trial was registered at www.clinicaltrials.gov as NCT01545934.

Project description:It is unclear whether weight management is still effective for pregnant women with excessive weight gain in the second or third trimester in China. This study adopted individualized weight management intervention for pregnant women with abnormal weight gain in the second or third trimester, to analyze the effect of intervention by observing the gestational weight gain and perinatal outcomes. This randomized controlled trial was performed at Aerospace Center Hospital. The obstetrician determined whether the pregnant women gained too much weight in the second or third trimester according to the Institute of Medicine guidelines, and randomly divided the pregnant women who gained too much weight in the second or third trimester into the intervention group or the control group according to the inclusion and exclusion criteria. The pregnant women in the intervention group and in the control group all received routine prenatal examination and diet nutrition education by the doctors in the Department of Obstetrics and Gynecology. The intervention group underwent individualized weight management, including individualized diet, exercise, psychological assessment, cognitive intervention and continuous communication, the whole process is tracked and managed by professional nutritionists. The obstetrician collected the prenatal examination data and pregnancy outcome data of all enrolled pregnant women. The primary outcome measure was weight gain during pregnancy. A generalized linear model and a logistic regression model were used to compare the outcomes between the two groups. In total, 348 pregnant women participated in this study with 203 in the intervention group and 145 in the control group. The whole gestational weight gain in the intervention group (15.8 ± 5.4 Kg) was lower than that in the control group (17.5 ± 3.6 Kg; adjusted β = - 1.644; 95% CI [-2.660--0.627]; P = 0.002). The percent of pregnant women with excessive weight gainbefore delivery was 54.2% (110/203) in the intervention group, which was lower than 69.7% (101/145) in the control group (adjusted RR = 0.468; 95% CI [0.284-0.769] P = 0.003). The pregnant women given the individualized weight management intervention from the second to the third trimester experienced less weight gain than that from the third trimester (15.5 ± 5.6 Kg vs. 16.2 ± 5.2 Kg), but without significant difference (P = 0.338). Lower rates of GDM, preeclampsia and gestational hypertension, higher rates of fetal distress and puerperal infection were observed in the intervention group than in the control group (all P < 0.05). Individualized weight management during the second or third trimesters is still beneficial for pregnant women who gain excessive weight and can decrease the associated adverse outcomes.

Project description: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.

Project description:BackgroundOnline interventions have emerged as a popular strategy to promote healthy behaviors. Currently, there is little agreement about how to capture online intervention engagement. It is also uncertain who engages with weight-related online interventions and how engagement differs by demographic and weight characteristics.ObjectiveThe objectives of this study were to (1) characterize how pregnant women engaged with features of an online intervention to prevent excessive gestational weight gain, (2) identify demographic and weight status subgroups of women within the sample, and (3) examine differences in use of intervention features across the demographic and weight status subgroups.MethodsA sample of racially and socioeconomically diverse pregnant women from a northeastern US city was assigned to the intervention group in a randomized controlled trial to prevent excessive gestational weight gain (n=1014). The intervention website included these features: weight-gain tracker, health-related articles, blogs, physical activity and diet goal-setting tools, and local resources. Engagement variables were created to capture the amount, consistency, and patterns of feature use across pregnancy using latent class analysis. Demographic/weight status subgroups were also created using latent class analysis. Differences in engagement across the demographic/weight status subgroups were examined using chi-square analysis.ResultsSix engagement patterns emerged: "super-users" (13.02%, 132/1014), "medium-users" (14.00%, 142/1014), "consistent weight-tracker users" (14.99%, 152/1014); "almost consistent weight-tracker users" (21.99%, 223/1014), "inconsistent weight-tracker users" (15.98%, 162/1014), and "non-users" (20.02%, 203/1014). Four demographic/weight status subgroups emerged: three minority and one white. There were different engagement patterns by demographic/weight status subgroups. Super-users were more likely to be in the white subgroup, while non-users were more likely to be in the minority subgroups. However, around a third of women in minority subgroups were consistently or almost consistently engaging with the weight-tracker (black, young women, 32.2%, 67/208; black, heavier women, 37.9%, 50/132; Hispanic women, 27.4%, 32/117).ConclusionsWhile white and higher income women had higher engagement in general, depending on the measure, there was still considerable engagement by the minority and low-income women.Trial registrationClinicaltrials.gov: NCT01331564; http://clinicaltrials.gov/ct2/show/NCT01331564 (Archived by WebCite at http://www.webcitation.org/6Rw4yKxI5).

Project description:BackgroundThe prevalence of excessive gestational weight gain (EGWG) during pregnancy is increasing, and it is extremely harmful to pregnant women and newborns. Previous studies have suggested that EGWG is associated with various factors. We conducted a systematic review and meta-analysis to identify, quantify and analyze determinants of EGWG and evaluate the effect of these determinants on EGWG.MethodsWe searched for articles, from January 2009 to November 2020, related to the determinants of EGWG during pregnancy using four Chinese and four English databases. The Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) statement was utilized to guide the systematic review and meta-analysis process.ResultsSeventy studies, which identified EGWG factors in pregnant women (58 factors, 3 themes: individual [7 aspects, 37 factors]; family [4 aspects, 8 factors]; and social [4 aspects, 13 factors]), were included and analyzed in the systematic review. A meta-analysis was conducted for 13 factors (including 10 individual factors, 2 family factors, and 1 social factor) and revealed that pre-pregnancy overweight (including obesity), younger age (≤ 30 years old), unemployed, primiparity, smoking, and being unmarried (including divorced) were risk factors for EGWG, while prepregnancy underweight and inadequate antenatal care were protective factors for EGWG. There was no significant correlation between EGWG and education level, alcohol consumption, planning pregnancy, food security, and whether access to nutrition guidance during pregnancy.ConclusionsEGWG was prevalent in pregnant women, and its prevalence seemed to be high and similar in many countries. Based on observational studies with medium-level and high-level evidence, some individual, family, and social factors were found to be associated with EGWG using qualitative and quantitative methods. In the future, exposure of pregnant women to risk factors for EGWG should be avoided, and interventions should be developed around the identified factors.

Dataset Information

Does Usage of an eHealth Intervention Reduce the Risk of Excessive Gestational Weight Gain? Secondary Analysis From a Randomized Controlled Trial.

Publications

Does Usage of an eHealth Intervention Reduce the Risk of Excessive Gestational Weight Gain? Secondary Analysis From a Randomized Controlled Trial.

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