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

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).

How an online intervention to prevent excessive gestational weight gain is used and by whom: a randomized controlled process evaluation.

BACKGROUND: Online 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. OBJECTIVE: The 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. METHODS: A 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. RESULTS: Six 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). CONCLUSIONS: While 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 REGISTRATION: Clinicaltrials.gov: NCT01331564; http://clinicaltrials.gov/ct2/show/NCT01331564 (Archived by WebCite at http://www.webcitation.org/6Rw4yKxI5).

Discordance in the assessment of prepregnancy weight status of adolescents: a comparison between the Centers for Disease Control and Prevention sex- and age-specific body mass index classification and the Institute of Medicine-based classification used for maternal weight gain guidelines.

In 1990, the Institute of Medicine (IOM) issued maternal weight gain guidelines to prevent intrauterine growth retardation based on adult prepregnancy body mass index (BMI; calculated as kg/m(2)). A recent IOM report, however, expressed concerns regarding application of adult criteria (prepregnancy BMI and gestational weight gain recommendations) to categorize pregnant adolescents. To draw attention to the assessment of prepregnancy weight status among adolescents and to its potential clinical implications, we estimated the percent discordance between the Centers for Disease Control and Prevention (CDC) BMI-for-age categories currently used for the assessment of adolescent weight status (underweight, healthy weight, at risk of overweight, and overweight) and the IOM-based categories (low, average, high, obese) among 11,656 adolescents 12 to 20 years old from a birth registry. Approximately one quarter of all adolescents in this sample and 40% of young adolescents (12 to 15 years old) were "misclassified." Among healthy weight adolescents, 23.4% and 0.6% were "misclassified" as low and high, respectively, by IOM categories. Among at-risk of overweight adolescents, 13.5% and 26.9% were "misclassified" as average and obese by IOM categories. Based on our findings, we suggest that adolescent prepregnancy weight categories be assessed using the CDC BMI charts and to examine gestational weight gain distributions exclusively among adolescents according to the CDC BMI categories.