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      Assessing the Feasibility of a Web-Based Weight Loss Intervention for Low-Income Women of Reproductive Age: A Pilot Study


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          Low-income women of reproductive age are at increased risk for obesity and resulting increases in the risk of maternal/fetal complications and mortality and morbidity. Very few weight-loss interventions, however, have been targeted to this high-risk group. Based on the high prevalence of social media use among young and low-income individuals and previous successes using group formats for weight-loss interventions, the use of social media as a platform for weight-loss intervention delivery may benefit low-income women of reproductive age.


          Examine the feasibility of delivering group-based weight-loss interventions to low-income women of reproductive age using face-to-face meetings and Web-based modalities including social media.


          Participants attended a family planning clinic in eastern North Carolina and received a 5-month, group- and Web-based, face-to-face weight-loss intervention. Measures were assessed at baseline and 20 weeks.


          Forty participants enrolled, including 29 (73%) African American women. The mean body mass index of enrollees was 39 kg/m 2. Among the 12 women who completed follow-up, mean weight change was -1.3 kg. Participation in the intervention was modest and retention at 5 months was 30%. Returnees suggested sending reminders to improve participation and adding activities to increase familiarity among participants.


          Engagement with the intervention was limited and attrition was high. Additional formative work on the barriers and facilitators to participation may improve the intervention’s feasibility with low-income women of reproductive age.

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          Most cited references16

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          A rapid food screener to assess fat and fruit and vegetable intake.

          The U.S. Preventive Services Task Force recommends that Americans lower dietary fat and cholesterol intake and increase fiber and fruit/vegetables to reduce prevalence of heart disease, cancer, stroke, hypertension, obesity, and non-insulin-dependent diabetes mellitus in the United States. To provide preventive services to all, a rapid, inexpensive, and valid method of assessing dietary intake is needed. We used a one-page food intake screener based on national nutrition data. Respondents can complete and score the screener in a few minutes and can receive immediate, brief feedback. Two hundred adults self-administered the food screener. We compared fat, fiber, and fruit/vegetable intake estimates derived from the screener with estimates from a full-length, 100-item validated questionnaire. The screener was effective in identifying persons with high-fat intake, or low-fruit/vegetable intake. We found correlations of 0.6-0.7 (p<0. 0001) for total fat, saturated fat, cholesterol, and fruit/vegetable intake. The screener could identify persons with high percentages of calories from fat, total fat, saturated fat, or cholesterol, and persons with low intakes of vitamin C, fiber, or potassium. This screener is a useful tool for quickly monitoring patients' diets. The health care provider can use it as a prelude to brief counseling or as the first stage of triage. Persons who score poorly can be referred for more extensive evaluation by low-cost paper-and-pencil methods. Those who still have poor scores at the second stage ultimately can be referred for in-person counseling.
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            Relationship Between Obesity and Diabetes in a US Adult Population: Findings from the National Health and Nutrition Examination Survey, 1999–2006

            Background Obesity is one of the most important modifiable risk factors for the prevention of type 2 diabetes. The aim of this study was to examine the prevalence of diabetes with increasing severity of obesity and the distribution of HbA1c levels in diabetics participating in the latest National Health and Nutrition Examination Survey (NHANES). Methods Data from a representative sample of adults with diabetes participating in the NHANES between 1999 and 2006 were reviewed. The prevalence of diabetes and levels of fasting glucose, insulin, c-peptide, and HbA1c were examined across different weight classes with normal weight, overweight, and obesity classes 1, 2, and 3 were defined as body mass index (BMI) of 8.0%) in 23%. The mean fasting glucose and HbA1c levels were highest for diabetics with BMI <25.0, suggesting a state of higher severity of disease. Mean insulin and c-peptide levels were highest for diabetics with BMI = 35.0, suggesting a state of insulin resistance. Conclusions In a nationally representative sample of US adults, the prevalence of diabetes increases with increasing weight classes. Nearly one fourth of adults with diabetes have poor glycemic control and nearly half of adult diabetics are considered obese suggesting that weight loss is an important intervention in an effort to reduce the impact of diabetes on the health care system.
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              Internet-Based Behavioral Interventions for Obesity: An Updated Systematic Review

              The objective of this systematic review is to update a previous systematic review on the effectiveness of internet-based interventions for weight loss and weight loss maintenance in overweight and obese people with new or additional studies. A literature search from 2008 to March 2010 was conducted. Studies were eligible for inclusion if: participants were adults with a body mass index ≤ 25, at least one study arm involved an internet-based intervention and the primary aims were weight loss or maintenance. Eight additional studies over the eighteen included in the previous review met the inclusion criteria. Data were extracted on sample characteristics, attrition, weight loss, duration of treatment and maintenance of weight loss. Effect sizes (Hedges g) and relative 95% confidence intervals were calculated for all two-way comparisons within each study. No attempt was made to pool the data in a meta-analysis because of the great heterogeneity of designs among studies. An examination of effect sizes show that the higher significant effects pertain studies that found a superiority of behavioral internet-based programs enhanced by features such as tailored feedback on self-monitoring of weight, eating and activity over education only internet-based interventions. However, control groups are very different among studies and this heterogeneity probably accounts for much of the variance in effect sizes. Hence, questions still remain as to the effectiveness of web-based interventions in achieving weight loss or maintenance. Implications for further research include using a “real” control group in order to make meta-analysis possible and developing multi-factorial design in order to separate components of interventions and identify which of them or patterns of them are keys to success.

                Author and article information

                JMIR Res Protoc
                JMIR Res Protoc
                JMIR Research Protocols
                JMIR Publications Inc. (Toronto, Canada )
                Jan-Mar 2016
                26 February 2016
                : 5
                : 1
                : e30
                [1] 1Case Western Reserve University Department of Nutrition Cleveland, OHUnited States
                [2] 2UNC Center for Health Promotion and Disease Prevention Chapel Hill, NCUnited States
                [3] 3East Carolina University Brody School of Medicine Department of Public Health Greenville, NCUnited States
                [4] 4Centers for Disease Control and Prevention National Center for Chronic Disease Prevention and Health Promotion Division of Reproductive Health Atlanta, GAUnited States
                [5] 5East Carolina University, Brody School of Medicine Department of Public Health Greenville, NCUnited States
                [6] 6UNC Center for Health Promotion and Disease Prevention Department of Medicine UNC School of Medicine Chapel Hill, NCUnited States
                [7] 7University of North Carolina at Chapel Hill Department of Biostatistics Chapel Hill, NCUnited States
                [8] 8Pitt County Health Department Greenville, NCUnited States
                [9] 9UNC Center for Health Promotion and Disease Prevention UNC Gillings School of Global Public Health and School of Medicine Chapel Hill, NCUnited States
                Author notes
                Corresponding Author: David N Cavallo david.cavallo@ 123456case.edu
                Author information
                ©David N Cavallo, Jessica A Sisneros, Ashley A Ronay, Cheryl L Robbins, Stephanie B Jilcott Pitts, Thomas C Keyserling, Ai Ni, John Morrow, Maihan B Vu, Larry F Johnston, Carmen D Samuel-Hodge. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 26.02.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

                : 25 June 2015
                : 22 July 2015
                : 4 September 2015
                : 14 November 2015
                Original Paper
                Original Paper

                obesity,nutrition,physical activity,minority health,healthcare disparities,intervention studies,internet,women,weight loss,mhealth


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