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      Using the RE-AIM framework to evaluate physical activity public health programs in México

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          Abstract

          Background

          Physical activity (PA) public health programming has been widely used in Mexico; however, few studies have documented individual and organizational factors that might be used to evaluate their public health impact. The RE-AIM framework is an evaluation tool that examines individual and organizational factors of public health programs. The purpose of this study was to use the RE-AIM framework to determine the degree to which PA programs in Mexico reported individual and organizational factors and to investigate whether reporting differed by the program’s funding source.

          Methods

          Public health programs promoting PA were systematically identified during 2008–2013 and had to have an active program website. Initial searches produced 23 possible programs with 12 meeting inclusion criteria. A coding sheet was developed to capture behavioral, outcome and RE-AIM indicators from program websites.

          Results

          In addition to targeting PA, five (42%) programs also targeted dietary habits and the most commonly reported outcome was change in body composition (58%). Programs reported an average of 11.1 (±3.9) RE-AIM indicator items (out of 27 total). On average, 45% reported reach indicators, 34% reported efficacy/effectiveness indicators, 60% reported adoption indicators, 40% reported implementation indicators, and 35% reported maintenance indicators. The proportion of RE-AIM indicators reported did not differ significantly for programs that were government supported ( M = 10, SD = 3.1) and programs that were partially or wholly privately or corporately supported ( M = 12.0, SD = 4.4).

          Conclusion

          While reach and adoption of these programs were most commonly reported, there is a need for stronger evaluation of behavioral and health outcomes before the public health impact of these programs can be established.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12889-015-1474-2) contains supplementary material, which is available to authorized users.

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          Most cited references26

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          How can we increase translation of research into practice? Types of evidence needed.

          This review summarizes key factors that have interfered with translation of research to practice and what public health researchers can do to hasten such transfer, focusing on characteristics of interventions, target settings, and research designs. The need to address context and to utilize research, review, and reporting practices that address external validity issues-such as designs that focus on replication, and practical clinical and behavioral trials-are emphasized. Although there has been increased emphasis on social-ecological interventions that go beyond the individual level, interventions often address each component as if it were an independent intervention. Greater attention is needed to connectedness across program levels and components. Finally, examples are provided of evaluation models and current programs that can help accelerate translation of research to practice and policy.
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            Obesity prevalence in Mexico: impact on health and economic burden.

            Along with other countries having high and low-to-middle income, Mexico has experienced a substantial change in obesity rates. This rapid growth in obesity prevalence has led to high rates of obesity-related diseases and associated health-care costs.
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              Childhood sleep time and long-term risk for obesity: a 32-year prospective birth cohort study.

              Associations between short sleep duration and increased BMI have been found in children and adults. However, it is not known whether short sleep time during childhood has long-term consequences. We assessed the association between sleep time in childhood and adult BMI in a birth cohort. Study members were a general-population birth cohort of 1037 participants (502 female) who were born in Dunedin, New Zealand, between April 1972 and March 1973. Parental reports of bedtimes and rising times collected at ages 5, 7, 9, and 11 years were used to estimate childhood sleep time. Linear regression analysis was used to analyze the association between childhood sleep time and BMI measured at 32 years of age. Shorter childhood sleep times were significantly associated with higher adult BMI values. This association remained after adjustment for adult sleep time and the potential confounding effects of early childhood BMI, childhood socioeconomic status, parental BMIs, child and adult television viewing, adult physical activity, and adult smoking. In logistic regression analyses, more sleep time during childhood was associated with lower odds of obesity at 32 years of age. This association was significant after adjustment for multiple potential confounding factors. These findings suggest that sleep restriction in childhood increases the long-term risk for obesity. Ensuring that children get adequate sleep may be a useful strategy for stemming the current obesity epidemic.
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                Author and article information

                Contributors
                Edtna.jauregui@hotmail.com
                annpacheco1@gmail.com
                Erigabsol@gmail.com
                teresiao@bcm.edu
                Cynthia.Castro@stanford.edu
                estabrkp@vt.edu
                lmcneill@mdanderson.org
                releephd@yahoo.com
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                19 February 2015
                19 February 2015
                2015
                : 15
                : 162
                Affiliations
                [ ]Institute de Ciencias Aplicadas a la Actividad Física y Deporte, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara, Mexico
                [ ]Departamento Medicina Preventiva, Secretaria de Salud, Jalisco, México
                [ ]Texas Obesity Research Center, Department of Health and Human Performance, University of Houston, Houston, TX USA
                [ ]USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
                [ ]Stanford Prevention Research Center, Stanford University School of Medicine, Stanford, CA USA
                [ ]Virginia Polytechnic Institute and State University, 295 West, Blacksburg, VA USA
                [ ]University of Texas MD Anderson Cancer Research Center, 1400 Pressler Street, Unit 1440, Houston, TX 77030 USA
                [ ]College of Nursing and Health Innovation, Arizona State University, 550 N 3rd St, Phoenix, AZ 85004 USA
                Article
                1474
                10.1186/s12889-015-1474-2
                4358862
                def8df81-98ad-48ba-b4f8-ef7f791db2a5
                © Jauregui et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 August 2014
                : 27 January 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Public health
                Public health

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