Conducting Needs Assessment Using the Comprehensive Participatory Planning and Evaluation Model to Develop Nutrition and Physical Activity Interventions in a Rural Community in the Mississippi Delta

Ndirangu, Murugi; Perkins, Helen; Yadrick, Kathleen; West, Jennifer Rebecca; Bogle, Margaret L.; Avis-Williams, Amanda; Santell, Ross; Connell, Carol

doi:10.1353/cpr.0.0005

Cited by 21 publications

(19 citation statements)

References 8 publications

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“…LMD community members have identified lack of diet knowledge, intake of unhealthy foods, and lack of PA as the top three problems associated with poor health . Much work has been done to describe LMD dietary intake and eating patterns .…”

Section: Discussionmentioning

confidence: 99%

Steps ahead: A randomized trial to reduce unhealthy weight gain in the lower Mississippi delta

Harrington

Champagne

Broyles

et al. 2014

Obesity

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ObjectiveThe Lower Mississippi Delta (LMD) region of the U.S. is characterized by high levels of obesity and physical inactivity. The objective was to test the effectiveness of adapting the 2010 Dietary Guidelines for Americans (DG), with and without a physical activity (PA) component, for attenuating weight gain.Design and MethodsOverall, 121 white and African-American adults (35–64 y; BMI 25–34.9 kg/m2) were randomized to a DG only group (n=61) or a DG+PA group (n=60). Both groups received a 12-week dietary education and behavior change intervention. The DG+PA also received PA education and a pedometer. Changes in weight (kg), %weight and waist circumference (WC; cm) were determined. Analyses considered all completers (n=99) and those who engaged with ≥80% of the intervention (n=83). General linear models compared mean changes between groups after adjustment for baseline values, race and sex.ResultsWeight, %weight and WC significantly decreased from baseline to follow-up in both groups (p<0.05; unadjusted values). Adjusted analysis showed a main effect of group for weight (p=0.041) and %weight (p=0.047) in the completers analysis and WC (p=0.046) in the ≥80% attendance analysis, with the DG+PA group improving weight-related outcomes more.ConclusionsLow-burden behavioral interventions could be effective strategies in attenuating unhealthy weight gain in the LMD.

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Section: Discussionmentioning

confidence: 99%

Steps ahead: A randomized trial to reduce unhealthy weight gain in the lower Mississippi delta

Harrington

Champagne

Broyles

et al. 2014

Obesity

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“…A dietary assessment prior to the study showed that the study population consumed insufficient fiber, fruit and vegetables, and an excess of added sugar, refined grains and processed foods during snacking [ 11 ]. These data served to define the intervention objectives and strategies using the Intervention Mapping (IM) [ 25 ] and the Comprehensive and Participatory Planning and Evaluation (CPPE) approach [ 26 ]. The possible intervention strategies identified during the CPPE were combined with the IM techniques to define the final intervention strategies [ 27 ].…”

Section: Methodsmentioning

confidence: 99%

A school-based intervention improved dietary intake outcomes and reduced waist circumference in adolescents: a cluster randomized controlled trial

Avilés

Verstraeten

Huybregts

et al. 2017

Nutr J

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BackgroundIn Ecuador, adolescents’ food intake does not comply with guidelines for a healthy diet. Together with abdominal obesity adolescent’s inadequate diets are risk factors for non-communicable diseases. We report the effectiveness of a school-based intervention on the dietary intake and waist circumference among Ecuadorian adolescents.MethodsA pair-matched cluster randomized controlled trial including 1430 adolescents (12–14 years old) was conducted. The program aimed at improving the nutritional value of dietary intake, physical activity (primary outcomes), body mass index, waist circumference and blood pressure (secondary outcomes). This paper reports: (i) the effect on fruit and vegetable intake, added sugar intake, unhealthy snacking (consumption of unhealthy food items that are not in line with the dietary guidelines eaten during snack time; i.e. table sugar, sweets, salty snacks, fast food, soft drinks and packaged food), breakfast intake and waist circumference; and, (ii) dose and reach of the intervention. Dietary outcomes were estimated by means of two 24-h recall at baseline, after the first 17-months (stage one) and after the last 11-months (stage two) of implementation. Dose and reach were evaluated using field notes and attendance forms. Educational toolkits and healthy eating workshops with parents and food kiosks staff in the schools were implemented in two different stages. The overall effect was assessed using linear mixed models and regression spline mixed effect models were applied to evaluate the effect after each stage.ResultsData from 1046 adolescents in 20 schools were analyzed. Participants from the intervention group consumed lower quantities of unhealthy snacks (−23.32 g; 95% CI: −45.25,-1.37) and less added sugar (−5.66 g; 95% CI: −9.63,-1.65) at the end of the trial. Daily fruit and vegetable intake decreased in both the intervention and control groups compared to baseline, albeit this decrease was 23.88 g (95% CI: 7.36, 40.40) lower in the intervention group. Waist circumference (−0.84 cm; 95% CI: −1.68, 0.28) was lower in the intervention group at the end of the program; the effect was mainly observed at stage one. Dose and reach were also higher at stage one.ConclusionsThe trial had positive effects on risk factors for non-communicable diseases, i.e. decreased consumption of unhealthy snacks. The program strategies must be implemented at the national level through collaboration between the academia and policy makers to assure impact at larger scale.Trial registration ClinicalTrial.gov-NCT01004367.

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“…This means that community members are not merely the objects of research but highly engaged in the research process (Ndirangu et al, 2008). Unlike community-placed research, CBPR requires a collaborative assessment with key informants and representation from across the community (Ndirangu et al, 2007). CBPR is a slower process than the more traditional intervention research methods but has gained in momentum because developing trusting relationships and enhancing empowerment or ownership promises to be a more sustainable and therefore more effective approach to promoting health through behavioral changes (Israel, 1998(Israel, , 2003Kone, 2000).…”

Section: Developing the Path To Personalized Health Interventionsmentioning

confidence: 99%

“…This program focused on developing a local collaborative effort among community residents, universities, and the United States Department of Agriculture, Agricultural Research Service that would build capacity of community residents to become full and equitable partners in all phases of the nutritional research identified by the community as priorities. Community members were trained in principles of CBPR methods through the application of the Comprehensive Participatory Planning and Evaluation Model (CPPE), which produced three major nutrition-related problems the communities wanted to address (Ndirangu et al, 2007). Four initial pilot studies in Arkansas consisted of a Walking Club, Walking Trail Focus Group, Obesity Prevention Summer Day Camp, and a WillTry nutrition intervention approach to encourage eating fruits and vegetables (http://www.ars.…”

Section: Initiating the Biomedical Research Dialoguementioning

confidence: 99%

Personalizing Nutrigenomics Research through Community Based Participatory Research and Omics Technologies

McCabe‐Sellers

Lovera

Nuss

et al. 2008

OMICS: A Journal of Integrative Biology

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Personal and public health information are often obtained from studies of large population groups. Risk factors for nutrients, toxins, genetic variation, and more recently, nutrient-gene interactions are statistical estimates of the percentage reduction in disease in the population if the risk were to be avoided or the gene variant were not present. Because individuals differ in genetic makeup, lifestyle, and dietary patterns than those individuals in the study population, these risk factors are valuable guidelines, but may not apply to individuals. Intervention studies are likewise limited by small sample sizes, short time frames to assess physiological changes, and variable experimental designs that often preclude comparative or consensus analyses. A fundamental challenge for nutrigenomics will be to develop a means to sort individuals into metabolic groups, and eventually, develop risk factors for individuals. To reach the goal of personalizing medicine and nutrition, new experimental strategies are needed for human study designs. A promising approach for more complete analyses of the interaction of genetic makeups and environment relies on community-based participatory research (CBPR) methodologies. CBPR's central focus is developing a partnership among researchers and individuals in a community that allows for more in depth lifestyle analyses but also translational research that simultaneously helps improve the health of individuals and communities. The USDA-ARS Delta Nutrition Intervention Research program exemplifies CBPR providing a foundation for expanded personalized nutrition and medicine research for communities and individuals.

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Conducting Needs Assessment Using the Comprehensive Participatory Planning and Evaluation Model to Develop Nutrition and Physical Activity Interventions in a Rural Community in the Mississippi Delta

Abstract: Directly involving community members in identifying health problems and solutions results in the development of interventions that are likely to have greater acceptability with the community.

Cited by 21 publications

References 8 publications

Steps ahead: A randomized trial to reduce unhealthy weight gain in the lower Mississippi delta

Steps ahead: A randomized trial to reduce unhealthy weight gain in the lower Mississippi delta

A school-based intervention improved dietary intake outcomes and reduced waist circumference in adolescents: a cluster randomized controlled trial

Personalizing Nutrigenomics Research through Community Based Participatory Research and Omics Technologies

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