Group 5 1 Running head: CORRELATION BETWEEN FRUIT AND VEGETABLE INTAKE AND BODY COMPOSITION

Transcription

1 Group 5 1 Running head: CORRELATION BETWEEN FRUIT AND VEGETABLE INTAKE AND BODY COMPOSITION Correlation between self-reported fruit and vegetable intake and measured body composition of adults Group 5 Amanda Sullivan, Jessie Nindel-Edwards, and Molly Jennings Research Project Proposal February 18, 2011

2 Group 5 2 OVERVIEW With the increasing prevalence of obesity and chronic diseases it is important to discover what factors have an effect on these two public health concerns. One area of current interest is the impact that fruit and vegetable intake has on overall health. Our study will examine the correlation between self-reported fruit and vegetable intake and body composition measures, including body mass index (BMI), waist circumference (WC), and percent body fat (%BF). The relationship between body composition measures and self-reported fruit and vegetable intake will be examined using correlation analysis. HYPOTHESES Alternative: We hypothesize that self-reported fruit and vegetable intake will be inversely correlated to markers of adiposity (BMI, WC, and %BF) in male and female adults years of age. In addition, we predict that out of the three body composition measures that there will be a stronger correlation between self-reported fruit and vegetable intake and WC. Null: There will be no correlation between self-reported fruit and vegetable intake and markers of adiposity (BMI, WC, and %BF) in male and female adults years of age. SPECIFIC AIMS 1. The primary aim of this study is to determine the correlation between self-reported fruit and vegetable intake in an adult population of males and females aged years and each measure of body composition including BMI, WC, and %BF. 2. Our secondary aim is to compare the correlations of fruit and vegetable intake and body composition measures including BMI, WC, and %BF. 3. An additional aim will be to compare the correlations of fruit and vegetable intake and body composition measures including BMI, WC, and %BF between different genders and age groups. BACKGROUND Obesity, defined as a BMI >30 kg/m 2, continues to be a growing problem with a prevalence of over 30% among adults in the United States (NHANES ). BMI, an estimate of total adiposity, is traditionally

3 Group 5 3 used as a predictor of risk for chronic diseases such as cardiovascular disease, diabetes, and hypertension. More recently, WC, a measure of central adipose tissue distribution, has been determined to be an equal or better indicator of disease risk (Huxley R, et al, 2010). Waist circumference greater than 35 inches in women and greater than 40 inches in men is associated with increased risk of chronic diseases (Janssen, I., et al, 2004). One studying concluded that a BMI between kg/m 2 (overweight) in older adults aged 65 and greater did not result in any excess risk of mortality (Diehr P., et al, 2008). Different age groups have different recommendations for healthy %BF ranges based on BMI limits (Gallagher,et al, 2009). There is a relationship between dietary energy density (the amount of energy able to be metabolized per unit weight or volume of food), nutrient density and obesity in U.S. adults. One study reported that an energy-dense, low-fiber, high-fat diet is associated with higher fat mass and greater odds of excess adiposity (Mendoza, J. A., et at, 2007). One way to reduce dietary energy density is to decrease consumption of high fat foods and refined carbohydrates and to increase consumption of fruits and vegetables (Bes-Rastrollo, M., et al, 2008). Another study found intake of fruit, vegetable and low fat dairy were inversely correlated with BMI and WC in women (McNaughten, S., et al, 2011). Within that study, WC, height, and weight were measured using a standardized protocol, and BMI was calculated (kg/m 2 ) (McNaughten, S., et al, 2011). Measured WC and BMI were used, as measures of body composition, but % BF was not measured or compared. Our study will look all three of those body composition measures and compare each one individually to fruit and vegetable consumption. The USDA 2010 Dietary Guidelines recommend that adults eat cups of fruit and 2-3 cups of vegetables per day with amounts depending on gender (see Table 1); but also reports that on average adults in the United States consume only about 55% of their recommended intake of fruits and vegetables. There is no clear and convincing evidence that relates fruit and vegetable intake to body composition measures. The results of this study will provide insight into the role that a diet rich in fruit and vegetables may play in promoting healthy adult weight and body composition. METHODS Study Design Using a cross-sectional, observational study design, we will determine the correlation between adult fruit and vegetable intake and measures of body composition.

4 Group 5 4 Participants Data collected from 2,442 adults between the ages of 20 and 85 years attending a Let s Get Healthy! fair will be analyzed to determine correlations between self-reported fruit and vegetable intake and measured BMI, WC, and %BF. Study Population Our target population is male and female adults years of age. We chose 20 years as the lowest age for analysis because World Health Organization (WHO) pediatric growth charts are used for individuals under 20 years, with BMI calculated as a percentile (De INCLUSION CRITERIA years of age; Participation in Let s Get Healthy! fair Total # of participants included: 619 EXCLUSION CRITERIA <20 years of age; >85 years of age; Incomplete dietary assessment; Incomplete body composition measurements Total # participants excluded:1823 Onis M., et al). The upper end of the age range is 85 years, which is the age limit allowable by IRB for anonymous reporting. Since participation at the research stations included at the Let s Get Healthy! fair was voluntary, some attendees did not participate at all of the data collection stations. Attendees who were missing any of the body composition measures or dietary questionnaire answers were excluded from the statistical analysis. Recruitment The Let s Get Healthy! fair has been held in various Oregon counties and locations such as Oregon Museum of Science & Industry (OMSI), Hermiston, Madras and around the greater Portland metropolitan area. Fliers, online videos, and a website were used to recruit community members to participate in the fair. Of the 2,442 adults surveyed, only 619 fit the inclusion criteria listed above. Assessment At the entry kiosk, participants were given information sheets about the study and, if they agreed to participate, a wristband imprinted with a random 8-digit barcode number so that data gathered at each station could be linked anonymously to the Let s Get Healthy! Health Discoveries Program (HDP) database. Participation at each station was voluntary allowing for a randomized sample collection. Upon entry into the fair, demographic information collected from attendees including age, gender, race, and ethnicity was encoded to their wristband.

5 Group 5 5 Dietary intake was assessed using the Block Fruit and Vegetable questionnaire, which consisted of 28 questions (Lalonde L., et al & Block, G., et al). This questionnaire was designed to be completed in less than five minutes on a touch-screen computer. Of the 28 questions, seven were related to fruit and vegetable intake. Participants were provided with instant feedback regarding daily average dietary intake based on their answers to frequency and portion size of foods (Block, G., et al). At the body measurement station, tape measures and a bioimpedence scale were used to gather height, weight, WC, and %BF measures. Height and WC were measured by trained volunteers and medical experts while weight, %BF, and BMI were calculated using a Tanita scale (bioimpedence scale) with precision to 0.2 lb (0.1 kg). Height and WC measures were entered by hand into the HDP database, while measurements from the Tanita scale were linked with the Let s Get Healthy! HDP database. Data Management The original data gathered from participants was saved in its entirety on OCTRI s bioinformatics secure server. A subset of data was transferred to a Microsoft Excel spreadsheet for this research project. We created a new document for filtering data of participants who did not meet the inclusion criteria. The cleaned data will be used to quantify the incidence of obesity and overweight in the adult population of male and female adults years of age, determine their self-reported fruit and vegetable intake, and analyze the relationship between fruit and vegetable intake and each measure of body composition (BMI, WC, and %BF). Only researchers who sign a Health Discoveries Program Data Usage Agreement have access to the database. Sample Size and Power Our study is retrospective in that it will evaluate data previously collected. Therefore, our ability to affect the study s power are limited. We calculated power for two commonly used correlation values (see Appendix B, Table 5) using Simple Interactive Statistical Analysis (Uitenbroek, D.G., 1997). In our study we plan to use an alpha value of This alpha value with our population size of 619 will result in an 89% power to detect a correlation between fruit and vegetable intake and body composition. Statistical Analysis Plan We will determine the correlations between self-reported fruit and vegetable intake and each measure of body composition (BMI, WC and %BF). Data will be divided into tables (see Appendix B), plotted on graphs, and then correlations will be compared visually. We will use Spearman s rank correlation coefficient to

6 Group 5 6 compare the plotted graphs. We will describe the study population in terms of mean body composition measures and mean fruit and vegetable intake for each age group and gender. Unique Features The design of the Let s Get Healthy! fair allows for screening of a large number of participants in a short amount of time as well as gathering information related to diet and health that can be used for many areas of research. Anticipated Limitations/Problems A limitation to this study is the number of participants who did not completely fill out the dietary assessment form or submit to all the measurements collected at the body composition station. Since attendees of the fair did not have to participate at all of the stations, many of them are missing a component of data needed for our study. Because of this we excluded over half of the data. However, this still leaves a substantial data set of 619 participants (63% female, 37% male). Another limitation is the wide age range included in the analysis since the recommendations for %BF shift throughout the life cycle. To account for this, we are also analyzing the data within specified age ranges and gender. Future Studies Eating fruits and vegetables are an important part of the USDA dietary guidelines for a healthy diet. What is not known is how fruit and vegetable intake impacts measures of body composition (BMI, WC, and %BF). More will be understood about how diet affects health by gaining a greater understanding of how fruit and vegetable intake impacts weight distribution and body composition measurements. Future studies will be able to build on correlations found in this study and will hopefully be able to find additional correlations relating to fruit and vegetable intake and disease risk.

7 Group 5 7 Appendix A: Body Composition Measures Table 1 Fruit and Vegetable Intake Recommendations (MyPyramid, 2010) Gender Age Fruit Vegetables Women cups cups Men cups cups Table 2 BMI (NIDDK, 2010) Ranges (kg/m 2 ) Classifications Below 18.5 Underweight 18.5 to 24.9 Healthy weight 25.0 to 29.9 Overweight 30 or higher Obese Table 3 Waist Circumference (NIDDK, 2010) Gender Measure* (inches) Men >40 Women >35 *measurements greater than these measures indicates higher disease

8 Group 5 8 Appendix B: Data Analysis Tables Table 1: BMI Male Female Age (yrs) Underweight Healthy Overweight Obese Underweight Healthy weight Overweight Obese weight Overall Table 2 % Body Fat Age (yrs) Overall Male Female Table 3 WC Male Female Age (yrs) Recommended At risk Recommended At risk Overall Table 4 Fruit and Vegetable Intake Age (yrs) Overall Male Below recommended fruit intake Recommended fruit intake Below recommended vegetable intake Recommended vegetable intake Female Below recommended fruit intake Recommended fruit intake Below recommended vegetable intake Recommended vegetable intake Table 5 Purpose of Power Correlation (r1) Power

9 Group 5 9 Appendix C: Project Timeline Project Timeline Week(s) of Tasks to be Completed 2/7 Project Proposal Due Small Group Meeting with Dr. Shannon and Dr. Stadler Continue cleaning data 2/14 Monthly Progress Report Due Start Analyzing Data 2/21, 2/28, 3/7 Complete Data Tables 3/14 Monthly Progress Report Due 3/21,3/28 Complete Statistical analysis 4/4 Monthly Progress Report Due 4/11, 4/18 Complete written analysis 4/25 Monthly Progress Report Due, First draft of poster completed 5/2, 5/9 Revised Poster completed 5/16, 5/23 Final Poster complete 5/30 Monthly Progress Report Due Poster of Research Project (due date TBA) 6/6 Newsletter Article Due Participation at Let s Get Healthy! fair (date TBA, possibly 6-8pm, Valley Catholic School, Portland)

10 Group 5 10 References Bes-Rastrollo, M., van Dam, R. M., Martinez-Gonzalez, M. A., Li, T. Y., Sampson, L. L., & Hu, F. B. (2008). Prospective study of dietary energy density and weight gain in women. The American Journal of Clinical Nutrition, 88(3), Block G, Gillespie C, Rosenbaum EH, Jenson C. A rapid food screener to assess fat and fruit and vegetable intake. Am J Prev Med 2000;18: Diehr, P, O'Meara, ES, Fitzpatrick, A, et al. Weight, mortality, years of healthy life, and active life expectancy in older adults. J Am Geriatr Soc 2008; 56:76. De Onis M, Onyango AW, Borghi E, Siyam A, Nishida C, Siekmann J. Growth Reference 5-19 years: Development of a WHO growth reference for school-aged children and adolescents. Bulletin of the World Health Organization 2007;85: Flegal, K. M., Carroll, M. D., Ogden, C. L., & Curtin, L. R. (2010). Prevalence and trends in obesity among US adults, JAMA: The Journal of the American Medical Association, 303(3), Gallagher et al. (2009). From the Pediatric Nutrition Handbook, 6 th Edition. American Academy of Pediatrics and Am J Clin Nut 2000; 72: Huxley R., Mendis S., Zheleznyakov E., Reddy S., Chan J. (2010). Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk a review of the literature. European Journal of Clinical Nutrition. 64(1): Epub 2009 Aug 5. Janssen, I., Katzmarzyk, P. T., & Ross, R. (2004). Waist circumference and not body mass index explains obesity-related health risk. The American Journal of Clinical Nutrition, 79(3), McNaughton, S. A., Mishra, G. D., Stephen, A. M., & Wadsworth, M. E. (2007). Dietary patterns throughout adult life are associated with body mass index, waist circumference, blood pressure, and red cell folate. The Journal of Nutrition, 137(1), Mendoza, J. A., Drewnowski, A., & Christakis, D. A. (April 2007). Dietary energy density is associated with obesity and the metabolic syndrome in U.S. adults. Diabetes Care, 30(4), National Institute of Diabetes and Digestive and Kidney Disease (NIDDK). Weight-control Information Network. Available from: Accessed January 16, Uitenbroek, D. G. (1997). SISA Binomial. Southampton: D.G. Uitenbroek. Available at: Accessed on February 7, USDA. Inside the Pyramid. Available at: Accessed January 16, 2010.