Project Number: 1950-51530-010-00-D
Project Type: Appropriated
Start Date: Jul 3, 2009
End Date: Apr 30, 2014
1. Use population-based approaches to explore the role of dietary patterns and diet quality in relation to weight gain and obesity among rural older-aged adults. 2. Use population-based approaches to explore the role of dietary patterns and diet quality in relation to obesity-related chronic diseases, such as cardiovascular disease, metabolic syndrome, and diabetes, among rural older-aged adults. 3. Develop and validate GRAS dietary instruments with a population of rural adults aged 80 years of age or greater.
The Geisinger Rural Aging Study (GRAS) is a longitudinal study of health outcomes in relation to nutritional status among 21,645 community-dwelling Pennsylvanians aged greater than or equal to 65 years. Initial screenings for GRAS participants took place between 1994-1999. The baseline nutrition risk screening data includes height, weight, reported weight gain/loss, depression, polypharmacy, eating habits, food security, oral health, and functional status. Follow up rescreening at 3-4 year intervals has encompassed this information as well as additional queries of medical history, weight history, family history, dietary practices, medical co-morbidities, medication use, general health, depression, mobility/functional status, and healthcare resource use. Our prior investigations have highlighted the growing prevalence of obesity and ill health among these individuals. Findings suggest that many of these obese older persons consume poor quality diets and have associated micronutrient deficiencies. Dietary patterns/quality and their relationships with obesity and chronic diseases of older persons are poorly characterized; especially among “old older” persons 80 years of age or greater. Current investigations have supported the development of a Population Specific Food Frequency Questionnaire (PSFFQ) and a 37 item Diet Quality Screening Questionnaire (DQSQ). The DQSQ is an innovative instrument for assessment of diet quality that will be made widely available to investigators and practitioners. Our proposed next steps to further characterize the GRAS cohort include longitudinal follow up of obesity-related and other health outcomes in relation to dietary patterns and diet quality among 459 subjects for whom we have conducted comprehensive assessments 5-10 years previously. We will confirm and/or refine the results of our previous dietary patterns analyses with these data then determine associations among dietary intake, dietary patterns, diet quality lifestyle factors and anthropometric (height, weight, body-mass index) and available laboratory measures. We are particularly interested in evaluating associations with weight gain and obesity in older-aged adults. These analyses will be facilitated by use of the Geisinger Health Plan EPIC electronic database. Subsequent analyses will focus on the relationship between the aforementioned dietary variables and obesity-related chronic diseases, such as cardiovascular disease, metabolic syndrome, and diabetes. We will also administer the new DQSQ to the next wave of GRAS screening participants via mailing with telephone follow-up as needed. Based upon our rescreening experience we estimate that over the next two years we will have access to approximately 2,000 respondents (57% female; 53% 80 years of age or older). We will then monitor their health-related outcomes prospectively in relation to diet quality. Anticipated products of this research include better understanding of obesity-related and other health outcomes in relation to dietary patterns/quality among rural older persons and further validation of the DQSQ in relation to health outcomes among “old older” persons.