Location: Boston, Massachusetts2013 Annual Report
1a. Objectives (from AD-416):
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.
1b. Approach (from AD-416):
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.
3. Progress Report:
Successfully published research findings for Objective 2 which evaluated the associations among three dietary patterns (i.e., Western, Health-Conscious, and Sweets and Dairy) and obesity and obesity-related health outcomes. In addition we also examined the association of these dietary patterns and weight changes. We observed that women who were characterized by the Sweets and Dairy and the Western dietary pattern were three and two times more likely to lose 10 pounds, respectively, compared to their counterparts in the Health-conscious dietary pattern. No relationships were found with weight gain. These findings support adoption of a healthier dietary pattern in older women who may be at risk for weight loss. For objective 3, continued our analyses of the remaining cohort of 4,009 subjects (mean age 81 years) and have examined the associations between diet quality, BMI, and health related quality of life as assessed by the Health and Activity Limitation Index (HALex) (manuscript in press). HALex scores were significantly lower for subjects with DQSQ (diet quality) scores categorized as unhealthy or borderline compared to those assigned healthy scores. HALex scores were also significantly lower for those with BMI <18.5 and for those with class II or class III obesity compared to those with BMI 18.5-24.9. Results from further testing also showed that those with higher, more favorable DQSQ scores were significantly more likely to be food sufficient, report eating breakfast, have no chewing difficulties, and report no decline in intake in the previous 6-months. We are currently prospectively monitoring their health-related outcomes including healthcare resource use and mortality in relation to diet quality. Of particular note is that this investigation is among the very first to conduct assessments of dietary patterns and diet quality in a cohort of such advanced age.
1. Diet quality screening identifies potential targets to improve health in older persons. The relationships between diet and health outcomes for persons of advanced age are poorly understood. ARS-supported researchers at the Geisinger Health System at Danville, Pennsylvania have administered a diet quality screening tool to over 4,000 community-dwelling persons with a mean age of 81 years. Individuals with poor diet quality were found to have poor health-related quality of life. The most significant accomplishment is the demonstration that the diet quality screening tool is able to identify potential targets for improving diet quality that may positively influence health-related outcomes. Such targets include food sufficiency and eating breakfast which are especially relevant to US agriculture.