Geisinger Rural Aging Study Research Articles

Prospective Study of Diet Quality and the Risk of Dementia in the Oldest Old.

This study examined the associations between overall diet quality and the risk of dementia in a rural cohort among the oldest old. Included in this prospective cohort study were 2232 participants aged ≥ 80 years and dementia-free at the baseline according to the Geisinger Rural Aging Study (GRAS), a longitudinal cohort in rural Pennsylvania. In 2009, diet quality was assessed by a validated dietary screening tool (DST). Incident cases of dementia during 2009-2021 were identified using diagnosis codes. This approach was validated by a review of electronic health records. Associations between diet quality scores and the incidence of dementia were estimated using the Cox proportional hazards models, adjusted for potential confounders. Across a mean of 6.90 years of follow-up, we identified 408 incident cases of all-cause dementia. Having a higher diet quality was not significantly associated with a lower risk for incidents of all-cause dementia (adjusted HR for the highest compared with the lowest tertile: 1.01, 95% CI: 0.79, 1.29, P-trend = 0.95). Similarly, we did not observe a significant association between diet quality and altered risks of Alzheimer's disease and other forms of dementia. Overall, having a higher diet quality was not significantly associated with a lower risk of dementia among the oldest old during the full follow-up.

Prospective Study of Diet Quality and the Risk of Dementia in the Oldest Old

ObjectivesStudies investigating the associations between diet, in particular diet quality, and the risk of dementia are few, especially in populations of advanced age, most notably among the very old. We examined the associations between diet quality and the longitudinal risk of dementia in a prospective rural cohort among the oldest old.MethodsIn our present study, we included 2,232 participants that were ≥80 years of age at baseline, from the Geisinger Rural Aging Study, a longitudinal cohort residing in rural Pennsylvania. In 2009, diet quality was captured by a validated dietary screening tool consisting of 25 questions on food-related and behavior-specific items. Incident cases of dementia were identified using diagnosis codes. This approach was validated by a review of electronic health records. After adjusting for sociodemographic factors, anthropometric measures, and health and lifestyle variables, we examined the associations between diet quality (in tertiles) and the incidence of dementia using Cox proportional hazards models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsAcross a mean of 6.90 years of follow-up, we identified 408 incident cases of all-type dementia. Having higher diet quality was not significantly associated with lower risk for incident all-type dementia (adjusted HR for the highest compared with the lowest tertile: 1.01, 95% CI: 0.79, 1.29, P-trend = 0.95). Similarly, we did not observe a significant association between diet quality and altered Alzheimer's disease risk (P-trend = 0.86).ConclusionsIn our prospective cohort study, having higher diet quality was not significantly associated with a lower risk of dementia among the oldest old. These findings contribute to the limited understanding of the impact of overall diet quality on the longitudinal risk of dementia in at-risk, rural populations of advanced age.Funding SourcesThis study is funded by the United States Department of Agriculture, Agricultural Research Service agreement #8050-51,530-015-00D.

The Association between Poor Diet Quality, Physical Fatigability and Physical Function in the Oldest-Old from the Geisinger Rural Aging Study

More perceived physical fatigability and poor diet quality are associated with impairments in physical function in older adults. However, the degree to which more perceived fatigability explains the association between poor diet quality and low physical function is unknown. We examined this relationship in 122 (66F, 56M) of the oldest-old participants from the Geisinger Rural Aging Study (GRAS). We used 24-h dietary recalls to assess the Healthy Eating Index (HEI), the Pittsburgh Fatigability Scale (PFS, 0–50) to assess perceived physical fatigability, and the PROMIS Physical Function 20a* to assess physical function. We grouped participants into three age categories: 80–84 (n = 51), 85–89 (n = 51), and 90+ (n = 20) years. Multiple linear regression revealed that a lower HEI was associated with higher PFS Physical score after adjusting for age group, sex, body mass index, and the number of medical conditions (p = 0.001). Several macro- and micro-nutrient intakes were also lower in those reporting more (≥15) compared to less (<15) perceived physical fatigability. Mediation analysis revealed that PFS Physical scores explained ~65% (p = 0.001) of the association between HEI total score and PROMIS19 Physical Function score. Poor diet quality may contribute to more perceived physical fatigability, which could exacerbate impairments in the oldest-old’s physical function.

28201 A cross-sectional study of dietary patterns and nutrient intakes in the oldest old

ABSTRACT IMPACT: Understanding dietary patterns and nutrient intakes of the aging population may help address concerns and dietary guidelines regarding their nutritional needs. OBJECTIVES/GOALS: The objective of this study is to test the hypothesis that a healthy dietary pattern in the oldest old (aged 80 years and older) is related to greater compliance with dietary recommendations and better nutrient intake profiles. METHODS/STUDY POPULATION: We conducted a cross-sectional study of 122 participants aged 82 to 97 years old from the Geisinger Rural Aging Study (GRAS) cohort in rural Pennsylvania (n = 56 men and 66 women). The main outcome measures of the investigation were the daily nutrient intakes and food group intakes evaluated from the average of three 24-hour dietary recalls. The dietary patterns were determined by cluster analysis from 28 food groups. Diet quality and adherence to the Dietary Guidelines for Americans was assessed by the Healthy Eating Index (HEI)-2015 and the Dietary Screening Tool (DST). Recommended intakes were determined by the Recommended Dietary Allowances (RDAs) or Adequate Intakes (AIs). RESULTS/ANTICIPATED RESULTS: Less than 50% of participants met the dietary recommended intakes for vitamins D, E, K, B6, dietary fiber, zinc, potassium, and calcium. The more-nutrient-dense cluster was characterized by higher intakes of fruits and vegetables. The less-nutrient-dense cluster was characterized by higher intakes of foods including desserts and sweets. After adjusting for age, sex, and energy intake, participants in the more-nutrient-dense dietary pattern had a higher intake of vitamins A, D, K, C, fiber, and potassium (p &lt; 0.05 for all). After adjusting for age and sex, participants in the more-nutrient-dense pattern had better diet quality assessed by the (HEI)-2015 (p &lt; 0.001) and DST (p = 0.006). DISCUSSION/SIGNIFICANCE OF FINDINGS: Among the oldest old, many participants were found to have nutrient intakes lower than the recommended levels for fundamental nutrients suggesting that dietary guidance in addition to a dietary pattern more aligned with dietary guidelines may be beneficial for supporting healthy aging.

Diet Quality and Risk of Parkinson's Disease: A Prospective Study and Meta-Analysis.

Several dietary components have been shown to be neuroprotective against risk of neurodegeneration. However, limited observational studies have examined the role of overall diet quality on risk of Parkinson's disease. We examined the associations between diet quality and risk of Parkinson's disease in a prospective cohort study and meta-analysis. Included in the cohort study were 3,653 participants (1,519 men and 2,134 women; mean age: 81.5 years) in the Geisinger Rural Aging Study longitudinal cohort in Pennsylvania. Diet quality was assessed using a validated dietary screening tool containing 25 food- and behavior-specific questions in 2009. Potential Parkinson's cases were identified using electronic health records based on ICD9 (332.*), ICD10 (G20), and Parkinson-related treatments. Hazard ratios (HRs) and 95% confidence intervals (CIs) across diet quality tertiles were calculated using Cox proportional hazards models after adjusting for potential confounders. We further performed a meta-analysis by pooling our study with four published papers on this topic. Random-effects model was utilized to calculate the pooled risk ratios and 95% CIs. During a mean of 6.94 years of follow-up, 47 incident Parkinson's cases were documented. Having high diet quality at baseline was associated with lower Parkinson's disease risk (adjusted HR for the highest vs the lowest diet quality tertile = 0.39; 95% CI: 0.17, 0.89; p-trend = 0.02). The meta-analysis including 140,617 individuals also showed that adherence to high diet quality or a healthy dietary pattern was associated with lower risk of Parkinson's disease (pooled risk ratio = 0.64; 95% CI: 0.49, 0.83). Having high diet quality or a healthy dietary pattern was associated with lower future risk of Parkinson's disease.

Diet Quality and Risk of Parkinson Disease: A Prospective Study and a Meta-Analysis

Abstract Objectives Several dietary components have been shown to be neuroprotective against risk of neurodegeneration. We thus examined the associations between diet quality and risk of Parkinson disease (PD) in a prospective cohort study and a meta-analysis. Methods Included in the cohort study were 3653 participants (1519 men and 2134 women; mean age: 81.5 years) in the Geisinger Rural Aging Study longitudinal cohort in Pennsylvania. Diet quality was assessed using a validated dietary screening tool containing 25 food- and behavior-specific questions in 2009 (baseline). Potential PD cases were identified using electronic health records based on ICD10 code (G20) and PD-related treatments. Incident PD cases were defined as being diagnosed after 1 year of follow-up and receiving PD-related medication treatments. Hazard ratios (HRs) and 95% confidence intervals (CIs) across diet quality tertiles were calculated using cox proportional hazards models after adjusting for age, sex, race, educational level, smoking, oral health, obesity and living arrangement. We further performed a meta-analysis by pooling our study with four published papers on this topic. Random-effects model was utilized to calculate the pooled risk ratios and 95% CIs. Results During a mean of 6.94 years of follow-up, 47 incident PD cases were documented. Having high diet quality at baseline was associated with lower PD risk (p-trend = 0.02). The adjusted HR was 0.39 (95% CI: 0.17–0.89) for the highest vs the lowest diet quality tertiles. The meta-analysis including 140,617 individuals also showed that adherence to a healthy dietary pattern was associated with lower risk of incident PD (pooled risk ratio = 0.64; 95% CI: 0.49–0.83). Conclusions Having high diet quality was associated with lower future risk of PD. Funding Sources United States Department of Agriculture, Agricultural Research Service agreement.

Diet Quality Is Associated With Mortality in Adults Aged 80 Years and Older: A Prospective Study.

Diet quality has been associated with health outcomes and quality of life. However, the association between diet quality and mortality in older people, those aged 80 years and older, is understudied. Therefore, we conducted a prospective study to examine whether better diet quality, assessed by a validated dietary screening tool (DST), was associated with lower mortality in those aged 80 years and older. Our study included 1990 participants (812 men and 1178 women), with a mean age of 84.1 years at baseline (ranging from 80 to 102 years old), from the Geisinger Rural Aging Study longitudinal cohort in Pennsylvania. Baseline descriptive information was obtained in 2009, and the DST was administered via mailed survey. The DST is composed of 25 food- and behavior-specific questions associated with dietary intake that generate a diet quality score ranging from 0 (lowest) to 100 (highest). Death was identified using electronic medical record and the Social Security Death Index data. Hazard ratios (HRs) and 95% confidence intervals (CIs) across three diet quality categories were calculated by using Cox proportional hazards models after adjusting for potential confounders. Over 8 years of follow-up (October 2009-February 2018), 931 deaths were documented. Higher diet quality was associated with lower mortality risk (P-trend = .04). Participants with high diet quality (defined as DST scores >75) had significantly lower risk of mortality compared with those with low diet quality (defined as DST scores <60) after adjusting for potential risk factors (adjusted HR = 0.76; 95% CI = 0.59-0.97). Diet quality, assessed by DST, is significantly associated with risk of mortality in older adults aged 80 years and older in our prospective cohort. Our results indicate that nutrition may have an important role in healthy aging, and more studies are needed to develop appropriate dietary recommendations for older persons. J Am Geriatr Soc 67:2180-2185, 2019.

Association between Fatigability and Physical Function among the Elderly in the Geisinger Rural Aging Study

Association between Fatigability and Physical Function among the Elderly in the Geisinger Rural Aging Study

Association between Dietary Quality and Fatigability among the Elderly in the Geisinger Rural Aging Study

Association between Dietary Quality and Fatigability among the Elderly in the Geisinger Rural Aging Study

Dietary Pattern, Nutrient Intake, and Perceived Fatigue in the Oldest Old (P18-027-19)

ObjectivesLittle is known regarding dietary patterns and diet composition for the oldest old (defined as adults ≥ 80 years old) who usually have compromised diet quality due to age-related decline. We examined overall dietary patterns and further related the patterns to consumption of selected nutrients as well as perceived physical and mental fatigue. We hypothesized that those that had a healthy dietary pattern would have better nutrient intake profiles and reduced perceived fatigue. MethodsWe studied a cross-section of the Geisinger Rural Aging Study (GRAS) longitudinal cohort in rural Pennsylvania that included 122 participants (56 men and 66 women) aged from 82 to 97 years old. Average daily nutrient and food group intake were calculated from the average of three dietary recalls (1 weekend and 2 weekdays) by telephone. Dietary patterns were characterized using cluster analysis of 34 food groups. Mean nutrient intake and standard errors across dietary patterns were calculated after adjusting for age, sex, and energy consumption. Mean Pittsburgh fatigability questionnaire score examining physical and mental fatigue were calculated after adjusting for age, sex, and body mass index. ResultsTwo dietary patterns were defined: one pattern (n = 53) characterized by its higher consumption of fruits, vegetables, seafood, and whole grains, and another pattern (n = 69), with higher intake of fats and oil, refined grains, and cheese. After adjusting for potential confounders, participants in the healthier pattern had significantly higher consumption of carbohydrate, protein, fiber, vitamin A, E, K, C, B6, B12, iron, zinc, and potassium with lower intakes of fat and sodium compared with those in the less healthy pattern (P < 0.05 for all). Participants in the healthier pattern had a higher Healthy Eating Index-2015 score (adjusted mean: 70.6 vs 51.8; P < 0.001) and a lower physical fatigue score (adjusted mean: 17.6 vs 21.9) and mental fatigue score (adjusted mean: 6.77 vs 11.6) relative to individuals in the other pattern (P < 0.05 for both). ConclusionsThese data suggest that a dietary pattern more consistent with dietary guidelines may have a beneficial impact on physical and mental fatigue in the oldest old. Funding SourcesUnited States Department of Agriculture, Agricultural Research Service agreement 8050–51530-012–01A. Supporting Tables, Images and/or Graphs▪▪▪▪

Body mass index and all-cause mortality among older adults.

To examine the association between baseline body mass index (BMI, kg/m(2) ) and all-cause mortality in a well-characterized cohort of older persons. The association between BMI (both as a categorical and continuous variable) and all-cause mortality was investigated using 4,565 Geisinger Rural Aging Study participants with baseline age 74.0 ± 4.7 years (mean ± SD) and BMI 29.5 ± 5.3 kg/m(2) over a mean of 10.9 ± 3.8 years of follow-up. The relationship between BMI (as a continuous variable) and all-cause mortality was found to be U-shaped (P nonlinearity <0.001). Controlling for age, sex, smoking, alcohol, laboratory values, medications, and comorbidity status, underweight (BMI <18.5 kg/m(2) ) individuals had significantly greater adjusted risk of all-cause mortality than persons of BMI 18.5 to 24.9 kg/m(2) (reference range). Participants with overweight (BMI 25.0-29.9 kg/m(2) ) and class I obesity (BMI 30.0-34.9 kg/m(2) ) had significantly lower adjusted-risk of all-cause mortality. Those with classes II/III obesity (BMI ≥ 35.0 kg/m(2) ) did not have significantly greater adjusted-risk of all-cause mortality. Findings were consistent using propensity score weights and among never-smokers with 2- and 5-year lag analysis and among those with no identified chronic disease. A U-shaped association was observed between BMI and all-cause mortality with lower risk among older persons with overweight and class I obesity in comparison with those with BMI 18.5 to 24.9 kg/m(2) .

Diet Quality and Body Mass Index Are Associated with Health Care Resource Use in Rural Older Adults

Health care resource consumption is a growing concern. The aim of this study was to examine the associations between diet quality and body mass index with health care resource use (HRU) in a cohort of advanced age. Participants in the Geisinger Rural Aging Study (n=5,993) were mailed demographic and dietary questionnaires in 2009. Of those eligible, 2,995 (50%; 1,267 male, 1,728 female; mean age 81.4±4.4 years) provided completed surveys. Multivariate negative binomial models were used to estimate relative risk and 95% CI of HRU outcomes with diet quality as assessed by the Dietary Screening Tool score and body mass index determined from self-reported height and weight. Poor diet quality was associated with a 20% increased risk for emergency room (ER) visits. Fruit and vegetable consumption was grouped into quintiles of intake, with the highest quintile serving as the reference group in analyses. The three lowest fruit and vegetable quintiles were associated with increased risk for ER visits (23% to 31%); the lowest quintile increased risk for inpatient visits (27%). Obesity increased risk of outpatient visits; however, individuals with class I obesity were less likely than normal-weight individuals to have ER visits (relative risk=0.84; 95% CI 0.70 to 0.99). Diets of greater quality, particularly with greater fruit and vegetable intake, are associated with favorable effects on HRU outcomes among older adults. Overweight and obesity are associated with increased outpatient HRU and, among obese individuals, with decreased ER visits. These findings suggest that BMI and diet quality beyond age 74 years continue to affect HRU measures.

The associations between diet quality, Body Mass Index (BMI) and Health and Activity Limitation Index (HALex) in the Geisinger Rural Aging Study (GRAS).

To determine the associations between diet quality, body mass index (BMI), and health-related quality of life (HRQOL) as assessed by the health and activity limitation index (HALex) in older adults. Multivariate linear regression models were used to analyze associations between Dietary Screening Tool (DST) scores, BMI and HALex score, after controlling for gender, age, education, living situation, smoking, disease burden and self-vs. proxy reporting. Geisinger Rural Aging Study, Pennsylvania. 5,993 GRAS participants were mailed HRQOL and DST questionnaires with 4,009 (1,722 male, 2,287 female; mean age 81.5 ± 4.4) providing complete data. HALex scores were significantly lower for participants with dietary intakes categorized as unhealthy (<60) (0.70, 95% CI 0.69, 0.72, p<0.05) or borderline (60-75) (0.71, 95% CI 0.70, 0.73, p<0.05) compared to those scoring in the healthy range (>75) (0.75, 95% CI 0.73, 0.77) based on DST scores. HALex scores were significantly lower for underweight (0.67, 95% CI 0.63, 0.72, p<0.05), obese class II (0.68, 95% CI 0.66, 0.71, p<0.05) and class III participants (0.62 95% CI 0.57, 0.67, p<0.05) compared to those with BMI 18.5-24.9. Poor diet quality, as assessed by the DST, is associated with lower HRQOL in adults ≥ 74 years of age.

Body Mass Index, Poor Diet Quality, and Health-Related Quality of Life Are Associated With Mortality in Rural Older Adults

In an aging population, potentially modifiable factors impacting mortality such as diet quality, body mass index (BMI), and health-related quality of life (HRQOL) are of interest. Surviving members of the Geisinger Rural Aging Study (GRAS) (n = 5,993; aged ≥74 years) were contacted in the fall of 2009. Participants in the present study were the 2,995 (1,267 male, 1,728 female; mean age 81.4 ± 4.4 years) who completed dietary and demographic questionnaires and were enrolled in the Geisinger Health Plan over follow-up (mean = 3.1 years). Cox proportional hazards multivariate regression models were used to examine the associations between all-cause mortality and BMI, diet quality, and HRQOL. Compared to GRAS participants with BMIs in the normal range, a BMI < 18.5 was associated with increased mortality (HR 1.85 95% CI 1.09, 3.14, P = 0.02), while a BMI of 25–29.9 was associated with decreased risk of mortality (HR 0.71 95% CI 0.55, 0.91, P = 0.007). Poor diet quality increased risk for mortality (HR 1.53 95% CI 1.06, 2.22, P = 0.02). Finally, favorable health-related quality of life was inversely associated with mortality (HR 0.09 95% CI 0.06, 0.13, P < 0.0001). Higher diet quality and HALex scores, and overweight status, were associated with reduced all-cause mortality in a cohort of advanced age. While underweight (BMI < 18.5) increased risk of all-cause mortality, no association was found between obesity and all-cause mortality in this aged cohort.

The association between diet quality, BMI and health‐related quality of life in the Geisinger Rural Aging Study (GRAS)

Nutrition status is a predictor of quality of life. This study sought to determine the association between diet quality, BMI, and health‐related quality of life (HRQOL) in a population of adults ≥74 y. The Diet Screening Tool (DST) is a 25 item questionnaire scored from 0 (poor) to 100 developed to assess diet quality in older adults. The Health and Activity Limitations Index (HALex) is a HRQOL measure scored on a 0.0 (death) to 1.0 (optimal health) scale. A total of 5,993 GRAS participants were mailed HRQOL and DST questionnaires with 2,975 (1260 male, 1715 female; mean age 81.4 ± 4.4) providing complete data. Multivariate linear regression models were used to analyze associations between HALex score, BMI and DST score after controlling for gender, age, education, and smoking. The mean adjusted HALex score for participants in the lowest quintile of DST scores was 0.72 ± 0.2 compared to 0.77 ± 0.2 for those in the highest quintile of DST Scores (p‐trend &lt;0.01). Adjusted mean HALex scores were significantly lower for obese (BMI ≥30; 0.72 ± 0.21, P=0.006) and underweight individuals (BMI &lt;18.5; 0.64 ± 0.23, P=0.02) and significantly higher for overweight individuals (BMI 25–29.9; 0.76 ± 0.18, P=0.02) compared to those with BMI 18.5–24.9 (0.73 ± 0.22). Poor diet quality, as assessed by the DST, is associated with lower HRQOL in older adults. USDA #1950–51530‐010–00Grant Funding Source: USDA

Dietary patterns and weight change in older adults ≥ 75 years old: What's the relationship?

Weight change is a common health concern among the elderly, yet little is known about the relationship between weight change and dietary patterns (DP) in older adults, especially the very old (≥ 75 y). This investigation examined the association between DP and 5‐ year weight change in community‐dwelling older adults (n=270; mean ± SD age: 78.6±3.9 y) of the Geisinger Rural Aging Study, a longitudinal cohort study. Using baseline 24‐hour dietary recall data, cluster analysis was used to derive ‘Sweets and dairy’ (SD), ‘Western’ (W) and ‘Health‐conscious’ (HC) DP. Weight change data was extracted from electronic medical records and was characterized using three methods: 1) overall 5‐y weight change, 2) 10 pounds gained or lost (y/n) and 3) 10% gained or lost (y/n). Kaplan‐Meier plots and Cox proportional hazards regression were used to examine the association between DP and weight change. Mean overall weight change was not significantly different across DP: −5.56 (all), −7.2, −4.8 and −3.3 pounds for the SD, the W, and the HC DP, respectively (p=0.17). In gender‐stratified analyses, compared to the HC DP, females characterized by the SD and W DP, were three and two times more likely to lose 10 pounds (Hazard ratio (95% CI): SD=3.2 (1.5–6.7); W=2.4 (1.1–5.6)), respectively. Findings suggest that a HC DP may be associated with weight stability in females, which provides additional impetus for promoting healthy DP in older women.Grant Funding Source: USDA #1950–51530‐010–02G

Association between Dietary Patterns in Older Adults and Obesity-Related Health Outcomes

The prevalence of obesity-related health outcomes is increasing among older adults. Because it is thought that nutrition plays an important role in successful aging, there has been considerable interest in the association between dietary patterns of older adults and obesity-related health outcomes. Cluster analysis, utilizing data from four 24-hour dietary recalls, was used to derive dietary patterns in a subgroup of 260 participants from the Geisinger Rural Aging Study (mean age: 78.6 3.9 years). Prevalence (5-year follow-up) of cardiovascular disease, diabetes mellitus, hypertension, and metabolic syndrome was extracted from the outpatient electronic medical records using a validated data abstraction process. Logistic regression, adjusting for relevant covariates, was used to examine the associations between dietary patterns and health outcomes. ‘Sweets and Dairy’ (49%), ‘Health-Conscious’ (27%) and ‘Western’ (24%) dietary patterns were identified at baseline. Prevalence of hypertension in the ’Sweets and Dairy’, ‘Health-conscious’, and ‘Western’ pattern was 81.3%, 65.7%, and 79.0%, respectively. Compared to the ‘Health-Conscious’ pattern, those in the ‘Sweets and Dairy’ pattern had increased odds of hypertension; adjusted odds ratio (95% CI) was 2.17 (1.11-4.27). No significant associations were found for cardiovascular disease, diabetes mellitus, or metabolic syndrome with dietary patterns. Although there was a statistically significant relationship between dietary pattern and prevalence of hypertension, the practical clinical utility remains unclear. The null findings for a 5-year follow-up of any elderly sample for cardiovascular disease, diabetes mellitus andmetabolic syndromedonot address the potential benefits of adopting a healthy dietary pattern at a younger age.

Relative validity of the Geisinger Rural Aging Study food frequency questionnaire.

To determine the relative validity of a population specific food frequency questionnaire (FFQ) and evaluate the effectiveness of the instrument for assessing nutritional risk in older adults. A cross-over design with participants completing two different dietary assessment instruments in random order. The Geisinger Rural Aging Study (GRAS), a longitudinal study of over 20,000 adults living in the central, northern and eastern counties of Pennsylvania. A subset of GRAS consisting of 245 older adults (60% women) ranging in age from 70 to 95 years. Energy and nutrient intakes were assessed from two instruments: a population specific food frequency questionnaire (FFQ) and four 24-hour dietary recalls conducted over a two week period. Pearson correlation coefficients between the FFQ and dietary recalls for most nutrients were 0.5 or higher which suggests that the FFQ provided relatively valid estimates of macro and micronutrient intakes examined. Bland-Altman plots were generated to examine the agreement between instruments. Data are shown for energy, folate and zinc with close agreement at lower intakes indicative of risk for folate and zinc. Sensitivity results also showed that the FFQ was able to correctly classify individuals adequately at risk for most nutrients examined. This population specific FFQ appears to be a valid instrument for use in in evaluating risk for many nutrients that are of particular concern in older adults residing throughout many predominately rural counties in Pennsylvania.

Development and evaluation of a method for calculating the Healthy Eating Index-2005 using the Nutrition Data System for Research

To develop and evaluate a method for calculating the Healthy Eating Index-2005 (HEI-2005) with the widely used Nutrition Data System for Research (NDSR) based on the method developed for use with the US Department of Agriculture's (USDA) Food and Nutrient Dietary Data System (FNDDS) and MyPyramid Equivalents Database (MPED). Cross-sectional. Non-institutionalized, community-dwelling adults aged 70 years and above. Two hundred and seventy-one adults participating in the Geisinger Rural Aging Study (GRAS) and 620 age- and race-matched adults from the National Health and Nutrition Examination Survey 2001-2002 (NHANES) were included in the analysis. The HEI-2005 scores were generated using NDSR in GRAS and compared to scores generated using FNDDS and MPED in NHANES. Similar total HEI-2005 scores (mean 62·0 (se 0·75) in GRAS v. 57·4 (se 0·55) in NHANES) were estimated, and the individual components most strongly correlated with total score in both samples were compared. Cronbach's coefficient α values of HEI-2005 were 0·52 in GRAS and 0·43 in NHANES. Since NDSR is commonly used for educational purposes, in clinical settings and in nutrition research, it is important to develop methodology for assessing diet quality through the use of HEI-2005 with this dietary analysis software application and its accompanying food and nutrient database. Results from the present study show that HEI-2005 scores can be generated with NDSR using the method described in the present study and the detailed USDA Center for Nutrition Policy and Promotion technical report as guidance.

Assessment of the effects of dietary supplement use (DSU) on Estimated Average Requirement (EAR) and Adequate Intake (AI) in older adults

Poor nutrient intakes are an adaptable risk factor associated with numerous public health outcomes. As older adults represent a vulnerable population for low nutrient intakes they may be ideal candidates for DSU. Usual nutrient intakes were estimated with and without DSU using the mean nutrient intake from 4, 24‐hour recalls in the Geisinger Rural Aging Study (114 m, 158 f; mean age 78.5 ± 6). We examined the impact of DSU on the proportion of our sample who met the EAR and AI for selected nutrients, as well as on the Mean Adequacy Ratio (MAR), an index of nutrient intake (range of 0–1). The nutrients used to calculate the MAR included calcium, folate, pantothenic acid, magnesium, zinc, potassium and Vitamins A, C, D, E, K, B6, and B12. The majority of the sample (74%) reported DSU. The MAR for our sample without accounting for DSU was 0.68 but increased to 0.82 with DSU. Using the EAR, the prevalence of inadequate intakes for nutrients was higher if DSU wasn't accounted for, and a similar trend was observed for those nutrients with an AI. Notably, only 1% of the sample met the AI for Vitamin D through diet alone; however, when DSU was factored in 68% were meeting the AI. Given the widespread prevalence of DSU in older adults and the large contribution of DSU to total nutrient intakes, it is imperative to account for DSU when estimating nutrient adequacies within groups. Supported in part by NIH R21AG023179‐01A1, USDA #58‐1950‐4‐401.