Location: Jean Mayer Human Nutrition Research Center On Aging
2020 Annual Report
Objectives
Objective 1: Continue to study the oldest old that survive in the existing Geisinger Rural Aging Study cohort in relation to longitudinal health outcomes and mortality. Perform sub-analyses on all of those who survive to 100 years of age or older, whether currently surviving or not, with a focus on nutrition risk, quality of life and health outcomes as predictors of living to become a centenarian. [NP107, C5, PS5A]
Sub-objective 1.A: Continue to study the oldest old that survive in the existing Geisinger Rural Aging Study cohort in relation to longitudinal health outcomes and mortality.
Sub-objective 1.B: Perform sub-analyses on all of those eligible to survive to 100 years of age or older, whether currently surviving or not, with a focus on nutrition risk, quality of life and health outcomes as predictors of living to become a centenarian.
Objective 2: Conduct secondary analyses of the entire existing Geisinger Rural Aging Study dataset to relate nutrition risk and other lifestyle variables at baseline enrollment with additional health outcomes not previously explored in our investigations (e.g., dementia). [NP107, C5, PS5A]
Sub-objective 2.A: Conduct secondary analyses of the entire existing Geisinger Rural Aging Study dataset to relate nutrition risk and other lifestyle variables at baseline enrollment to dementia outcomes.
Sub-objective 2.B: Conduct secondary analyses of the entire existing Geisinger Rural Aging Study dataset to relate nutrition risk and other lifestyle variables at baseline enrollment to additional health outcomes not previously explored.
Approach
The Geisinger Rural Aging Study (GRAS) was initiated between 1994-99 as a longitudinal study of health outcomes in relation to nutritional status among 21,645 individuals =65-years of age. Participants have been rescreened at 3-4-year intervals with questionnaires that encompass multiple domains of nutrition risk. Our investigations have found high prevalence of poor quality diets, obesity, and ill health. We continue to validate our diet quality screening questionnaire (DQSQ) in relation to health outcomes and mortality. We have found that DQSQ scores are significantly correlated with Healthy Eating Index (HEI) scores, which were based on 24-hour dietary recall. Those that were considered not at nutritional risk as determined by the DQSQ score had significantly higher HEI scores compared to those who were in the at-risk or possibly at risk groups. These results suggest that the DQSQ is a valid measure of diet quality even in the oldest old. Recent analysis has also revealed that higher diet quality is associated with lower mortality. Participants with the lowest diet quality scores had significantly increased risk of mortality compared to those with the highest scores. These findings suggest that diet quality may play an integral role in healthy aging with potential impact on dietary guidance for older adults. Further research will afford a unique opportunity to better characterize the impact of diet quality in a cohort of the oldest old which include a growing number of centenarians. Out of the original Geisinger Rural Aging Study (GRAS) cohort of 21,645 community-dwelling Pennsylvanians aged =65-years who completed a baseline nutrition risk screening at over 100 Geisinger clinic sites between 1994-1999, we have identified 4,245 participants that remain active in the Geisinger Healthcare System. Our analysis indicates that we already have 130 confirmed centenarians (living or expired) and we project that an additional 70-170 will become available for investigation over the coming 5-years. We will continue to study the oldest old in relation to health outcomes and mortality. By performing sub-analyses on those eligible to have survived =100 years, we will discern whether nutrition risk, quality of life and health outcomes are predictors of living to become a centenarian. In particular, our robust longitudinal dataset now spans more than two decades and will provide unparalleled opportunities for secondary analyses that explore nutrition risk in relation to additional health outcomes like dementia. By studying the oldest old we can identify potentially modifiable diet and lifestyle factors to promote healthy aging.
Progress Report
Mortality: Using existing survival status contained within the Electronic Health Record (EHR), the most recent data extraction on the 21,645 Geisinger Rural Aging Study participants included 15,404 (71%) with a patient status of deceased. This figure corresponds to an additional 568 deaths since June 2019.
Centenarians: Using existing survival status contained within the Electronic Health Record, we have identified 142 GRAS participants that died at age =100 years. We look to expand the overall count of centenarians by the following methods:
We identified 660 that are eligible to be with =100 years (based on date of birth) but have an unknown death status. These 660 will be cross referenced with the National Death Index. The application to the National Death Index was reviewed and comments were returned. We are in the process of submitting the resubmission for final approval. This process was slowed due the current COVID-19 pandemic.
There are 221 GRAS participants that were alive and aged 94-99 that are eligible to become a centenarian during the study period.
We projected the expected number of centenarians in all 21,645 GRAS participants by using Center for Disease Control life tables and date of births. This resulted in an expected number of 230 centenarians (of which 142 have already been identified).
Dementia: The electronic health record was used to derive a simple, electronic algorithm (using dementia diagnosis codes) for identifying GRAS participants with dementia. Of 13,889 with eligible follow-up in the electronic health record (median follow-up 10.6 years), there were 2507 with diagnosed dementia. The overall 10-year incidence of new dementia was 14.0% and it increased with baseline age (see table).
N total 1-year 3-year 5-year 10-year 15-year
Age <70 2583 0.2% 1.0% 1.8% 5.6% 12.2%
Age 70-79 8245 1.4% 3.5% 5.5% 13.0% 25.6%
Age 80-89 2814 4.9% 10.1% 14.7% 28.2% -
Age 90+ 247 9.3% 17.2% 22.1% - -
The accuracy of this algorithm will be tested by chart review. The chart review process was informed by consultation with a Geisinger neurologist that has insight into how to identify dementia patients within the Geisinger electronic health record system (e.g. look for dementia medication use, with diagnosis of memory loss, review clinic notes for results of mini-mental exam, and search for key words within the electronic health record system). The chart review will include a randomized sample of 25-30 Geisinger Rural Aging Study participants with and without dementia diagnosis codes. The chart review process will begin soon. The results of the chart review will used to assess the utility of the electronic algorithm and, if needed, to improve the algorithm for application within the entire GRAS cohort.
Parkinson disease: A manuscript was developed and submitted entitled “Diet quality and risk of Parkinson disease: a prospective study and a meta-analysis”. This study identified Parkinson patients using diagnosis codes and medication treatment within the GRAS cohort. Six other study populations were included in a meta-analysis. The results show that adherence to a healthy dietary pattern or having high diet quality was associated with lower odds of Parkinson’s disease. In conclusion, a healthy dietary pattern may be a potential modifiable lifestyle factor that may delay onset or prevent the onset of Parkinson’s disease. To the best of our knowledge, this meta-analysis is the first study to investigate the association between overall diet quality and risk of Parkinson’s disease.
Fatigability: A manuscript was developed and submitted entitled: “Associations between Diet Quality and Perceived Physical and Mental Fatigability in the Oldest-Old Participants in the Geisinger Rural Aging Study”. Results show that total Healthy Eating Index scores and scores for total vegetables, total protein foods and refined grains were higher in those participants who reported lower physical and mental fatigability. In addition, higher perceived physical and mental fatigability scores were associated with lower intakes of some key nutrients including protein, fiber, vitamins A, K, and B6, magnesium, zinc, manganese and phosphorus. Future work is needed to determine whether targeted improvements in diet quality and intake can lead to improvements in perceptions of physical and mental fatigability and potentially impact quality of life in the oldest old.
Accomplishments
