Promoting appropriate diabetes management in older adults using principles from behavioral economics
Faculty Mentor: Dr. Hayley Belli | Graduate Student Mentor: Yiwei Li
Intensive glycemic control is of unclear benefit and carries an increased risk for older adults with type II diabetes. The American Geriatrics Society, therefore, released a set of guidelines, which promote less aggressive glycemic targets and reductions in pharmacologic therapy for older adults with Type II diabetes. However, some providers may be unaware of these guidelines, resulting in glycemic indices that are too tightly controlled among older adults. One approach to bringing provider awareness to these guidelines is through the use of behavioral economics nudges. Behavioral economics is a field that combines the disciplines of psychology and economics to provide insight into how humans often face challenges carefully weighing the costs and benefits in decision-making and arriving at optimal choices. Meanwhile a nudge is a behavioral economics tool that seeks to provide positive reinforcement and influence the behavior and decision-making of individuals or groups.
An 18 month cluster randomized controlled trial funded by the National Institutes of Health (NIH) National Institute on Aging (NIA) was launched across 66 NYU Langone Health clinics to test the effectiveness of a toolbox of six different behavioral economics nudges at promoting appropriate diabetes management in older adults (age 76+) with type II diabetes. The clinical trial was a pragmatic study with patient outcomes collected from NYU Langone Health electronic health records.
With the trial closing in May 2022, this research aims to explore the effectiveness of the behavioral economics intervention at promoting appropriate diabetes management. The team will have the opportunity to explore the relationship between the nudges received by providers and the resulting glycemic indices (Hb A1c values) of their patients. With access to electronic health record data, the team may also explore differences in glycemic control among older adults across a variety of patient socio-demographic and clinical characteristics, thus identifying for which provider-patient groups behavioral economics nudges may be most effective at promoting appropriate diabetes management.
PQAR Students: Kelsey Bhola, Joshua Bott, Justin Wang.
Examining the Association Between the ‘Southern Diet’, Socio-demographic Factors, and Obesity Status Among Women in Alabama
Faculty Mentor: Dr. Anarina Murillo | Graduate Student Mentor: Emma Risner
According to the CDC, Alabama ranks third in adult obesity prevalence with 39% of the population having obesity. Obesity is associated with diet quality, which is characterized in Southern states by “added fats, fried food, refined sugars, and sweetened beverages'' (Strath, 2021). This ‘Southern Diet’ is understood to increase the risk of obesity and affect the gut microbiome. Social determinants of health such as race, income, and education are also associated with increased risk of obesity. This study examined the association between diet, socio-demographic factors, the gut microbiome, and obesity among a racially balanced sample of Alabama residents. Secondary data analysis was conducted for a study of 71 women residing in Birmingham, Alabama. Socio-demographic variables included race, income, and education. T-tests were used to examine mean differences in dietary intake based on obesity status. Chi-square tests were used to assess associations among socio-demographic factors and obesity status. The associations between diet, obesity status, socio-demographic factors, and the gut microbiota were analyzed using negative binomial models. Preliminary results suggest that obese participants ate fewer fruits and that fruit intake, seafood and plant protein, and empty calories differed by education. These findings may inform future interventions that address the driving influence of socio-demographic factors to promote health across Southern communities.
PQAR Students: Clementine Sikpe, Valerie Lobato, Lourdes Sofia Romanach-Alvarez.
Drug use among older adults
Faculty Mentor: Dr. Danielle Ompad | Graduate Student Mentor: Abbey Jones
While considerable literature has reported on the initiation of tobacco, alcohol, marijuana, and injection drug use, data are sparse on crack cocaine initiation, especially among older adults. A study in Atlanta used in-depth interviews to explore late initiation crack use, defined as after age 50 for men and after age 35 for women (1). They observed three typologies for men: (a) former IDUs that transitioned to exclusive crack use, (b) heavy alcohol users who initiated crack at an older age, and (c) men with no history of either drug or alcohol abuse that transition directly to crack. For the latter two, the authors suggest that introduction to crack is through young crack-using female sexual partners. For women, there were two typologies: those that never used drugs and (a) did not have a child or sexual partner that used drugs and (b) had a child or sexual partner that used drugs. In this project, students will determine demographic and drug use correlates of late versus early crack initiation.
(1) Johnson WA, Sterk CE. Late-onset crack users: an emergent HIV risk group. J Acquir Immune Defic Syndr 2003; 33 Suppl 2:S229-32.: S229-S232.
PQAR Students: Rachel Mack, Jessica Airhienbuwa, Tayna Gebhardt.
Detection of cerebral metabolic abnormalities in Alzheimer’s disease by multiple testing
Faculty Mentor: Dr. Hai Shu | Graduate Student
Mentor: Taehyo Kim
Alzheimer’s disease (AD) is the most common type of dementia, accounting for approximately 60–80% of all cases. As a neurodegeneration biomarker, Fluorine-18 fluorodeoxyglucose positron emission tomography (FDG-PET) measures the cerebral metabolic rate of glucose (CMRgl) as a proxy of neural activity and is extensively used in early diagnosis and monitoring progression of AD. The CMRgl difference between two disease-status groups can be investigated by testing the difference in the mean values of CMRgl at each brain image voxel, thereby becoming a high-dimensional multiple testing problem. The false discovery rate (FDR), a measure of type I error, provides a powerful and practical criterion for large-scale multiple testing problems. However, most FDR controlling approaches used in neuroimaging studies ignore the spatial dependence among the test statistics obtained from brain voxels and thus lose substantial power to effectively and accurately identify AD-related regions. This project aims to conduct a comparative study of existing FDR controlling approaches, in particular, recent spatial FDR methods, on AD's FDG-PET neuroimaging data to discover new and important AD-related brain regions that are missed by conventional FDR methods. We will use the FDG-PET data from the Alzheimer’s Disease Neuroimaging Initiative, and compare the CMRgl differences between the three disease-status groups, including AD patients, mild cognitive impairment patients, and cognitively normal subjects.
PQAR Students: Angie Gonzalez, Vanessa Martinez Lenis, Gabriel Grajeda.