Biography
Bandana Neupane Poudel is an International student (from Nepal) at Florida Atlantic University. She is in the mid of BSN to PHD program. Bandana is also doing a research assistantship at the College of Nursing, FAU.
Bandana did her BSN at B.P. Koirala Institute of Health Sciences, Nepal. After her BSN, she taught in the Manipal College of Medical Sciences Nursing Program for about three and half years. She taught Fundamentals of Nursing, Maternal Health Nursing and Integrated Science to Proficiency Certificate Level and BSN students. Bandana also guided and supervised the students in medical-surgical units, orthopedic units and community field postings. She also has one year of experience of wardenship in the nursing hostel of Manipal College of Medical Sciences.
Bandana has passion for doing research. She has the experience of working on various federally-funded research projects, manipulating databases, conducting univariate and multivariate analyses and creating interpretation with APA formatted tables. She has recently received a grant from Institute for Healthy Aging (I-HeAL) for doing her pilot research project. Her current research focuses primarily on calculation of biological ages, examination of the discrepancy between chronological and biological age in a sample of low and moderate-income adult clients aged 50 years and older from FAU Community Health Center, a primary care clinic in South Florida and to identify social, economic and demographic factors associated with and contributing to the discrepancy.
Neupane Poudel, B.
Poster
Factors Predicting Premature Aging: A Pilot Research Project for Health Promotion and Lifestyle
Individuals’ aging trajectories diverge in adulthood. A person is said to have premature aging if his/her biological age is ahead of his chronological age. Based on a relatively sparse literature on the subject and a small preliminary study, I hypothesize that people living in poverty most of their lives are more likely to age prematurely than their peers with higher income. The objectives of the study are to 1: examine the discrepancy between chronological and biological age in a sample of low and moderate-income adult clients aged 50 years and older from FAU Community Health Center, a primary care clinic in South Florida that provides health care services to a diverse population and 2: to identify social, economic and demographic factors associated with and contributing to the discrepancy. Identifying the factors influencing biological age by studying the diverse group will be key to recognizing and ameliorating the factors associated with the premature aging. This study utilizes an explanatory sequential design to analyze and explain the de-identified data extracted from the electronic medical records of the Center. A modification of the Klemera-Doubal equation will be utilized to obtain an estimated biologic age. Multiple Linear Regression (MLR) and Logistic Regression (LR) will be used to answer the quantitative research aims. MLR will test the unique variance accounted for by the social, economic, and demographic variables. Logistic regression will be used to investigate the likelihood of participants having premature aging as well as the odd ratio associated with the increase likelihood of premature aging for each of the social, economic, and demographic variables. Hermeneutic phenomenological design including in-depth interviews and photography will be used for the exploration of lived experiences, and examination of the findings across the two groups, those evidencing premature aging and those who do not as informed by the quantitative analysis. This study will identify the social, economic and demographic factors associated with the discrepancy between the chronological and biological age. The results from this study will add to the body of knowledge and lay the groundwork for future studies. They will also be used as the bases for potentially informing, supporting, and challenging policy and action in the communities and help preparing programs to resolve the problems influencing premature aging.
Keywords: biological age, social, economic, demographic, premature aging
