Determinants of Vulnerability to Environmental Stress Among the Elderly ADRD Population As individuals live longer, healthier lives, the number of people living with, and dying from, Alzheimer?s Disease (AD) has risen. AD prevalence and mortality are expected to continue to rise in the future. However, while AD is fatal and individuals living with AD have high mortality rates, their immediate cause of death is usually respiratory disease or ischemic heart disease rather than dementia. Consequently, improving the health and quality of life of people living with ADRD depends on understanding their vulnerability to these diseases, and how these conditions interact with their dementia. Our proposed study focuses on the determinants of health and mortality among those in the Medicare population who have been identified as living with ADRD. Because cardiovascular and respiratory diseases have been identified as frequent causes of death among the ADRD population, we focus on an environmental stressor that increases the likelihood of death due to cardiovascular and respiratory causes: acute exposure to air pollution. Using a large dataset of Medicare beneficiaries and machine-learning techniques applied to quasi-random variation in pollution exposure generated by changes in local wind direction, we find that acute exposure to air pollution increases mortality risk for only about one quarter of the elderly. While individuals living with ADRD are much more likely to be in this vulnerable group than the typical Medicare beneficiary, we find that acute air pollution exposure does not increase mortality risk for a large fraction (44%) of Medicare beneficiaries living with ADRD. In this study, we will apply machine learning and ?big data? techniques to Medicare administrative data, local characteristics, and atmospheric variables in order to understand why some individuals living with ADRD suffer harm from the increased cardiovascular and respiratory stress induced by air pollution exposure while others do not. These factors, once identified and verified in continuing research, will provide guidance that can improve the health and quality of life of individuals living with ADRD by better directing resources to those most in need and guiding interventions aimed at reducing vulnerability to these and other hazards. As part of the project, we will develop a publicly available database that provides the following data at the ZIP code level: ADRD prevalence, vulnerability to air pollution exposure among the ADRD population, and ZIP code level characteristics that have been shown to affect vulnerability. Other researchers can then use this data for any other study seeking to understand the effects of geographically defined factors or policies on the ADRD population.
While Alzheimer?s disease is a fatal form of dementia, the top two immediate causes of death for people with Alzheimer?s disease are respiratory illness (55.5%) and ischemic heart disease (23.1%), which are both exacerbated by exposure to environmental hazards such as air pollution. In this study, we will apply machine learning and ?big data? techniques to Medicare administrative data in order to identify risk factors that predict vulnerability to the harmful effects of pollution exposure for individuals living with ADRD, allowing for better targeting of resources to those most in need and contributing to the improvement of interventions aimed at reducing vulnerability to these and other hazards.
| Jena, Anupam B; Olenski, Andrew R; Molitor, David et al. (2017) Association between rainfall and diagnoses of joint or back pain: retrospective claims analysis. BMJ 359:j5326 |
