# Towards a Machine Learning Model for Detection of Dementia Using Lifestyle Parameters
## 2 Materials and Method  
### Source Data  
Our work uses data from the National Health and Ageing Trends (NHATS) study [10]. John Hopkins University, Westat, and the National Institute on Aging have an ongoing study called the NHATS (National Health and Ageing Trends Study). The study aims to track and observe more than 500 parameters of the past and present lifestyles of persons who are 65 years of age and above residing in the United States of America. This is a multidisciplinary study with contributions from researchers in various fields such as geriatric medicine, demography, epidemiology, economics, etc. It also includes distinct markers that indicate whether the person is suffering from dementia or not. NHATS sample collection commenced in 2011. In 2015, more subjects were added to the study to represent the older population. For subjects already enrolled in the study, interviews are carried out regularly on an annual basis to track how parameters vary over time. The NHATS initiative carries out interviews on monthly basis. If the respondent passes away, the respondent's last interview becomes the last month of life interview. Racial diversity and fair old age representation are ensured by oversampling racially diverse and older people. The information collected from each individual spans various aspects of the interviewe's physical, social, and technological environment. The study also collects information about how an individual carries out their daily life activities. Several screening tests are also part of this study. These screening tests help in recording the physical and cognitive capacity of a person. It is an ongoing longitudinal study that is carried out to understand the trajectory of old age disability [11]. This study contains data from around 4800 unique individuals, spanning 10 years (multi-domain data)--541 questions per individual. This data is available in the public domain for research. The data can be obtained after signing up to their portal [www.NHATS.org] (accessed on 21 April 2023). After accepting agreement to NHATS's terms of use. There are 11 rounds of data available on the portal (one round for each year). In the NHATS data, there are distinct parameters that indicate that an individual is suffering from dementia. An individual is marked as dementia patient if there is a formal report of diagnosis of dementia from a doctor or a proxy reports that the subject is unable to respond due to dementia. Screening test scores are also considered while deciding whether the subject is suffering from dementia or not. The protocol for deciding whether the subject is suffering from dementia or not is based on whether the cognitive, memory, and orientation evaluation test score is below 1.5 standard deviations of the mean in at least two faculties [12; 13]. Since the NHATS gathers multi-domain, multi-disciplinary data, people from various disciplines and areas of interest have analysed it for various purposes. A major component of the study was a meta-analysis of the data itself. 1. [PERSON] and [PERSON] et al. studied the cohort profile of the NHATS study [14] and used it to extend the study to the classification of people by their dementia status [15]. 2. [PERSON] et al. explored the longitudinal associations of stroke with cognitive impairment in older US adults using NHATs data from 2011 to 2019. They found that older adults who suffered strokes are at higher risk of dementia [16]. 3. [PERSON] [17] et al. constructed a typology of social isolation using data from NHATS and estimated the correlation between social isolation and health outcomes. 4. [PERSON] [18] explored short-term changes in the prevalence of probable dementia using NHATS data and found that the prevalence of probable dementia declines over this period by 1.4% to 2.6% per year. Declines are concentrated among women, non-Hispanic whites, and black groups, and those with no vascular conditions or risk factors. 5. [PERSON] et al.