Gil B Rosa, Pedro B Júdice, Megan Hetherington-Rauth, João P Magalhães, Inês R Correia, Luís B Sardinha
{"title":"A hierarchy of correlates for objectively measured physical activity, sedentary time, and physical fitness in older adults: A CHAID analysis.","authors":"Gil B Rosa, Pedro B Júdice, Megan Hetherington-Rauth, João P Magalhães, Inês R Correia, Luís B Sardinha","doi":"10.1080/17461391.2022.2127377","DOIUrl":null,"url":null,"abstract":"<p><p>The aging process reflects, in many cases, not only a decline in physical activity (PA) and physical fitness (PF), but also an increase in overall levels of sedentary time (ST). In order to hierarchically identify the most powerful correlates related to low and high levels of objectively assessed PA, ST, and PF during the late adulthood, a total of 2666 older adults were cross-sectionally evaluated. Multidimensional correlates were obtained through interview. Using chi-squared automatic detection analysis to identify the cluster of correlates with most impact on PA (<21.4 min/day), ST (≥8 h/day), and PF (<33.3th percentile), was found that the most likely subgroup to be physically inactive consisted of widowers not owning a computer and sport facilities in the neighbourhood (94.7%), while not being widowed, reporting to have a family that exercises and a computer at home (54.3%) represented the subgroup less likely to be inactive. Widowers without sidewalks in the neighbourhood were the most sedentary group (91.0%), while being a married woman and reporting to have space to exercise at home (40%) formed the most favourable group of correlates regarding ST. Men reporting a financial income <500€ and physical problems frequently formed the group with the lowest PF level (70.3%). In contrast, the less likely subgroup to have low levels of PF level consisted of having a financial income ≥1000€ and a computer at home (3.4%). Future interventions should target widowers with limited accessibility to computer and urban/sport-related infrastructures, as well as impaired older adults with low financial income.<b>Highlights</b>Chi-squared automatic interaction detection was used to identify and hierarchise correlates of objectively measured physical activity, sedentary time, and fitness.Widowers not having a computer at home and sport facilities in the neighbourhood were the most likely to be physically inactive, while not being widowed, having a family that exercises and a computer at home represented the subgroup less likely to be physically inactive.The most likely to be classified as sedentary were widowers without sidewalks in the neighbourhood, while the most favourable group of correlates regarding ST was formed by married women and reporting to have space to exercise at home.Individuals with a low financial income and physical problems comprised the population subgroup with the lowest PF levels, while having a medium-high financial income and a computer at home represented the less likely subgroup to have low levels of PF.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/17461391.2022.2127377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
The aging process reflects, in many cases, not only a decline in physical activity (PA) and physical fitness (PF), but also an increase in overall levels of sedentary time (ST). In order to hierarchically identify the most powerful correlates related to low and high levels of objectively assessed PA, ST, and PF during the late adulthood, a total of 2666 older adults were cross-sectionally evaluated. Multidimensional correlates were obtained through interview. Using chi-squared automatic detection analysis to identify the cluster of correlates with most impact on PA (<21.4 min/day), ST (≥8 h/day), and PF (<33.3th percentile), was found that the most likely subgroup to be physically inactive consisted of widowers not owning a computer and sport facilities in the neighbourhood (94.7%), while not being widowed, reporting to have a family that exercises and a computer at home (54.3%) represented the subgroup less likely to be inactive. Widowers without sidewalks in the neighbourhood were the most sedentary group (91.0%), while being a married woman and reporting to have space to exercise at home (40%) formed the most favourable group of correlates regarding ST. Men reporting a financial income <500€ and physical problems frequently formed the group with the lowest PF level (70.3%). In contrast, the less likely subgroup to have low levels of PF level consisted of having a financial income ≥1000€ and a computer at home (3.4%). Future interventions should target widowers with limited accessibility to computer and urban/sport-related infrastructures, as well as impaired older adults with low financial income.HighlightsChi-squared automatic interaction detection was used to identify and hierarchise correlates of objectively measured physical activity, sedentary time, and fitness.Widowers not having a computer at home and sport facilities in the neighbourhood were the most likely to be physically inactive, while not being widowed, having a family that exercises and a computer at home represented the subgroup less likely to be physically inactive.The most likely to be classified as sedentary were widowers without sidewalks in the neighbourhood, while the most favourable group of correlates regarding ST was formed by married women and reporting to have space to exercise at home.Individuals with a low financial income and physical problems comprised the population subgroup with the lowest PF levels, while having a medium-high financial income and a computer at home represented the less likely subgroup to have low levels of PF.