The Patterns and Predictors of Physical Activity and its Impact on Cardiovascular Disease in Community Dwelling Older Adults
Citation:KILROY, SEAN, The Patterns and Predictors of Physical Activity and its Impact on Cardiovascular Disease in Community Dwelling Older Adults, Trinity College Dublin.School of Nursing & Midwifery.GENERAL NURSING, 2018
Final Thesis SubmissionLAST.pdf (PDF) 2.326Mb
Background: Physical activity in older adults is extremely important in the prevention of and protection from many non-communicable diseases including cardiovascular disease (CVD) which is the leading cause of death worldwide. However, a large proportion of older adults worldwide fail to meet the current recommended guidelines. Thus, to develop preventive lifestyle strategies and identify targets for intervention it is necessary to have information regarding the factors predicting physical activity levels and physical activity patterns. In addition, although physical activity level is inversely associated with CVD morbidity and mortality, the mechanisms involved are complex and the key mediating role that cardio-metabolic risk factors play in the relationship has yet to be fully elucidated. Understanding the predictors and effects of physical activity in older adults is crucial so participation can be appropriately promoted for the primary and secondary prevention in CVD. Methods: Utilising 2 waves of data from the Irish Longitudinal Study on Ageing (TILDA), this study aimed to assess the patterns and predictors of physical activity and assess the impact of physical activity on cardio-metabolic risk factors and CVD. Participants were community dwelling older adult s aged 65 years and older living in Ireland who completed the International Physical Activity Questionnaire (IPAQ) and who attended a health assessment. Baseline data was collected via three methods: a computer-aided personal interview, a self-completion questionnaire and a health assessment. Two years later participants completed the IPAQ (follow-up data). A series of multivariate binary logistic regression analysis were employed to assess the impact of a wide range of factors (socio-demographic, social engagement, physical and mental health, cognitive and behavioural health factors) on baseline physical activity level and also on change in physical activity levels from baseline to follow up. In addition, adjusted binary logistic regression models were used to assess the impact of physical activity on cardio-metabolic risk factors and CVD. Dichotomous mediation analysis utilising logistic regression models examined the mediating effect of the cardio-metabolic risk factors on the relationship between physical activity and CVD. Statistical analysis was conducted using SPSS version 24. Results: In total, 2,360 community dwelling Irish older adults (≥65) took part in this study at baseline. Of the 65% reaching the recommended physical activity guidelines, those with a chronic health problem, higher quality of life and higher anxiety were significantly more likely to be active. Being older, female, unemployed, having poor self-rated health, functional limitations, greater sitting time, muscle weakness, diabetes, cognitive impairment and depression were all associated with lower odds of being physically active. Active participants had lower odds of having high blood pressure, diabetes, obesity, abdominally obesity and CVD. The relationship between physical activity and CVD was partially mediated by high blood pressure, obesity and abdominal obesity. Physical activity levels declined longitudinally over the two year period. Four patterns of physical activity were identified: those who remained active (Active maintainer), became inactive (Relapser), remained inactive (Inactive maintainer) and became active (Adopter). For those active at baseline, being older, female, a chronic health problem, abdominal obesity, depression, being a smoker and sitting for more than 8 hours per day were all associated with higher odds of relapsing at follow up, whereas participants with better hearing and higher education had lower odds of relapsing. Those inactive at baseline, who had better self-rated health, had higher odds of adopting at follow-up. In addition, secondary education, pain and functional mobility impairment was associated with lower odds of adopting. Conclusion: This study found a longitudinal decline in physical activity over time and identified particular groups of the Irish older adult population who are at risk of becoming physically inactive. Although the relationship between physical activity and CVD was partially explained by some cardio-metabolic risk factors, those reaching the recommended were less likely to have CVD regardless of many of the socio-demographic, behavioural and cardio-metabolic risk factors. Identifying these predictive factors of future activity is helpful in identifying targets for interventions to maintain physical activity over time in older adults. The implications of these associations should be incorporated in the implementation of future health promotion interventions and within community health practice.
Author: KILROY, SEAN
Publisher:Trinity College Dublin. School of Nursing & Midwifery. Discipline of Nursing
Type of material:Thesis
Availability:Full text available