Level of cognitive performance as a correlate and predictor of health behaviors that protect against cognitive decline in late life: The path through life study
Section snippets
Study design and participants
The sample came from the PATH Through Life Project, a large community survey concerned with the health and well being of people aged 20 to 24 (20s), 40 to 44 (40s), and 60 to 64 (60s) years who live in Canberra or the neighbouring town of Queanbeyan, Australia (Jorm, Anstey, Christensen, & Rodgers, 2004). Each cohort is to be followed up every 4 years over a total period of 20 years. Results presented here concern the first and second wave interviews with 20- to 24-year-olds being conducted in
Descriptive statistics for cognition and health behaviors
Table 1 shows the descriptive statistics for the cognitive measures at Wave 1. Results confirm the usual pattern of lack of age-differences in verbal ability but poorer scores on processing speed (SDMT) in the older cohorts. The correlation between STW and SDMT was .113 (p < .01). Table 2 shows the frequencies of health behaviors by cohort at Waves 1 and 2. The significance of change in the level of health behaviors between waves was evaluated in the GEE models and is reported below.
Effect of verbal intelligence on health behaviors and change in health behaviors
Table 3 shows
Discussion
The present study demonstrated several associations between both precautionary and adaptive health behaviors and cognitive performance. In general, higher levels of verbal ability and processing speed were associated with higher levels of physical activity, greater likelihood of taking vitamin and mineral supplements, reduced likelihood of current smoking and abstaining from alcohol. However, lower levels of verbal ability and processing speed were associated with higher rates of cholesterol
Acknowledgements
We thank the study participants, PATH Interviewers, Patricia Jacomb, Karen Maxwell, Bryan Rodgers and Tony Jorm. The first two waves of the PATH Through Life Study were funded by the National Health and Medical Research Council Grants #229936 and #179839. Anstey, Low and Christensen are funded by NHMRC fellowships # 366756, #455377, and #366781.
References (22)
- et al.
Cholesterol as a risk factor for dementia and cognitive decline: a systematic review of prospective studies with meta-analysis
American Journal of Geriatric Psychiatry
(2008) - et al.
Gender differences in cognitive abilities: the mediating role of health state and health habits
Intelligence
(2004) - et al.
Health inequalities among British civil servants: the Whitehall II study
Lancet
(1991) - et al.
The age-dependent relation of blood pressure to cognitive function and dementia
Lancet Neurology
(2005) - et al.
Is antioxidant therapy a viable alternative for mild cognitive impairment? Examination of the evidence
Dementia and Geriatric Cognitive Disorders
(2007) - et al.
The relationship between cognition and mortality in patients with stroke, coronary heart disease or cancer
European Psychologist
(2006) - et al.
Smoking as a risk factor for dementia and cognitive decline: a meta-analysis of prospective studies
American Journal of Epidemiology
(2007) - et al.
The Spot-the-Word Test
(1992) Impact of nutrition on ageing and disease
Current Opinion in Clinical Nutrition and Metabolic Care
(2006)- et al.
Neurocognitive aging and cardiovascular fitness: recent findings and future directions
Journal of Molecular Neuroscience
(2004)
Applied longitudinal analysis
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