Physical activity and trajectories in cognitive function: English Longitudinal Study of Ageing

Background: There are limited data on physical activity in relation to trajectories in cognitive function. The aim was to examine the association of physical activity with trajectories in cognitive function, measured from repeated assessments over 10 years. Methods: We conducted a ten year follow-up of 10,652 (aged 65 ± 10.1 years) men and women from the English Longitudinal Study of Ageing, a cohort of community dwelling older adults. Self-reported physical activity was assessed at baseline and neuropsychological tests of memory and executive function were administered at regular 2-year intervals. Data from six repeated measurements of memory over ten years and five repeated measurements of executive function over eight years were used. Results: The multivariable models revealed relatively small baseline differences in cognitive function by physical activity status in both men and women. Over the ten year follow-up, physically inactive women experienced a greater decline in their memory (-0.20 recalled words, 95% CI, -0.29 to -0.11, per study wave) and in executive function ability (-0.33 named animals; -0.54 to -0.13, per study wave) in comparison with the vigorously active reference group. In men there were no differences in memory (-0.08 recalled words, 95% CI, -0.18 to 0.01, per study wave), but small differences in executive function (-0.23 named animals; -0.46 to -0.01, per study wave) between inactive and vigorously active. Conclusion: Physical activity was associated with preservation of memory and executive function over ten years follow-up. The results were, however, more pronounced in women

Non-exercise physical activity and survival: English longitudinal study of ageing

Background: The activity patterns of older adults include more light/mild-intensity or “nonexercise” activity and less moderate- to vigorous-intensity activity. The health benefits of this type of activity pattern remain unclear. Purpose: To examine dose–response associations between physical activity and survival using time-varying analysis to understand the importance of “non-exercise” activity for survival in older adults. Methods: Participants (N¼10,426) were drawn from The English Longitudinal Study of Ageing, a representative sample of men and women aged Z50 years living in England. Participant data were linked with death records from the National Health Service registries from 2002 to 2011. Analyses were conducted in 2013. Cox proportional hazards models were used to estimate the risk of death according to time-varying estimates of physical activity. Results: Over an average follow-up of 7.8 years (median follow-up, 8.5 years), there were 1,896 deaths. In models adjusted for comorbidities, psychosocial factors, smoking, and obesity, there was a dose–response association between time-varying physical activity and mortality, with the greatest survival benefit in vigorously active participants. However, participating in mild (“non-exercise”)- intensity physical activity was also associated with a lower risk of all-cause mortality (hazard ratio [HR]¼0.76, 95% CI¼0.69, 0.83); cardiovascular mortality (HR¼0.74, 95% CI¼0.64, 0.85); and death by other causes (HR¼0.67, 95% CI¼0.58, 0.78). Time-varying models produced stronger, more robust estimates than models using a single measurement of physical activity at baseline. Conclusions: Older adults gain health benefits from participating in regular “non-exercise” physical activity, although the greatest benefits are observed for more vigorous activity

The InterLACE study: design, data harmonization and characteristics across 20 studies on women's health

The International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events (InterLACE) project is a global research collaboration that aims to advance understanding of women's reproductive health in relation to chronic disease risk by pooling individual participant data from several cohort and cross-sectional studies. The aim of this paper is to describe the characteristics of contributing studies and to present the distribution of demographic and reproductive factors and chronic disease outcomes in InterLACE

The prospective association between type 2 diabetes, elevated depressive symptoms and word recall summary score (memory) over 10 years in 10524 participants aged ≥50 years.

<p>The prospective association between type 2 diabetes, elevated depressive symptoms and word recall summary score (memory) over 10 years in 10524 participants aged ≥50 years.</p

The baseline characteristics of 10524 women and men aged ≥50 years by type 2 diabetes and elevated depressive symptoms.

<p>The baseline characteristics of 10524 women and men aged ≥50 years by type 2 diabetes and elevated depressive symptoms.</p

The trajectories of executive function (animal naming score) by diabetes and elevated depressive symptoms among participants aged 50 to 64 (top panel) and 65 years or older (bottom panel).

<p>The trajectories of executive function (animal naming score) by diabetes and elevated depressive symptoms among participants aged 50 to 64 (top panel) and 65 years or older (bottom panel).</p

The trajectories of memory (word recall summary score) by diabetes and elevated depressive symptoms among participants aged 50 to 64 (top panel) and 65 years or older (bottom panel).

<p>The trajectories of memory (word recall summary score) by diabetes and elevated depressive symptoms among participants aged 50 to 64 (top panel) and 65 years or older (bottom panel).</p

Reply to: “Talking about mediation in health and physical activity sciences”

Reply to: “Talking about mediation in health and physical activity sciences

Longitudinal associations between social capital at baseline (2006–07) predicting oral health at follow-up (2010–11); (Model 2^a and Model 3^b) OR (95%CI).

<p>^<b>a</b>Model adjusted for baseline demographic, socio-economic, health-related factors and smoking status (but excluding baseline dependent variable)</p><p>^bModel adjusted for baseline demographic, socio-economic, health-related factors, smoking status, and baseline dependent variable</p><p>*<i>p</i>< 0.05</p><p>**<i>p</i>< 0.01</p><p>***<i>p</i>< 0.001</p><p>Longitudinal associations between social capital at baseline (2006–07) predicting oral health at follow-up (2010–11); (Model 2<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125557#t003fn001" target="_blank">^a</a> and Model 3<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125557#t003fn002" target="_blank">^b</a>) OR (95%CI).</p

Longitudinal associations between oral health at baseline (2006–07) predicting social capital at follow-up (2010–11); (Model 2^a and Model 3^b) RRR (95%CI).

<p>^<b>a</b>Model adjusted for baseline demographic, socio-economic, health-related factors and smoking status (but excluding baseline dependent variable)</p><p>^bModel adjusted for baseline demographic, socio-economic, health-related factors, smoking status, and baseline dependent variable</p><p>*<i>p</i>< 0.05</p><p>** <i>p</i>< 0.01</p><p>*** <i>p</i>< 0.001</p><p>Longitudinal associations between oral health at baseline (2006–07) predicting social capital at follow-up (2010–11); (Model 2<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125557#t004fn001" target="_blank">^a</a> and Model 3<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0125557#t004fn002" target="_blank">^b</a>) RRR (95%CI).</p