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      Body mass index and cognitive function: the potential for reverse causation

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          Abstract

          Background/Objective

          Higher late life body mass index (BMI) is unrelated to or even predicts lower risk of dementia in late-life, a phenomenon that may be explained by reverse causation due to weight loss during pre-clinical phases of dementia. We aim to investigate the association of baseline BMI and changes in BMI with dementia in a large prospective cohort, and to examine whether weight loss predicts cognitive function.

          Methods

          Using a national cohort of adults average age 58 at baseline in 1994 (n=7,029), we investigated the associations between baseline BMI in 1994 and memory scores from 2000 to 2010. We also examined the association of BMI change from 1994 to 1998 with memory scores from 2000 to 2010. Lastly, to investigate reverse causation, we examined whether memory scores in 1996 predicted BMI trajectories from 2000 to 2010.

          Results

          Baseline overweight predicted better memory scores 6 to 16 years later (β=0.012, 95%CI=0.001; 0.023). Decline in BMI predicted lower memory scores over the subsequent 12 years (β= −0.026, 95%CI= −0.041; −0.011). Lower memory scores at mean age 60 in 1996 predicted faster annual rate of BMI decline during follow-up (β= −0.158 kg/m 2 per year, 95% CI= −0.223;−0.094).

          Conclusion

          Consistent with reverse causation, greater decline in BMI over the first four years of the study was associated with lower memory scores over the next decade and lower memory scores was associated with a decline in BMI. These findings suggest that pre-clinical dementia predicts weight loss for people as early as their late 50s.

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          Most cited references38

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men.

            Standard methods for survival analysis, such as the time-dependent Cox model, may produce biased effect estimates when there exist time-dependent confounders that are themselves affected by previous treatment or exposure. Marginal structural models are a new class of causal models the parameters of which are estimated through inverse-probability-of-treatment weighting; these models allow for appropriate adjustment for confounding. We describe the marginal structural Cox proportional hazards model and use it to estimate the causal effect of zidovudine on the survival of human immunodeficiency virus-positive men participating in the Multicenter AIDS Cohort Study. In this study, CD4 lymphocyte count is both a time-dependent confounder of the causal effect of zidovudine on survival and is affected by past zidovudine treatment. The crude mortality rate ratio (95% confidence interval) for zidovudine was 3.6 (3.0-4.3), which reflects the presence of confounding. After controlling for baseline CD4 count and other baseline covariates using standard methods, the mortality rate ratio decreased to 2.3 (1.9-2.8). Using a marginal structural Cox model to control further for time-dependent confounding due to CD4 count and other time-dependent covariates, the mortality rate ratio was 0.7 (95% conservative confidence interval = 0.6-1.0). We compare marginal structural models with previously proposed causal methods.
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              Body mass index in midlife and late-life as a risk factor for dementia: a meta-analysis of prospective studies.

              The relationship between body mass index (BMI) (in midlife and late-life) and dementia was investigated in meta-analyses of 16 articles reporting on 15 prospective studies. Follow-ups ranged from 3.2 to 36.0 years. Meta-analyses were conducted on samples including 25 624 participants evaluated for Alzheimer's disease (AD), 15 435 participants evaluated for vascular dementia (VaD) and 30 470 followed for any type of dementia (Any Dementia). Low BMI in midlife was associated with 1.96 [95% confidence interval (CI): 1.32, 2.92] times the risk of developing AD. The pooled relative risks for AD, VaD and Any Dementia for overweight BMI in midlife compared with normal BMI were 1.35 (95% CI:1.19, 1.54), 1.33 (95% CI: 1.02, 1.75) and 1.26 (95% CI: 1.10, 1.44), respectively. The pooled relative risks of AD and Any Dementia for obese BMI in midlife compared to normal BMI were 2.04 (95% CI: 1.59, 2.62) and 1.64 (95% CI: 1.34, 2.00), respectively. Continuous BMI in late-life was not associated with dementia. Small numbers of studies included in pooled analyses reduce generalizability of findings, and emphasize the need for publication of additional findings. We conclude that underweight, overweight and obesity in midlife increase dementia risk. Further research evaluating late-life BMI and dementia is required. © 2011 The Authors. obesity reviews © 2011 International Association for the Study of Obesity.
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                Author and article information

                Journal
                101256108
                32579
                Int J Obes (Lond)
                Int J Obes (Lond)
                International journal of obesity (2005)
                0307-0565
                1476-5497
                4 May 2015
                08 May 2015
                September 2015
                01 March 2016
                : 39
                : 9
                : 1383-1389
                Affiliations
                [(1) ]Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, MA, USA
                [(2) ]Discipline of Geriatrics, University of Sao Paulo Medical School, Sao Paulo, SP, Brazil
                [(3) ]Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
                Author notes
                Corresponding author: Claudia Kimie Suemoto, Department of Social and Behavioral Sciences, Harvard School of Public Health, 677 Huntington Avenue, Kresge Building, Boston, MA, 02115, USA, Phone and fax: (617) 432-3761, csuemoto@ 123456mail.harvard.edu
                Article
                NIHMS684204
                10.1038/ijo.2015.83
                4758694
                25953125
                a57d3b0a-3b16-4e43-9e63-9201e55d0fa3

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                Nutrition & Dietetics
                Nutrition & Dietetics

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