Leisure-time Physical Activity and All-cause Mortality in an Elderly Cohort

Bembom, Oliver; Laan, Mark van der; Haight, Thaddeus; Tager, Ira B.

doi:10.1097/ede.0b013e31819e3f28

Cited by 51 publications

(32 citation statements)

References 28 publications

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“…Our data were consistent with the evidence which indicates that depending on frequency and intensity, not only exercise, habitual physical activity-defined as all forms of body movement with energy expenditure above resting levels including household chores-can beneficially influence health parameters [42]. By doing household chores, it can reduce the time spent being sedentary and may be as important for the promotion of physical activity to prevent fat gain, simultaneously reduce obesity among women [43].…”

Section: J Fundam Appl Sci 2017 9(4s) 905-919 913supporting

confidence: 79%

High body fat percentage among adult women in Malaysia: the role of lifestyle

Johari

Nordin

Sahar

et al. 2018

J. Fundam and Appl Sci.

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Body fat percentage is regarded as an important measurement for diagnosis of obesity. The aim of this study is to determine the association of high body fat percentage (BF%) and lifestyle among adult women. The study was conducted on 327 women, aged 40-59 years, recruited during a health screening program. Data on socio-demography, dietary intake and physical activity were collected through validated questionnaires. BF% was measured using InBody 270 Body Impedance analyzer machine. Association between lifestyle factors and body fat percentage were investigated using multiple linear regression, adjusted for age and body mass index (BMI). Intake of protein, calcium and physical activity on household intensity were the predictors of high BF%.

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Section: J Fundam Appl Sci 2017 9(4s) 905-919 913supporting

confidence: 79%

High body fat percentage among adult women in Malaysia: the role of lifestyle

Johari

Nordin

Sahar

et al. 2018

J. Fundam and Appl Sci.

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“…Physical activity in older adults has consistently been linked to mortality and morbidity (Bembom et al 2009;Benetos et al 2005;Blair and Brodney 1999;Yates et al 2008). Additionally, risk factors occurring between the baseline and incidence of non-survival or survival to age 85 were not examined which may have led to an underestimation of associations.…”

Section: Discussionmentioning

confidence: 99%

Predicting survival and morbidity-free survival to very old age

Newson

Witteman

Franco

et al. 2010

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As life expectancy continually increases, it is imperative to identify determinants of survival to the extreme end of the lifespan and more importantly to identify factors that increase the chance of survival free of major morbidities. As such, the current study assessed 45 common disease factors as predictors of survival and morbidity-free survival to age 85 years. Within the Rotterdam Study, a population-based cohort, we evaluated morbidity-free participants who were able to attain age 85 within the study duration (n=2,008). Risk factors were assessed at baseline (1990)(1991)(1992)(1993), and mortality and morbidities were then collected continuously until mortality or the occurrence of their 85th birthday (average time of 7.9 years). Risk factors included demographic and lifestyle variables, health and morbidity indicators and physiological makers. Major morbidities examined included dementia, cancer, cerebrovascular accident, heart failure and myocardial infarction. Logistic regression analyses demonstrated that many of the variables were independently predictive for survival and for morbidity-free ageing to 85 years. These included being female, absence of left ventricular abnormalities, stable body weight, unimpaired instrumental activities of daily living, lower C-RP levels and higher levels of femoral neck bone mineral density and albumin. Relative to nonsurvival, predictors were stronger for morbidity-free survival than for total survival or survival with morbidity. This suggests that lifespan and healthy survival to older age can be relatively well predicted. Understanding predictors of a long and healthy lifespan is vital for developing primary and secondary preventions to help improve the quality of life of older adults and for reducing the financial burden of the rapidly escalating ageing population.

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“…the targeted loss function L(Q * ) using the super learning methodology, and due to the targeted MLE step the resulting substitution estimator of ψ 0 is now asymptotically linear as well if the targeted fluctuation function is estimated at a good enough rate (and only requiring adjustment by confounders not yet accounted for by initial estimator: see collaborative targeted MLE): either way, bias reduction will occur as long as the censoring/treatment mechanism is estimated consistently. Targeted MLE have been applied in a variety of estimation problems: Bembom et al (2008), Bembom et al (2009) …”

Section: An Overview Of Relevant Literaturementioning

confidence: 99%

Collaborative Double Robust Targeted Maximum Likelihood Estimation

Laan¹,

Gruber²

2010

The International Journal of Biostatistics

152

141

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Collaborative double robust targeted maximum likelihood estimators represent a fundamental further advance over standard targeted maximum likelihood estimators of a pathwise differentiable parameter of a data generating distribution in a semiparametric model, introduced in van der Laan, Rubin (2006). The targeted maximum likelihood approach involves fluctuating an initial estimate of a relevant factor (Q) of the density of the observed data, in order to make a bias/variance tradeoff targeted towards the parameter of interest. The fluctuation involves estimation of a nuisance parameter portion of the likelihood, g. TMLE has been shown to be consistent and asymptotically normally distributed (CAN) under regularity conditions, when either one of these two factors of the likelihood of the data is correctly specified, and it is semiparametric efficient if both are correctly specified.In this article we provide a template for applying collaborative targeted maximum likelihood estimation (C-TMLE) to the estimation of pathwise differentiable parameters in semi-parametric models. The procedure creates a sequence of candidate targeted maximum likelihood estimators based on an initial estimate for Q coupled with a succession of increasingly non-parametric estimates for g. In a departure from current state of the art nuisance parameter estimation, C-TMLE estimates of g are constructed based on a loss function for the targeted maximum likelihood estimator of the relevant factor Q that uses the nuisance parameter to carry out the fluctuation, instead of a loss function for the nuisance parameter itself. Likelihood-based crossvalidation is used to select the best estimator among all candidate TMLE estimators of Q 0 in this sequence. A penalized-likelihood loss function for Q is suggested when the parameter of interest is borderline-identifiable.We present theoretical results for "collaborative double robustness," demonstrating that the collaborative targeted maximum likelihood estimator is CAN even when Q and g are both misspecified, providing that g solves a specified score equation implied by the difference between the Q and the true Q 0 . This marks an improvement over the current definition of double robustness in the estimating equation literature.We also establish an asymptotic linearity theorem for the C-DR-TMLE of the target parameter, showing that the C-DR-TMLE is more adaptive to the truth, and, as a consequence, can even be super efficient if the first stage density estimator does an excellent job itself with respect to the target parameter.Unauthenticated Download Date | 5/9/18 7:57 AM This research provides a template for targeted efficient and robust loss-based learning of a particular target feature of the probability distribution of the data within large (infinite dimensional) semi-parametric models, while still providing statistical inference in terms of confidence intervals and p-values. This research also breaks with a taboo (e.g., in the propensity score literature in the field of causal inference) ...

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Leisure-time Physical Activity and All-cause Mortality in an Elderly Cohort

Cited by 51 publications

References 28 publications

High body fat percentage among adult women in Malaysia: the role of lifestyle

High body fat percentage among adult women in Malaysia: the role of lifestyle

Predicting survival and morbidity-free survival to very old age

Collaborative Double Robust Targeted Maximum Likelihood Estimation

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