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4 results on '"Robertson, Henry"'

1. Association of Run-in Periods with Weight Loss in Obesity Randomized Controlled Trials

Author

Affuso, Olivia, Kaiser, Kathryn A., Carson, Tiffany L., Ingram, Katherine H., Schwiers, Michael, Robertson, Henry, Abbas, Firas, and Allison, David B.

Subjects
Adult, Male, Patient Selection, Middle Aged, Weight Gain, Article, Body Mass Index, Research Design, Weight Loss, Humans, Female, Obesity, Sex Distribution, Randomized Controlled Trials as Topic
Abstract

Study-level design characteristics that inform the optimal design of obesity randomized controlled trials (RCTs) have been examined in few studies. A pre-randomization run-in period is one such design element that may influence weight loss. We examined 311 obesity RCTs published between January 1, 2007 and July 1, 2009 that examined weight loss or weight gain prevention as a primary or secondary endpoint. Variables included run-in period, pre-post intervention weight loss, study duration (time), intervention type, percent female, and degree of obesity. Linear regression was used to estimate weight loss as a function of 1) run-in (yes/no), and 2) run-in, time, percent female, body mass index, intervention type. Interaction terms were also examined. Approximately nineteen percent (18.6%) of the studies included a run-in period with pharmaceutical studies having the highest frequency. Although all intervention types were associated with weight loss (Mean = 2.80 kg, SD=3.52), the inclusion of a pre-randomization run-in was associated with less weight loss (p=0.0017) compared to studies that did not include a run-in period. However, this association was not consistent across intervention types. Our results imply that in trials primarily targeting weight loss in adults, run-in periods may not be beneficial for improving weight loss outcomes in interventions.

Published
2013

2. Empirical Evidence Does Not Support an Association between Less Ambitious Pre-Treatment Goals and Better Treatment Outcomes: A Meta-Analysis

Author

Durant, Nefertiti H., Joseph, Rodney P., Affuso, Olivia H., Dutton, Gareth R., Robertson, Henry T., and Allison, David B.

Subjects
Treatment Outcome, Weight Loss, Humans, Obesity, Goals, Article, Body Mass Index
Abstract

Setting realistic weight loss goals may play a role in weight loss. We abstracted data from randomized controlled trials and observational studies conducted between 1998 and 2012 concerning the association of weight loss goals with weight loss. Studies included those that (i) were conducted in humans; (ii) delivered a weight loss intervention; (iii) lasted ≥6 weeks; (iv) assessed baseline weight loss goals; (vi) assessed pre- and post-weight either in the form of body mass index or some other measure that could be converted to weight loss based on information included in the original study or later provided by the author(s); and (vii) assessed the correlation between weight loss goals and final weight loss or provided data to calculate the correlation. Studies that included interventions to modify weight loss goals were excluded. Eleven studies met inclusion criteria. The overall correlation between goal weight and weight at intervention completion was small and statistically insignificant (ρ=0.0 5 ; P = 0.20). The current evidence does not demonstrate that setting realistic goals leads to more favourable weight loss outcomes. Thus, our field may wish to reconsider the value of setting realistic goals in successful weight loss.

Published
2013

3. Turning the analysis of obesity-mortality associations upside down: Modeling years of life lost through conditional distributions.

Author

Robertson, Henry T., Campos, Gustavo de los, and Allison, David B.

Subjects
OBESITY, MORTALITY, SURVIVAL analysis (Biometry), BODY mass index, PROPORTIONAL hazards models, LOGISTIC regression analysis
Abstract

Objective: We demonstrate the utility of parametric survival analysis. The analysis of longevity as a function of risk factors such as body mass index (BMI; kg/m2), activity levels, and dietary factors is a mainstay of obesity research. Modeling survival through hazard functions, relative risks, or odds of dying with methods such as Cox proportional hazards or logistic regression are the most common approaches and have many advantages. However, they also have disadvantages in terms of the ease of interpretability, especially for non-statisticians; the need for additional data to convert parameter estimates to estimates of years of life lost (YLL); debates about the appropriate time scale in the model; and an inability to estimate median survival time when the censoring rate is too high. Design and Methods: We will conduct parametric survival analyses with multiple distributions, including distributions that are known to be poor fits (Gaussian), as well as a newly discovered 'Compressed Gaussian''' distribution. Results: Parametric survival analysis models were able to accurately estimate median survival times in a population-based data set of 15,703 individuals, even for distributions that were not good fits and the censoring rate was high, due to the central limit theorem. Conclusions: Parametric survival models are able to provide more direct answers, and in our analysis of an obesity-related data set, gave consistent YLL estimates regardless of the distribution used. We recommend increased consideration of parametric survival models in chronic disease and risk factor epidemiology. [ABSTRACT FROM AUTHOR]

Published
2013
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4. Is Socioeconomic Status of the Rearing Environment Causally Related to Obesity in the Offspring?

Author

Fontaine, Kevin R., Robertson, Henry T., Holst, Claus, Desmond, Renee, Stunkard, Albert J., Sørensen, Thorkild I. A., and Allison, David B.

Subjects
*CHILDHOOD obesity, *SOCIAL status, *CHILDREN'S health, *BODY mass index, *ADOPTED children, *NUTRITION disorders
Abstract

We attempt to elucidate whether there might be a causal connection between the socioeconomic status (SES) of the rearing environment and obesity in the offspring using data from two large-scale adoption studies: (1) The Copenhagen Adoption Study of Obesity (CASO), and (2) The Survey of Holt Adoptees and Their Families (HOLT). In CASO, the SES of both biological and adoptive parents was known, but all children were adopted. In HOLT, only the SES of the rearing parents was known, but the children could be either biological or adopted. After controlling for relevant covariates (e.g., adoptee age at measurement, adoptee age at transfer, adoptee sex) the raw (unstandardized) regression coefficients for adoptive and biological paternal SES on adoptee body mass index (BMI: kg/m2) in CASO were -.22 and -.23, respectively, both statistically significant (p = 0.01). Controlling for parental BMI (both adoptive and biological) reduced the coefficient for biological paternal SES by 44% (p = .034) and the coefficient for adoptive paternal SES by 1%. For HOLT, the regression coefficients for rearing parent SES were -.42 and -.25 for biological and adoptive children, respectively. Controlling for the average BMI of the rearing father and mother (i.e., mid-parental BMI) reduced the SES coefficient by 47% in their biological offspring (p#.0001), and by 12% in their adoptive offspring (p = .09). Thus, despite the differing structures of the two adoption studies, both suggest that shared genetic diathesis and direct environmental transmission contribute about equally to the association between rearing SES and offspring BMI. [ABSTRACT FROM AUTHOR]

Published
2011
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