Interpreting Incomplete Data in Studies of Diet and Weight Loss
Abstract
The prevalence of obesity among Americans 20 to 74 years of age increased from 15 percent during the period between 1976 and 1980 to 27 percent in 19991 and continues to increase, with alarming implications for public health. At any time, about 45 percent of women and 30 percent of men in this country are actively seeking to lose weight — in most cases, to no avail.2 Thus, the public has a keen interest in diets that might help in the battle against the bulge.Although most physicians recommend low-fat diets, low-carbohydrate diets such as the Atkins diet have had . . .
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Using the last observation carried forward for repeated measures can distort trends over time if persons who experience a foreshadowing of the outcome selectively drop out.
“Using the last observation carried forward for repeated measures can distort trends over time if persons who experience a foreshadowing of the outcome selectively drop out [ 109 ].”
From Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration (2007) · cites this paper as [109]
Attrition is a serious difficulty in weight loss trials because of its potential to bias results.
“Attrition is a serious difficulty in weight loss trials because of its potential to bias results [35].”
From Adherence to a Smartphone Application for Weight Loss Compared to Website and Paper Diary: Pilot Randomized Controlled Trial (2013) · cites this paper as [35]
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- Authors
- Ware, J. H.
- Corresponding author
- Ware, James H.
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2003-05-22
- Volume
- 348
- Issue
- 21
- Pages
- 2136-2137
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- OpenAlex
- W2079565252
- Cited by
- 205
- References
- 7
- Citations by year
- 2026: 1 · 2025: 4 · 2024: 2 · 2022: 3 · 2021: 6 · 2020: 6 · 2019: 5 · 2018: 8 · 2017: 6 · 2016: 6 · 2015: 9 · 2014: 11 · 2013: 18 · 2012: 6
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- New England Journal of Medicine (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- missing data, diet, weight loss, obesity, low-carbohydrate diet, Atkins diet, low-fat diet, dietary intervention studies
- MeSH terms
- Data Interpretation, Statistical, Diet, Reducing, Dietary Carbohydrates, Female, Humans, Male, Obesity, Patient Dropouts, Research Design, Randomized Controlled Trials as Topic, Diet, Fat-Restricted
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