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Full-Text Articles in Medicine and Health Sciences
Start Date May Predict Attrition 6 Months Into A 12mth Dietary Intervention Weight Loss Trial, Jane O'Shea, Linda Tapsell, Marijka Batterham, Karen Charlton, Yasmine Probst, Rebecca Thorne, Qingsheng Zhang, Holley Jones
Start Date May Predict Attrition 6 Months Into A 12mth Dietary Intervention Weight Loss Trial, Jane O'Shea, Linda Tapsell, Marijka Batterham, Karen Charlton, Yasmine Probst, Rebecca Thorne, Qingsheng Zhang, Holley Jones
Qingsheng Zhang
Participant recruitment is a difficult and time consuming aspect of clinical trials, often resulting in delays and budget overruns. Having reached recruitment targets the next challenge is participant retention. Some weight-loss studies have attrition rates around 60% which may introduce bias in the results. It may be possible to reduce attrition rates if known predictors can be found but to date few studies produced consistent results. The aim of this exploratory study was to determine whether start date could be a predictor of attrition for participants involved in the SMART weight loss clinical trial (ACTRN12608000425392). Recruitment for the trial occurred …
Baseline Characteristics Of Volunteers In The Smart Clinical Trial: Associations Between Habitual Physical Activity And Lifestyle Disease Risk Factors, Qingsheng Zhang, Jane E. O'Shea, Rebecca L. Thorne, Linda C. Tapsell, Marijka Batterham, Karen E. Charlton
Baseline Characteristics Of Volunteers In The Smart Clinical Trial: Associations Between Habitual Physical Activity And Lifestyle Disease Risk Factors, Qingsheng Zhang, Jane E. O'Shea, Rebecca L. Thorne, Linda C. Tapsell, Marijka Batterham, Karen E. Charlton
Qingsheng Zhang
Physical Activity has been suggested to have favorable effects on various cardiovascular risk factors, and may serve as an intervening variable in life-style intervention studies. We aimed to examine the relationship between habitual physical activity and selected cardiovascular markers at baseline in a sample of overweight women who participated in the SMART clinical trial [ACTRN12608000425392]. A sub-sample of eighty-six overweight/obese women (mean age ± S.D.: 45 ± 7.9 years) were included in this analysis. Anthropometric and fasting blood data was collected at baseline (t = 0). Habitual physical activity was assessed by a validated questionnaire (Baecke questionnaire). Associations were examined …
Conversion Of Australian Food Composition Data From Ausnut1999 To 2007 In The Clinical Trial Context, Elizabeth P. Neale, Yasmine C. Probst, Rebecca Thorne, Qingsheng Zhang, Jane E. O'Shea, Marijka J. Batterham, Linda C. Tapsell
Conversion Of Australian Food Composition Data From Ausnut1999 To 2007 In The Clinical Trial Context, Elizabeth P. Neale, Yasmine C. Probst, Rebecca Thorne, Qingsheng Zhang, Jane E. O'Shea, Marijka J. Batterham, Linda C. Tapsell
Qingsheng Zhang
An Australian food composition database, AUSNUT1999, does not include long chain omega-3 polyunsaturated fatty acid (LC omega-3 PUFA) data. Measurement of the fatty acid content of diets initially analysed using AUSNUT1999 requires conversion to AUSNUT2007, an updated database inclusive of LC omega-3 PUFA. The aim of this study was to convert clinical trial dietary data from AUSNUT1999 to AUSNUT2007 and measure LC omega-3 PUFA intake. Clinical trial diet history (DH) data was converted from AUSNUT1999 to 2007 using a staged approach. Macronutrient intake from AUSNUT1999 and 2007 were calculated and compared via paired t-tests and Wilcoxon Signed Ranks tests. Mean …