The definition of weight maintenance

Stevens, June; Truesdale, Kimberly P.; McClain, Jill E; Cai, Jianwen

doi:10.1038/sj.ijo.0803175

Cited by 377 publications

(367 citation statements)

References 66 publications

(55 reference statements)

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“…A change of 5 % in baseline WC is an arbitrary threshold for WC change; however, there is evidence in the literature to support its use. Stevens et al (30) recommend that a change of 63 % should be considered a weight gain/loss, and that a change of 65 % is large enough to be considered clinically relevant. However, we did explore other groupings, such as a 5 % gain in WC v. the rest of the population (including people with WC gain, WC maintenance and WC loss), and a $2 % increase and change from 2 % in baseline WC (data not shown).…”

Section: Discussionmentioning

confidence: 99%

Predictors of increasing waist circumference in an Australian population

Walls

Magliano

McNeil

et al. 2010

Public Health Nutr.

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Objective: To identify predictors of increasing waist circumference (WC) over a 5-year period in a contemporary population of Australian adults. Design: Longitudinal national cohort of adults participating in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Settings: Australian adults in 2000 and 2005. Subjects: A total of 2521 men and 2726 women aged $25 years at baseline who participated in AusDiab and provided anthropometric measurements at baseline (1999)(2000) and follow-up (2005). Results: A $5 % increase of baseline WC occurred in 27 % of men and 38 % of women over the 5-year period. In the multivariate analysis of the total population, there was a higher risk of $5 % gain in baseline WC in women, younger people, people with a lower baseline WC, people who never married compared with married/de facto, current smokers compared with never smokers, people with a poorer diet quality and people with a low energy intake. However, there was no significant association with many expected predictors of waist gain such as physical activity. There were some associations between other lifestyle factors and change of WC by sex, age, level of education and across WC categories, but the associations differed across these groups. Conclusions: A $5 % increase of baseline WC occurred in a significant proportion of men and women over the 5-year period. Of the behavioural factors, poor diet quality was the key predictor of the $5 % increase of baseline WC in this cohort. The findings highlight the need to understand better the causal role of lifestyle in regard to increasing WC over time. Keywords Waist circumferenceWeight gain Obesity Predictors DietRecent reports have shown faster increases in waist circumference (WC) than BMI (1,2) , suggesting that the nature of excess body weight may be changing over time to one of greater central adiposity, rather than a more peripheral distribution of body fat (1,2) . This has significant implications, considering that WC measures the central or abdominal distribution of excess body fat, which appears to be strongly correlated with metabolic and cardiovascular risk (3,4) . However, little is known about the drivers of increases in WC. Few studies have examined the predictors of increasing weight in adults, and we are not aware of any that have examined a range of behavioural lifestyle factors potentially predictive of abdominal weight gain. Table 1 summarises those studies exploring predictors of change in BMI, weight and/or WC. The only study we were able to source that explored behavioural predictors of change in WC examined a limited selection of predictors in women (5) . Previous cross-sectional analyses have found lifestyle factors such as higher television (TV) viewing time and lower levels of physical activity to be associated with higher WC (6)(7)(8)(9) , and studies analysing predictors of gain in BMI/weight have found associations with factors such as higher TV viewing time and lower levels of physical activity (5,(10)(11)(12)(13)(14) . Sternfeld et al...

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Section: Discussionmentioning

confidence: 99%

Predictors of increasing waist circumference in an Australian population

Walls

Magliano

McNeil

et al. 2010

Public Health Nutr.

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“…Weight loss >5% is widely regarded to be clinically significant, 104 whereas a weight change <3% has been used to define weight maintenance. 105 Hence, the net weight change for the E-LITE self-directed intervention relates to the minimal clinically important difference in weight reduction. To preserve statistical power, no multiplicity adjustment will be made for secondary analyses.…”

Section: Sample Size and Data Interpretationmentioning

confidence: 99%

Evaluation of a culturally-adapted lifestyle intervention to treat elevated cardiometabolic risk of Latino adults in primary care (Vida Sana): A randomized controlled trial

Rosas

Xiao

et al. 2016

Contemporary Clinical Trials

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Latinos bear a disproportionate burden of the dual pandemic of obesity and diabetes. However, successful interventions addressing this disparity through primary care are lacking. To address this gap, the 5-year Vida Sana (Healthy Life) study tests a culturally adapted and technology-enhanced group-based Diabetes Prevention Program intervention in a randomized controlled trial with overweight/obese Latino adults who have metabolic syndrome and/or pre-diabetes. Eligible, consenting patients (n=186) from a large community-based multispecialty group practice in Northern California will be randomly assigned to receive the culturally-adapted intervention or usual care. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework guided the planned evaluations. The primary aim is to determine the effectiveness of the intervention (the "E" in RE-AIM). We hypothesize that the intervention will lead to a greater mean reduction in weight at 24 months (primary endpoint) vs. usual care. Secondary outcomes will include measures of cardiometabolic risk factors (e.g., blood pressure), psychosocial wellbeing (e.g., health-related quality of life), and behavior change (e.g., physical activity). The secondary aim is to evaluate the other RE-AIM dimensions using mixed methods: reach (e.g., participation rate of the target population), adoption (e.g., participating clinic and provider characteristics), implementation (e.g., intervention fidelity), and maintenance (e.g., sustainability in the practice setting). These findings have real word applicability with value to clinicians, patients, and other decision makers considering effective diabetes prevention programs for primary

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“…5 However, there are few studies in which incident strokes have been analyzed in combination with weight changes among Asian populations. 10 It is unclear whether smoking or common diseases such as diabetes mellitus can confound the association between body weight, ill health and mortality, 11 because smokers or those with serious medical conditions are likely to have a lower body weight and a higher risk for serious diseases. Moreover, the proportions of the subtypes of stroke in Asian populations are different from those among Caucasians.…”

Section: Introductionmentioning

confidence: 99%

Body mass index, weight change and risk of stroke and stroke subtypes: the Japan Public Health Center-based prospective (JPHC) study

et al. 2010

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Objective: The Japan Public Health Center-based prospective Study examined the association of body mass index (BMI) and weight change with incident stroke in Japanese individuals, for whom BMI levels are generally low. Methods: We used initial data from 1990 to 1994 and 5-year follow-up surveys from 1995 to 1999. We calculated weight change over a 5-year period for 32 847 men and 38 875 women, aged 45-74 years, with no history of cardiovascular disease or cancer. Subjects were followed from the 1995-1999 survey to the end of 2005, and hazard ratios of self-reported BMI levels and weight change for incident stroke were estimated using Cox's proportional hazard models adjusted for potential confounders. Results: During the follow-up period (median 7.9 years) there were 2019 incident strokes, including subtypes. Multivariableadjusted hazard ratios for all stroke events by BMI levels of 27.0-29.9 and X30 kg m -2 versus 23.0-24.9 kg m -2 were 1.09 (95% confidence interval 0.88, 1.36) and 1.25 (0.86, 1.84) in men (P for trend ¼ 0.22), and 1.29 (1.01, 1.65) and 2.16 (1.60, 2.93) in women (P for trend o0.001), respectively. A weight change of X10% in the previous 5 years was associated with total strokes and ischemic strokes in women. Conclusion: Higher BMI levels and a weight gain of X10% over 5 years were associated with an increased risk of stroke in women, whereas this association was weak in men.

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The definition of weight maintenance

Cited by 377 publications

References 66 publications

Predictors of increasing waist circumference in an Australian population

Predictors of increasing waist circumference in an Australian population

Evaluation of a culturally-adapted lifestyle intervention to treat elevated cardiometabolic risk of Latino adults in primary care (Vida Sana): A randomized controlled trial

Body mass index, weight change and risk of stroke and stroke subtypes: the Japan Public Health Center-based prospective (JPHC) study

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