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      Prevalence of and risk factors for binge eating behaviour in 6930 adults starting a weight loss or maintenance programme


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          Conflicting data are available on the prevalence of binge eating behaviour (BE) in individuals seeking to lose or maintain weight. The present study aimed to estimate the prevalence of and the risk factors for BE in a large sample of men and women starting a weight loss or maintenance programme.


          Cross-sectional study. BE was defined as a Binge Eating Scale (BES) score ≥18. The State-Trait Anxiety Inventory and the Italian Depression Questionnaire were used to assess anxiety and depression. Besides sex, age and BMI, marital status, educational level, smoking and physical activity were evaluated as potential risk factors for BE. Uni- and multivariable Poisson working regression models were used to estimate prevalence ratios (PR) and marginal probabilities.


          Nutritional research centre.


          Adults ( n 6930; 72 % women) with a median age of 46 years (range 18–81 years) were consecutively studied.


          BE prevalence in the pooled sample was 17 %. At multivariable analysis, being a woman (PR=2·70), smoking (PR=1·15) and increasing BMI (PR=1·05 for 1 kg/m 2 increase) were risk factors for BE. On the contrary, being older (PR=0·99 for 1-year increase), performing physical activity (PR=0·89) and being married (PR=0·88) were protective factors for BE. Anxiety and depression were more common in subjects with BE.


          BE is common in individuals seeking to lose or maintain weight. The prevalence of BE is higher in young obese women. However, BE is present also in men, elders and normal-weight subjects.

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          Most cited references40

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          Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio

          Background Cross-sectional studies with binary outcomes analyzed by logistic regression are frequent in the epidemiological literature. However, the odds ratio can importantly overestimate the prevalence ratio, the measure of choice in these studies. Also, controlling for confounding is not equivalent for the two measures. In this paper we explore alternatives for modeling data of such studies with techniques that directly estimate the prevalence ratio. Methods We compared Cox regression with constant time at risk, Poisson regression and log-binomial regression against the standard Mantel-Haenszel estimators. Models with robust variance estimators in Cox and Poisson regressions and variance corrected by the scale parameter in Poisson regression were also evaluated. Results Three outcomes, from a cross-sectional study carried out in Pelotas, Brazil, with different levels of prevalence were explored: weight-for-age deficit (4%), asthma (31%) and mother in a paid job (52%). Unadjusted Cox/Poisson regression and Poisson regression with scale parameter adjusted by deviance performed worst in terms of interval estimates. Poisson regression with scale parameter adjusted by χ2 showed variable performance depending on the outcome prevalence. Cox/Poisson regression with robust variance, and log-binomial regression performed equally well when the model was correctly specified. Conclusions Cox or Poisson regression with robust variance and log-binomial regression provide correct estimates and are a better alternative for the analysis of cross-sectional studies with binary outcomes than logistic regression, since the prevalence ratio is more interpretable and easier to communicate to non-specialists than the odds ratio. However, precautions are needed to avoid estimation problems in specific situations.
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            The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication.

            Little population-based data exist on the prevalence or correlates of eating disorders. Prevalence and correlates of eating disorders from the National Comorbidity Replication, a nationally representative face-to-face household survey (n = 9282), conducted in 2001-2003, were assessed using the WHO Composite International Diagnostic Interview. Lifetime prevalence estimates of DSM-IV anorexia nervosa, bulimia nervosa, and binge eating disorder are .9%, 1.5%, and 3.5% among women, and .3% .5%, and 2.0% among men. Survival analysis based on retrospective age-of-onset reports suggests that risk of bulimia nervosa and binge eating disorder increased with successive birth cohorts. All 3 disorders are significantly comorbid with many other DSM-IV disorders. Lifetime anorexia nervosa is significantly associated with low current weight (body-mass index or =40). Although most respondents with 12-month bulimia nervosa and binge eating disorder report some role impairment (data unavailable for anorexia nervosa since no respondents met criteria for 12-month prevalence), only a minority of cases ever sought treatment. Eating disorders, although relatively uncommon, represent a public health concern because they are frequently associated with other psychopathology and role impairment, and are frequently under-treated.
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              Who succeeds in maintaining weight loss? A conceptual review of factors associated with weight loss maintenance and weight regain.

              Weight loss is difficult to achieve and maintaining the weight loss is an even greater challenge. The identification of factors associated with weight loss maintenance can enhance our understanding for the behaviours and prerequisites that are crucial in sustaining a lowered body weight. In this paper we have reviewed the literature on factors associated with weight loss maintenance and weight regain. We have used a definition of weight maintenance implying intentional weight loss that has subsequently been maintained for at least 6 months. According to our review, successful weight maintenance is associated with more initial weight loss, reaching a self-determined goal weight, having a physically active lifestyle, a regular meal rhythm including breakfast and healthier eating, control of over-eating and self-monitoring of behaviours. Weight maintenance is further associated with an internal motivation to lose weight, social support, better coping strategies and ability to handle life stress, self-efficacy, autonomy, assuming responsibility in life, and overall more psychological strength and stability. Factors that may pose a risk for weight regain include a history of weight cycling, disinhibited eating, binge eating, more hunger, eating in response to negative emotions and stress, and more passive reactions to problems.

                Author and article information

                Public Health Nutr
                Public Health Nutr
                Public Health Nutrition
                Cambridge University Press (Cambridge, UK )
                11 May 2015
                January 2016
                : 19
                : 1
                : 71-77
                [1 ] International Center for the Assessment of Nutritional Status (ICANS), Department of Food, Environmental and Nutritional Sciences (DEFENS), University of Milan , Via Botticelli 21, 20133 Milan, Italy
                [2 ] Clinical Epidemiology Unit, Liver Research Center , Basovizza, Trieste, Italy
                [3 ] Department of Health Sciences, School of Medicine, University of Milan–Bicocca , Milan, Italy
                Author notes
                [* ] Corresponding author: Email simona.bertoli@ 123456unimi.it
                S1368980015001068 00106
                © The Authors 2015

                This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                : 05 December 2014
                : 19 February 2015
                : 06 March 2015
                Page count
                Figures: 1, Tables: 3, Pages: 7
                Research Papers
                Behavioural Nutrition

                Public health
                epidemiology,cross-sectional study,obesity,weight loss,binge eating,anxiety,depression
                Public health
                epidemiology, cross-sectional study, obesity, weight loss, binge eating, anxiety, depression


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