Treatment and prevention of obesity: what works, what doesn't work, and what might work

A scoping review of unintended harm associated with public health interventions: towards a typology and an understanding of underlying factors

OBJECTIVES

Unintended harm theory as related to public health interventions (PHI) is under developed, with harm evaluation and reporting often absent or incomplete. This review presents a typology for, and underlying factors linked to, PHI-associated unintended harm.

METHODS

This scoping review was conducted electronically and includes articles from 1992 to June of 2013. Out of 2,490 originally identified titles, 26 full-text articles were included that discussed unintended harm associated with PHI. An iterative data analysis process was utilized to identify both a typology and underlying factors associated with unintended harm.

RESULTS

A typology of PHI-associated unintended harm was identified: (1) physical; (2) psychosocial; (3) economic; (4) cultural and (5) environmental. Five underlying factors associated with PHI unintended harm emerged: (1) limited and/or poor quality evidence; (2) prevention of one extreme leads to another (boomerang effects); (3) lack of community engagement; (4) ignoring root causes; and (5) higher-income country PHI implementation in a lower- or middle-income country.

CONCLUSIONS

PHI planning and evaluation frameworks may benefit from the consideration and potential incorporation of the unintended harm typology and underlying factors.

Determinants of overweight in a cohort of Dutch children

BACKGROUND

To improve the effective prevention and treatment of obesity, it is important to focus on body weight (BW) development and its determinants during childhood.

OBJECTIVE

The aim of the present study was to investigate the effects of early development, parental and genetic variables, and behavioral determinants on overweight at 12 y.

DESIGN

In a Dutch cohort of 105 children, anthropometric measurements were conducted from birth until age 7 y. At age 12 y, anthropometric measurements were obtained again, as were measurements of body composition, leptin concentration, 3 polymorphisms, and physical activity, and the Three-Factor Eating Questionnaire was conducted. In addition, parental body mass indexes (BMIs, in kg/m2) and Three-Factor Eating Questionnaire scores were determined.

RESULTS

The children's mean (+/-SD) BMI at 12 y was 19.0 +/- 2.6, and 15.2% were classified as overweight. From the first year of life, BMI tracked significantly with BMI at age 12 y (r = 0.24, P < 0.05). Linear regression analyses showed that a rapid increase in BW during the first year of life, a high BMI of the father, and a high dietary restraint score of the mother were significantly associated with overweight at age 12 y (P < 0.05). No significant genetic relation was observed. In addition, overweight was positively associated with dietary restraint of the child, and percentage body fat was negatively associated with the child's activity score (P < 0.05).

CONCLUSIONS

In this homogeneous cohort of normal-weight to moderately overweight children, tracking of BMI during childhood took place from the first year of life. Overweight at age 12 y was predicted by an early rapid increase in BW and parental influences. Overweight during childhood may be maintained or even promoted by a high dietary restraint score and low physical activity.

Does weight loss prognosis depend on genetic make-up?

The prevalence of obesity is rising throughout the world. Indeed, obesity has reached epidemic proportions in many developed and transition countries. Obesity is a complex disease with multifactorial origin, which in many cases appears as a polygenic condition affected by environmental factors. Treatment or prevention of obesity is necessary to reverse or avoid the onset of type 2 diabetes and other obesity-related diseases. Weight loss is a complex trait that depends on many environmental, behavioural and genetic influences. An effective programme for the management of overweight and obesity must take into account all of these factors. Individual responses to weight loss interventions vary widely and reliable predictors of successful slimming are poorly understood. The individual genetic make-up participating in energy expenditure regulation, appetite control, lipid metabolism and adipogenesis, have been reported to affect the risk of treatment failure in some subjects. In addition, the genotype could also help to predict the changes in lipid profile, cardiovascular risk factors and insulin sensitivity in response to weight loss. Herein, the current evidence from human studies that support the existence of a genetic component and the participation of different polymorphisms in the prognosis of weight loss induced by interventions leading to a negative energy balance are reviewed.