Plenary Lecture 1: Dietary strategies for the prevention and treatment of obesity
- PMID: 19954563
- PMCID: PMC2841962
- DOI: 10.1017/S0029665109991674
Plenary Lecture 1: Dietary strategies for the prevention and treatment of obesity
Abstract
Obesity is a rapidly-growing public health problem that is related in part to the foods available in the eating environment. Properties of foods such as portion size and energy density (kJ/g) have robust effects on energy intake; large portions of energy-dense foods promote excess consumption and this effect starts in early childhood. Studies show, however, that in both adults and children these food characteristics can also be used strategically to moderate energy intake, as well as to improve diet quality. Dietary energy density can be reduced by increasing intake of water-rich foods such as vegetables and fruits. Their high water content allows individuals to eat satisfying portions of food while decreasing energy intake. Filling up at the start of a meal with vegetables or fruit and increasing the proportion of vegetables in a main course have been found to control hunger and moderate energy intake. Data from several clinical trials have also demonstrated that reducing dietary energy density by the addition of water-rich foods is associated with substantial weight loss even though participants eat greater amounts of food. Population-based assessments indicate that beginning in childhood there is a relationship between consuming large portions of energy-dense foods and obesity. These data suggest that the promotion of diets that are reduced in energy density should be an important component of future efforts to both prevent and treat obesity.
Conflict of interest statement
The author declares no conflict of interest.
Figures
); tertile 2, medium decrease ( − 0·5 to − 2·1kJ ( − 0·11 to − 0·51 kcal)/d;
); tertile 3, large decrease ( − 2·2 to − 9·8kJ ( − 0·52 to − 2·35 kcal)/d; □). Values are means with their standard errors represented by vertical bars. x,y,zMeans with unlike superscript letters were significantly different (P<0.05) using ANOVA with a general linear model adjustment for baseline values followed by a Tukey-Kramer adjustment for multiple comparisons. (From Ledikwe et al.(56).)References
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