Literature DB >> 10889790

Routes to obesity: phenotypes, food choices and activity.

J E Blundell1, J Cooling.   

Abstract

Gain in body weight over a number of years could be achieved through cumulative positive energy balances. These positive balances could come about through adjustments in the various components of energy expenditure or fuel utilization, together with shifts in food selection or eating patterns leading to adjustments in macronutrient intake. This means that many combinations of intake and expenditure could lead to a positive energy balance; these combinations can be called routes to body weight gain. However, these routes are difficult to trace by studying random samples of individuals. Previous investigations have found a clear association between high fat consumption and the occurrence of obesity, and although a high fat intake is a strong behavioural risk factor for weight gain, the relationship does not constitute a biological inevitability. Some normal-weight and lean individuals appear to eat a high-fat diet. To investigate reasons for this we have studied individuals initially defined by particular clusters of dietary characteristics related to fat and carbohydrate consumption. Habitual high-fat (HF) and low-fat (LF) consumers have been termed phenotypes. Various aspects of energy expenditure (physiological and behavioural) and energy intake were measured in these individuals with contrasting profiles. HF phenotypes had high intakes of fatty foods and an overall higher energy intake than LF. However, these groups of young adult males had similar BMIs and percentage body fat. The HF had a significantly higher resting metabolic rate (RMR) and a lower RQ, together with high plasma fasting leptin levels, and a higher sleeping heart rate. In HF individuals the physical activity level was somewhat lower and they had significantly more periods of sedentary behaviour than LF subjects. Although HF individuals appear to be more vulnerable to developing obesity, both phenotypes carry particular risk factors and protective factors for weight gain. The use of phenotypes has allowed the identification of different potential routes to weight gain. Different strategies are required to prevent age-related increase in body weight in these quite different individuals.

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Year:  2000        PMID: 10889790     DOI: 10.1017/s0007114500000933

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  33 in total

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Authors:  Yanjun Li; Jonathan R Gaillard; Tracey McLaughlin; Thorkild Ia Sørensen; Vipul Periwal
Journal:  Adipocyte       Date:  2015-04-21       Impact factor: 4.534

2.  The melanocortin antagonist AgRP (83-132) increases appetitive responding for a fat, but not a carbohydrate, reinforcer.

Authors:  Andrea L Tracy; Deborah J Clegg; Jeffrey D Johnson; T L Davidson; Stephen C Benoit
Journal:  Pharmacol Biochem Behav       Date:  2007-12-23       Impact factor: 3.533

3.  Managing the pandemic of obesity: siding with the fox or the hedgehog?

Authors:  Michael Myslobodsky; Loring J Ingraham
Journal:  Obes Facts       Date:  2009-12-18       Impact factor: 3.942

4.  Effects of postnatal overfeeding and fish oil diet on energy expenditure in rats.

Authors:  Yanyan Dai; Nan Zhou; Fan Yang; Shanshan Zhou; Lijun Sha; Jianping Wang; Xiaonan Li
Journal:  Pediatr Res       Date:  2017-10-04       Impact factor: 3.756

5.  Association of UCP-3 rs1626521 with obesity and stomach functions in humans.

Authors:  Andres Acosta; Michael Camilleri; Andrea Shin; Maria I Vazquez-Roque; Johanna Iturrino; Ian R Lanza; K Sreekumaran Nair; Duane Burton; Jessica O'Neill; Deborah Eckert; Paula Carlson; Adrian Vella; Alan R Zinsmeister
Journal:  Obesity (Silver Spring)       Date:  2015-03-07       Impact factor: 5.002

Review 6.  The biological control of voluntary exercise, spontaneous physical activity and daily energy expenditure in relation to obesity: human and rodent perspectives.

Authors:  Theodore Garland; Heidi Schutz; Mark A Chappell; Brooke K Keeney; Thomas H Meek; Lynn E Copes; Wendy Acosta; Clemens Drenowatz; Robert C Maciel; Gertjan van Dijk; Catherine M Kotz; Joey C Eisenmann
Journal:  J Exp Biol       Date:  2011-01-15       Impact factor: 3.312

7.  Questionnaire and laboratory measures of eating behavior. Associations with energy intake and BMI in a community sample of working adults.

Authors:  Simone A French; Nathan R Mitchell; Julian Wolfson; Graham Finlayson; John E Blundell; Robert W Jeffery
Journal:  Appetite       Date:  2013-10-02       Impact factor: 3.868

8.  Transcriptional profiling of chromosome 17 quantitative trait Loci for carbohydrate and total calorie intake in a mouse congenic strain reveals candidate genes and pathways.

Authors:  K Ganesh Kumar; Brenda K Smith Richards
Journal:  J Nutrigenet Nutrigenomics       Date:  2008-01-17

9.  Examining the effect of binge eating and disinhibition on compensatory changes in energy balance following exercise among overweight and obese women.

Authors:  Rebecca L Emery; Michele D Levine; John M Jakicic
Journal:  Eat Behav       Date:  2016-04-02

10.  Oral sensory phenotype identifies level of sugar and fat required for maximal liking.

Authors:  John E Hayes; Valerie B Duffy
Journal:  Physiol Behav       Date:  2008-05-02
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