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Original Article

The Response to Long-Term Overfeeding in Identical Twins

Claude Bouchard, Ph.D., Angelo Tremblay, Ph.D., Jean-Pierre Després, Ph.D., André Nadeau, M.D., Paul J. Lupien, M.D., Ph.D., Germain Thériault, M.D., Jean Dussault, M.D., Sital Moorjani, Ph.D., Sylvie Pinault, M.D., and Guy Fournier, B.Sc.

N Engl J Med 1990; 322:1477-1482May 24, 1990

Abstract
Abstract

We undertook this study to determine whether there are differences in the responses of different persons to long-term overfeeding and to assess the possibility that genotypes are involved in such differences. After a two-week base-line period, 12 pairs of young adult male monozygotic twins were overfed by 4.2 MJ (1000 kcal) per day, 6 days a week, for a total of 84 days during a 100-day period. The total excess amount each man consumed was 353 MJ (84,000 kcal).

During overfeeding, individual changes in body composition and topography of fat deposition varied considerably. The mean weight gain was 8.1 kg, but the range was 4.3 to 13.3 kg. The similarity within each pair in the response to overfeeding was significant (P<0.05) with respect to body weight, percentage of fat, fat mass, and estimated subcutaneous fat, with about three times more variance among pairs than within pairs (r ≈ 0.5). After adjustment for the gains in fat mass, the within-pair similarity was particularly evident with respect to the changes in regional fat distribution and amount of abdominal visceral fat (P<0.01), with about six times as much variance among pairs as within pairs (r ≈ 0.7).

We conclude that the most likely explanation for the intrapair similarity in the adaptation to long-term overfeeding and for the variations in weight gain and fat distribution among the pairs of twins is that genetic factors are involved. These may govern the tendency to store energy as either fat or lean tissue and the various determinants of the resting expenditure of energy. (N Engl J Med 1990; 322:1477–82.)

Media in This Article

Figure 1Similarity within Pairs with Respect to Changes in Body Weight in 12 Pairs of Male Twins in Response to 100 Days of Overfeeding.
Figure 2Similarity within Pairs with Respect to Changes in Abdominal Visceral Fat in 12 Pairs of Male Twins in Response to 100 Days of Overfeeding after Adjustment for Gain in Fat Mass.
Article

THERE are large differences among persons of a given age and sex in body fat content and regional distribution of body fat. The reasons for such differences are not known, but it is increasingly recognized that inheritance is a factor in obesity and regional fat distribution.

One line of research studies biologic relatives and relatives by adoption and relies on the tools of genetic epidemiology to estimate the genetic and nongenetic sources of variation in body fat content and regional fat distribution.1 , 2 Another, more experimental, approach requires the study of the differences between people in the response to a well-defined positive or negative energy balance. This strategy allows the amount of weight gained or lost to be determined, as well as the physiologic and biochemical correlates of the response to the change in energy balance. Among studies of the adaptation to short-term and long-term overfeeding, significant differences between people have been found in the response to a regimen of overfeeding.3 4 5 Such differences were clearly evident in the Vermont study of overfeeding reported by Sims and his colleagues more than 20 years ago.5 6 7

We have extended this work by studying the effects of a positive or negative energy balance on pairs of identical twins.8 , 9 In these studies, both members of each pair of twins undergo exactly the same treatment in order to determine not only the extent of variation in the individual responses to the experimental situation but also the components of variance within pairs and between pairs, thereby permitting an assessment of the role of inherited characteristics in the response. We previously reported the results of a short-term (22-day) study of overfeeding conducted with six pairs of monozygotic twins.9 10 11 12 13 14 The results of that experiment were not conclusive, however, partly because the effect of treatment was small. Therefore, we undertook this long-term study of overfeeding to clarify some of the issues still in doubt. Twelve pairs of male monozygotic twins were overfed by 4.2 MJ (1000 kcal) per day, 6 days a week, over a period of 100 days. We describe the changes in body mass, total body fat, and fat distribution during the period of overfeeding, in which a total energy excess of 353 MJ (84,000 kcal) was administered.

Methods

Subjects

We studied 24 sedentary young men (mean [±SD] age, 21±2 years) living in the province of Quebec. Each man gave written consent for participation in this study, which was approved by the Laval University Medical Ethics Committee and the Office for Protection from Research Risks of the National Institutes of Health, Bethesda, Md. These men constituted 12 pairs of identical twins. The youngest pair was 19 years of age, and the oldest pair was 27. The twins had been reared together and had been living together before this study.

The monozygosity of the twins was established on the basis of a questionnaire, their physical appearance, and the similarity of 12 polymorphic red-cell antigens and enzymes, the A, B, and C loci of the HLA-antigen system, and 10 polymorphic adipose-tissue proteins visualized by two-dimensional gel electrophoresis. None of the men had a history of recent illness, obesity, hypertension, diabetes, hyperlipidemia, or endocrinopathy, and each had a normal physical examination and normal fasting serum glucose, triglyceride, and cholesterol concentrations. Men whose parents were obese or had diabetes or lipid disorders were not accepted into the study.

Four pairs of twins were studied at a time over a period of 18 months: one subgroup starting in early August, a second in February, and the third the following August. The results were similar in all three subgroups. The men were housed in a closed section of a dormitory on the campus of Laval University and were under 24-hour supervision by members of the project staff living with them. Each man stayed in the unit for 120 consecutive days — 14 days for base-line testing, 3 days for testing before the period of overfeeding, 100 days for the period of overfeeding, and 3 days for testing after the period of overfeeding. During the base-line testing, body weight was measured daily, skin-fold thickness was measured at 10 sites five times, and body density was measured three times by underwater weighing.

The men were not allowed to drink alcoholic beverages during the study. Five of the pairs of twins were light smokers, but smoking was not permitted during the study. We believe that these men reduced their frequency of smoking to a few cigarettes a day, but did not stop entirely.

Base-Line Test Period

During the base-line period, the men ate freely in a special dining room. The food was prepared by university personnel but was put aside for the men by the dietitians involved in the study. All foods selected by the men were recorded and weighed. All foods not eaten were weighed separately, and their weight was subtracted from that of the food selected so that the net intake could be calculated. The nutrient composition and energy content of the food were derived from a computerized version of the Canadian food-composition tables.15 , 16 Each man's habitual daily energy intake under conditions of stable body weight and body composition was calculated from the 14-day record of food intake and was generally based on the entries for the last 12 days, the variations in body weight, and the changes in fat mass or fat-free mass, if any, determined from the body-density measurements. The energy content of body fat was assumed to be 37.8 MJ (9300 kcal) per kilogram, whereas that of lean tissue was assumed to be 4.2 MJ (1020 kcal) per kilogram.17 The body energy content was the sum of these two components. The average nutrient composition of the food eaten during the baseline period was 52±6 percent carbohydrate, 34±6 percent lipid, and 14±6 percent protein.

Testing before and after the Overfeeding Period

On the first day of the three-day test period before the overfeeding period, we measured the resting metabolic rate and the thermic effect of food. On the third day, underwater weighing, biopsies of adipose tissue, and exercise-tolerance testing were performed. About five days before the overfeeding period, a CT scan of the abdomen was performed. The same studies were repeated during the three-day test period after the overfeeding period.

Overfeeding Period

After the base-line period, the men were fed a diet containing 4.2 MJ ( 1000 kcal) per day more than their established base-line energy intake from food, 6 days a week for 100 days. On the seventh day of each week they consumed the base-line number of calories. They were thus overfed for 84 of the 100 days, the total excess energy intake being 353 MJ or 84,000 kcal. The food consumed each day had the following prescribed nutrient composition: 50 percent carbohydrate, 35 percent fat, and 15 percent protein. The men ate three meals per day plus an evening snack tailored to complete the daily prescription for energy intake.

Physical activity was limited during the entire study; the daily schedule included such activities as reading, playing video games, playing cards, and watching television, as well as an outdoor walk for 30 minutes per day. The men were occasionally taken as a group to a play or a movie. They were carefully supervised at all times during all activities, and as far as we could ascertain their compliance with the regimen of dietary intake and the limitations on their activities was perfect. During this period, body weight was measured daily, skin-fold thickness every 5 days, and waist and hip circumference every 25 days.

Body Composition and Regional Fat Distribution

Blood pressure, pulse rate, and body weight were measured (the latter with the men wearing light exercise shorts) each morning before breakfast. The body-mass index was calculated as the body weight (in kilograms) divided by the height (in meters squared). Body density was determined by underwater weighing,18 and fat mass and fat-free mass were calculated with a standard equation.19 The volume of air remaining in the lungs was determined while each man was in the water tank, and the pulmonary residual volume was measured by the helium-dilution technique.20 The data on body weight represent the mean measurements of three days, in each case the day on which the underwater weighing was done and the days before and after. The skin-fold thickness was measured at 10 sites, as were the waist and hip circumferences, according to the procedures recommended at the Airlie Conference.21 The ratio of the sum of the skin-fold—thickness values for the trunk (subscapular, suprailiac, abdominal, midaxillary, and chest) to the sum of the values for the limbs (biceps, triceps, front midthigh, suprapatellar, and medial calf) was used as one estimate of the regional subcutaneous fat distribution.22 The ratio of the waist to the hip circumference was used as another estimate of regional fat distribution.21 For all the anthropometric measurements, two measurements were always made, and the mean was used if the difference between the two measurements was less than 5 percent. If the difference was 5 percent or more, a third measurement was made, and the mean of the two most similar values was used.21 We also determined the mean adipose-cell mass in the abdominal (umbilicus level) and femoral (midthigh) areas,23 using data on isolated fat cells obtained by collagenase digestion and the density of triolein to convert the adipose-cell volume to mass.

CT scanning was performed before and after the overfeeding period with a Siemens Somatom DRH scanner (Erlangen, Federal Republic of Germany). The men were examined in the supine position with their arms stretched above their heads.24 The scans were obtained at the pubic symphysis and at the levels of the disks between the fourth and fifth lumbar vertebrae and between the eighth and ninth thoracic vertebrae. The attenuation interval used in the quantification of the areas of adipose tissue was −30 to −190 Hounsfield units. The total areas of abdominal and abdominal visceral fat were calculated by delineating their surfaces with a computerized pen. The abdominal visceral fat was defined by drawing a line on the inside of the muscle wall surrounding the abdominal cavity. The area of subcutaneous abdominal fat was computed as the total abdominal fat minus the visceral fat. The sum of the three trunk scans was used as an estimate of the response of the trunk fat to overfeeding.

The reproducibility of all the measurements of fat areas by anthropometry, studies of body composition, and CT scanning has been determined by several investigators and is known to be quite high when performed by the same observer, as in this study. The intraclass reliability coefficients for the variables reported were generally above 0.9.21 , 24 , 25

Statistical Analysis

The study design allowed testing for the presence of similarities within pairs of twins in the response to long-term overfeeding. The effects of overfeeding and the interactions between genotype and overfeeding were assessed with a two-way analysis of variance for repeated measures on one factor (time). The twins were considered nested within the pair, whereas the treatment effect was defined as a fixed variable. The intraclass correlation coefficient for the changes brought about by overfeeding was computed from the between-pairs and within-pair means of squares.26 This coefficient provides a quantitative estimate of the similarity within pairs in the response to overfeeding. An intra-class correlation coefficient close to 1.0 would indicate a perfect within-pair resemblance in response to overfeeding, whereas a coefficient close to zero would imply that there was no within-pair resemblance in response to the treatment. Similarly, a high F ratio indicates a high ratio of the variance between pairs to the variance within pairs in response to overfeeding, whereas a low F ratio (close to 1) indicates that the variances in response between and within pairs of twins are comparable. In some analyses, the results were adjusted for gains in total fat mass. These adjustments were performed by regression of the variable to be adjusted on the gain in fat mass after overfeeding, with the 24 subjects considered as unrelated persons. P values ≤0.05 were considered statistically significant.

Results

Body weight increased significantly (P<0.001) during overfeeding, the average gain being 8.1 kg (Table 1Table 1Effect of 100 Days of Overfeeding in 12 Pairs of Male Twins and Measures of the Similarity within Pairs with Respect to the Absolute Response to Overfeeding.*). Body composition also changed significantly. Fat mass and fat-free mass increased, but the gain in adipose tissue was greater than the increase in lean tissue, as shown by the changes in the ratio of fat mass to fat-free mass, which increased from 0.13 to 0.22 (P<0.001). The sum of the skin-fold—thickness measurements, used to estimate the changes in the amount of subcutaneous fat, increased from 76 to 129 mm, or about 70 percent (P<0.001). The mean resting heart rate increased from 58 to 63 beats per minute by the end of the overfeeding period (P<0.01). Systolic blood pressure was unaltered, but diastolic blood pressure increased from 66 to 70 mm Hg (P<0.05; data not shown).

There were considerable differences between persons with respect to changes in body weight and body composition with overfeeding. Although the mean increase in body weight was 8.1 kg, the standard deviation was 2.4 kg and the range 4.3 to 13.3 kg. The individual differences in body weight and body composition as a result of overfeeding, however, were not distributed randomly among the 24 men. This is demonstrated by the similarity of the absolute changes within pairs shown in Table 1. The F ratios of the variances between pairs to the variances within pairs were about 3, and the intraclass correlation coefficients computed on the basis of the changes resulting from overfeeding were clustered around 0.50. The within-pair similarity was slightly less for fat-free mass (about 0.4). The within-pair similarity for the changes in body weight is illustrated in Figure 1Figure 1Similarity within Pairs with Respect to Changes in Body Weight in 12 Pairs of Male Twins in Response to 100 Days of Overfeeding..

Regional fat distribution was estimated by several methods (Table 2Table 2Effect of 100 Days of Overfeeding on Regional Fat Distribution in 12 Pairs of Male Twins and the Similarity within Pairs in Response to Overfeeding.*). The amount of subcutaneous fat, as estimated on the basis of skin-fold thickness, increased on both the trunk and limbs, but more so on the trunk (about 85 percent vs. 50 percent). Accordingly, the trunk-to-limb ratio of skin-fold thickness increased from 1.26 to 1.60 (P<0.001). Both the waist and the hip circumference increased significantly, but the ratio of the waist to the hip circumference also increased (P<0.001), indicating that more fat was gained at the waist level than at the hip level. The within-pair similarity in the response to overfeeding was generally significant with respect to the changes in anthropometric indicators of regional fat distribution, but not with respect to abdominal and femoral fat-cell mass. However, when the data were adjusted for the increase in total fat mass, there was a strong indication that trunk fat and peripheral fat, as well as the descriptors of regional fat distribution — namely, the trunk-to-limb skin-fold—thickness ratio (F = 6.92, P<0.001), the waist-to-hip ratio (F = 6.10, P<0.01) and the ratio of abdominal-to-femoral fat-cell mass (F = 3.11, P<0.05) — were all characterized by a significant similarity within pairs in the response to overfeeding.

The effects of overfeeding on abdominal and trunk fat as measured by CT are shown in Table 3Table 3Effect of 100 Days of Overfeeding on CT-Assessed Trunk and Abdominal Fat in 12 Pairs of Male Twins and the Similarity within Pairs in Response to Overfeeding.*. Overfeeding increased the adipose-tissue surface areas in all the subcutaneous and visceral or deep anatomical sections (P<0.001). Again, however, there were considerable differences between persons with respect to changes in the CT-assessed fat areas, as shown by the percent changes of abdominal visceral fat. In this case, the responses ranged from about zero to an increase of more than 200 percent (data not shown). The within-pair similarity in response was significant with respect to the CT-assessed abdominal visceral fat (P<0.05). When the changes in CT-assessed fat were adjusted for the gain in total fat mass, however, the similarity within pairs became significant with respect to all CT trunk and abdominal measurements. The resemblance was greatest with respect to abdominal visceral fat. The within-pair resemblance in the response of visceral fat, after adjustment for the gains in total body fat, is shown in Figure 2Figure 2Similarity within Pairs with Respect to Changes in Abdominal Visceral Fat in 12 Pairs of Male Twins in Response to 100 Days of Overfeeding after Adjustment for Gain in Fat Mass..

We explored the relation among the changes in the various components of body fat by calculating the correlation coefficients of the absolute response values for each of the 24 men (Table 4Table 4Correlations between the Gains in Body Fat, Trunk Fat, and Abdominal Visceral Fat in the 12 Pairs of Male Twins during the Period of Overfeeding.*). As the correlations suggest, the common variance (r2 × 100) between the gains in body weight or fat mass and the gains in fat on the trunk varied from about 40 to 60 percent. On the other hand, the gains in body weight or fat mass were not significantly correlated with the gains in the two indicators of changes in regional fat distribution —the trunk-to-limb ratio of skin-fold thickness and the ratio of waist to hip circumference. Finally, only the changes in the waist circumference and in the ratio of the waist to the hip circumference were significantly correlated with the gains in the CT-assessed abdominal visceral fat, but the common variance reached only 20 to 30 percent. The same trends were found when the correlations were computed with the mean changes observed for each pair of twins (12 sets of scores) instead of the 24 individual sets of scores.

There were interesting relations between the gains in the ratio of fat mass to fat-free mass during the overfeeding period and the gains in body weight (r = 0.61, P<0.01), the sum of the five trunk skin-fold—thickness measurements (r = 0.62, P<0.001), and the waist circumference (r = 0.66, P<0.001) (data not shown). There was no correlation, however, between the changes in the ratio of fat mass to fat-free mass and the changes in abdominal visceral fat (r = 0.21) or overall regional fat distribution, as assessed by the trunk-to-limb ratio of skin-fold thickness (r = 0.23) or the waist-to-hip ratio (r = 0.37).

Discussion

Three major components of the obese state can be identified when obesity is considered from the perspective of health — namely, excess total body fat, excess trunk fat or abdominal subcutaneous fat, and excess abdominal visceral fat.27 These three components were recognized as important at a recent workshop presented by the National Institutes of Health on the clinical implications of regional fat distribution.28 The results reported here allow assessment of the response of each component to long-term overfeeding.

We found wide differences between individuals in the response to long-term overfeeding. Such heterogeneity was found when only 12 genotypes were exposed to the regimen of positive energy balance. The heterogeneity would probably have been greater if a large number of unrelated subjects had been studied. The changes in body weight, body composition, trunk fat, and visceral-fat deposition varied between the high and the low weight gainers by at least threefold. Individual differences in weight gain have been found during overfeeding before,3 4 5 , 9 , 10 , 29 30 31 but this study demonstrates them even more clearly, because the degree of overfeeding was identical for each man and the duration was long enough to induce changes in body composition and regional fat distribution reliable beyond any errors in measurement. Thus, a comparable surplus intake of energy over a relatively long period does not cause identical responses with respect to body mass, body composition, or regional fat distribution in sedentary young men.

The average gain in fat mass was 5.4 kg or about 210 MJ (52,220 kcal), whereas the gain in fat-free mass was 2.7 kg or approximately 11.5 MJ (2754 kcal). On average, about 121 MJ (29,000 kcal) did not appear as weight gain when constants were used to convert tissue gains into energy equivalents,17 and presumably this energy was dissipated in some way. One third of the weight gained by the group as a whole was in the form of fat-free mass, a proportion comparable with that reported previously.4 , 9 The man who gained the most weight (13.3 kg) had no evidence of energy dissipation by any mechanism, whereas in the man who gained the least weight (4.3 kg) only about 40 percent of the extra calories were deposited as body tissues. The men who gained more fat than lean tissue tended to gain more weight and to gain more fat in the truncal—abdominal area. On the basis of the correlations we found, 37 to 44 percent of the gains in weight or trunk fat were accounted for by the increments in the proportion of fat and lean tissues.

When the results for all 24 men were analyzed, the correlations between the total energy ingested during the 100-day period (including the 84,000-kcal surplus) and the gains in body weight (r = 0.26), fat mass (r = 0.26), sum of 10 skin-fold—thickness measurements (r = 0.25), and abdominal visceral fat (r = −0.31) were not statistically significant. In addition, the increases in total body fat were correlated with the gains in truncal subcutaneous fat but not with the changes in the distribution of regional fat and particularly abdominal visceral fat (Table 4). In other words, the accumulation of visceral fat cannot be predicted from the increase in body mass or body fat induced by long-term overfeeding. These results demonstrate that people rely on different strategies to cope with long-term overfeeding, even in terms of tissue gained and sites of deposition.

The alterations in body weight, body composition, and body energy content during overfeeding were characterized by about three times more variance between the pairs of twins than within the pairs. The similarity in the response within pairs was a little less than that reported with respect to body weight and indexes of body composition in one study of six pairs of monozygotic twins who were overfed for 22 days.9 , 10 The within-pair similarity in the changes during overfeeding was higher with respect to anthropometric indicators of regional fat distribution and abdominal visceral fat after adjustment for the gains in total fat mass. There was a significant resemblance within pairs with respect to the increase in the ratio of abdominal-to-femoral fat-cell mass, but only when individual differences in total fat increases were taken into account. In view of the implications of truncal—abdominal obesity and excessive abdominal visceral fat for insulin metabolism and plasma lipid and lipoprotein levels, and their relations to mortality and morbidity,28 , 32 33 34 35 the findings that some persons were more prone than others to store fat on the trunk, in the abdominal cavity, or both are of considerable clinical interest.

The most likely explanation for the resemblance between identical twins in the response to overfeeding is that a person's genotype is an important determinant of adaptation to a sustained energy surplus. Since the excess energy intake involved the same composition of macronutrients and was fixed at 84,000 kcal for all the men, and since they kept the same relatively sedentary schedule during the period of overfeeding, differences in the efficiency of weight gain could result either from individual variation in the preferential storage of energy as fat or lean tissue (as shown here) or from variation in the components of energy expenditure during rest.

Our results strongly support the view that there are individual differences in the tendency toward obesity and in the distribution of body fat, and they suggest that these differences are partly related to undetermined genetic characteristics.

Supported by a grant (DK 34624) from the National Institutes of Health.

We are indebted to Jacque Bouillon, M.Sc., Suzie Hamel, M.Sc., Brigitte Zement, M.Sc., Marcel R. Boulay, Ph.D., Maryse Lebrun, B.Sc., Martine Marcotte, M.Sc., Claude Leblanc, M.Sc., Monique Chagnon, A.R.T., Josée Lapointe, Henri Bessette, Gilles Bouchard, and Serge Carbonneau for their contributions to the study.

Source Information

From the Physical Activity Sciences Laboratory, Laval University (C.B., AT., J.-P.D., G.T., G.F.), and the Diabetes Research Unit (A.N.), the Lipid Research Clinic (P.J.L., S.M.), the Ontogenetic and Molecular Genetic Research Unit (J.D.), and the Department of Radiology (S.P.), Laval University Medical Center, Ste. Foy, Quebec, Canada. Address reprint requests to Dr. Bouchard at the Physical Activity Sciences Laboratory, Laval University, Ste. Foy, PQ G1K 7P4, Canada.

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Citing Articles

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    Mindy E. Hoffmann, Sarah M. Rodriguez, Dinah M. Zeiss, Kelley N. Wachsberg, Robert F. Kushner, Lewis Landsberg, Robert A. Linsenmeier. (2012) 24-h Core Temperature in Obese and Lean Men and Women. Obesity
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    Samuel J. Kallus, Lawrence J. Brandt. (2011) The Intestinal Microbiota and Obesity. Journal of Clinical Gastroenterology1
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    Xihui Xu, Jun Ren. (2011) Unmasking the Janus Faces of Autophagy in Obesity-Associated Insulin Resistance and Cardiac Dysfunction. Clinical and Experimental Pharmacology and Physiologyno-no
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    Susanne F. Meisel, Catherine Walker, Jane Wardle. (2011) Psychological Responses to Genetic Testing for Weight Gain: A Vignette Study. Obesity
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    J Naukkarinen, A Rissanen, J Kaprio, K H Pietiläinen. (2011) Causes and consequences of obesity: the contribution of recent twin studies. International Journal of Obesity
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    Joerg Koenigstorfer, Walter F.J. Schmidt. (2011) Effects of exercise training and a hypocaloric diet on female monozygotic twins in free-living conditions. Physiology & Behavior 104:5, 838-844
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    Maarit Ahtiainen, Eija Pöllänen, Paula H. A. Ronkainen, Markku Alen, Jukka Puolakka, Jaakko Kaprio, Sarianna Sipilä, Vuokko Kovanen. (2011) Age and estrogen-based hormone therapy affect systemic and local IL-6 and IGF-1 pathways in women. AGE
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    K H Pietiläinen, S E Saarni, J Kaprio, A Rissanen. (2011) Does dieting make you fat? A twin study. International Journal of Obesity
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    Ina Garthe, Truls Raastad, Jorunn Sundgot-Borgen. (2011) Long-term effect of nutritional counselling on desired gain in body mass and lean body mass in elite athletes. Applied Physiology, Nutrition, and Metabolism 36:4, 547-554
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    F. Johnson, A. Mavrogianni, M. Ucci, A. Vidal-Puig, J. Wardle. (2011) Could increased time spent in a thermal comfort zone contribute to population increases in obesity?. Obesity Reviews 12:7, 543-551
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    Shwetha Ramachandrappa, I. Sadaf Farooqi. (2011) Genetic approaches to understanding human obesity. Journal of Clinical Investigation 121:6, 2080-2086
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    Magnus Hølmo Fasting, Tom Ivar Lund Nilsen, Turid Lingaas Holmen, Torstein Vik. (2011) Changes in parental weight and smoking habits and offspring adiposity: Data from the HUNT-study. International Journal of Pediatric Obesity 6:2-2, e399-e407
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    Paul T. Williams. (2011) Attenuated Inheritance of Body Weight by Running in Monozygotic Twins. Medicine & Science in Sports & Exercise1
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    2011. References. , 283-360.
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    Roger Cooke. (2011) The role of the myosin ATPase activity in adaptive thermogenesis by skeletal muscle. Biophysical Reviews 3:1, 33-45
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    Qinghua He, Pingping Ren, Xiangfeng Kong, Yongning Wu, Guoyao Wu, Peng Li, Fuhua Hao, Huiru Tang, François Blachier, Yulong Yin. (2011) Comparison of serum metabolite compositions between obese and lean growing pigs using an NMR-based metabonomic approach. The Journal of Nutritional Biochemistry
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    Motonaka Kuroda, Masanori Ohta, Tatsuya Okufuji, Chieko Takigami, Masafumi Eguchi, Hitomi Hayabuchi, Masaharu Ikeda. (2011) Frequency of Soup Intake Is Inversely Associated with Body Mass Index, Waist Circumference, and Waist-to-Hip Ratio, but Not with Other Metabolic Risk Factors in Japanese Men. Journal of the American Dietetic Association 111:1, 137-142
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    P. Russo, F. Lauria, A. Siani. (2010) Heritability of body weight: Moving beyond genetics. Nutrition, Metabolism and Cardiovascular Diseases 20:10, 691-697
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    Paula H. A. Ronkainen, Eija Pöllänen, Markku Alén, Reino Pitkänen, Jukka Puolakka, Urho M. Kujala, Jaakko Kaprio, Sarianna Sipilä, Vuokko Kovanen. (2010) Global gene expression profiles in skeletal muscle of monozygotic female twins discordant for hormone replacement therapy. Aging Cell 9:6, 1098-1110
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    M Rosenbaum, R L Leibel. (2010) Adaptive thermogenesis in humans. International Journal of Obesity 34, S47-S55
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    C. Ciangura, E. Touizer, A. Basdevant. (2010) Qui est obèse ? Pourquoi ? Conséquences clinique et thérapeutique. Journal de Chirurgie Viscérale 147:5, S4-S9
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    J. P. Block, A. Chandra, K. D. McManus, W. C. Willett. (2010) Point-of-Purchase Price and Education Intervention to Reduce Consumption of Sugary Soft Drinks. American Journal of Public Health 100:8, 1427-1433
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    Bryan Hanley, Jean Dijane, Mary Fewtrell, Alain Grynberg, Sandra Hummel, Claudine Junien, Berthold Koletzko, Sarah Lewis, Harald Renz, Michael Symonds, Marjan Gros, Lucien Harthoorn, Katherine Mace, Fiona Samuels, Eline M. van Der Beek. (2010) Metabolic imprinting, programming and epigenetics – a review of present priorities and future opportunities. British Journal of Nutrition 104:S1, S1-S25
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    M. Lehtovirta, K. H. Pietiläinen, E. Levälahti, K. Heikkilä, L. Groop, K. Silventoinen, M. Koskenvuo, J. Kaprio. (2010) Evidence that BMI and type 2 diabetes share only a minor fraction of genetic variance: a follow-up study of 23,585 monozygotic and dizygotic twins from the Finnish Twin Cohort Study. Diabetologia 53:7, 1314-1321
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    Lillian Cuppari, Talat Alp Ikizler. (2010) Energy Balance in Advanced Chronic Kidney Disease and End-Stage Renal Disease. Seminars in Dialysis 23:4, 373-377
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    Leila Azarbad, Linda Gonder-Frederick. (2010) Obesity in Women. Psychiatric Clinics of North America 33:2, 423-440
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    A Beyerlein, A M Toschke, R von Kries. (2010) Risk factors for childhood overweight: shift of the mean body mass index and shift of the upper percentiles: results from a cross-sectional study. International Journal of Obesity 34:4, 642-648
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    D. H. McGibbon. 2010. Subcutaneous Fat. , 1-49.
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    Anke Hinney, Carla I. G. Vogel, Johannes Hebebrand. (2010) From monogenic to polygenic obesity: recent advances. European Child & Adolescent Psychiatry 19:3, 297-310
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    Yasutomi Kamei, Takayoshi Suganami, Tatsuya Ehara, Sayaka Kanai, Koji Hayashi, Yuji Yamamoto, Shinji Miura, Osamu Ezaki, Masaki Okano, Yoshihiro Ogawa. (2010) Increased Expression of DNA Methyltransferase 3a in Obese Adipose Tissue: Studies With Transgenic Mice. Obesity 18:2, 314-321
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    L Rigoli, C Munafò, C Di Bella, A Salpietro, V Procopio, C Salpietro. (2010) Molecular analysis of the CART gene in overweight and obese Italian children using family-based association methods. Acta Paediatrica
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    Ellen Schur, Carolyn Noonan, Janet Polivy, Jack Goldberg, Dedra Buchwald. (2009) Genetic and environmental influences on restrained eating behavior. International Journal of Eating Disorders 42:8, 765-772
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    Tomoaki Matsuo, Yoshio Nakata, Yasutomi Katayama, Motoyuki Iemitsu, Seiji Maeda, Tomohiro Okura, Maeng-Kyu Kim, Hiroyuki Ohkubo, Kikuko Hotta, Kiyoji Tanaka. (2009) PPARG Genotype Accounts for Part of Individual Variation in Body Weight Reduction in Response to Calorie Restriction. Obesity 17:10, 1924-1931
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    Shaoyan Zhang, Christos Tjortjis, Xiaojun Zeng, Hong Qiao, Iain Buchan, John Keane. (2009) Comparing data mining methods with logistic regression in childhood obesity prediction. Information Systems Frontiers 11:4, 449-460
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    MK Song, MJ Rosenthal, AM Song, K Uyemura, H Yang, ME Ament, DT Yamaguchi, EM Cornford. (2009) Body weight reduction in rats by oral treatment with zinc plus cyclo-(His-Pro). British Journal of Pharmacology 158:2, 442-450
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    A. Singh, M. Wirtz, N. Parker, M. Hogan, J. Strahler, G. Michailidis, S. Schmidt, A. Vidal-Puig, S. Diano, P. Andrews, M. D. Brand, J. Friedman. (2009) Leptin-mediated changes in hepatic mitochondrial metabolism, structure, and protein levels. Proceedings of the National Academy of Sciences 106:31, 13100-13105
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    Takeshi Inagaki, Makoto Tachibana, Kenta Magoori, Hiromi Kudo, Toshiya Tanaka, Masashi Okamura, Makoto Naito, Tatsuhiko Kodama, Yoichi Shinkai, Juro Sakai. (2009) Obesity and metabolic syndrome in histone demethylase JHDM2a-deficient mice. Genes to Cells 14:8, 991-1001
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    Dara P. Schuster. (2009) Changes in physiology with increasing fat mass. Seminars in Pediatric Surgery 18:3, 126-135
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    Robert Murray, Michelle Battista. (2009) Managing the Risk of Childhood Overweight and Obesity in Primary Care Practice. Current Problems in Pediatric and Adolescent Health Care 39:6, 146-165
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    A. Jonsson, F. Renström, V. Lyssenko, E. C. Brito, B. Isomaa, G. Berglund, P. M. Nilsson, L. Groop, P. W. Franks. (2009) Assessing the effect of interaction between an FTO variant (rs9939609) and physical activity on obesity in 15,925 Swedish and 2,511 Finnish adults. Diabetologia 52:7, 1334-1338
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    Lewis Landsberg, James B. Young, William R. Leonard, Robert A. Linsenmeier, Fred W. Turek. (2009) Is obesity associated with lower body temperatures? Core temperature: a forgotten variable in energy balance. Metabolism 58:6, 871-876
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    D Andersson, H Wahrenberg, P Löfgren. (2009) β3-Adrenoceptor function and long-term changes in body weight. International Journal of Obesity 33:6, 662-668
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    Xiaoling Wang, Xiuhua Ding, Shaoyong Su, Zhibin Li, Harriette Riese, Julian F. Thayer, Frank Treiber, Harold Snieder. (2009) Genetic influences on heart rate variability at rest and during stress. Psychophysiology 46:3, 458-465
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    Stefan Gebhardt, Michael Haberhausen, Monika Heinzel-Gutenbrunner, Nadine Gebhardt, Helmut Remschmidt, Jürgen-Christian Krieg, Johannes Hebebrand, Frank M. Theisen. (2009) Antipsychotic-induced body weight gain: Predictors and a systematic categorization of the long-term weight course. Journal of Psychiatric Research 43:6, 620-626
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    S. L. J. Wijers, W. H. M. Saris, W. D. van Marken Lichtenbelt. (2009) Recent advances in adaptive thermogenesis: potential implications for the treatment of obesity. Obesity Reviews 10:2, 218-226
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    Piia Leskelä, Olavi Ukkola, Johanna Vartiainen, Tapani Rönnemaa, Jaakko Kaprio, Claude Bouchard, Y. Antero Kesäniemi. (2009) Fasting plasma total ghrelin concentrations in monozygotic twins discordant for obesity. Metabolism 58:2, 174-179
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    F. Renstrom, F. Payne, A. Nordstrom, E. C. Brito, O. Rolandsson, G. Hallmans, I. Barroso, P. Nordstrom, P. W. Franks, . (2009) Replication and extension of genome-wide association study results for obesity in 4923 adults from northern Sweden. Human Molecular Genetics 18:8, 1489-1496
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    Peter J. Turnbaugh, Micah Hamady, Tanya Yatsunenko, Brandi L. Cantarel, Alexis Duncan, Ruth E. Ley, Mitchell L. Sogin, William J. Jones, Bruce A. Roe, Jason P. Affourtit, Michael Egholm, Bernard Henrissat, Andrew C. Heath, Rob Knight, Jeffrey I. Gordon. (2009) A core gut microbiome in obese and lean twins. Nature 457:7228, 480-484
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    Johannes Hebebrand, Anke Hinney. (2009) Environmental and Genetic Risk Factors in Obesity. Child and Adolescent Psychiatric Clinics of North America 18:1, 83-94
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    R L Leibel. (2008) Molecular physiology of weight regulation in mice and humans. International Journal of Obesity 32, S98-S108
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    J Galgani, E Ravussin. (2008) Energy metabolism, fuel selection and body weight regulation. International Journal of Obesity 32, S109-S119
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    Craig H. Warden, Janis S. Fisler. (2008) Gene–Nutrient and Gene–Physical Activity Summary—Genetics Viewpoint. Obesity 16, S55-S59
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    Myles S. Faith. (2008) Behavioral Science and the Study of Gene–Nutrition and Gene–Physical Activity Interactions in Obesity Research. Obesity 16, S82-S84
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    Arnaud Basdevant. (2008) Obesity: Pathophysiological concepts. Joint Bone Spine 75:6, 665-666
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    Tuomo Rankinen, Claude Bouchard. (2008) Gene–Physical Activity Interactions: Overview of Human Studies. Obesity 16, S47-S50
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    S O'Rahilly, I S Farooqi. (2008) Human obesity as a heritable disorder of the central control of energy balance. International Journal of Obesity 32, S55-S61
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    Molly S. Bray. (2008) Implications of Gene–Behavior Interactions: Prevention and Intervention for Obesity. Obesity 16, S72-S78
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    Claude Bouchard. (2008) Gene–Environment Interactions in the Etiology of Obesity: Defining the Fundamentals. Obesity 16, S5-S10
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    C Bouchard. (2008) How much progress have we made over the last few decades?. International Journal of Obesity 32, S2-S7
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    Jeremy Freese. (2008) Genetics and the Social Science Explanation of Individual Outcomes. American Journal of Sociology 114:S1, S1-S35
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    Ruth McPherson. (2008) Beyond calories: Genetic determinants of eating, satiety and metabolism underlying obesity. Canadian Journal of Cardiology 24, 15C-17C
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    Mary-Ellen Harper, Katherine Green, Martin D. Brand. (2008) The Efficiency of Cellular Energy Transduction and Its Implications for Obesity. Annual Review of Nutrition 28:1, 13-33
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    C E Hallgreen, K D Hall. (2008) Allometric relationship between changes of visceral fat and total fat mass. International Journal of Obesity 32:5, 845-852
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    C Bouchard. (2008) Response to ‘The thrifty gene hypothesis: maybe everyone is right?’. International Journal of Obesity 32:4, 725-726
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    Peter T. Katzmarzyk, Louise A. Baur, Steven N. Blair, Estelle V. Lambert, Jean-Michel Oppert, Chris Riddoch. (2008) International conference on physical activity and obesity in children: summary statement and recommendationsThis summary statement and recommendations from the International Conference on Physical Activity and Obesity in Children is being published simultaneously in the International Journal of Pediatric Obesity and Applied Physiology, Nutrition, and Metabolism.For the International Association for the Study of Obesity Physical Activity Task Force and the Conference Speaker Panel (the conference speaker panel includes Tom Baranowski, Claude Bouchard, Kelly Brownell, Deborah Cohen, William H. Dietz, Rod Dishman, Mary Flynn, William Haskell, James O. Hill, W.P.T. (Philip) James, Russell Pate, John Peters, Michael Pratt, Harry Rutter, James Sallis, Jo Salmon, Chantal Simon, and Boyd Swinburn).. Applied Physiology, Nutrition, and Metabolism 33:2, 371-388
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    Jacob v.B. Hjelmborg, Corrado Fagnani, Karri Silventoinen, Matt McGue, Maarit Korkeila, Kaare Christensen, Aila Rissanen, Jaakko Kaprio. (2008) Genetic Influences on Growth Traits of BMI: A Longitudinal Study of Adult Twins. Obesity 16:4, 847-852
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    W. P. T. James. (2008) The fundamental drivers of the obesity epidemic. Obesity Reviews 9:s1, 6-13
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    A. Bellisari. (2008) Evolutionary origins of obesity. Obesity Reviews 9:2, 165-180
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    Margarita Terán-García, Jean-Pierre Després, Angelo Tremblay, Claude Bouchard. (2008) Effects of cholesterol ester transfer protein (CETP) gene on adiposity in response to long-term overfeeding. Atherosclerosis 196:1, 455-460
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    N A King, M Hopkins, P Caudwell, R J Stubbs, J E Blundell. (2008) Individual variability following 12 weeks of supervised exercise: identification and characterization of compensation for exercise-induced weight loss. International Journal of Obesity 32:1, 177-184
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    Emmanuelle Meugnier, Cécile Bossu, Myriam Oliel, Sakina Jeanne, Angélique Michaut, Monique Sothier, John Brozek, Sophie Rome, Martine Laville, Hubert Vidal. (2007) Changes in Gene Expression in Skeletal Muscle in Response to Fat Overfeeding in Lean Men**. Obesity 15:11, 2583-2594
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    Garden Tabacchi, Santo Giammanco, Maurizio La Guardia, Marco Giammanco. (2007) A review of the literature and a new classification of the early determinants of childhood obesity: from pregnancy to the first years of life. Nutrition Research 27:10, 587-604
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    Claude Bouchard. 2007. Genetics of Obesity in Humans: Current Issues. , 108-117.
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    Arne Astrup. 2007. Obesity and Metabolic Efficiency. , 159-173.
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    Per Björntorp. 2007. Diabetes. , 68-89.
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    C Bouchard. (2007) The biological predisposition to obesity: beyond the thrifty genotype scenario. International Journal of Obesity 31:9, 1337-1339
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    Margaret Schneider, Genevieve Fridlund Dunton, Dan Michael Cooper. (2007) Media Use and Obesity in Adolescent Females*. Obesity 15:9, 2328-2335
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    J. A. Levine. (2007) Nonexercise activity thermogenesis ? liberating the life-force. Journal of Internal Medicine 262:3, 273-287
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    Scott Owens, Bernard Gutin, Paule Barbeau. 2007. Childhood Obesity and Exercise. , 889-902.
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    Luigi Bouchard, Claude Bouchard, Yvon C. Chagnon, Louis Perusse. (2007) Evidence of Linkage and Association with Body Fatness and Abdominal Fat on Chromosome 15q26*. Obesity 15:8, 2061-2070
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    Eva Warensjö, Erik Ingelsson, Per Lundmark, Lars Lannfelt, Ann-Christine Syvänen, Bengt Vessby, Ulf Risérus. (2007) Polymorphisms in the SCD1 Gene: Associations With Body Fat Distribution and Insulin Sensitivity*. Obesity 15:7, 1732-1740
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    Anne-Sofie Furberg, Sissi Espetvedt, Aina Emaus, Noor Khan, Inger Thune. (2007) Low high-density lipoprotein cholesterol may signal breast cancer risk: recent findings and new hypotheses. Biomarkers in Medicine 1:1, 121-131
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    V. Pudel. (2007) Anmerkungen zur Ernährungspsychologie. Ernährung - Wissenschaft und Praxis 1:4, 162-166
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    John B. Dixon, Boyd J. G. Strauss, Cheryl Laurie, Paul E. O’Brien. (2007) Smaller Hip Circumference is Associated with Dyslipidemia and the Metabolic Syndrome in Obese Women. Obesity Surgery 17:6, 770-777
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    Neil A. King, Phillipa Caudwell, Mark Hopkins, Nuala M. Byrne, Rachel Colley, Andrew P. Hills, James R. Stubbs, John E. Blundell. (2007) Metabolic and Behavioral Compensatory Responses to Exercise Interventions: Barriers to Weight Loss*. Obesity 15:6, 1373-1383
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    Constantina Papoutsakis, George V Dedoussis. (2007) Gene–diet interactions in childhood obesity: paucity of evidence as the epidemic of childhood obesity continues to rise. Personalized Medicine 4:2, 133-146
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    George Corcoran. 2007. Obesity as an Occult Risk Factor for Drug and Chemical Toxicities. , 165-173.
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    Kristi B. Adamo, Frédérique Tesson. (2007) Genotype-specific weight loss treatment advice: how close are we?. Applied Physiology, Nutrition, and Metabolism 32:3, 351-366
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    Esther A. Beek, Arjen H. Bakker, Philip M. Kruyt, Marten H. Hofker, Wim H. Saris, Jaap Keijer. (2007) Intra- and interindividual variation in gene expression in human adipose tissue. Pflügers Archiv - European Journal of Physiology 453:6, 851-861
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    N. Klöting, M. Stumvoll, M. Blüher. (2007) Biologie des viszeralen Fetts. Der Internist 48:2, 126-133
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    G C Major, E Doucet, P Trayhurn, A Astrup, A Tremblay. (2007) Clinical significance of adaptive thermogenesis. International Journal of Obesity 31:2, 204-212
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    Warren G. Thompson, David A. Cook, Matthew M. Clark, Aditya Bardia, James A. Levine. (2007) Treatment of Obesity. Mayo Clinic Proceedings 82:1, 93-102
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    W. G. Thompson, D. A. Cook, M. M. Clark, A. Bardia, J. A. Levine. (2007) Treatment of Obesity. Mayo Clinic Proceedings 82:1, 93-102
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    Jean-Pierre Després, Isabelle Lemieux. (2006) Abdominal obesity and metabolic syndrome. Nature 444:7121, 881-887
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    S. B. Heymsfield, J. B. Harp, P. N. Rowell, A. M. Nguyen, A. Pietrobelli. (2006) How much may I eat? Calorie estimates based upon energy expenditure prediction equations. Obesity Reviews 7:4, 361-370
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    Cabot, Richard C.Harris, Nancy Lee, Shepard, Jo-Anne O., Rosenberg, Eric S., Cort, Alice M., Ebeling, Sally H.Peters, Christine C., Hoppin, Alison G., Katz, Eliot S., Kaplan, Lee M., Lauwers, Gregory Y., . (2006) Case 31-2006. New England Journal of Medicine 355:15, 1593-1602
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    Allyn L Mark. (2006) DIETARY THERAPY FOR OBESITY IS A FAILURE AND PHARMACOTHERAPY IS THE FUTURE: A POINT OF VIEW. Clinical and Experimental Pharmacology and Physiology 33:9, 857-862
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    Lewis Landsberg. (2006) A TELEOLOGICAL VIEW OF OBESITY, DIABETES AND HYPERTENSION. Clinical and Experimental Pharmacology and Physiology 33:9, 863-867
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    A. N. Jacob, B. Adams-Huet, P. Raskin. (2006) The visceral and subcutaneous fat changes in type 1 diabetes: a pilot study. Diabetes, Obesity and Metabolism 8:5, 524-530
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    Marc-Andre Cornier, Bryan C. Bergman, Daniel H. Bessesen. (2006) The effects of short-term overfeeding on insulin action in lean and reduced-obese individuals. Metabolism 55:9, 1207-1214
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    A BASDEVANT. (2006) L'obésité : origines et conséquences d'une épidémie. Comptes Rendus Biologies 329:8, 562-569
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    S. O'Rahilly, I.S. Farooqi. (2006) Genetics of obesity. Philosophical Transactions of the Royal Society B: Biological Sciences 361:1471, 1095-1105
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    David B. Sarwer, Anthony N. Fabricatore, Thomas A. Wadden. (2006) The Behavioral Evaluation of Bariatric Surgery Candidates. Obesity Management 2:3, 103-109
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    G Eiben, L Lissner. (2006) Health Hunters–an intervention to prevent overweight and obesity in young high-risk women. International Journal of Obesity 30:4, 691-696
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    2006. References. , 285-330.
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    Thomas A. Wadden, David B. Sarwer. (2006) Behavioral Assessment of Candidates for Bariatric Surgery: A Patient-Oriented Approach. Obesity 14:3S, 53S-62S
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    Greeshma K. Shetty, Christos S. Mantzoros. 2006. Insulin Resistance, Obesity, Body Fat Distribution, and Risk of Cardiovascular Disease. , 51-74.
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    Megan A. McCrory, Edward Saltzman, Barbara J. Rolls, Susan B. Roberts. (2006) A twin study of the effects of energy density and palatability on energy intake of individual foods. Physiology & Behavior 87:3, 451-459
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    A M C P Joosen, A H F Bakker, A H G Zorenc, S Kersten, P Schrauwen, K R Westerterp. (2006) PPARγ activity in subcutaneous abdominal fat tissue and fat mass gain during short-term overfeeding. International Journal of Obesity 30:2, 302-307
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    M. Slawik, F. Beuschlein. (2006) Genetik und Pathophysiologie der Adipositas. Der Internist 47:2, 120-129
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    George A. Bray. 2006. Obesity Is a Major Health Problem: Causes and Natural History. , 1-20.
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    Kijin KIM, Seungno LEE, Sunjang LEE, Kiwon LIM, Wookwang CHEUN, Nayoung AHN, Yoonjung SHIN, Jusik PARK, Changbae HONG, Sanghyun KIM. (2006) Comparison of Body Fat Distribution and Blood Lipid Profiles according to Trp64Arg Polymorphism for the .BETA.3-Adrenergic Receptor Gene in Korean Middle-Aged Women. Journal of Nutritional Science and Vitaminology 52:4, 281-286
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    Shelley Tworoger, Monica McGrath. 2005. Genetics, Obesity, and Cancer. , 341-354.
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    David W Haslam, W Philip T James. (2005) Obesity. The Lancet 366:9492, 1197-1209
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    Nancy Clark. (2005) Bulking Up. ACSM's Health & Fitness Journal 9:5, 15-19
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    G BRAY. (2005) Epidemiology, risks and pathogenesis of obesity. Meat Science 71:1, 2-7
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    Annemiek M.C.P. Joosen, Arjen H.F. Bakker, Klaas R. Westerterp. (2005) Metabolic efficiency and energy expenditure during short-term overfeeding. Physiology & Behavior 85:5, 593-597
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    V. Pudel, T. Ellrott. (2005) Adipositas — ein gesellschaftspolitisches Problem?. Der Chirurg 76:7, 639-646
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    Claude Bouchard, Tuomo Rankinen. (2005) Genetics and Obesity: What Does It Mean to the Clinician?. Obesity Management 1:3, 100-104
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