Changes in physical activity over the lifespan: impact on body composition and sarcopenic obesity.

Physical activity and body composition show a typical pattern over the lifecycle. Fat-free mass and physical performance generally peak in early adulthood. Here, evidence for a relation between physical activity changes over the life span and the development of sarcopenic obesity is presented. Activity-induced energy expenditure increases with body size and physical activity during growth. The physical activity level, calculated by expressing total energy expenditure as a multiple of resting energy expenditure, gradually increases from early age to adulthood to decrease again in old age. Habitual physical activity has a significant effect on growth of fat-free mass during adolescence and thus on peak fat-free mass and physical performance in early adulthood. Older subjects have a lower fat-free mass and lower physical activity levels but there is no association, suggesting physical activity does not protect against loss of lean body mass at higher age. Prevention of sarcopenic obesity starts with a physically active lifestyle to develop a healthy peak fat-free mass and subsequent prevention of excess fat gain. The change from a physically active to a more sedentary routine in later life requires restriction of energy intake to maintain energy balance.

Control of energy expenditure in humans.

Energy expenditure is determined by body size and body composition and by food intake and physical activity. Body size and body composition are the determinants of resting energy expenditure. Higher weight results in higher energy requirement through a higher resting requirement because of a higher maintenance cost of a larger body. Activity-induced energy expenditure is the most variable component of total energy expenditure. Smaller and leaner subjects generally move more as activity energy expenditure in larger subjects is not higher in proportion to the cost of moving with a higher body weight. Food intake induces changes in energy expenditure as a function of changes in body size and body composition. In addition, energy restriction induces an adaptive reduction of energy expenditure through a lowering of tissue metabolism and a reduction of body movement. An exercise-induced increase in activity expenditure is a function of the training status. In untrained subjects, exercise induces a larger increase in total energy expenditure than can be attributed to the energy cost of a training program. Trained subjects have a higher performance at the same expenditure through a higher exercise economy.

Heritability and genetic etiology of habitual physical activity: a twin study with objective measures.

Twin studies with objective measurements suggest habitual physical activity (HPA) are modestly to highly heritable, depending on age. We aimed to confirm or refute this finding and identify relevant genetic variants using a candidate gene approach. HPA was measured for 14 days with a validated triaxial accelerometer (Tracmor) in two populations: (1) 28 monozygotic and 24 dizygotic same-sex twin pairs (aged 22 ± 5 years, BMI 21.8 ± 3.4 kg/m(2), 21 male, 31 female pairs); (2) 52 and 65 unrelated men and women (aged 21 ± 2 years, BMI 22.0 ± 2.5 kg/m(2)). Single nucleotide polymorphisms (SNPs) in PPARD, PPARGC1A, NRF1 and MTOR were considered candidates. Association analyses were performed for both groups separately followed by meta-analysis. Structural equation modeling shows significant familiality for HPA, consistent with a role for additive genetic factors (heritability 57 %, 95 % CI 32-74 %, AE model) or common environmental factors (47 %, 95 % CI 23-65 %, CE model). A moderate heritability was observed for the time spent on low- and high-intensity physical activity (P ≤ 0.05), but could not be confirmed for the time spent on moderate-intensity physical activity. For PPARD, each additional effect allele was inversely associated with HPA (P ≤ 0.01; rs2076168 allele C) or tended to be associated with HPA (P ≤ 0.05; rs2267668 allele G). Linkage disequilibrium existed between those two SNPs (alleles A/G and A/C, respectively) and meta-analysis showed that carriers of the AA GC haplotype were less physically active than carriers of the AA AA and AA AC haplotypes combined (P = 0.017). For PPARGC1A, carriers of AA in rs8192678 spent more time on high-intensity physical activity than GG carriers (P = 0.001). No associations were observed with SNPs in NRF1 and MTOR. In conclusion, HPA may be modestly heritable, which is confirmed by an association with variants in PPARD.

Validating measures of free-living physical activity in overweight and obese subjects using an accelerometer.

BACKGROUND: Free-living physical activity can be assessed with an accelerometer to estimate energy expenditure but its validity in overweight and obese subjects remains unknown. OBJECTIVE: Here, we validated published prediction equations derived in a lean population with the TracmorD accelerometer (DirectLife, Philips Consumer Lifestyle) in a population of overweight and obese. We also explored possible improvements of new equations specifically developed in overweight and obese subjects. DESIGN: Subjects were 11 men and 25 women (age: 41±7 years; body mass index: 31.0±2.5 kg m(-2)). Physical activity was monitored under free-living conditions with TracmorD, whereas total energy expenditure was measured simultaneously with doubly-labeled water. Physical activity level (PAL) and activity energy expenditure (AEE) were calculated from total energy expenditure and sleeping metabolic rate. RESULTS: The published prediction equation explained 47% of the variance of the measured PAL (P<0.001). PAL estimates were unbiased (errors (bias±95% confidence interval): -0.02±0.28). Measured and predicted AEE/body weight were highly correlated (r(2)=58%, P<0.001); however, the prediction model showed a significant bias of 8 kJ kg(-1) per day or 17.4% of the average AEE/body weight. The new prediction equation of AEE/body weight developed in the obese group showed no bias. CONCLUSIONS: In conclusion, equations derived with the TracmorD allow valid assessment of PAL and AEE/body weight in overweight and obese subjects. There is evidence that estimates of AEE/body weight could be affected by gender. Equations specifically developed in overweight and obese can improve the accuracy of predictions of AEE/body weight.

Daily physical activity assessment with accelerometers: new insights and validation studies.

The field of application of accelerometry is diverse and ever expanding. Because by definition all physical activities lead to energy expenditure, the doubly labelled water (DLW) method as gold standard to assess total energy expenditure over longer periods of time is the method of choice to validate accelerometers in their ability to assess daily physical activities. The aim of this paper was to provide a systematic overview of all recent (2007-2011) accelerometer validation studies using DLW as the reference. The PubMed Central database was searched using the following keywords: doubly or double labelled or labeled water in combination with accelerometer, accelerometry, motion sensor, or activity monitor. Limits were set to include articles from 2007 to 2011, as earlier publications were covered in a previous review. In total, 38 articles were identified, of which 25 were selected to contain sufficient new data. Eighteen different accelerometers were validated. There was a large variability in accelerometer output and their validity to assess daily physical activity. Activity type recognition has great potential to improve the assessment of physical activity-related health outcomes. So far, there is little evidence that adding other physiological measures such as heart rate significantly improves the estimation of energy expenditure.

Metabolic adaptations to over--and underfeeding--still a matter of debate?

Weight changes in response to a change in energy intake are smaller than calculated from the excess or deficit of energy intake. Digestion efficiency is not affected by intake level when consuming the same diet. Over- or underfeeding induces an increase or decrease in energy expenditure. Intake-induced expenditure changes are largely explained by proportional changes in diet-induced energy expenditure, in activity-induced energy expenditure and in maintenance expenditure as a function of changes in body weight and body composition. Additionally, underfeeding causes a metabolic adaptation as reflected in a reduction of maintenance expenditure below predicted values and defined as adaptive thermogenesis. Thus, alternating overfeeding and underfeeding with an iso-energetic amount results in a positive energy balance. The latter might be one of the explanations for the increasing incidence of obesity in our current society with an ample food supply.

Wrist-worn accelerometers in assessment of energy expenditure during intensive training.

We assessed the ability of the Polar activity recorder (AR) to measure energy expenditure (EE) during military training. Twenty-four voluntary male conscripts participated in the study and wore an AR on the non-dominant wrist 24 h a day for 7 d. The AR analyzed and stored the frequency of hand movements (f_hand) into memory at 1 min intervals. The relationship between f_hand and EE was studied over a 7 d period of military training using the doubly labeled water (DLW) technique. In addition, the relationship between f_hand and EE was analyzed during walking and running on a treadmill with an indirect calorimeter (IC), and f_hand was measured during a supervised 45 min field march test where the conscripts carried combat gear. EE was expressed as physical activity level (PAL), total energy expenditure (TEE), and activity-induced energy expenditure adjusted for body mass (AEE/BM). Over the 7 d period, f_hand alone explained 46% of inter-individual variation in PAL(DLW). After inclusion of body height and mass in the model used to predict PAL(DLW) from f_hand, a very high positive correlation and a low standard error of estimate (SEE) were observed between the AR and DLW techniques: for TEE r = 0.86 (p < 0.001), the SEE was 6.3%, and for AEE/BM r = 0.84 (p < 0.001), the SEE was 12.8%. In the treadmill exercise, f_hand correlated highly with PAL(IC) (r = 0.97 ± 0.02). In the 45 min field march test, the AR measured similar f_hand as on the treadmill at the same speed. In conclusion, the wrist-worn AR can be regarded as a reliable and valid method for assessing EE during intensive training.

Obesity: lessons from evolution and the environment.

The 9th Stock Conference acknowledged the complex background of genetic, cultural, environmental and evolutionary factors of obesity. Gene-environment interactions underlie the flexibility in body-weight and body-fat regulation, illustrated by the hunter-gatherers' feast and famine lifestyle, the variation in physical activity over the lifespan being highest at reproductive age, the variation in energy intake through 'eating in the absence of hunger', while running the risk of exceeding the capacity of triacylglyceride storage, leading to lipotoxicity and metabolic problems. Perinatal metabolic programming for obesity via epigenetic changes in response to a 'Western diet' results in production of lipid-poor milk and metabolically efficient pups, contributing to the perpetuation of obesity throughout generations. Evolutionary insight from comparative physiology and ecology indicates that over generations activity-induced energy expenditure has remained the same compared to wild mammals, that energy balance might be dependant on protein balance, while the function of taste changed from detection of poison or energy to social drinking and social behaviour. At present, the impact of assortative mating on obesity prevalence is unambiguously positive. The complexity that appeared can only be fully appreciated by setting the data into the context of our evolutionary history.

Aspects of activity behavior as a determinant of the physical activity level.

This study investigated which aspects of the individuals' activity behavior determine the physical activity level (PAL). Habitual physical activity of 20 Dutch adults (age: 26-60 years, body mass index: 24.5 ± 2.7 kg/m(2)) was measured using a tri-axial accelerometer. Accelerometer output was used to identify the engagement in different types of daily activities with a classification tree algorithm. Activity behavior was described by the daily duration of sleeping, sedentary behavior (lying, sitting, and standing), walking, running, bicycling, and generic standing activities. Simultaneously, the total energy expenditure (TEE) was measured using doubly labeled water. PAL was calculated as TEE divided by sleeping metabolic rate. PAL was significantly associated (P<0.05) with sedentary time (R=-0.72), and the duration of walking (R=0.49), bicycling (R=0.77), and active standing (R=0.62). A negative association was observed between sedentary time and the duration of active standing (R=-0.87; P<0.001). A multiple-linear regression analysis showed that 75% of the variance in PAL could be predicted by the duration of bicycling (Partial R(2) =59%; P<0.01), walking (Partial R(2) =9%; P<0.05) and being sedentary (Partial R(2) =7%; P<0.05). In conclusion, there is objective evidence that sedentary time and activities related to transportation and commuting, such as walking and bicycling, contribute significantly to the average PAL.

Advances in physical activity monitoring and lifestyle interventions in obesity: a review.

Obesity represents a strong risk factor for developing chronic diseases. Strategies for disease prevention often promote lifestyle changes encouraging participation in physical activity. However, determining what amount of physical activity is necessary for achieving specific health benefits has been hampered by the lack of accurate instruments for monitoring physical activity and the related physiological outcomes. This review aims at presenting recent advances in activity-monitoring technology and their application to support interventions for health promotion. Activity monitors have evolved from step counters and measuring devices of physical activity duration and intensity to more advanced systems providing quantitative and qualitative information on the individuals' activity behavior. Correspondingly, methods to predict activity-related energy expenditure using bodily acceleration and subjects characteristics have advanced from linear regression to innovative algorithms capable of determining physical activity types and the related metabolic costs. These novel techniques can monitor modes of sedentary behavior as well as the engagement in specific activity types that helps to evaluate the effectiveness of lifestyle interventions. In conclusion, advances in activity monitoring have the potential to support the design of response-dependent physical activity recommendations that are needed to generate effective and personalized lifestyle interventions for health promotion.

Measurement of longitudinal changes in body composition during weight loss and maintenance in overweight and obese subjects using air-displacement plethysmography in comparison with the deuterium dilution technique.

BACKGROUND: Air-displacement plethysmography (ADP) may be a valid and practical technique to assess body composition in a clinical setting. OBJECTIVE: This study aimed to assess longitudinal changes in body composition using ADP and to compare it with the deuterium dilution technique. DESIGN: The study was a 6-months dietary intervention, consisting of four phases. The first month, subjects were fed in energy balance (phase I). This was followed by 1 month with an energy intake of 33% of energy requirements (phase II), followed by 2 months at 67% of energy requirements (phase III) and 2 months of ad libitum intake (phase IV). Body composition was assessed using ADP (Bod Pod) and deuterium dilution at baseline and at the end of each phase. The baseline analysis included 111 subjects (88 female). Sixty-one subjects (50 female) completed all measurements and were included in the longitudinal analysis. RESULTS: At baseline, the fat mass (FM) as assessed with the Bod Pod was on average 2.3 ± 4.2 kg (mean ± 2 s.d.) higher than that assessed with deuterium dilution. The difference in FM between techniques increased significantly with increasing FM (R(2)=0.23; P<0.001). Both techniques showed significant changes in FM over time P<0.001). On average, FM as assessed with the Bod Pod was 2.0 kg higher than with deuterium dilution (P<0.001). During phase II, there was a significant interaction between time and method, meaning that the Bod Pod showed a larger decrease in FM than deuterium dilution. CONCLUSIONS: The Bod Pod was able to detect all changes in the body composition, but consistently measured a higher FM than deuterium dilution.

No long-term weight maintenance effects of gelatin in a supra-sustained protein diet.

In the short-term, gelatin showed stronger hunger suppression and less energy intake compared with other proteins. This study investigated if a supra-sustained gelatin-milk protein (GMP) diet improves weight maintenance (WM) compared with a sustained milk protein (SMP) diet and supra-sustained milk protein (SSMP) diet during a 4-months WM period after 8-week weight loss (WL) in sixty-five healthy subjects (28.6+/-3.4kg/m(2); 44+/-10years). Absolute protein intake was kept constant (sustained) throughout per subject. Diets were: protein(P)/fat(F)/carbohydrate(C): 15/40/45% of energy (En%) (SMP) and 30/25/45 En% (SSMP or GMP) for weeks 9-16. Diets on weeks 17-24: P/F/C: 30/35/35 En% (SMP) and 60/5/35 En% (SSMP or GMP). From weeks 8 to 16, and weeks 16 to 24, changes in BMI were similar between the GMP (-0.4+/-0.6 and 0.3+/-0.7kg/m(2) respectively), and the SMP (-0.7+/-0.9 and 0.1+/-0.7kg/m(2) respectively) and SSMP (-0.6+/-0.6 and 0.3+/-0.6kg/m(2) respectively) diets. Sparing of fat free mass (FFM): increases/decreases in FFM%/fat-mass% from weeks 8 to 16 were similar between the GMP and both control diets, and maintained from weeks 16 to 24. In conclusion, all 3 diets resulted in a successful WM period, while a GMP diet does not improve body weight maintenance and related variables after weight loss compared with a SMP and SSMP diet.

Ethnic differences in body composition and the associated metabolic profile: a comparative study between Asians and Caucasians.

It is estimated that Asia will be the home of more than 100 million people with type 2 diabetes by the year of 2025. This region combines a high proportion of the world's population with rapidly rising diabetes prevalence rates. The increase in diabetes in Asia differs from that reported in other parts of the world: it has developed in a shorter time, in a younger age group, and in people with lower body-mass index (BMI). Studies reported that for the same BMI, Asians have a higher body fat percentage, a prominent abdominal obesity, a higher intramyocellular lipid and/or a higher liver fat content compared to Caucasians. These characteristics may contribute to a higher predisposition to insulin resistance at a lesser degree of obesity than Caucasians. The differences in body composition are more pronounced depending on the region. For the same BMI, among three major ethnic groups in Asia, Asian Indians have the highest body fat, followed by Malay and Chinese. Lower insulin sensitivity is already observed in Asian Indian adolescents with a higher body fat and abdominal obesity compared to Caucasian adolescents. In general, Asian adolescents share the same feature of body composition such as higher body subcutaneous fat, lower appendicular skeletal muscle and lower gynoid fat compared to Caucasian adolescents. This unfavourable body composition may predispose to the development of insulin resistance at later age. Genetics may play a role and the interaction with environmental factors (changes in lifestyle) could increase the risk of developing the metabolic syndrome.

Inaccuracies in food and physical activity diaries of obese subjects: complementary evidence from doubly labeled water and co-twin assessments.

OBJECTIVE: To study whether eating or physical-activity (PA) habits differ between obese and non-obese monozygotic (MZ) co-twins independent of genetic effects. METHODS: Rare MZ pairs discordant for obesity (n=14, body mass index difference 5.2+/-1.8 kg m(-2)) and weight-concordant control pairs (n=10, 1.0+/-0.7 kg m(-2)), identified through a population-based registry of 24-28-year-old twins (n=658 MZ pairs), completed 3-day food and PA diaries and eating behavior questionnaires. Each twin was asked to compare his/her own eating and PA patterns with the co-twin's behavior by structured questionnaires. Accuracy of energy intake was validated by doubly labeled water. RESULTS: Non-obese co-twins consistently reported that their obese twin siblings ate more food overall, consumed less healthy foods and exercised less than the non-obese co-twins do. However, no differences in energy intake (9.6+/-1.0 MJ per day vs 9.8+/-1.1 MJ per day, respectively) in the food diaries or in the mean PA level (1.74+/-0.02 vs 1.79+/-0.04, respectively) in the PA diaries were found between obese and non-obese co-twins. A considerable underreporting of energy intake (3.2+/-1.1 MJ per day, P=0.036) and overreporting of PA (1.8+/-0.8 MJ per day, P=0.049) was observed in the obese, but not in the non-obese co-twins. CONCLUSIONS: On the basis of rare MZ twin pairs discordant for obesity, the co-twin assessments confirmed substantial differences in eating and PA behavior between obese and non-obese persons. These may be overlooked in population studies using food and PA diaries because of considerable misreporting by the obese.

Body composition in 10-13-year-old children: a comparison between air displacement plethysmography and deuterium dilution.

OBJECTIVE: Air diplacement plethysmography (ADP) has become increasingly popular to assess body composition in children. The aim of this study was to compare ADP with deuterium dilution and to investigate the effect of using child-specific prediction equations to correct raw body volume from ADP for thoracic gas volume (TGV) and body surface area (BSA). METHODS: Thirty-seven healthy Dutch children (17 girls, 20 boys) aged 10-13 years were recruited. Body volume was measured using the Bod Pod. Both adult and child-specific prediction equations were used to correct raw body volume from the Bod Pod for TGV and BSA. Total body water (TBW) was assessed using deuterium dilution. Child-specific densities and hydration fractions of fat-free mass were used to convert body volume and TBW to percentage fat mass (%FM). Correlation and agreement between methods was assessed using linear regression analysis and Bland-Altman plots. RESULTS: Despite a high correlation between the Bod Pod and deuterium dilution (R=0.91, p <0.001), a significant difference was found between %FM obtained using the Bod Pod and deuterium dilution (p <0.001), regardless of the equation used to correct raw body volume for TGV and BSA. Bland-Altman plots showed a systematic bias towards a smaller difference between techniques at higher %FM. CONCLUSION: Significant differences in %FM were found between both methods. Given the underlying assumptions to translate body volume or TBW to %FM, it is recommended to use a 3- or 4-compartment model when assessing body composition in children.

Improving assessment of daily energy expenditure by identifying types of physical activity with a single accelerometer.

Accelerometers are often used to quantify the acceleration of the body in arbitrary units (counts) to measure physical activity (PA) and to estimate energy expenditure. The present study investigated whether the identification of types of PA with one accelerometer could improve the estimation of energy expenditure compared with activity counts. Total energy expenditure (TEE) of 15 subjects was measured with the use of double-labeled water. The physical activity level (PAL) was derived by dividing TEE by sleeping metabolic rate. Simultaneously, PA was measured with one accelerometer. Accelerometer output was processed to calculate activity counts per day (AC(D)) and to determine the daily duration of six types of common activities identified with a classification tree model. A daily metabolic value (MET(D)) was calculated as mean of the MET compendium value of each activity type weighed by the daily duration. TEE was predicted by AC(D) and body weight and by AC(D) and fat-free mass, with a standard error of estimate (SEE) of 1.47 MJ/day, and 1.2 MJ/day, respectively. The replacement in these models of AC(D) with MET(D) increased the explained variation in TEE by 9%, decreasing SEE by 0.14 MJ/day and 0.18 MJ/day, respectively. The correlation between PAL and MET(D) (R(2) = 51%) was higher than that between PAL and AC(D) (R(2) = 46%). We conclude that identification of activity types combined with MET intensity values improves the assessment of energy expenditure compared with activity counts. Future studies could develop models to objectively assess activity type and intensity to further increase accuracy of the energy expenditure estimation.

Dietary protein, weight loss, and weight maintenance.

The role of dietary protein in weight loss and weight maintenance encompasses influences on crucial targets for body weight regulation, namely satiety, thermogenesis, energy efficiency, and body composition. Protein-induced satiety may be mainly due to oxidation of amino acids fed in excess, especially in diets with "incomplete" proteins. Protein-induced energy expenditure may be due to protein and urea synthesis and to gluconeogenesis; "complete" proteins having all essential amino acids show larger increases in energy expenditure than do lower-quality proteins. With respect to adverse effects, no protein-induced effects are observed on net bone balance or on calcium balance in young adults and elderly persons. Dietary protein even increases bone mineral mass and reduces incidence of osteoporotic fracture. During weight loss, nitrogen intake positively affects calcium balance and consequent preservation of bone mineral content. Sulphur-containing amino acids cause a blood pressure-raising effect by loss of nephron mass. Subjects with obesity, metabolic syndrome, and type 2 diabetes are particularly susceptible groups. This review provides an overview of how sustaining absolute protein intake affects metabolic targets for weight loss and weight maintenance during negative energy balance, i.e., sustaining satiety and energy expenditure and sparing fat-free mass, resulting in energy inefficiency. However, the long-term relationship between net protein synthesis and sparing fat-free mass remains to be elucidated.

Skeletal muscle fiber-type distribution and habitual physical activity in daily life.

The capacity to perform physical activity largely depends on physical fitness. Muscle fiber-type distribution (Muscle(FTD)) is associated with physical fitness and may influence the capacity to perform physical activity. The purpose of this study was to determine whether habitual physical activity in daily life (PA(DL)) and Muscle(FTD) are related. Thirty-eight healthy non-athletes (31 women, 7 men) were recruited. PA(DL) was measured twice for 14 days using a tri-axial accelerometer for movement registration (Tracmor). From Tracmor output, the proportion of time subjects were physically active at low, moderate, and high intensities was determined (%Low, %Moderate, and %High, respectively). A total activity index (PA(index)) and sub-scores on work, leisure-time and sports were obtained using the Baecke questionnaire. Muscle(FTD) was determined using immuno-fluorescence against respective myosin heavy chain isoforms. No relationship was observed between PA(DL) and Muscle(FTD). %Low, %Moderate, and %High, as well as PA(index) and its sub-scores, were not related to Muscle(FTD) either. The time spent on sports was associated with the proportion of type I and II(X) fibers (P=0.06 and P<0.01, respectively). In conclusion, Muscle(FTD) probably cannot explain why some people are more prone to engaging in physical activities than others.

Aerobic fitness, energy balance, and body mass index are associated with training load assessed by activity energy expenditure.

The present study examined whether activity energy expenditure related to body mass (AEE/kg) is associated with maximal aerobic fitness (VO(2max)), energy balance, and body mass index (BMI) during the 2 hardest weeks of the military basic training season (BT). An additional purpose was to study the accuracy of the pre-filled food diary energy intake. Energy expenditure (EE) with doubly labeled water, energy intake (EI), energy balance, and mis-recording was measured from 24 male conscripts with varying VO(2max). AEE/kg was calculated as (EE x 0.9-measured basal metabolic rate)/body mass. The reported EI was lower (P<0.001) than EE (15.48 MJ/day) and mis-recording of the pre-filled diary was -20%. The negative energy balance (-6+/-26%) was non-significant; however, the variation was high. The subjects with a low VO(2max), a high BMI, and a negative energy balance were vulnerable to low AEE/kg. However, in the multivariate regression analysis only BMI remained in the model, explaining 33% of the variation in AEE/kg. During wintertime BT, AEE/kg is affected by energy balance, VO(2max), and BMI. From these three factors, overweight limits high-level training the most. Furthermore, an optimal energy balance facilitates physical performance and enables high training loads to be sustained during the BT season.

SNP analyses of postprandial responses in (an)orexigenic hormones and feelings of hunger reveal long-term physiological adaptations to facilitate homeostasis.

BACKGROUND: The postprandial responses in (an)orexigenic hormones and feelings of hunger are characterized by large inter-individual differences. Food intake regulation was shown earlier to be partly under genetic control. OBJECTIVE: This study aimed to determine whether the postprandial responses in (an)orexigenic hormones and parameters of food intake regulation are associated with single nucleotide polymorphisms (SNPs) in genes encoding for satiety hormones and their receptors. DESIGN: Peptide YY (PYY), glucagon-like peptide 1 and ghrelin levels, as well as feelings of hunger and satiety, were determined pre- and postprandially in 62 women and 41 men (age 31+/-14 years; body mass index 25.0+/-3.1 kg/m(2)). Dietary restraint, disinhibition and perceived hunger were determined using the three-factor eating questionnaire. SNPs were determined in the GHRL, GHSR, LEP, LEPR, PYY, NPY, NPY2R and CART genes. RESULTS: The postprandial response in plasma ghrelin levels was associated with SNPs in PYY (215G>C, P<0.01) and LEPR (326A>G and 688A>G, P<0.01), and in plasma PYY levels with SNPs in GHRL (-501A>C, P<0.05) and GHSR (477G>A, P<0.05). The postprandial response in feelings of hunger was characterized by an SNP-SNP interaction involving SNPs in LEPR and NPY2R (668A>G and 585T>C, P<0.05). Dietary restraint and disinhibition were associated with an SNP in GHSR (477G>A, P<0.05), and perceived hunger with SNPs in GHSR and NPY (477G>A and 204T>C, P<0.05). CONCLUSIONS: Part of the inter-individual variability in postprandial responses in (an)orexigenic hormones can be explained by genetic variation. These postprandial responses represent either long-term physiological adaptations to facilitate homeostasis or reinforce direct genetic effects.