846 resultados para FAT-FREE MASS


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People with Parkinson’s disease (PD) are at higher risk of malnutrition due to PD symptoms and pharmacotherapy side effects. Poorer outcomes are associated with higher amounts of weight loss (>5%) and lower levels of fat free mass. When pharmacotherapy is no longer effective for symptom control, deep-brain stimulation (DBS) surgery may be considered. People with PD scheduled for DBS surgery were recruited from a Brisbane neurological clinic (n=11 out of 16). The Scale for Outcomes of Parkinson’s disease –Autonomic (SCOPA-AUT), Modified Constipation Assessment Scale (MCAS), and a 3-day food diary were mailed to participants’ homes for completion prior to hospital admission. During admission, the Patient-Generated Subjective Global Assessment (PG-SGA), weight, height and body composition were assessed. Mean(±s.d.) PD duration from diagnosis and time since occurrence of PD symptoms was 9.0(±8.0) and 12(±8.8) years, respectively. Five participants reported unintentional weight loss (average loss of 15.6%). PD duration but not years since symptom onset significantly predicted PG-SGA scores (β=4.2, t(8)=2.7, p<.05). Both were positively correlated with PG-SGA score (r = .667, r=.587). On average, participants classified as well-nourished (SGA-A) (n=4) were younger, had shorter disease durations, lower PG-SGA scores, higher body mass (BMI) and fat free mass (FFMI) indices when compared to malnourished participants (SGA-B) (n=7). They also reported fewer non-motor symptoms on the SCOPA-AUT and MCAS. Three participants had previously received dietetic advice but not in relation to PD. These findings demonstrate that malnutrition remains unrecognised and untreated in this group despite unintentional weight loss and a high prevalence of malnutrition.

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Objectives: People with Parkinson’s disease (PD) are at higher risk of malnutrition due to PD symptoms and pharmacotherapy side effects. When pharmacotherapy is no longer effective for symptom control, deep-brain stimulation (DBS) surgery may be considered. The aim of this study was to assess the nutritional status of people with PD who may be at higher risk of malnutrition related to unsatisfactory symptom management with optimised medical therapy. Design: This was an observational study using a convenience sample. Setting: Participants were seen during their hospital admission for their deep brain stimulation surgery. Participants: People with PD scheduled for DBS surgery were recruited from a Brisbane neurological clinic (n=15). Measurements: The Patient-Generated Subjective Global Assessment (PG-SGA), weight, height and body composition were assessed to determine nutritional status. Results: Six participants (40%) were classified as moderately malnourished (SGA-B). Eight participants (53%) reported previous unintentional weight loss (average loss of 13.3%). On average, participants classified as well-nourished (SGA-A) were younger, had shorter disease durations, lower PG-SGA scores, higher body mass (BMI) and fat free mass indices (FFMI) when compared to malnourished participants (SGA-B). Five participants had previously received dietetic advice but only one in relation to unintentional weight loss. Conclusion: Malnutrition remains unrecognised and untreated in this group despite unintentional weight loss and presence of nutrition impact symptoms. Improving nutritional status prior to surgery may improve surgical outcomes.

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A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.

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Background: There are strong logical reasons why energy expended in metabolism should influence the energy acquired in food-intake behavior. However, the relation has never been established, and it is not known why certain people experience hunger in the presence of large amounts of body energy. Objective: We investigated the effect of the resting metabolic rate (RMR) on objective measures of whole-day food intake and hunger. Design: We carried out a 12-wk intervention that involved 41 overweight and obese men and women [mean ± SD age: 43.1 ± 7.5 y; BMI (in kg/m2): 30.7 ± 3.9] who were tested under conditions of physical activity (sedentary or active) and dietary energy density (17 or 10 kJ/g). RMR, daily energy intake, meal size, and hunger were assessed within the same day and across each condition. Results: We obtained evidence that RMR is correlated with meal size and daily energy intake in overweight and obese individuals. Participants with high RMRs showed increased levels of hunger across the day (P < 0.0001) and greater food intake (P < 0.00001) than did individuals with lower RMRs. These effects were independent of sex and food energy density. The change in RMR was also related to energy intake (P < 0.0001). Conclusions: We propose that RMR (largely determined by fat-free mass) may be a marker of energy intake and could represent a physiologic signal for hunger. These results may have implications for additional research possibilities in appetite, energy homeostasis, and obesity. This trial was registered under international standard identification for controlled trials as ISRCTN47291569.

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Human immunodeficiency virus (HIV) that leads to acquired immune deficiency syndrome (AIDs) reduces immune function, resulting in opportunistic infections and later death. Use of antiretroviral therapy (ART) increases chances of survival, however, with some concerns regarding fat re-distribution (lipodystrophy) which may encompass subcutaneous fat loss (lipoatrophy) and/or fat accumulation (lipohypertrophy), in the same individual. This problem has been linked to Antiretroviral drugs (ARVs), majorly, in the class of protease inhibitors (PIs), in addition to older age and being female. An additional concern is that the problem exists together with the metabolic syndrome, even when nutritional status/ body composition, and lipodystrophy/metabolic syndrome are unclear in Uganda where the use of ARVs is on the increase. In line with the literature, the overall aim of the study was to assess physical characteristics of HIV-infected patients using a comprehensive anthropometric protocol and to predict body composition based on these measurements and other standardised techniques. The other aim was to establish the existence of lipodystrophy, the metabolic syndrome, andassociated risk factors. Thus, three studies were conducted on 211 (88 ART-naïve) HIV-infected, 15-49 year-old women, using a cross-sectional approach, together with a qualitative study of secondary information on patient HIV and medication status. In addition, face-to-face interviews were used to extract information concerning morphological experiences and life style. The study revealed that participants were on average 34.1±7.65 years old, had lived 4.63±4.78 years with HIV infection and had spent 2.8±1.9 years receiving ARVs. Only 8.1% of participants were receiving PIs and 26% of those receiving ART had ever changed drug regimen, 15.5% of whom changed drugs due to lipodystrophy. Study 1 hypothesised that the mean nutritional status and predicted percent body fat values of study participants was within acceptable ranges; different for participants receiving ARVs and the HIV-infected ART-naïve participants and that percent body fat estimated by anthropometric measures (BMI and skinfold thickness) and the BIA technique was not different from that predicted by the deuterium oxide dilution technique. Using the Body Mass Index (BMI), 7.1% of patients were underweight (<18.5 kg/m2) and 46.4% were overweight/obese (≥25.0 kg/m2). Based on waist circumference (WC), approximately 40% of the cohort was characterized as centrally obese. Moreover, the deuterium dilution technique showed that there was no between-group difference in the total body water (TBW), fat mass (FM) and fat-free mass (FFM). However, the technique was the only approach to predict a between-group difference in percent body fat (p = .045), but, with a very small effect (0.021). Older age (β = 0.430, se = 0.089, p = .000), time spent receiving ARVs (β = 0.972, se = 0.089, p = .006), time with the infection (β = 0.551, se = 0.089, p = .000) and receiving ARVs (β = 2.940, se = 1.441, p = .043) were independently associated with percent body fat. Older age was the greatest single predictor of body fat. Furthermore, BMI gave better information than weight alone could; in that, mean percentage body fat per unit BMI (N = 192) was significantly higher in patients receiving treatment (1.11±0.31) vs. the exposed group (0.99±0.38, p = .025). For the assessment of obesity, percent fat measures did not greatly alter the accuracy of BMI as a measure for classifying individuals into the broad categories of underweight, normal and overweight. Briefly, Study 1 revealed that there were more overweight/obese participants than in the general Ugandan population, the problem was associated with ART status and that BMI broader classification categories were maintained when compared with the gold standard technique. Study 2 hypothesized that the presence of lipodystrophy in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Results showed that 112 (53.1%) patients had experienced at least one morphological alteration including lipohypertrophy (7.6%), lipoatrophy (10.9%), and mixed alterations (34.6%). The majority of these subjects (90%) were receiving ARVs; in fact, all patients receiving PIs reported lipodystrophy. Period spent receiving ARVs (t209 = 6.739, p = .000), being on ART (χ2 = 94.482, p = .000), receiving PIs (Fisher’s exact χ2 = 113.591, p = .000), recent T4 count (CD4 counts) (t207 = 3.694, p = .000), time with HIV (t125 = 1.915, p = .045), as well as older age (t209 = 2.013, p = .045) were independently associated with lipodystrophy. Receiving ARVs was the greatest predictor of lipodystrophy (p = .000). In other analysis, aside from skinfolds at the subscapular (p = .004), there were no differences with the rest of the skinfold sites and the circumferences between participants with lipodystrophy and those without the problem. Similarly, there was no difference in Waist: Hip ratio (WHR) (p = .186) and Waist: Height ratio (WHtR) (p = .257) among participants with lipodystrophy and those without the problem. Further examination showed that none of the 4.1% patients receiving stavudine (d4T) did experience lipoatrophy. However, 17.9% of patients receiving EFV, a non-nucleoside reverse transcriptase inhibitor (NNRTI) had lipoatrophy. Study 2 findings showed that presence of lipodystrophy in participants receiving ARVs was in fact far higher than that of HIV-infected ART-naïve participants. A final hypothesis was that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants. Moreover, data showed that many patients (69.2%) lived with at least one feature of the metabolic syndrome based on International Diabetic Federation (IDF, 2006) definition. However, there was no single anthropometric predictor of components of the syndrome, thus, the best anthropometric predictor varied as the component varied. The metabolic syndrome was diagnosed in 15.2% of the subjects, lower than commonly reported in this population, and was similar between the medicated and the exposed groups (χ 21 = 0.018, p = .893). Moreover, the syndrome was associated with older age (p = .031) and percent body fat (p = .012). In addition, participants with the syndrome were heavier according to BMI (p = .000), larger at the waist (p = .000) and abdomen (p = .000), and were at central obesity risk even when hip circumference (p = .000) and height (p = .000) were accounted for. In spite of those associations, results showed that the period with disease (p = .13), CD4 counts (p = .836), receiving ART (p = .442) or PIs (p = .678) were not associated with the metabolic syndrome. While the prevalence of the syndrome was highest amongst the older, larger and fatter participants, WC was the best predictor of the metabolic syndrome (p = .001). Another novel finding was that participants with the metabolic syndrome had greater arm muscle circumference (AMC) (p = .000) and arm muscle area (AMA) (p = .000), but the former was most influential. Accordingly, the easiest and cheapest indicator to assess risk in this study sample was WC should routine laboratory services not be feasible. In addition, the final study illustrated that the prevalence of the metabolic syndrome in participants receiving ARVs was not different from that of HIV-infected ART-naïve participants.

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Dual-energy X-ray absorptiometry (DXA) and isotope dilution technique have been used as reference methods to validate the estimates of body composition by simple field techniques; however, very few studies have compared these two methods. We compared the estimates of body composition by DXA and isotope dilution (18O) technique in apparently healthy Indian men and women (aged 19–70 years, n 152, 48 % men) with a wide range of BMI (14–40 kg/m2). Isotopic enrichment was assessed by isotope ratio mass spectroscopy. The agreement between the estimates of body composition measured by the two techniques was assessed by the Bland–Altman method. The mean age and BMI were 37 (SD 15) years and 23·3 (SD 5·1) kg/m2, respectively, for men and 37 (SD 14) years and 24·1 (SD 5·8) kg/m2, respectively, for women. The estimates of fat-free mass were higher by about 7 (95 % CI 6, 9) %, those of fat mass were lower by about 21 (95 % CI 218,223) %, and those of body fat percentage (BF%) were lower by about 7·4 (95 % CI 28·2, 26·6) % as obtained by DXA compared with the isotope dilution technique. The Bland–Altman analysis showed wide limits of agreement that indicated poor agreement between the methods. The bias in the estimates of BF% was higher at the lower values of BF%. Thus, the two commonly used reference methods showed substantial differences in the estimates of body composition with wide limits of agreement. As the estimates of body composition are method-dependent, the two methods cannot be used interchangeably

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Although a number of studies have examined the role of gastric emptying (GE) in obesity, the influences of habitual physical activity level, body composition and energy expenditure (EE) on GE have received very little consideration. In this study, we have compared GE in active and inactive males, and we have characterised relationships with body composition (fat and fat free mass) and EE. Forty-four males (Active: n=22, Inactive: n=22; range BMI 21-36kg/m2; range percent fat mass 9-42%) were studied, with GE of a standardised (1676 kJ) pancake meal being assessed by 13C-octanoic acid breath test, body composition by air displacement plethysmography, resting metabolic rate (RMR) by indirect calorimetry and activity EE (AEE) by accelerometry. Results showed that GE was faster in active compared to inactive males (mean ±SD half time (t1/2): Active: 157±18 and Inactive: 179±21 min, p<0.001). When data from both groups were pooled, GE t1/2 was associated with percent fat mass (r=0.39, p<0.01) and AEE (r =-0.46, p<0.01). After controlling for habitual physical activity status, the association between AEE and GE remained, but not that for percent fat mass and GE. BMI and RMR were not associated with GE. In summary, faster GE is considered to be a marker of a habitually active lifestyle in males, and is associated with a higher AEE and lower percent fat mass. The possibility that GE contributes to a gross physiological regulation (or dysregulation) of food intake with physical activity level deserves further investigation.

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Objective To develop a height and weight based equation to estimate total body water (TBW) in Sri Lankan children. Methods Cross sectional descriptive study done involving 5–15 year old healthy children. Height and weight were measured. TBW was assessed using isotope dilution method (D2O) and fat free mass (FFM) calculated. Multiple regression analysis was used to develop prediction equation and validated using PRESS statistical technique. Height, weight and sex code (male=1; female=0) were used as prediction variables. Results This study provides height and weight equation for the prediction of TBW in Sri Lankan children. To the best of our knowledge there are no published height weight prediction equations validated on South Asian populations. Conclusion Results of this study need to be affirmed by more studies on other closely related populations by using multicomponent body composition.

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Background: Body mass index (BMI) is widely used as a measure of adiposity. However, currently used cut-off values are not sensitive in diagnosing obesity in South Asian populations. Aim: To define BMI and waist circumference (WC), cut-off values representing percentage fat mass (%FM) associated with adverse health outcomes. Subjects and methods: A cross-sectional descriptive study of 285 5–14 year old Sri Lankan children (56% boys) was carried out. Fat mass (FM) was assessed using the isotope (D2O) dilution technique based on 2C body composition model. BMI and WC cut-off values were defined based on %FM associated with adverse health outcomes. Results: Sri Lankan children had a low fat free mass index (FFMI) and a high fat mass index (FMI). Individuals with the same BMI had %FM distributed over a wide range. Lean body tissue grew very little with advancing age and weight gain was mainly due to increases in body fat. BMI corresponding to 25% in males and 35% in females at 18 years was 19.2 kg/m2 and 19.7 kg/m2, respectively. WC cut-off values for males and females were 68.4 cm and 70.4 cm, respectively. Conclusion: This chart analysis clearly confirms that Sri Lankan children have a high %FM from a young age. With age, more changes occur in FM than in fat free mass (FFM). Although the newly defined BMI and WC cut-off values appear to be quite low, they are comparable to some recent data obtained in similar populations.

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Abstract: Over the years bioelectrical impedance assay (BIA) has gained popularity in the assessment of body composition. However, equations for the prediction of whole body composition use whole body BIA. This study attempts to evaluate the usefulness of segmental BIA in the assessment of whole body composition. A cross sectional descriptive study was conducted at the Professorial Paediatric Unit of Lady Ridgeway Hospital, Colombo, involving 259 (M/F:144/115) 5 to 15 year old healthy children. The height, weight, total and segmental BIA were measured and impedance indices and specific resistivity for the whole body and segments were calculated. Segmental BIA indices showed a significant association with whole body composition measures assessed by total body water (TBW) using the isotope dilution method (D2O). Impedance index was better related to TBW and fat free mass (FFM), while specific resistivity was better related to the fat mass of the body. Regression equations with different combinations of variables showed high predictability of whole body composition. Results of this study showed that segmental BIA can be used as an alternative approach to predict the whole body composition in Sri Lankan children.

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Background: Body mass index (BMI) is used to diagnose obesity. However, its ability to predict the percentage fat mass (%FM) reliably is doubtful. Therefore validity of BMI as a diagnostic tool of obesity is questioned. Aim: This study is focused on determining the ability of BMI-based cut-off values in diagnosing obesity among Australian children of white Caucasian and Sri Lankan origin. Subjects and methods: Height and weight was measured and BMI (W/H2) calculated. Total body water was determined by deuterium dilution technique and fat free mass and hence fat mass derived using age- and gender-specific constants. A %FM of 30% for girls and 20% for boys was considered as the criterion cut-off level for obesity. BMI-based obesity cut-offs described by the International Obesity Task Force (IOTF), CDC/NCHS centile charts and BMI-Z were validated against the criterion method. Results: There were 96 white Caucasian and 42 Sri Lankan children. Of the white Caucasians, 19 (36%) girls and 29 (66%) boys, and of the Sri Lankans 7 (46%) girls and 16 (63%) boys, were obese based on %FM. The FM and BMI were closely associated in both Caucasians (r = 0.81, P<0.001) and Sri Lankans (r = 0.92, P<0.001). Percentage FM and BMI also had a lower but significant association. Obesity cut-off values recommended by IOTF failed to detect a single case of obesity in either group. However, NCHS and BMI-Z cut-offs detected cases of obesity with low sensitivity. Conclusions: BMI is a poor indicator of percentage fat and the commonly used cut-off values were not sensitive enough to detect cases of childhood obesity in this study. In order to improve the diagnosis of obesity, either BMI cut-off values should be revised to increase the sensitivity or the possibility of using other indirect methods of estimating the %FM should be explored.

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Objective: To develop bioelectrical impedance analysis (BIA) equations to predict total body water (TBW) and fat-free mass (FFM) of Sri Lankan children. Subjects/Methods: Data were collected from 5- to 15-year-old healthy children. They were randomly assigned to validation (M/F: 105/83) and cross-validation (M/F: 53/41) groups. Height, weight and BIA were measured. TBW was assessed using isotope dilution method (D2 O). Multiple regression analysis was used to develop preliminary equations and cross-validated on an independent group. Final prediction equation was constructed combining the two groups and validated by PRESS (prediction of sum of squares) statistics. Impedance index (height2/impedance; cm2/Ω), weight and sex code (male = 1; female = 0) were used as variables. Results: Independent variables of the final prediction equation for TBW were able to predict 86.3% of variance with root means-squared error (RMSE) of 2.1l. PRESS statistics was 2.1l with press residuals of 1.2l. Independent variables were able to predict 86.9% of variance of FFM with RMSE of 2.7 kg. PRESS statistics was 2.8 kg with press residuals of 1.4 kg. Bland Altman technique showed that the majority of the residuals were within mean bias±1.96 s.d. Conclusions: Results of this study provide BIA equation for the prediction of TBW and FFM in Sri Lankan children. To the best of our knowledge there are no published BIA prediction equations validated on South Asian populations. Results of this study need to be affirmed by more studies on other closely related populations by using multi-component body composition assessment.

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Objectives: Obesity is a disease with excess body fat where health is adversely affected. Therefore it is prudent to make the diagnosis of obesity based on the measure of percentage body fat. Body composition of a group of Australian children of Sri Lankan origin were studied to evaluate the applicability of some bedside techniques in the measurement of percentage body fat. Methods: Height (H) and weight (W) was measured and BMI (W/H2) calculated. Bioelectrical impedance analysis (BIA) was measured using tetra polar technique with an 800 μA current of 50 Hz frequency. Total body water was used as a reference method and was determined by deuterium dilution and fat free mass and hence fat mass (FM) derived using age and gender specific constants. Percentage FM was estimated using four predictive equations, which used BIA and anthropometric measurements. Results: Twenty-seven boys and 15 girls were studied with mean ages being 9.1 years and 9.6 years, respectively. Girls had a significantly higher FM compared to boys. The mean percentage FM of boys (22.9 ± 8.7%) was higher than the limit for obesity and for girls (29.0 ± 6.0%) it was just below the cut-off. BMI was comparatively low. All but BIA equation in boys under estimated the percentage FM. The impedance index and weight showed a strong association with total body water (r 2 = 0.96, P < 0.001). Except for BIA in boys all other techniques under diagnosed obesity. Conclusions: Sri Lankan Australian children appear to have a high percentage of fat with a low BMI and some of the available indirect techniques are not helpful in the assessment of body composition. Therefore ethnic and/or population specific predictive equations have to be developed for the assessment of body composition, especially in a multicultural society using indirect methods such as BIA or anthropometry.

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Background: A knowledge of energy expenditure in infancy is required for the estimation of recommended daily amounts of food energy, for designing artificial infant feeds, and as a reference standard for studies of energy metabolism in disease states. Objectives: The objectives of this study were to construct centile reference charts for total energy expenditure (TEE) in infants across the first year of life. Methods: Repeated measures of TEE using the doubly labeled water technique were made in 162 infants at 1.5, 3, 6, 9 and 12 months. In total, 322 TEE measurements were obtained. The LMS method with maximum penalized likelihood was used to construct the centile reference charts. Centiles were constructed for TEE expressed as MJ/day and also expressed relative to body weight (BW) and fat-free mass (FFM). Results: TEE increased with age and was 1.40,1.86, 2.64, 3.07 and 3.65 MJ/day at 1.5, 3, 6, 9 and 12 months, respectively. The standard deviations were 0.43, 0.47, 0.52,0.66 and 0.88, respectively. TEE in MJ/kg increased from 0.29 to 0.36 and in MJ/day/kg FFM from 0.36 to 0.48. Conclusions: We have presented centile reference charts for TEE expressed as MJ/day and expressed relative to BW and FFM in infants across the first year of life. There was a wide variation or biological scatter in TEE values seen at all ages. We suggest that these centile charts may be used to assess and possibly quantify abnormal energy metabolism in disease states in infants.

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OBJECTIVE To monitor the seasonal body composition alterations in 18 lightweight rowers (six females, 12 males) across a rowing season incorporating preseason, early competition, competition, and postseason. METHODS Subject age was 23.1 (SD 4.5) years, height 170.8 (5.6) cm (female, 23.5 (3.5) years, 180.5 (2.7) cm (male). Body weight, fat mass, and fat-free mass (FFM) were assessed using dual energy x ray absorptiometry (DXA-L Lunar) and skinfold techniques. Weight control techniques were documented before major regattas by a questionnaire. RESULTS Female body weight was reduced from 61.3 (2.9) to 57.0 (1.1) kg (5.9%), while male body weight was reduced from 75.6 (3.1) to 69.8 (1.6) kg (7.8%) preseason to competition season respectively. These body weight reductions were mirrored by a significant reduction in fat mass as indicated by the sum of skinfolds [female seven sites: 80.9 (8.1) to 68.2 (11.8) mm; male eight sites: 54.2 (8.7) to 41.8 (4.8) mm], percentage body fat [female 22.1 (1.0) to 19.7 (2.4)%; male 10.0 (0.9) to 7.8 (0.8)%], and total fat [female 12.5 (5.2) to 10.9 (1.4) kg; male 7.3 (1.9) to 5.6 (1.8) kg] (DXA). In contrast, no changes were observed in FFM despite a season of intensive rowing training. Seasonal body weight control was achieved through reduced total energy and dietary fat intakes. Acute body weight reductions were achieved by exercise in 73.3% of participants, food restriction in 71.4%, and fluid restrictions in 62.9%. CONCLUSIONS Seasonal body weight alterations in lightweight rowers are in response to a significant reduction in fat mass. However, the weight restrictions appear to be limiting an increase in FFM which could be beneficial to rowing performance.