The purpose of this thesis was to monitor body composition and energy expenditure changes during weight loss in subjects encouraged to maintain a diet equal to 90% of resting energy expenditure (REE). Over six months, 69 female subjects had REE measured at baseline and weeks 13 and 25 with fortnightly body composition measurements. Subjects lost significant total body mass (17.2 lb) and fat mass (16.7 lb) (p≤.000). Fat-free mass remained stable during the six month period. REE was significantly higher at baseline (1701.1 kcal) than weeks 13 (1576.3 kcal) and 25 (1579.4) (p≤.000); REE at weeks 13 and 25 were similar (p≥.05). Predicted REE at weeks 13 (1671.3 ± 254.7 kcal) and 25 (1658.5 ± 252.4 kcal), compared to measured REE, was significantly lower, 1576.3 kcal and 1579.4 kcal, respectively (p≤.000). Results of this study illustrate that individuals can lose significant amounts of total body mass while preserving fat-free mass and that during active weight loss, there is a metabolic adaptation to reduced caloric intake. / Department of Family and Consumer Sciences

The purpose of this study was to determine the effect of 100% cotton underwear worn beneath a swimsuit on the accuracy and reliability of percent body fat measurements in the BOD POD. Sixty adults (30 males, 30 females) of various ages (1887 years) and body composition (1.95-57.15%) were tested four times in one day. Subjects wore a swimsuit and swimcap for two trials and 100% cotton underwear beneath the swimsuit and a swimcap for the remaining trials. The clothing order was randomized. Thoracic gas volume was predicted. ANOVA found no significant difference between the swimsuit only trials (25.4+12.4%) and swimsuit with underwear trials (25.1+12.3%) for all subjects. Intra-class correlation coefficients were 0.994 and 0.995 for the swimsuit only and swimsuit with underwear trials, respectively. In conclusion, these results suggest that wearing 100% cotton underwear beneath a swimsuit is an acceptable practice for fitness laboratories and the reliability was very good. / School of Physical Education

The Relationships Between Real Time Energy Balance, Hunger, and Body Composition Delk A, Benardot D, Nucci A, & Thompson WR. Georgia State University Introduction: Previous research has indicated that hunger is associated with the quantity, volume, and macronutrient composition of food intake. Hunger has never been assessed from the viewpoint of real time energy balance, although there is limited research on hunger and eating frequency. Purpose: The purpose of this study was to evaluate the relationships between real time energy balance, hunger, and body composition in college students between the ages of 18-30. Methods: Participants were assessed for body composition using a Tanita scale and energy balance was determined on an hourly basis using NutriTiming® software. A hunger scale was used to assess participant hunger every hour. Results: There is a statistically significant relationship for the entire population between energy balance average and body fat percent (R= -0.376; P=0.037). Hours spent in energy deficient is positively associated with body fat percent (R=0.467; P=0.008), while hours spent in an optimal energy balance is negatively associated with body fat percent (R= -0.465; P=0.009). Hours spent in an energy balance surplus (+400 kcals) were not significantly associated with body fat percent. However, hours spent in an anabolic state (>0 kcals) was negatively associated with body fat percent (R=-.457; P=.010). Conversely, hours spent in a catabolic state (<0 kcals) were positively associated with body fat percent (R=.457; P=0.10). Using linear regression analysis with body fat percentage as the dependent variables and age, height, weight, gender, and hours in optimal energy balance, we determined that we could predict a large amount of variance in body fat percentage (R= .931; P= <.001). The only time during the day that there was a significant correlation between body fat percent and hunger was at 5pm (R= -0.391, P = 0.029). Conclusions: These data suggest that that the more time spent in energy deficit is associated with a higher body fat percent. This should encourage college students between the age of 18-30 to avoid restrictive eating patterns and strive to maintain optimal energy balance in order to achieve a low body fat percent.

In South Africa a remarkable weight gain is found in black adolescent girls during mid-adolescence, which is not necessarily the case among boys (Kalk, 2001:577) . Anthropometry is one of the most basic methods for determining over-nutrition and malnutrition status. A considerable amount of research is indeed done on obesity, and quite an amount on growth stunting (OS), but few interventions exist for prevention and treatment of OS. The World Health Organization (WHO) has determined that approximately 230 million children world wide are growth stunted (OS) (WHO working group, 1986). Physical activity in children is affected by average or serious malnutrition and influences adolescents' body build and body composition (BC) because they are in a period of development. Hoffman et al. (2006), Mantsena et al. (2005) and Monyeki et al. (2005) have all found that OS children/adolescents are shorter in length and lighter in mass than adolescents that grow normally. But most OS adolescents have shown a higher skin fold-fat percentage as well as a higher body mass index (BMI). Intra-abdominal fat storage is also found in OS adolescents and children, which is a health risk. Cross sectional studies show that physical activity (p A) decrease with up to 50% during adolescence, which influences body composition. Research has indicated that a P A participation peak is reached between aged 13 and 14 years, when boys are more active than girls. What is less clear is how the pattern of adolescent obesity differs in terms of race, gender and age (Popkin & Udry, 1998). Firstly, the aim of this study was to determine what the nature of research is that has been undertaken regarding body composition (BC) of OS and malnourished adolescents in Africa and South America, by means of a literature study. The second aim was to determine which body composition variables best describe changes in BC in adolescents (13-18 years) after participation in a physical activity intervention. Thirdly, the aim was to determine which BC, relations and maturation differences are found between OS and non growth stunted (NOS) adolescents between ages 13 and 18 years. Finally, the aim was to establish whether the physical activity levels and physical activity patterns of adolescents (13 to 18 years) change congruent to age increase. The study was compiled by means of an availability sample by making use of two secondary black schools in Ikageng (Potchefstroom) in the North West Province. The availability sample comprised a control group and an experimental group of black learners each. The study was of a longitudinal study design nature which stretched from March 2004 to September 2006. Adolescents (N=309) in the North West Province (Potchefstroom, South Africa (158 boys, 211 girls) between ages 13 and 18 years were used in this study. All the learners were in grade 8 at the onset of the study 2004. The experimental group participated in a physical activity intervention programme for practically one hour, two days per week after school hours for twenty-three weeks in 2004 and in 2005 they practised three times per week for nineteen weeks (July school holiday excluded). Attendance percentage of the PA programme was noted according to attendance registers with the experimental group split into three categories, namely low (0%-30% attended), average (30%-60%) and high (60% and higher). The control group (N=87) attended no intervention program. BC, middle-to-hip ratio (MHR), body mass index (BMI), percentage body fat (% LV) and skin folds were measured for baseline and again after completion of the intervention programme. Maturation phase was determined by means of two gender specific questionnaires (Tanner Questionnaires). The Previous Physical Activity Recall (PDPAR), compiled by Trost et al. (1999), was used for the study to analyse the PA levels. Statistica (Statsoft Inc 9) and SAS (SAS Institute Inc, edition 8, Cary NC) computer processing packages were used to process the data collected. Descriptive statistics were used to represent BC components and participants. A Repeated measurements co-variance analysis (ANCOVA) (corrected for attendance percentage and gender) variance analysis (ANOVA) over time, with a Bonferroni post hoc analysis to establish how the different variables differ from each other over the various test period in months. The significance of differences found was set on p<0.05. Next the Mann-Whitney U test was applied to calculate the significant differences of certain variables between the GS and non-growth stunted (NGS) adolescents. The Chi-square test was also used to determine the categorical variables, namely differences in the distribution within the five Tanner phases, as well as the differences between the GS and NGS girls and boys separately, with regard to the distribution between the groups with a body fat percentage lower or higher than the median. The technique of multilevel modelling was used for analysing the change in PA data over time. The result gained from the literature clearly indicates that GS generally occurs in adolescents and children in developing countries. It was also found that physical activity is. beneficial to the adolescents in terms of body composition, especially for the boys. According to the body mass index (BM!) values, a small percentage of children are classified as overweight, whilst with methods such as the sum of skin folds calculation of skin fold fat percentage and %BF measured by means of air transfer pletismografie (ADP), a larger percentage of children was classified as "over fat". It has also been found that significant differences occurred between the mass, length, length-for-age-z-score (LOZ) , arm span, middle circumference, hip circumference and lean body mass of the GS (28 girls and 28 boys) and NGS (113 girls and 90 boys) groups. The results also indicated a difference in PA levels of boys in the experimental and control groups after participation in the P A programme. With increase in age and over time there was a decrease in weekend physical activity patterns in both groups (experimental and control) for both genders. The experimental group ended at higher PA level than that of the control group of boys over the 30.75 months period. Opposed to this the girls (152 and 59 subjects respectively) did indeed show significant differences during the week as well as during the weekend with the baseline measurements, whereas the experimental group initially showed higher PA levels. These differences were, however, not more significant during end measurements. Both groups of girls further showed a lower curve of PA than that of the boys. The experimental group of boys and girls, as well as the control groups displayed a decrease in PA over the 30.75 months period. With increase in age and over time, a decrease was observed in PA patterns in both groups for both genders, although the last two measurements showed a slight upward inclination, especially in the experimental group of boys. The results showed a difference in PA patterns in the boys in the experimental and control groups, which can be attributed to the PA intervention. From the literature overview the conclusion can be drawn that African countries and other developing countries, where food scarcity is more common, experience a larger extent of problems with GS. The occurrence of GS in South Africa is average. Hence it can be deduced that growth and development need to be taken into consideration when BC is determined in adolescents. Fat percentage is more sensitive measure of obesity than BMI following participation in a PA intervention programme in town community adolescents. Determining BF percentage by means of skin folds and air replacement pletismografie (ADP) is more accurate than BMI in this specific group of experimental subjects. From this study the conclusion can be drawn that differences occur between GS and NGS adolescents of both genders in certain BC and body proportion components, without a difference in sexual development. With regard to the girls in terms of PA levels, it had another effect as with the boys with the intervention. The experimental group of boys, after 3 years (of which they underwent a PA intervention for 2 years) showed a higher PA level than the control group of boys that did not participate in a PA intervention. From this it can be deduced that this intervention did indeed contribute to differences in PA of boys that participate in physical activity programmes in deprived environments, while strategies different from these will need to be developed for girls from these communities. / Thesis (Ph.D. (Human Movement Science))--North-West University, Potchefstroom Campus, 2010.

The objectives of this study was to examine the efficacy and safety of graded doses of c9, t11, t10, c12 CLA isomers on body composition, energy expenditure, lipid profile and hepatic biomarkers in hamsters. Male Golden Syrian hamsters (n=105) were randomized to seven treatments (control; 1, 2, 3% of c9, t11; 1, 2, 3% of t10, c12) for 28 days. Compared with control, 1% and 3% t10, c12 had lowered food intake with all three doses of t10, c12 lowering (p<0.0001) body fat mass (g). Groups fed with 1, 2, 3% t10, c12 and 3% c9, t11 treatments showed higher lean mass compared to control and other treatment groups. However, neither body weights, nor serum HDL or triglyceride levels differed across treatment groups. The 3% t10, c12 groups exhibited higher (p<0.0001) cholesterol and LDL-C levels compared to control or other treatment groups. The 2% and 3% t10, c12 groups also presented elevated ALT level (p<0.05). The present data suggest that 3% t10, c12 possess potential adverse effects on liver and posing unfavorable change in lipid profile.

PURPOSE: To establish the reliability of anthropometric and dual energy X-ray absorptiometry(DXA) techniques used to assess percent body fat (% BF)in female athletes; to establish limits for detecting the smallest real change in % BF associated with anthropometric and DXA testing;to evaluate the validity of commonly used % BF prediction equations recommended by national certification programs along with equations derived from Multicompartment (MC), and DXA, in female athletes; and to create a new DXA based regression equation for elite female athletes. METHODS:Female athletes aged 17-31 were recruited into the study and participated in the establishment of anthropometric reliability (N=20), DXA reliability (N=32), and /or skinfold validity (N=95) testing. Anthropometric testing consisted of measurements of skinfolds,circumferences, and breadths. DXA measurements were conducted using a GE Lunar Prodigy DXA which served as the criterion measure (% BF DXA). RESULTS: Excellent reliability for both anthropometric sum5 skinfolds (ICC= .997, %TEM=0.9 %) and DXA (ICC =.996, CV =1.13% BF) techniques allows for detection of smallest real differences of 2.2 mm and 721g in summed skinfolds (sum5) and fat mass respectively. The DXA based equation of Ball et al.(2004) displayed the greatest validity of existing equations R=.874, total error (TE) 2.9% BF, and Bland Altman Limits of Agreement -4.7to 6.5 % BF. The newly created regression equation demonstrated a non-linear characteristic and displayed similar predictive ability R= .840, TE 3.0%BF, and Bland Altman Limits of Agreement of -6.1to 6.1 % BF. CONCLUSIONS: Anthropometric equations derived from various criteria yielded dissimilar results. Long utilized popular equations advocated in national accreditation schemes (ACSM, CSEP) show considerable bias compared to modern values obtained by current DXA technology. A new regression equation was created for female Canadian athletes 17-31yrs of age using skinfolds taught in the Canadian national professional certification program (CSEP).

In South Africa a remarkable weight gain is found in black adolescent girls during mid-adolescence, which is not necessarily the case among boys (Kalk, 2001:577) . Anthropometry is one of the most basic methods for determining over-nutrition and malnutrition status. A considerable amount of research is indeed done on obesity, and quite an amount on growth stunting (OS), but few interventions exist for prevention and treatment of OS. The World Health Organization (WHO) has determined that approximately 230 million children world wide are growth stunted (OS) (WHO working group, 1986). Physical activity in children is affected by average or serious malnutrition and influences adolescents' body build and body composition (BC) because they are in a period of development. Hoffman et al. (2006), Mantsena et al. (2005) and Monyeki et al. (2005) have all found that OS children/adolescents are shorter in length and lighter in mass than adolescents that grow normally. But most OS adolescents have shown a higher skin fold-fat percentage as well as a higher body mass index (BMI). Intra-abdominal fat storage is also found in OS adolescents and children, which is a health risk. Cross sectional studies show that physical activity (p A) decrease with up to 50% during adolescence, which influences body composition. Research has indicated that a P A participation peak is reached between aged 13 and 14 years, when boys are more active than girls. What is less clear is how the pattern of adolescent obesity differs in terms of race, gender and age (Popkin & Udry, 1998). Firstly, the aim of this study was to determine what the nature of research is that has been undertaken regarding body composition (BC) of OS and malnourished adolescents in Africa and South America, by means of a literature study. The second aim was to determine which body composition variables best describe changes in BC in adolescents (13-18 years) after participation in a physical activity intervention. Thirdly, the aim was to determine which BC, relations and maturation differences are found between OS and non growth stunted (NOS) adolescents between ages 13 and 18 years. Finally, the aim was to establish whether the physical activity levels and physical activity patterns of adolescents (13 to 18 years) change congruent to age increase. The study was compiled by means of an availability sample by making use of two secondary black schools in Ikageng (Potchefstroom) in the North West Province. The availability sample comprised a control group and an experimental group of black learners each. The study was of a longitudinal study design nature which stretched from March 2004 to September 2006. Adolescents (N=309) in the North West Province (Potchefstroom, South Africa (158 boys, 211 girls) between ages 13 and 18 years were used in this study. All the learners were in grade 8 at the onset of the study 2004. The experimental group participated in a physical activity intervention programme for practically one hour, two days per week after school hours for twenty-three weeks in 2004 and in 2005 they practised three times per week for nineteen weeks (July school holiday excluded). Attendance percentage of the PA programme was noted according to attendance registers with the experimental group split into three categories, namely low (0%-30% attended), average (30%-60%) and high (60% and higher). The control group (N=87) attended no intervention program. BC, middle-to-hip ratio (MHR), body mass index (BMI), percentage body fat (% LV) and skin folds were measured for baseline and again after completion of the intervention programme. Maturation phase was determined by means of two gender specific questionnaires (Tanner Questionnaires). The Previous Physical Activity Recall (PDPAR), compiled by Trost et al. (1999), was used for the study to analyse the PA levels. Statistica (Statsoft Inc 9) and SAS (SAS Institute Inc, edition 8, Cary NC) computer processing packages were used to process the data collected. Descriptive statistics were used to represent BC components and participants. A Repeated measurements co-variance analysis (ANCOVA) (corrected for attendance percentage and gender) variance analysis (ANOVA) over time, with a Bonferroni post hoc analysis to establish how the different variables differ from each other over the various test period in months. The significance of differences found was set on p<0.05. Next the Mann-Whitney U test was applied to calculate the significant differences of certain variables between the GS and non-growth stunted (NGS) adolescents. The Chi-square test was also used to determine the categorical variables, namely differences in the distribution within the five Tanner phases, as well as the differences between the GS and NGS girls and boys separately, with regard to the distribution between the groups with a body fat percentage lower or higher than the median. The technique of multilevel modelling was used for analysing the change in PA data over time. The result gained from the literature clearly indicates that GS generally occurs in adolescents and children in developing countries. It was also found that physical activity is. beneficial to the adolescents in terms of body composition, especially for the boys. According to the body mass index (BM!) values, a small percentage of children are classified as overweight, whilst with methods such as the sum of skin folds calculation of skin fold fat percentage and %BF measured by means of air transfer pletismografie (ADP), a larger percentage of children was classified as "over fat". It has also been found that significant differences occurred between the mass, length, length-for-age-z-score (LOZ) , arm span, middle circumference, hip circumference and lean body mass of the GS (28 girls and 28 boys) and NGS (113 girls and 90 boys) groups. The results also indicated a difference in PA levels of boys in the experimental and control groups after participation in the P A programme. With increase in age and over time there was a decrease in weekend physical activity patterns in both groups (experimental and control) for both genders. The experimental group ended at higher PA level than that of the control group of boys over the 30.75 months period. Opposed to this the girls (152 and 59 subjects respectively) did indeed show significant differences during the week as well as during the weekend with the baseline measurements, whereas the experimental group initially showed higher PA levels. These differences were, however, not more significant during end measurements. Both groups of girls further showed a lower curve of PA than that of the boys. The experimental group of boys and girls, as well as the control groups displayed a decrease in PA over the 30.75 months period. With increase in age and over time, a decrease was observed in PA patterns in both groups for both genders, although the last two measurements showed a slight upward inclination, especially in the experimental group of boys. The results showed a difference in PA patterns in the boys in the experimental and control groups, which can be attributed to the PA intervention. From the literature overview the conclusion can be drawn that African countries and other developing countries, where food scarcity is more common, experience a larger extent of problems with GS. The occurrence of GS in South Africa is average. Hence it can be deduced that growth and development need to be taken into consideration when BC is determined in adolescents. Fat percentage is more sensitive measure of obesity than BMI following participation in a PA intervention programme in town community adolescents. Determining BF percentage by means of skin folds and air replacement pletismografie (ADP) is more accurate than BMI in this specific group of experimental subjects. From this study the conclusion can be drawn that differences occur between GS and NGS adolescents of both genders in certain BC and body proportion components, without a difference in sexual development. With regard to the girls in terms of PA levels, it had another effect as with the boys with the intervention. The experimental group of boys, after 3 years (of which they underwent a PA intervention for 2 years) showed a higher PA level than the control group of boys that did not participate in a PA intervention. From this it can be deduced that this intervention did indeed contribute to differences in PA of boys that participate in physical activity programmes in deprived environments, while strategies different from these will need to be developed for girls from these communities. / Thesis (Ph.D. (Human Movement Science))--North-West University, Potchefstroom Campus, 2010.

Background: The customary mechanism for assessing weight change involves an assessment of the imbalance in the energy consumed vs. the energy expended. This energy balance ratio is commonly assessed in 24-hour periods, but this strategy fails to account for the timing of macronutrient intake and within-day fluctuations in energy balance, which have an influence on body composition and, ultimately, weight. Hourly fluctuations in energy balance provides information on the time spent in a catabolic state and time spent in an anabolic state, which is not possible with a 24-hour energy balance assessment. Measuring hourly energy balance to optimize absorption and storage of specific nutrients may be a practical strategy for obese individuals to improve body composition. Purpose: The purpose of this study was to observe current dietary habits and assess hourly energy balance of college students with different BMI categories (i.e., below and above a BMI of 30) to determine if there are differences between body composition and hours spent in different energy balance states. Methods: The subjects completed a four-day diet and physical activity record from which energy intake and energy expenditures from a relative intensity activity scale was predicted linked to MET values. After completing the record, subject weight, height, % body fat and fat free mass was assessed using a multi-frequency bioelectrical impedance segmental body composition analyzer. Results: Data were analyzed from a total of 17 college students (9 men and 8 women) ranging from 20-28 years old (mean age 23 ± 2.6). Predicted energy intake averaged 2237.3 ± 749.3 kcals/d and predicted energy expenditure averaged 2941.7 ± 552.7 kcals/d. The average body fat % of the subjects was 27.1 ± 11.6% and the average BMI of the subjects 28.8 ± 5.8. Using an Independent Samples T-Test, eight subjects with a BMI ≥ 30 spent more time in hours high deficit (< -400 kcals Energy Balance) when compared to nine subjects with a BMI < 30. Nine subjects with a BMI < 30 spent more time in ±400 kcal energy balance. Using a Spearman Rho correlation, body fat % was positively correlated to hours high deficit (p ≤ 0.01) and negatively correlated to hours in ±400 kcal energy balance (p ≤ 0.01). Analysis of men and women found that body fat % of men was not significantly associated to any energy balance variables. While not significant, there was a trend toward a positive correlation between body fat % and hours high deficit (p=0.065) and a negative correlation between body fat % and hours in ±400 kcal energy balance (p=0.065). In women, subjects who spent more time in high energy deficit (< -400 kcals Energy Balance) had higher body fat % (p ≤ 0.05). Subjects who spent more hours in optimum energy balance (± 400 kcal Energy Balance) had lower body fat % (p ≤ 0.05). Conclusions: These data suggest that spending long periods of time in an energy deficit is correlated with higher body fat % and higher BMI in college students. Particularly for women, it may be beneficial for body composition to avoid long periods of time in energy deficit and strive to remain in or near ±400 kcal energy balance. College students may be especially prone to extreme deficits in energy balance because of unpredictable schedules and frequent meal skipping. Recommendations for avoiding large energy deficits throughout the day may be beneficial for this population.

Body fat, regional body fat and bone mineral mass, are linked to health conditions such as obesity and osteoporosis. The ethnic comparison of body composition may help to explain and understand the difference of health outcomes and health status in different ethnic groups. NZ Chinese is the largest Asian group in New Zealand, however, knowledge about health risks and body composition for NZ Chinese is very limited. Therefore, the aims of this thesis were: 1) To compare the relationships between body mass index (BMI) and percentage body fat (%BF) of European (M29, F37), Maori (M23, F23), Pacific people (M15, F23), and Asian Indian (M29, F25) (existing data) with NZ Chinese aged 30-39 years; 2) To compare fat distribution, appendicular skeletal muscle mass (ApSM), bone mineral density (BMD) and limb bone lengths across these five ethnic groups. A convenience sample of healthy NZ Chinese (M20, F23) was selected by BMI to cover a wide range of body fatness. Total and regional body fat, fat free mass (FFM) and bone mineral content were measured by whole-body Dual-energy X-ray absorptiometry (DEXA). The main study findings were: • For a fixed BMI, NZ Chinese had a higher %BF than European and less %BF than Asian Indian. At a %BF equivalent to a BMI of 30 kg.m-2 in Europeans (WHO threshold for obesity), BMI values for Asian Indian and NZ Chinese women were 5.8 and 2.2 BMI units lower than European, respectively, and for Asian Indian and NZ Chinese men, 8.2 and 3.0 BMI units lower. • Abdominal-to-thigh fat ratio of NZ Chinese was significantly higher than that of European (P<0.001) and similar to that of Asian Indian. NZ Chinese had a significantly higher central-to-appendicular fat ratio than both Asian Indian and European (P<0.001). NZ Chinese was centrally fatter than European and Asian Indian. • For the same height and weight, NZ Chinese had significantly less FFM (-2.1 kg, P=0.039) and ApSM (-1.4kg, P=0.007) than European. NZ Chinese had significantly more FFM (+3.2 kg, P=0.001) than Asian Indian and similar ApSM to Asian Indian. • For the same weight, NZ Chinese had a similar BMD as European for female and male. NZ Chinese male had a higher BMD (+0.07 g.cm-2, P= 0.001) than Asian Indian male. • Among the five ethnic groups, NZ Chinese had the shortest leg (-1.5cm, P=0.016) and arm bone lengths (-2.3cm, P=0.001) (measured by DEXA) for the same DEXA height. Therefore, the relationship between percent body fat and BMI for Asian Indian and NZ Chinese differs from Europeans and from each other, which indicates that different BMI thresholds for obesity may be required for these Asian ethnic groups. Given the relatively high percentage body fat, low appendicular skeletal muscle mass and high central fat to appendicular fat ratio of NZ Chinese aged 30-39 years demonstrated in this study, promotion of healthy eating and physical activity is needed to be tailored for NZ Chinese. The NZ Chinese community should be advised to keep fit, prevent limited movements in older age, and to prevent obesity and obesity-related diseases.

The high prevalence of overweight and obesity among older Australian adults and their strong association with an increased risk of ill health, functional limitation and disability, are well documented. This thesis examines the assessment and management of overweight and obesity in older adults. Meta-analyses of randomised controlled trials were undertaken to assess the effects of psychological interventions and of exercise on body weight and health. A series of analyses were then undertaken using data from the 1053 participants enrolled in The Tasmanian Older Adult Cohort Study, an ongoing prospective cohort study whose aim is to identify the environmental, genetic and biochemical factors associated with the development and progression of a number of chronic diseases. The purpose of the analyses was to investigate changes in body composition (measured using dual-energy X-ray absorptiometry) that occur with age, the most accurate field methods for assessing body composition in different age groups, the influence of lifestyle risk factors on body composition, and the complex interrelationships between age, lifestyle, body composition and cardiovascular disease risk factors. Results demonstrate that body fat increases and lean body mass decreases with increasing age in older adults. The most accurate field methods for assessing body composition in older adults are body mass index (BMI) and waist circumference. Lean body mass is predominantly influenced by age in older adults and decreases as age increases. Body fat, however, is predominantly influenced by lifestyle risk factors. Physical activity levels, smoking and alcohol consumption in females are associated with lower body fat, whereas the presence of chronic pain and alcohol consumption in males are associated with higher body fat. In younger and middle aged adults, meta-analyses of randomised controlled trials demonstrate that exercise is an effective weight loss intervention, particularly when combined with low fat or low calorie diets. Exercise also improves factors commonly associated with cardiovascular disease, even in the absence of weight loss. Meta-analyses of randomised controlled trials also demonstrate that adults who are overweight or obese can reduce weight with psychological interventions, particularly behavioural and cognitive behavioural interventions. In older adults, observational data demonstrate that higher levels of pedometer-determined physical activity are associated with lower body fat, supporting the efficacy of physical activity or an active lifestyle as a weight loss intervention in this group also. The greatest impact of physical activity on body fat is observed when participants increase activity levels to greater than 7 500 steps per day. However, higher levels of physical activity are not associated individually with improved blood pressure, lipids or fasting serum glucose. Instead, higher physical activity levels are associated with a lower total number of cardiovascular risk factors, suggesting that in older adults, physical activity reduces the likelihood of multiple cooccurring cardiovascular disease risk factors. The studies within this thesis provide an evidence base for the continued development of an understanding of the assessment and management of overweight and obesity in older adults. A number of research priorities have also been highlighted. These include the need for long-term randomised controlled clinical trials in older adults in order to: assess the efficacy and safety of multi-component weight loss therapies (diet, physical activity and psychological therapy); determine the combination of physical activity and dietary therapy that will maximize loss of body fat while maintaining lean body mass in older adults for whom weight loss therapy is appropriate; and assess the effect of weight loss, diet and physical activity on clinical outcomes, particularly chronic disease end-points and risk factors in older adults. Longitudinal studies are required to: explore the interrelations between ageing, physical activity levels, body composition and cardiovascular disease risk in older adults; determine the causal relationships that exist between lifestyle risk factors, body composition and chronic disease in older adults; and better assess the effect of alcohol consumption on body composition using sensitive measures in older adults.