Introduction: The World Health Organisation (WHO) defines overweight and obesity as a condition in which an abnormal or excessive fat accumulation exists to an extent in which health and well-being are impaired. The most recent South African National Health and Nutrition Examination Survey (SANHANES) reported that the prevalence of overweight and obesity, according to body mass index (BMI) classification, in all South African women was significantly higher than in men (24.8% and 39.2% compared to 20.1% and 10.6% for women and men, respectively). Blood pressure is often increased in obese patients and is probably the most common co-morbidity associated with obesity. Currently approximately one third (30.4%) of the adult South African population has hypertension. Hypertension is responsible for a significant percentage of the high rates of cardiovascular disease and stroke in South Africa. Limited South African data are available regarding the agreement between the measures of adiposity, including BMI, waist circumference (WC) and percentage body fat (%BF), and the association with high blood pressure. Measures of adiposity were found in previous research to be ethnicity, age and gender specific. Measuring %BF to classify adiposity takes body composition into account and is a more physiological measurement of obesity than BMI. Objective: This study aimed to investigate the agreement between adiposity classified by BMI categories and %BF cut-off points, and the association between the different measures of adiposity and high blood pressure. Method: A representative sample of black women (n=435), aged 29 years to 65 years from Ikageng in the North West Province of South Africa were included in this cross-sectional epidemiological study. Socio-demographic questionnaires were completed. Pregnancy and HIV tests were performed and those with positive test results or those who declined HIV testing were excluded. Weight and height were measured and BMI was calculated. WC, %BF using dual-energy X-ray absorptiometry (DXA), and blood pressure were measured. Results: The prevalence of overweight (BMI 25.0 kg/m² – 29.9 kg/m²) was 24.4% and obesity (BMI ≥ 30kg/m²) was 52.4%. High blood pressure was found to be present in more than two thirds of the study participants (68.5%). In this study BMI, WC and %BF as measures of adiposity were significantly correlated. There were significant agreements between combined overweight/obesity that was defined by %BF (≥35.8% 29-45 years; ≥37.7% ≥50 years) and BMI ≥ 25kg/m² (ᵡ²=199.0, p<0.0001; κ=0.68, p<0.0001), and between the presence of high %BF and obesity only, that was defined by BMI ≥ 30 kg/m² (ᵡ²=129.1, p<0.0001; κ=0.48, p<0.0001). The effect size of the agreement between the WHO BMI category for combined overweight/obesity and %BF cut-off points according to the kappa value of κ=0.68 was substantial (κ range 0.61-0.80). The effect size of the agreement between the WHO BMI category for obesity only and %BF cut-off points according to the kappa value of κ=0.48 was moderate (κ range 0.41-0.60). No association was found between high blood pressure and BMI categorised combined overweight/obesity (ᵡ²=3.19; p=0.74), but a significant association was found between high blood pressure and BMI categorised obesity only (ᵡ²=4.10; p=0.043). A significantly increased odds ratio (OR) of high blood pressure existed in the obesity BMI category (OR=1.52; p=0.045) as opposed to the overweight/obesity BMI category (OR=1.51; p=0.075). There were significant associations between high blood pressure and WC ≥ 80cm (ᵡ²=10.9; p=0.001; OR=2.08; p=0.001), WC ≥ 92cm (ᵡ²=20.1; p<0.0001; OR=1.79; p=0.011) and %BF above the age-specific cut-off points (ᵡ²=6.61; p=0.010; OR=1.70; p=0.011). Discussion and conclusion: This study found that in a sample of black urban South African women significant agreements existed between adiposity defined by %BF cut-off points for combined overweight/obesity and both WHO BMI categorised combined overweight/obesity (BMI ≥ 25 kg/m2) and obesity only (BMI ≥ 30 kg/m2), respectively. A stronger agreement was found between WHO categorised combined overweight/obesity and %BF. Furthermore, this study concluded that the BMI category according to the WHO cut-off point for overweight/obesity had insufficient sensitivity to detect the presence of high blood pressure, and that the BMI category according to the WHO cut-off point for obesity alone could detect the presence of high blood pressure. The WHO BMI classification for obesity, in contrast to the WHO BMI classification for combined overweight/obesity, is therefore appropriate to classify these black South African women at increased risk for high blood pressure. The WC and %BF cut-off points used which were specific to ethnicity, age and gender, had significant associations with high blood pressure and have good capacity to detect high blood pressure. In this study abdominal obesity as defined by the South African cut-off point of WC ≥ 92 cm had a stronger association with high blood pressure, than the international cut-off point (WC ≥ 80 cm). The South African cut-off point is, therefore, more appropriate to screen black South African women for increased risk for high blood pressure. The study therefore concluded that a stronger agreement was found between WHO categorised combined overweight/obesity and %BF than with obesity only (BMI ≥ 30 kg/m2). To ensure consistency and accuracy, and to take body composition into consideration, it is recommended that, where possible, in clinical practice the appropriate WC and %BF cut-off points together with BMI categories should be used as measures of adiposity for diagnosis of overweight and obesity and to screen or detect an increased risk for high blood pressure. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2015

Introduction: The World Health Organisation (WHO) defines overweight and obesity as a condition in which an abnormal or excessive fat accumulation exists to an extent in which health and well-being are impaired. The most recent South African National Health and Nutrition Examination Survey (SANHANES) reported that the prevalence of overweight and obesity, according to body mass index (BMI) classification, in all South African women was significantly higher than in men (24.8% and 39.2% compared to 20.1% and 10.6% for women and men, respectively). Blood pressure is often increased in obese patients and is probably the most common co-morbidity associated with obesity. Currently approximately one third (30.4%) of the adult South African population has hypertension. Hypertension is responsible for a significant percentage of the high rates of cardiovascular disease and stroke in South Africa. Limited South African data are available regarding the agreement between the measures of adiposity, including BMI, waist circumference (WC) and percentage body fat (%BF), and the association with high blood pressure. Measures of adiposity were found in previous research to be ethnicity, age and gender specific. Measuring %BF to classify adiposity takes body composition into account and is a more physiological measurement of obesity than BMI. Objective: This study aimed to investigate the agreement between adiposity classified by BMI categories and %BF cut-off points, and the association between the different measures of adiposity and high blood pressure. Method: A representative sample of black women (n=435), aged 29 years to 65 years from Ikageng in the North West Province of South Africa were included in this cross-sectional epidemiological study. Socio-demographic questionnaires were completed. Pregnancy and HIV tests were performed and those with positive test results or those who declined HIV testing were excluded. Weight and height were measured and BMI was calculated. WC, %BF using dual-energy X-ray absorptiometry (DXA), and blood pressure were measured. Results: The prevalence of overweight (BMI 25.0 kg/m² – 29.9 kg/m²) was 24.4% and obesity (BMI ≥ 30kg/m²) was 52.4%. High blood pressure was found to be present in more than two thirds of the study participants (68.5%). In this study BMI, WC and %BF as measures of adiposity were significantly correlated. There were significant agreements between combined overweight/obesity that was defined by %BF (≥35.8% 29-45 years; ≥37.7% ≥50 years) and BMI ≥ 25kg/m² (ᵡ²=199.0, p<0.0001; κ=0.68, p<0.0001), and between the presence of high %BF and obesity only, that was defined by BMI ≥ 30 kg/m² (ᵡ²=129.1, p<0.0001; κ=0.48, p<0.0001). The effect size of the agreement between the WHO BMI category for combined overweight/obesity and %BF cut-off points according to the kappa value of κ=0.68 was substantial (κ range 0.61-0.80). The effect size of the agreement between the WHO BMI category for obesity only and %BF cut-off points according to the kappa value of κ=0.48 was moderate (κ range 0.41-0.60). No association was found between high blood pressure and BMI categorised combined overweight/obesity (ᵡ²=3.19; p=0.74), but a significant association was found between high blood pressure and BMI categorised obesity only (ᵡ²=4.10; p=0.043). A significantly increased odds ratio (OR) of high blood pressure existed in the obesity BMI category (OR=1.52; p=0.045) as opposed to the overweight/obesity BMI category (OR=1.51; p=0.075). There were significant associations between high blood pressure and WC ≥ 80cm (ᵡ²=10.9; p=0.001; OR=2.08; p=0.001), WC ≥ 92cm (ᵡ²=20.1; p<0.0001; OR=1.79; p=0.011) and %BF above the age-specific cut-off points (ᵡ²=6.61; p=0.010; OR=1.70; p=0.011). Discussion and conclusion: This study found that in a sample of black urban South African women significant agreements existed between adiposity defined by %BF cut-off points for combined overweight/obesity and both WHO BMI categorised combined overweight/obesity (BMI ≥ 25 kg/m2) and obesity only (BMI ≥ 30 kg/m2), respectively. A stronger agreement was found between WHO categorised combined overweight/obesity and %BF. Furthermore, this study concluded that the BMI category according to the WHO cut-off point for overweight/obesity had insufficient sensitivity to detect the presence of high blood pressure, and that the BMI category according to the WHO cut-off point for obesity alone could detect the presence of high blood pressure. The WHO BMI classification for obesity, in contrast to the WHO BMI classification for combined overweight/obesity, is therefore appropriate to classify these black South African women at increased risk for high blood pressure. The WC and %BF cut-off points used which were specific to ethnicity, age and gender, had significant associations with high blood pressure and have good capacity to detect high blood pressure. In this study abdominal obesity as defined by the South African cut-off point of WC ≥ 92 cm had a stronger association with high blood pressure, than the international cut-off point (WC ≥ 80 cm). The South African cut-off point is, therefore, more appropriate to screen black South African women for increased risk for high blood pressure. The study therefore concluded that a stronger agreement was found between WHO categorised combined overweight/obesity and %BF than with obesity only (BMI ≥ 30 kg/m2). To ensure consistency and accuracy, and to take body composition into consideration, it is recommended that, where possible, in clinical practice the appropriate WC and %BF cut-off points together with BMI categories should be used as measures of adiposity for diagnosis of overweight and obesity and to screen or detect an increased risk for high blood pressure. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2015

Introdução: A medida do percentual de gordura corporal (PGC) sofre a influência de diversos fatores (obesidade severa, acúmulo excessivo de gordura no abdomen, hidratação, etc), dependendo da técnica utilizada, podendo comprometer o desempenho das mesmas. Muitos destes fatores estão frequentemente presentes nos pacientes com DM tipo 2, o que torna essencial o estudo da acurácia destes métodos nesta população. Objetivo: Avaliar a Bioimpedância (BIA) e as Dobras Cutâneas (DC) como métodos de estimativa da gordura corporal em pacientes com DM tipo 2, comparando-os com a Absorciometria de Raios X de Dupla Energia (DXA), como método de referência. Métodos: Neste estudo de acurácia diagnóstica, os pacientes foram submetidos à avaliação da composição corporal através da BIA (InBody 230, Biospace, Coréia), das DC (Lange, Fórmulas de Petroski e de Durnin) e da DXA (Lunar - iDXA). Para avaliação clínica foram analisados o controle metabólico (glicêmico e perfil lipídico) e pressórico e pesquisadas as complicações crônicas do DM. Resultados. Foram avaliados 133 pacientes (76 mulheres; idade: 63,6 ± 9,1 anos, duração do DM: 15,5 ± 10,3 anos; IMC: 29,2 ± 3,6), sendo que o PGC médio foi de 42,4 ± 4,8% nas mulheres e 31,1 ± 4,7% nos homens (p<0,001). A correlação do PGC estimado pela BIA e pelas DC com o estimado pela DXA foi, respectivamente r=0,93 (p<0,001) e r=0,81 (p<0,001). A BIA subestimou o PGC em 1,4 ± 3,2 (p<0,05) nas mulheres e 2,3 ± 3,3% (p<0,05) nos homens, quando comparada a DXA, sendo estas diferenças menos acentuadas nos pacientes com IMC≥ 30 kg/m2 (Gráficos de Bland-Altman). As DC subestimaram o PGC quando calculado com a Fórmula de Petroski, (3,7 ± 4,0% [p<0,05] nas mulheres e 1,55 ± 3,8% [p<0,05] nos homens) e superestimaram quando calculado com a Fórmula de Durnin ajustada para a idade, sendo que este ultimo apenas nas mulheres (1,8 ± 4,5% [p<0,05]). Na análise das curvas ROC, a área sob a curva da BIA foi 0,945 nas mulheres e 0,897 nos homens. Para as DC, utilizando as diferentes fórmulas, as áreas sob a curva variaram de 0,611 a 0,673 nas mulheres e foram 0,960 nos homens. Conclusão: Para a avaliação da composição corporal de pacientes com DM tipo 2, tanto a BIA como as DC (dependendo da fórmula) subestimam o PGC, comparados a DXA, mas em valores não clinicamente relevantes. A BIA apresentou uma boa acurácia em ambos sexos. Já a medida pelas DC mostrou acurácia semelhante, mas apenas nos homens. / Objective. To evaluate the performance of bioimpedance (BIA) and skinfold thickness as methods to estimate percentage body fat (PBF) in patients with Type 2 diabetes, comparing them to Dual Energy X-Ray Absorptiometry (DXA), as a reference standard. Research Design and Methods. In this study of diagnostic accuracy, the patients were submitted to evaluation of body composition with BIA (InBody 230, Biospace, Korea), skinfold thickness (Lange caliper) and DXA (Lunar - iDXA). PBF estimated by skinfold thickness was calculated with three equations: Petroski, Durnin & Womersley (DW) gender-adjusted and DW age-adjusted. Clinical evaluation consisted of the metabolic (glycemic and lipid profile) and blood pressure control, as well as the search for diabetic chronic complications. Results. One hundred and thirty-three patients were evaluated (76 women; age: 63.6 ± 9.1 years, duration of diabetes: 15.5 ± 10.3 years; body mass index [BMI]: 29.2 ± 3.6 kg/m2). PBF estimated by DXA was 42.4 ± 4.8% in women and 31.1 ± 4.7% in men (p<0.001). The correlation of the PBF estimated by BIA and by skinfold thickness with that estimated by DXA was, respectively, 0.93 (p<0.001) and 0.81 (p<0.001). BIA underestimated the PBF at 1.4 ± 3.2 (p<0.05) in women and 2.3 ± 3.3% (p<0.05) in men, compared to DXA, and these differences were less pronounced in patients with BMI ≥ 30 kg/m2 (Bland-Altman Plots). PBF calculated by Petroski’s equations was underestimated in 3.7 ± 4.0% [p<0,05] in women and 1.55 ± 3.8% [p<0.05] in men; and overestimated in 1.8 ± 4.5% [p<0.05] when calculated using DW equations age-adjusted only in women. The area under the ROC curves for BIA as a method to identify patients with increased PBF was 0.945 (p<0.001) in women and 0.897 (p<0.001) in men. The area under the ROC curves for skinfold thickness varied from 0.611 to 0.673 (all p>0.05) in women and was 0.960 (all P<0,05) in men. Conclusion. In patients with type 2 diabetes, both BIA and skinfold thickness underestimated PBF, when compared to DXA, at values that ranged from 1.4 to 2.3% and 1.5 to 4.5%, respectively. BIA was accurate in both sexes as a method to estimate PBF and to identify patients with increased PBF. On the other hand, PBF estimated by skinfold thickness was similarly accurate, but only in males.

Introdução: A medida do percentual de gordura corporal (PGC) sofre a influência de diversos fatores (obesidade severa, acúmulo excessivo de gordura no abdomen, hidratação, etc), dependendo da técnica utilizada, podendo comprometer o desempenho das mesmas. Muitos destes fatores estão frequentemente presentes nos pacientes com DM tipo 2, o que torna essencial o estudo da acurácia destes métodos nesta população. Objetivo: Avaliar a Bioimpedância (BIA) e as Dobras Cutâneas (DC) como métodos de estimativa da gordura corporal em pacientes com DM tipo 2, comparando-os com a Absorciometria de Raios X de Dupla Energia (DXA), como método de referência. Métodos: Neste estudo de acurácia diagnóstica, os pacientes foram submetidos à avaliação da composição corporal através da BIA (InBody 230, Biospace, Coréia), das DC (Lange, Fórmulas de Petroski e de Durnin) e da DXA (Lunar - iDXA). Para avaliação clínica foram analisados o controle metabólico (glicêmico e perfil lipídico) e pressórico e pesquisadas as complicações crônicas do DM. Resultados. Foram avaliados 133 pacientes (76 mulheres; idade: 63,6 ± 9,1 anos, duração do DM: 15,5 ± 10,3 anos; IMC: 29,2 ± 3,6), sendo que o PGC médio foi de 42,4 ± 4,8% nas mulheres e 31,1 ± 4,7% nos homens (p<0,001). A correlação do PGC estimado pela BIA e pelas DC com o estimado pela DXA foi, respectivamente r=0,93 (p<0,001) e r=0,81 (p<0,001). A BIA subestimou o PGC em 1,4 ± 3,2 (p<0,05) nas mulheres e 2,3 ± 3,3% (p<0,05) nos homens, quando comparada a DXA, sendo estas diferenças menos acentuadas nos pacientes com IMC≥ 30 kg/m2 (Gráficos de Bland-Altman). As DC subestimaram o PGC quando calculado com a Fórmula de Petroski, (3,7 ± 4,0% [p<0,05] nas mulheres e 1,55 ± 3,8% [p<0,05] nos homens) e superestimaram quando calculado com a Fórmula de Durnin ajustada para a idade, sendo que este ultimo apenas nas mulheres (1,8 ± 4,5% [p<0,05]). Na análise das curvas ROC, a área sob a curva da BIA foi 0,945 nas mulheres e 0,897 nos homens. Para as DC, utilizando as diferentes fórmulas, as áreas sob a curva variaram de 0,611 a 0,673 nas mulheres e foram 0,960 nos homens. Conclusão: Para a avaliação da composição corporal de pacientes com DM tipo 2, tanto a BIA como as DC (dependendo da fórmula) subestimam o PGC, comparados a DXA, mas em valores não clinicamente relevantes. A BIA apresentou uma boa acurácia em ambos sexos. Já a medida pelas DC mostrou acurácia semelhante, mas apenas nos homens. / Objective. To evaluate the performance of bioimpedance (BIA) and skinfold thickness as methods to estimate percentage body fat (PBF) in patients with Type 2 diabetes, comparing them to Dual Energy X-Ray Absorptiometry (DXA), as a reference standard. Research Design and Methods. In this study of diagnostic accuracy, the patients were submitted to evaluation of body composition with BIA (InBody 230, Biospace, Korea), skinfold thickness (Lange caliper) and DXA (Lunar - iDXA). PBF estimated by skinfold thickness was calculated with three equations: Petroski, Durnin & Womersley (DW) gender-adjusted and DW age-adjusted. Clinical evaluation consisted of the metabolic (glycemic and lipid profile) and blood pressure control, as well as the search for diabetic chronic complications. Results. One hundred and thirty-three patients were evaluated (76 women; age: 63.6 ± 9.1 years, duration of diabetes: 15.5 ± 10.3 years; body mass index [BMI]: 29.2 ± 3.6 kg/m2). PBF estimated by DXA was 42.4 ± 4.8% in women and 31.1 ± 4.7% in men (p<0.001). The correlation of the PBF estimated by BIA and by skinfold thickness with that estimated by DXA was, respectively, 0.93 (p<0.001) and 0.81 (p<0.001). BIA underestimated the PBF at 1.4 ± 3.2 (p<0.05) in women and 2.3 ± 3.3% (p<0.05) in men, compared to DXA, and these differences were less pronounced in patients with BMI ≥ 30 kg/m2 (Bland-Altman Plots). PBF calculated by Petroski’s equations was underestimated in 3.7 ± 4.0% [p<0,05] in women and 1.55 ± 3.8% [p<0.05] in men; and overestimated in 1.8 ± 4.5% [p<0.05] when calculated using DW equations age-adjusted only in women. The area under the ROC curves for BIA as a method to identify patients with increased PBF was 0.945 (p<0.001) in women and 0.897 (p<0.001) in men. The area under the ROC curves for skinfold thickness varied from 0.611 to 0.673 (all p>0.05) in women and was 0.960 (all P<0,05) in men. Conclusion. In patients with type 2 diabetes, both BIA and skinfold thickness underestimated PBF, when compared to DXA, at values that ranged from 1.4 to 2.3% and 1.5 to 4.5%, respectively. BIA was accurate in both sexes as a method to estimate PBF and to identify patients with increased PBF. On the other hand, PBF estimated by skinfold thickness was similarly accurate, but only in males.

Introdução: A medida do percentual de gordura corporal (PGC) sofre a influência de diversos fatores (obesidade severa, acúmulo excessivo de gordura no abdomen, hidratação, etc), dependendo da técnica utilizada, podendo comprometer o desempenho das mesmas. Muitos destes fatores estão frequentemente presentes nos pacientes com DM tipo 2, o que torna essencial o estudo da acurácia destes métodos nesta população. Objetivo: Avaliar a Bioimpedância (BIA) e as Dobras Cutâneas (DC) como métodos de estimativa da gordura corporal em pacientes com DM tipo 2, comparando-os com a Absorciometria de Raios X de Dupla Energia (DXA), como método de referência. Métodos: Neste estudo de acurácia diagnóstica, os pacientes foram submetidos à avaliação da composição corporal através da BIA (InBody 230, Biospace, Coréia), das DC (Lange, Fórmulas de Petroski e de Durnin) e da DXA (Lunar - iDXA). Para avaliação clínica foram analisados o controle metabólico (glicêmico e perfil lipídico) e pressórico e pesquisadas as complicações crônicas do DM. Resultados. Foram avaliados 133 pacientes (76 mulheres; idade: 63,6 ± 9,1 anos, duração do DM: 15,5 ± 10,3 anos; IMC: 29,2 ± 3,6), sendo que o PGC médio foi de 42,4 ± 4,8% nas mulheres e 31,1 ± 4,7% nos homens (p<0,001). A correlação do PGC estimado pela BIA e pelas DC com o estimado pela DXA foi, respectivamente r=0,93 (p<0,001) e r=0,81 (p<0,001). A BIA subestimou o PGC em 1,4 ± 3,2 (p<0,05) nas mulheres e 2,3 ± 3,3% (p<0,05) nos homens, quando comparada a DXA, sendo estas diferenças menos acentuadas nos pacientes com IMC≥ 30 kg/m2 (Gráficos de Bland-Altman). As DC subestimaram o PGC quando calculado com a Fórmula de Petroski, (3,7 ± 4,0% [p<0,05] nas mulheres e 1,55 ± 3,8% [p<0,05] nos homens) e superestimaram quando calculado com a Fórmula de Durnin ajustada para a idade, sendo que este ultimo apenas nas mulheres (1,8 ± 4,5% [p<0,05]). Na análise das curvas ROC, a área sob a curva da BIA foi 0,945 nas mulheres e 0,897 nos homens. Para as DC, utilizando as diferentes fórmulas, as áreas sob a curva variaram de 0,611 a 0,673 nas mulheres e foram 0,960 nos homens. Conclusão: Para a avaliação da composição corporal de pacientes com DM tipo 2, tanto a BIA como as DC (dependendo da fórmula) subestimam o PGC, comparados a DXA, mas em valores não clinicamente relevantes. A BIA apresentou uma boa acurácia em ambos sexos. Já a medida pelas DC mostrou acurácia semelhante, mas apenas nos homens. / Objective. To evaluate the performance of bioimpedance (BIA) and skinfold thickness as methods to estimate percentage body fat (PBF) in patients with Type 2 diabetes, comparing them to Dual Energy X-Ray Absorptiometry (DXA), as a reference standard. Research Design and Methods. In this study of diagnostic accuracy, the patients were submitted to evaluation of body composition with BIA (InBody 230, Biospace, Korea), skinfold thickness (Lange caliper) and DXA (Lunar - iDXA). PBF estimated by skinfold thickness was calculated with three equations: Petroski, Durnin & Womersley (DW) gender-adjusted and DW age-adjusted. Clinical evaluation consisted of the metabolic (glycemic and lipid profile) and blood pressure control, as well as the search for diabetic chronic complications. Results. One hundred and thirty-three patients were evaluated (76 women; age: 63.6 ± 9.1 years, duration of diabetes: 15.5 ± 10.3 years; body mass index [BMI]: 29.2 ± 3.6 kg/m2). PBF estimated by DXA was 42.4 ± 4.8% in women and 31.1 ± 4.7% in men (p<0.001). The correlation of the PBF estimated by BIA and by skinfold thickness with that estimated by DXA was, respectively, 0.93 (p<0.001) and 0.81 (p<0.001). BIA underestimated the PBF at 1.4 ± 3.2 (p<0.05) in women and 2.3 ± 3.3% (p<0.05) in men, compared to DXA, and these differences were less pronounced in patients with BMI ≥ 30 kg/m2 (Bland-Altman Plots). PBF calculated by Petroski’s equations was underestimated in 3.7 ± 4.0% [p<0,05] in women and 1.55 ± 3.8% [p<0.05] in men; and overestimated in 1.8 ± 4.5% [p<0.05] when calculated using DW equations age-adjusted only in women. The area under the ROC curves for BIA as a method to identify patients with increased PBF was 0.945 (p<0.001) in women and 0.897 (p<0.001) in men. The area under the ROC curves for skinfold thickness varied from 0.611 to 0.673 (all p>0.05) in women and was 0.960 (all P<0,05) in men. Conclusion. In patients with type 2 diabetes, both BIA and skinfold thickness underestimated PBF, when compared to DXA, at values that ranged from 1.4 to 2.3% and 1.5 to 4.5%, respectively. BIA was accurate in both sexes as a method to estimate PBF and to identify patients with increased PBF. On the other hand, PBF estimated by skinfold thickness was similarly accurate, but only in males.

The increased prevalence of obesity amongst adolescents is considered a worldwide epidemic. Within the black population of South Africa, obesity is significantly more prevalent amongst black girls than black boys. The high prevalence of obesity amongst children can be attributed to a combination of various lifestyle factors, namely a decrease in physical activity, an increase in television viewing, Westernization and increased food supply. The decrease in physical activity amongst adolescents over the last few decades has led to an increase in the number adolescents diagnosed with type 2 diabetes mellitus. Research has indicated that insulin sensitivity improves with regular physical endurance activity, irrespective of change in bodyweight. Regular physical exercise also lowers the risk of type 2 diabetes mellitus, and prevents the development of coronary heart diseases, hypertension and obesity. The primary goals of this study were two-fold: Firstly, to determine the relationship between BMI, percentage body fat and insulin sensitivity amongst black adolescents, and, secondly, to determine whether there exists a positive correlation between current cardiovascular fitness (V02-maximum),together with everyday physical activity status, and insulin sensitivity amongst black adolescents. One hundred and twenty-four (124) black boys and 148 black girls between the ages of 14 and 17 participated in the study. The BOD-POD was used to calculate percentage body fat, and blood analysis for fasting glucose and insulin were completed. Insulin sensitivity (QUIKI-index) and resistance (HOMA) were also calculated, and habitual physical activity was measured using the "Previous Day Physical Activity Recall" (pDPAR) questionnaire. Physical development was determined with the Tanner questionnaire, cardiovascular fitness (VO2-maximum) was determined using the "Bleep" test and anthropometry (mass, length, skin folds, waist and hip circumference) was measured to determine body composition. The results of this study found a statistically significant negative correlation between skin fold thickness, percentage body fat, BMI and insulin sensitivity in girls. A significant negative correlation between percentage body fat and V02-maximum was found in boys, while their self-reported activity (PDPAR) did not correlate with percentage body fat. Current cardiovascular fitness and habitual physical activity status (PDPAR) showed no significant relationship with insulin sensitivity. Amongst the girls there was however a tendency towards a positive correlation between insulin sensitivity and V02-maximum. / Thesis (M.Sc. (Human Movement Science))--North-West University, Potchefstroom Campus, 2006.

The increased prevalence of obesity amongst adolescents is considered a worldwide epidemic. Within the black population of South Africa, obesity is significantly more prevalent amongst black girls than black boys. The high prevalence of obesity amongst children can be attributed to a combination of various lifestyle factors, namely a decrease in physical activity, an increase in television viewing, Westernization and increased food supply. The decrease in physical activity amongst adolescents over the last few decades has led to an increase in the number adolescents diagnosed with type 2 diabetes mellitus. Research has indicated that insulin sensitivity improves with regular physical endurance activity, irrespective of change in bodyweight. Regular physical exercise also lowers the risk of type 2 diabetes mellitus, and prevents the development of coronary heart diseases, hypertension and obesity. The primary goals of this study were two-fold: Firstly, to determine the relationship between BMI, percentage body fat and insulin sensitivity amongst black adolescents, and, secondly, to determine whether there exists a positive correlation between current cardiovascular fitness (V02-maximum),together with everyday physical activity status, and insulin sensitivity amongst black adolescents. One hundred and twenty-four (124) black boys and 148 black girls between the ages of 14 and 17 participated in the study. The BOD-POD was used to calculate percentage body fat, and blood analysis for fasting glucose and insulin were completed. Insulin sensitivity (QUIKI-index) and resistance (HOMA) were also calculated, and habitual physical activity was measured using the "Previous Day Physical Activity Recall" (pDPAR) questionnaire. Physical development was determined with the Tanner questionnaire, cardiovascular fitness (VO2-maximum) was determined using the "Bleep" test and anthropometry (mass, length, skin folds, waist and hip circumference) was measured to determine body composition. The results of this study found a statistically significant negative correlation between skin fold thickness, percentage body fat, BMI and insulin sensitivity in girls. A significant negative correlation between percentage body fat and V02-maximum was found in boys, while their self-reported activity (PDPAR) did not correlate with percentage body fat. Current cardiovascular fitness and habitual physical activity status (PDPAR) showed no significant relationship with insulin sensitivity. Amongst the girls there was however a tendency towards a positive correlation between insulin sensitivity and V02-maximum. / Thesis (M.Sc. (Human Movement Science))--North-West University, Potchefstroom Campus, 2006.

Title: Lifestyle changes to lifestyle modification for people with multiple sclerosis Aim: Designing a program that affects lifestyle, fitness and physiological parameters in subjects of different age and different sex of people who have a diagnosis of multiple sclerosis (MS). Method: A literary review to make a summary of knowledge on MS and use of physical activities as opportunities to influence the overall lifestyle of people with MS. Results: The result is an overview of the programs and its evaluation - changes in physiological parameters, condition and subjective feelings. We found that when respecting the state of health programs may be implemented in the long term. Conclusion: The success of interventions depends on collaboration, time availability, but also the respecting of the designed programs of people involved. At the same time, however, assumes that an active lifestyle affects the mental aspect of individuals and their subjective feelings. Keywords: Multiple sclerosis, physical condition, subjective feelings, body fat percentage, body water percentage, body weight, muscle dysbalance

There is an increase in the prevalence of obesity among people with schizophrenia thought to be due in part to the weight enhancing side-effects of medications commonly used to treat the symptoms of schizophrenia. Despite the deleterious health effects associated with obesity and its impact on quality of life and medication compliance, little is known about body composition and energy expenditure in this clinical group. The primary purpose of this thesis was to enhance understanding of body composition and energy expenditure, particularly resting energy expenditure in men with schizophrenia who take atypical antipsychotic medications. Unique to this investigation is the evaluation of clinical tools used to predict body composition and energy expenditure against reference methodologies in men with schizophrenia. Further, given the known links between obesity and physical activity, an additional but less comprehensive component of the thesis was a consideration of total and activity energy expenditure in addition to the interaction between psychiatric symptoms, side-effects of antipsychotic medications and physical activity also occurred as part of this thesis. Collectively, the goals of this thesis were addressed through a series of studies – the first two studies were related to the measurement and characteristics of body composition in men with schizophrenia, while the third and fourth studies were related to the measurement and characteristics of resting energy expenditure in men with schizophrenia. The fifth and sixth studies the utilised doubly labelled water technique to quantify activity and total energy expenditure in a small group of men with schizophrenia and explored the use of accelerometry in this cohort. The final study briefly considered the impact of psychiatric symptoms and self-reported medication side-effects on objectively measured physical activity. In the first study, thirty-one male adults previously diagnosed with schizophrenia and sixteen healthy male controls were recruited. Estimates of body composition derived from an anthropometry-based equation and from bioelectric impedance analysis (BIA) using deuterium dilution as the reference methodology to determine total body water were compared. The study also determined the validity of equations commonly used to predict body composition from BIA in the men with schizophrenia. A further aim was to determine the superiority of either BIA or body mass index (BMI) as an indicator of obesity in this cohort. The inclusion of the control group, closely matched for age, body size and body composition demonstrated that there was no difference in the ability of body composition prediction methods to distinguish between fat and fat-free mass (FFM) in controls and men with schizophrenia when both groups had similar body composition. However this study indicated that an anthropometry-based equation previously used in people with schizophrenia was a poor predictor of body composition in this cohort, as evidenced by wide limits of agreement (25%) and systematic variation of the bias. In comparison, the best predictor of percentage body fat (%BF) in this group was gained when impedance values were used to predict percentage body fat via the equation published by Lukaski et al (1986). Although percentage body fat was underpredicted using the Lukaski et al. (1986) equation, the mean magnitude was relatively small (1.3%), with the limits of agreement approximately 13%. Linear regression analysis revealed that %BF predicted using the Lukaski et al. (1986) equation explained 25% more of the variance in percentage body fat than BMI. Further, this study also indicated that BIA was more sensitive than BMI in distinguishing between overweight and obesity in this cohort of men with schizophrenia. Because of the almost exclusive use of BMI as an indicator of obesity in people with schizophrenia, the level of excess body fat may be in excess of that previously indicated. The second study extended the examination of body composition in men with schizophrenia. In this study, the thirty-one participants with schizophrenia (age, 34.2 ± 5.7 years; BMI, 30.2 ± 5.7 kg/m2) were individually matched with sedentary controls by age, weight and BMI. Deuterium dilution was used to distinguish between FFM and fat mass. The previous study had indicated that while BIA was a suitable group measure for obesity, on an individual level the technique lacked the precision required for investigating body composition in men with schizophrenia. Waist circumference was used as an indicator of body fat distribution. The findings of this study indicated that in comparison with healthy sedentary controls of similar body size and age, men with schizophrenia had higher levels of body fat which was more centrally distributed. Percentage body fat was on average 4% higher and waist circumference, on average 5 cm greater in men with schizophrenia than the sedentary controls of the same age and BMI. Further, this study indicates that the use of BMI to predict body fat in men with schizophrenia will result in greater bias than when it is used to predict body fat in other sedentary men. Commonly used regression equations to predict energy requirements at rest are based on the relationships between weight and resting energy expenditure (REE) and in such equations, weight acts as a surrogate measure of FFM. The objectives of study three were to measure REE in a small group of men with schizophrenia who were taking the antipsychotic medication clozapine and to determine whether REE can be predicted with sufficient accuracy to substitute for the measurement of REE in the clinical and/or research settings. Body composition was determined using deuterium dilution and REE was measured using a Deltatrac Metabolic Cart via a ventilated hood. The male participants, (aged 28.0 ± 6.7 yrs, BMI 29.8 ± 6.8 kg/m2) were weight stable at the time of the study and had been taking clozapine for 20.5 ± 12.8 months, with doses of 450 ± 140 mg/day. Of the six prediction equations evaluated, the equation of Mifflin et al. (1990) with no systematic bias, the lowest bias and the lowest limits of agreement proved to be the most suitable equation to predict REE in this cohort. The overestimation of REE can be corrected for by deducting 160 kcal/day from the predicted REE value when using the Mifflin et al. (1990) equations. However, the magnitude of the error associated with the prediction of REE for an individual is 370 kcal/day. The findings of this study indicate that REE cannot be predicted with sufficient individual accuracy in men with schizophrenia, therefore it was necessary to measure rather than predict REE in subsequent studies. In the fourth study, indirect calorimetry (Deltatrac Metabolic Cart via ventilated hood) and deuterium dilution were used to accurately determine REE, respiratory quotient (RQ) and FFM in 31 men with schizophrenia and healthy sedentary controls individually matched for age and BMI. Data from this study indicated that gross REE was lower in men with schizophrenia than in healthy sedentary controls of a similar age and body size. However, there was no difference between the groups in REE when REE was adjusted for FFM using the mathematically correct method (analysis of covariance with FFM as the covariate). There was however a statistically and clinically significant difference in resting, fasted RQ between men with schizophrenia and controls, suggesting that RQ rather than REE may be an important correlate worthy of further investigation in men with schizophrenia who take antipsychotic medications. Studies five and six involved the application of the doubly labelled water (DLW) technique to accurately determine total energy expenditure (TEE) and activity energy expenditure (AEE) in a small group of men with schizophrenia who had been taking the atypical antipsychotic medication clozapine. The participants were those who took part in study three. The purpose of these studies was to assess the validity of a commercially available tri-axial accelerometer (RT3) for predicting free-living AEE and to investigate TEE and AEE in men with schizophrenia. There was poor agreement between AEE measured using DLW and AEE predicted using the RT3. However, using the RT3 to measure inactivity explained over two-thirds of the variance in AEE. This study found that the relationship between current AEE per kilogram of body weight and change from baseline weight in men taking clozapine was strong although not significant. The sedentary nature of the group of participants in this study was reflected in physical activity levels, (PAL, 1.39 ± 0.27), AEE (435 ±352 kcal/day) and TEE (2511 ± 606 kcal/day) that fell well short of values recommended by WHO (2000) for optimal health and to prevent weight gain. Given the increasing recognition of the importance of sedentary behaviour to weight gain in the general community, further examination of the unique contributing factors such as medication side effects and symptoms of mental illness to activity levels in this clinical group is warranted. The final study used accelerometry (RT3) to objectively measure activity in a group of 31 men with schizophrenia who had been taking atypical antipsychotic medications for more than four months. The purpose of this study was to explore the relationships between psychiatric symptomatology, side-effects of medication and physical activity. Accelerometry output was analysed to provide a measure of inactivity and moderate intensity activity (MIA). The well-validated and reliable standardised clinical interview, the Positive and Negative Syndrome Scale (PANSS) was used as a measure of psychiatric symptoms. Perceived side-effects of medication were assessed using the Liverpool University Neuroleptic Rating Side-Effects Scale (LUNSER). Surprisingly, there was no relationship reported between any measures of negative symptoms and physical inactivity. However, self-reported measures of medication side-effects relating to fatigue, sleepiness during the day and extrapyramidal symptoms explained 40% of the variance in inactivity. This study found significant relationships between some negative symptoms and moderate intensity activity. Despite the expectation that as symptoms of mental illness reduce, inactivity may diminish and moderate intensity activity will increase, it may not be surprising that in practice this is an overly simplistic view. It may be that measures of social functioning and possibly therefore cognition may be better predictors of physical activity than psychiatric symptomatology per se.