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Biomedical subjects

T S Han

Publications and source records attributed to T S Han.

35 records · Page 2Linked to original sources
PubMed1997

Waist circumference reduction and cardiovascular benefits during weight loss in women.

OBJECTIVE: To examine the relationship between waist circumference and cardiovascular risk factors during weight loss, and to consider possible waist reduction targets for weight management. DESIGN: Single strand six month weight loss study on food based diets in 110 women aged 18-68 y, and body mass index > or = 25 kg/m2 set at an outpatient clinic. MAIN OUTCOME MEASURES: Waist circumference, weight, body mass index (BMI), total plasma cholesterol, low (LDL) and high density lipoprotein (HDL) cholesterol, triglyceride, and blood pressure. RESULTS: Anthropometric and metabolic measurements improved with mean weight loss of 4.9 (s.e.m. +/- 0.4) kg at three months and 6.2 (s.e.m. +/- 0.4) kg at six months. Weight loss closely related to waist reduction (% Weight loss = 0.85 x Waist reduction (cm)-2.09; r = 0.79). The proportion of subjects with waist circumference below Action Level 1 (< 80 cm) or above Action Level 2 (> or = 88 cm) were 9 and 60% at baseline, 29 and 38% at three months and 36 and 33% at six months. Waist reduction (adjusted for age, smoking, alcohol consumption, diet treatment and baseline dependent and independent variables) correlated significantly with falls in total cholesterol (r = 0.31; P < 0.01), LDL cholesterol (r = 0.35; P < 0.01) and diastolic blood pressure (r = 0.32; P < 0.01), but not significantly with HDL cholesterol, triglyceride or systolic blood pressure. BMI showed similar correlations, whereas waist to hip ratio changes were not associated with changes in any cardiovascular risk factors. Amongst those whose waist fell by > or = 5 cm, 45 at three months and 43 at six months, there were > or = 10% improvements in at least one risk factor for 71 and 84% respectively. Amongst those whose waist fell by 5-10 cm, 40 women at three months and 30 at six months, at least one risk factor improved by > or = 10% in 70% and in 83% respectively. CONCLUSIONS: Waist reduction of 5-10 cm in Caucasian women, across a range of baseline BMI 25-50 kg/m2 or waist circumference 72-133 cm, may be used as guideline to encourage overweight women to achieve a realistic target with a high probability of health benefits.

Adult↗
PubMed1997

Predicting intra-abdominal fatness from anthropometric measures: the influence of stature.

OBJECTIVE: To investigate the influence of height on the relationships between the intra-abdominal fat and anthropometric measures. SUBJECTS: Twenty healthy female volunteers aged 20-51 y from Aberdeen, and 71 men and 34 women aged 19-85 y from Nijmegen, The Netherlands. OUTCOME MEASURES: Intra-abdominal fat volumes by magnetic resonance imaging (MRI) in Aberdeen and cross-sectional areas at L4-L5 level by computerised tomography (CT) in Nijmegen, height, body mass index (BMI), waist circumference, waist sagittal and transverse diameters, waist to hip ratio, and skinfolds. RESULTS: In the MRI study the women with BMI 20-33 kg/m2, waist circumference 62-97 cm, height 148-172 cm, and intra-abdominal fat volume 0.07-2.66 kg, waist circumference gave the highest correlation of simple indices with intra-abdominal fat volume, explaining 77.8% of variance. Single cross-sectional MRI cuts predicted volume with r = 0.94-0.99. Height in various levels of index power was not related to waist circumference, waist diameters, BMI, or skinfolds and did not improve prediction of intra-abdominal fat volume or of cross-sectional intra-abdominal fat area at any level. The CT study of men and women with BMI 18-32 kg/m2 and 19-38 kg/m2, waist circumference 71-112 cm and 74-125 cm, height 158-197 cm and 151-182 cm, and intra-abdominal fat area 13-274 cm2 and 19-221 cm2 respectively, height also had little influence on the relationships of intra-abdominal fat area with waist circumference or with any other indices of adiposity in linear or quadratic models. Compared to younger subjects, intra-abdominal fat area was higher in older subjects for a given waist circumference. CONCLUSIONS: Height does not importantly influence the differences in measures of adiposity or intra-abdominal fat volume in women, or intra-abdominal fat area in both sexes. Age does influence the prediction of intra-abdominal fat from waist circumference, but waist circumference alone has a predictable simple relationship with intra-abdominal fat volume or area, which is likely to relate to the prediction of health risk for health promotion.

Abdomen↗
PubMed1997

The prevalence of low back pain and associations with body fatness, fat distribution and height.

OBJECTIVES: To examine the associations of low back pain symptoms with waist circumference, height, waist to hip ratio and body mass index, and to test the interactions between (1) waist circumference and height, and (2) waist to hip ratio and body mass index. SETTING: Cross-sectional study set in The Netherlands of a random sample of 5887 men and 7018 women aged 20-60 y. RESULTS: The prevalences of low back pain in men and women in the past 12 months were 46% and 52%, of whom 17% and 21% had low back pain for a total of 12 or more weeks, and 13% and 18% had symptoms suggestive of intervertebral disc herniation. After adjustments for age, smoking and education, more women in the highest tertile of waist circumference reported low back pain in the past 12 months (odds ratio = 1.2, 95% confidence interval: 1.1-1.4), low back pain for a total of 12 or more weeks (odds ratio = 1.5, 95% confidence interval: 1.3-1.8), and intervertebral disc herniation symptoms (odds ratio = 1.3, 95% confidence interval: 1.1-1.6) than women in the lowest waist tertile. Corresponding values of low back pain symptoms for women with high body mass index or high waist to hip ratio were similar to those with high waist. There were no significant differences between men in different tertiles of waist, waist to hip ratio or body mass index reporting low back pain symptoms. Tallest subjects did not report low back pain symptoms more often than shortest subjects. There was no significant interactions between waist and height or between waist to hip ratio and body mass index on low back pain symptoms. CONCLUSIONS: Women who are overweight or with a large waist have a significantly increased likelihood of low back pain. There are no significant interactions between waist and height, or waist to hip ratio and body mass index on low back pain symptoms.

Adipose Tissue↗
PubMed1997

Relationship between volumes and areas from single transverse scans of intra-abdominal fat measured by magnetic resonance imaging.

OBJECTIVE: To determine the level of a single transverse scan of intra-abdominal fat between L1 and L5 vertebrae that best predicts intra-abdominal fat volumes. SUBJECTS: Sixteen male and seven female patients with non-insulin-dependent diabetes mellitus, aged 44-74 y. OUTCOME MEASURES: Volumes and areas from single scans of intra-abdominal fat measured by magnetic resonance imaging with a 1.5 Tesla magnetic field strength. RESULTS: Intra-abdominal fat volumes and were calculated from fat areas from eight cross-sectional transverse single scans (nine scans in eight men) of 20 mm thickness. Men and women, respectively, had mean body mass index (BMI) of 27.9 (s.d. 3.0) and 31.6 (s.d. 4.7) kg/m2, and intra-abdominal fat of 2.3 (s.d. 0.5) and 2.5 (s.d. 0.6) kg. Intra-abdominal fat area of the fourth scan (in the direction of L1 to L5) gave the highest prediction of total intra-abdominal fat both in men (r = 0.959, P < 0.001) and in women (r = 0.973, P < 0.001). The intra-abdominal fat area of the third scan gave almost as good a prediction. These third and fourth scans corresponded to L2 and L3 vertebrae. The intra-abdominal fat areas from the sixth and seventh scans, corresponded to the frequently used L4-L5 and had lower correlations with intra-abdominal fat. There were no gender differences in the prediction of volumes from areas of intra-abdominal fat. Intra-abdominal fat areas of the fourth scan explained 93% of variance (SEE = 0.14 kg) of total of intra-abdominal fat for both genders: intra-abdominal fat (kg) = 0.0108 x intra-abdominal fat area of the fourth scan (cm2) + 0.244. CONCLUSIONS: In large studies of intra-abdominal fat, using magnetic resonance imaging (MRI) or computerised tomography scanning, a single intra-abdominal fat area at the intervertebral disc between L-2 and L-3 vertebrae offers a cheaper, faster and safer method, with high prediction of total intra-abdominal fat volumes and masses.

Abdomen↗
PubMed1997

Narrow hips and broad waist circumferences independently contribute to increased risk of non-insulin-dependent diabetes mellitus.

OBJECTIVES: Patients with non-insulin-dependent diabetes mellitus (NIDDM) have been shown to be more obese and have higher waist-to-hips circumference ratios compared to nondiabetics. In this study, we tried to dissociate obesity, waist and hip circumference from NIDDM. DESIGN: A cross-sectional population-based case-control study. SETTING: General population. SUBJECTS CONTROLS: 5887 men and 7018 women, aged 20-59 years, without known diabetes or hyperglycaemia. CASES: 93 men and 66 women were diagnosed with NIDDM. MAIN OUTCOME MEASURES: We predicted waist and hips' circumference from the body mass index, weight/height2, (BMI) on the basis of linear regression. Differences between observed and expected values (residuals) of waist and hip circumference were categorized into tertiles. The relative odds of having NIDDM in tertiles of waist and hip residuals (middle tertile as reference) were calculated by multiple logistic regression analysis adjusted for each other and for age, smoking, physical activity, alcohol consumption and education. RESULTS: NIDDM was most prevalent in men and women who had larger waists and in those who had smaller hip circumferences than expected from their BMI. Adjusted odds ratios (95% CI) for NIDDM were 2.9 (1.6-5.1) in men and 2.8 (1.5-5.1) in women who had a larger than expected waist, and were 3.7 (2.1-6.5) in men and 2.1 (1.1-3.8) in women who had smaller than expected hips. CONCLUSIONS: Our findings suggest that diabetics have larger waists and smaller hips compared to nondiabetics, irrespective of their degree of obesity, age and life-style factors. One possibility is that besides abdominal fatness, peripheral muscle atrophy is one of the factors associated with NIDDM.

Abdomen↗
PubMed1996

Waist circumference as a screening tool for cardiovascular risk factors: evaluation of receiver operating characteristics (ROC).

UNLABELLED: To evaluate the receiver operating characteristics (ROC) to determine the cutoffs of waist circumference as a potential population directed screening tool for hypercholesterolaemia (> or = 6.5 mmol/L), low high density lipoprotein cholesterol (< 0.9 mmol/L), and hypertension (treated and/or systolic > or = 160 and/or diastolic blood pressure > or = 95 mmHg), in 2183 men and 2698 women aged 20 to 59 years selected at random from Dutch civil registries. MAIN OUTCOME MEASURES: Height, weight, body mass index (BMI), waist circumference, total plasma cholesterol and high density lipoprotein cholesterol concentrations, and blood pressure. RESULTS: ROC curves showed that sensitivity equalled specificity at waist circumferences between 93-95 cm in men and 81-84 cm in women for identifying individual risk factors, and 92 cm in men and 81 cm in women for identifying those with at least one risk factor. Sensitivity and specificity were equal at levels between 61% to 69% for identifying individual risk factors, with positive predictions (56.8% in men and 37.8% in women) within 2% of those using previously defined 'Action Level 1' of waist circumference 94 cm in men and 80 cm in women (58.8% in men and 37.4% in women). Risk prediction by anthropometric methods was relatively low: ROC areas for identifying each risk factor by waist varied from 55% to 60%, and reached about 65% for identifying at least one risk factor. Height accounted for less than 0.3% of variance in waist circumference. Using BMI at 25 kg/m2 gave similar prediction to waist, but its combination with waist did not improve predictive values. CONCLUSIONS: Measurement of waist circumference 'Action Level 1' at 94 cm (37 inches) in men and 80 cm (32 inches) in women could be adopted as a simpler valid alternative to BMI for health promotion, to alert those at risk of cardiovascular disease, and as a guide to risk avoidance by self-weight management.

Adult↗
PubMed1996

Predicting body composition by densitometry from simple anthropometric measurements.

New equations have been developed to predict body fat (percent BF) calculated from body density measured by underwater weighing from simple anthropometric measurements, using stepwise-multiple-regression analysis in 63 men and 84 women. Log10 sum of four skinfold thickness explained 80.1% (SE = 3.8) of variance of percent BF in men and 76.4% (SE = 4.6) in women. Alternative equations using limb lengths instead of height may be valuable for epidemiologic and clinical work, with particular advantages for the chair- or bed bound, for whom no previous predictive equations existed. Five equations combining triceps-skinfold thickness with other anthropometric measurements explained > 80% (men) and 77% (women) of variance. The most powerful prediction was from waist circumference and triceps-skinfold thickness, which explained 86.6% (SE = 3.2) of variance of percent BF in men and 79.0% (SE = 4.0) in women. Percent BF for men = 0.353 waist (cm) + 0.756 triceps (mm) + 0.235 age (y) - 26.4; for women = 0.232 waist (cm) + 0.657 triceps (mm) + 0.215 age (y) - 5.5. The equations were tested in a separately studied validation sample of 146 men and 238 women aged 18-83 y. Skinfold-thickness measurements continued to give good predictions of mean body density, but with significant bias at extremes of body fat and age. The most robust prediction with the least bias was from waist circumference adjusted for age. Percent BF for men = 0.567 waist (cm) + 0.101 age (y) - 31.8; and for women = 0.439 waist (cm) + 0.221 age (y) - 9.4.

Adipose Tissue↗
PubMed1996

Lower leg length as an index of stature in adults.

OBJECTIVE: To derive regression equations using lower leg length (knee height) or arm span to predict height, and equations using ratios of weight/lower leg length or weight/arm span to predict body mass index and % body fat. SUBJECTS: Determination sample of 78 men and 82 women aged 17-70 years, and validation sample of 53 men and 121 women aged 18-82 years. MEASUREMENTS: Height, weight, lower leg length measured from the top of the patella with knee flexed at 90 degrees, arm span, % body fat by densitometry, and age. RESULTS: Lower leg length gave good prediction of height (men: r2 = 79%, SEE = 3.2 cm; women: r2 = 73%, SEE = 3.4 cm). Weight/lower leg length ratio was highly predictive of body mass index (men: r2 = 95%, SEE = 1.1 kg/m2, women: r2 = 94%, SEE = 1.1 kg/m2), and gave an estimation comparable to that of body mass index for predicting % body fat (men: r200 = 68%, SEE = 5.0% of body weight; women: r2 = 72%, SEE = 4.6% of body weight). Applying these equations based on lower leg length and weight/lower leg length ratio to a separate sample of men and women showed 95% of the errors of height estimate were within 6.5 cm, and of body mass index estimate were within 2 kg/m2. The same analysis of arm span showed the errors of body composition prediction were unacceptably high. CONCLUSION: Lower leg length is useful for estimating body composition when height measurement is not available.

Adolescent↗
PubMed1996

The influence of fat free mass on prediction of densitometric body composition by bioelectrical impedance analysis and by anthropometry.

OBJECTIVE: To examine the effect of varying size of fat free mass (FFM) on the precision and bias of body composition prediction by bioelectrical impedance analysis (BIA) from four equations of Segal et al (BIA-Segal), Gray et al (BIA-Gray, Lukaski et al (BIA-Lukaski) and those from a manufacturer (BIA-EZC), by body mass index (BMI), and by skinfold methods with reference to estimation by densitometry. SUBJECTS: 73 men and 77 women aged 17-71 years, were measured for height, weight, FFM, bioelectrical impedance and age. RESULTS: BIA-Segal gave the highest precision (men: R2 = 83%, women: R2 = 75%) and the least bias (men: slope = 0.88; women: slope = 0.81) of all BIA methods. There were poorer precision (R2 < or = 50%) and more bias (slope < 0.70) by BIA-Lukaski and BIA-EZC in both sexes, which were comparable to the simpler BMI method. The skinfold method gave R2 = 83% and slope = 0.84 in men and R2 = 61% and slope = 0.86 in women. Bland and Altman analysis showed BIA-Segal gave prediction of FFM within +/-6 kg of 95% confidence interval limit of agreement of that estimated by UWW in most subjects. Other BIA methods presented unacceptably large underestimates of up to 15-17 kg in FFM. CONCLUSIONS: The BIA-Segal provide the best predictions of the methods tested, but using BMI-or waist-specific equations may be more practical than the original BIA-Segal method, which BIA methods are affected by large FFM, and not better than anthropometric methods in predicting FFM.

Adolescent↗
PubMed1996

Comparisons between fat measurements by dual-energy X-ray absorptiometry, underwater weighing and magnetic resonance imaging in healthy women.

OBJECTIVE: To compare the results of measurements of total and regional fat by dual-energy X-ray absorptiometry (DXA), underwater weighing (UWW) and magnetic resonance imaging (MRI) in women. DESIGN: 13 volunteer pre-menopausal women measured with a Norland XR26 HS DXA instrument, hydrodensitometry equipment and a 0.08 Tesla MRI scanner. SETTING: Aberdeen Royal Infirmary. RESULTS: There were high correlations between measurements of total-body fat by the different techniques, but poor agreement. The mean values of fat as a percentage of the total body mass were UWW = 28.6%, DXA = 40.0%, MRI = 23.0%, although the MRI excluded the head, forearms and feet, estimated from the DXA measurements to contain 8% of the body fat. Although the correlations were apparently linear in the ranges examined, those including the Norland DXA had high intercepts. Bland and Altman plots showed no dependence of the differences on the degree of fatness. Evidence was obtained from in vivo comparisons and phantom measurements that the fat calibration of the Norland DXA had changed during a three year period, suggesting that fat calibration errors contributed to the MRI/DXA differences. Previous comparisons between the Norland DXA and other brands indicate that Hologic and Lunar instruments would show a closer agreement with MRI and UWW. Profiles of fat distribution along the body showed variations in the DXA/MRI ratio, particularly in the chest, with the DXA pattern thought to be the less accurate. The DXA measurements of bone mineral, fat and lean tissue were used to demonstrate the variable proportion of bone in fat-free tissue, leading to errors in UWW. CONCLUSIONS: Each method has its assumptions, which are often not sufficiently appreciated. Each method may be useful for testing and improving the assumptions in the other methods. No method can yet be regarded as a satisfactory reference technique.

Absorptiometry, Photon↗
PubMed1995

Waist circumference action levels in the identification of cardiovascular risk factors: prevalence study in a random sample.

OBJECTIVE: To determine the frequency of cardiovascular risk factors in people categorised by previously defined "action levels" of waist circumference. DESIGN: Prevalence study in a random population sample. SETTING: Netherlands. SUBJECTS: 2183 men and 2698 women aged 20-59 years selected at random from the civil registry of Amsterdam and Maastricht. MAIN OUTCOME MEASURES: Waist circumference, waist to hip ratio, body mass index (weight (kg)/height (m2)), total plasma cholesterol concentration, high density lipoprotein cholesterol concentration, blood pressure, age, and lifestyle. RESULTS: A waist circumference exceeding 94 cm in men and 80 cm in women correctly identified subjects with body mass index of > or = 25 and waist to hip ratios > or = 0.95 in men and > or = 0.80 in women with a sensitivity and specificity of > or = 96%. Men and women with at least one cardiovascular risk factor (total cholesterol > or = 6.5 mmol/l, high density lipoprotein cholesterol < or = 0.9 mmol/l, systolic blood pressure > or = 160 mm Hg, diastolic blood pressure > or = 95 mm Hg) were identified with sensitivities of 57% and 67% and specificities of 72% and 62% respectively. Compared with those with waist measurements below action levels, age and lifestyle adjusted odds ratios for having at least one risk factor were 2.2 (95% confidence interval 1.8 to 2.8) in men with a waist measurement of 94-102 cm and 1.6 (1.3 to 2.1) in women with a waist measurement of 80-88 cm. In men and women with larger waist measurements these age and lifestyle adjusted odds ratios were 4.6 (3.5 to 6.0) and 2.6 (2.0 to 3.2) respectively. CONCLUSIONS: Larger waist circumference identifies people at increased cardiovascular risks.

Adult↗
PubMed1995

Waist circumference as a measure for indicating need for weight management.

OBJECTIVE: To test the hypothesis that a single measurement, waist circumference, might be used to identify people at health risk both from being overweight and from having a central fat distribution. DESIGN: A community derived random sample of men and women and a second, validation sample. SETTING: North Glasgow. SUBJECT: 904 men and 1014 women (first sample); 86 men and 202 women (validation sample). MAIN OUTCOME MEASURES: Waist circumference, body mass index, waist:hip ratio. RESULTS: Waist circumference > or = 94 cm for men and > or = 80 cm for women identified subjects with high body mass index (> or = 25 kg/m2) and those with lower body mass index but high waist:hip ratio (> or = 0.95 for men, > or = 0.80 women) with a sensitivity of > 96% and specificity > 97.5%. Waist circumference > or = 102 cm for men or > or = 88 cm for women identified subjects with body mass index > or = 30 and those with lower body mass index but high waist:hip ratio with a sensitivity of > 96% and specificity > 98%, with only about 2% of the sample being misclassified. CONCLUSIONS: Waist circumference could be used in health promotion programmes to identify individuals who should seek and be offered weight management. Men with waist circumference > or = 94 cm and women with waist circumference > or = 80 cm should gain no further weight; men with waist circumference > or = 102 cm and women with waist circumference > or = 88 cm should reduce their weight.

Adult↗