Neighborhood Walkability Index and Its Association With Indices of Childhood Obesity in Bengaluru, Karnataka

Background: The prevalence of childhood obesity is increasing in low-middle income countries like India. Built environment features such as walkability can influence weight-related outcomes but data from developing countries are scanty. Objective: To develop population level walkability index in urban Bengaluru, and examine its association with indices of childhood obesity in school children. Study Design: Nested cross-sectional study based on a cohort. Participants: Normal healthy children aged 6 to 15 years from urban schools in Bengaluru. The children were stratified into different land use classification such as residential, commercial and open space based on residential address. Methods: Anthropometric data, body composition data, measured using air displacement plethysmography. Outcomes: Walkability index derived using residential density, street connectivity and land-use mix environment variables. Results: The mean (SD) of age, body mass index (BMI), BMI zscore and percentage body fat (% Body fat) of 292 (50% boys) children were 10.8 (2.9) year, 17.4 (3.3) kg/m2, -0.27 (1.35) and 20.9% (8.8), respectively. The mean (SD) walkability index was 16.5, which was negatively associated with BMI (slope -0.25 and -0.08) and percentage body fat (slope -0.47 and -0.21) for age 5 and 10 years, respectively in children, but the effects decreased with increasing age. Conclusions: The findings of this pilot study suggest that the neighborhood walkability may be associated with the obesity indices in younger children. Future longitudinal studies are needed to understand how built environment affects health and body composition of children in India and other low-middle income countries.

A 4-compartment model based validation of air displacement plethysmography, dual energy X-ray absorptiometry, skinfold technique & bio-electrical impedance for measuring body fat in Indian adults.

Background & objectives: Many methods are available for measuring body fat of an individual, each having its own advantages and limitations. The primary objective of the present study was to validate body fat estimates from individual methods using the 4-compartment (4C) model as reference. The second objective was to obtain estimates of hydration of fat free mass (FFM) using the 4C model. Methods: The body fat of 39 adults (19 men and 20 women) aged 20-40 yr was estimated using air displacement plethysmography (ADP), dual energy X-ray absorptiometry (DEXA), 4-skinfold technique and bio-electrical impedance (BIA). Total body water was estimated using isotope dilution method. Results: All the methods underestimated body fat when compared to 4C model, except for DEXA and the mean difference from the reference was lowest for DEXA and ADP. The precision of the fat mass estimated from 4C model using the propagation of error was 0.25 kg, while the mean hydration factor obtained by the 4C model was found to be 0.74 ± 0.02 in the whole group of men and women. Interpretations & conclusion: The results of the present study suggest that DEXA and ADP methods can provide reasonably accurate estimates of body fat, while skinfold and bio-electrical impedance methods require the use of population specific equations.

Potential Factors Related to Waist Circumference in Urban South Indian Children.

Objectives: To identify important factors (linked to lifestyle, eating and sedentary behaviors) relating to waist circumference among urban South Indian children aged 3 to 16 years. Design: Cross sectional. Setting: Urban schools of Bangalore, from August 2008 to January 2010. Participants: 8444 children; 4707 children aged 3-10 years and 3737 children aged 10-16 years. Methods: Data were collected on the frequency of consumption of certain foods, physical activity patterns, sedentary habits at home, sleep duration and behaviors such as habits of snacking, skipping breakfast, eating in front of television and frequency of eating out. Simple linear regression analysis of waist circumference on various food items, physical activity, behavior and parental BMI were performed. A path model was developed to R E S E A R C H P A P E R identify potential causal pathways to increase in waist circumference. Results: Increased consumption of bakery items, non vegetarian foods, increased television viewing, decreased sleep duration, eating while watching television, snacking between meals, family meals, skipping breakfast (in older children), and parental BMI were found to be related to waist circumference. Older children possibly underreported their intake of “unhealthy” foods, but not behaviors. Conclusions: This study identified potential behaviors related to waist circumference in urban school children in India. Longitudinal studies with better measures of morbidity and adiposity are warranted in order to derive casual relationships between various determinants and waist circumference.

Waist Circumference and Waist for Height Percentiles in Urban South Indian Children Aged 3-16 Years.

Objectives: To develop age and gender specific waist circumference references for urban Indian children aged 3 -16 years. Design: Cross-sectional study. Setting: Urban preschools and schools of Bangalore. Participants: 9060 children (5172 boys and 3888 girls) in the age group of 3-16 years. Methods: Weight, height, and waist circumference were measured using standard anthropometric methodology. Percentiles for waist circumference and Waist/height ratio (W/Ht) for each age and gender were constructed and smoothed using the LMS method. Results: Mean waist circumference increased with age for both girls and boys. The upper end of curve in boys continued to increase, whereas in the girls it tended to plateau at 14 years. The waist circumference of the Indian children from the present study was higher than age and sex matched European children. The proportion of children with W/Ht ratio greater than 0.5 decreased as their age increased. Conclusions: These curves represent the first waist and waist height ratio percentiles for Indian children and could be used as reference values for urban Indian children. We suggest that for a start, the 75th percentile of waist circumference from this study be used as an “action point” for Indian children to identify obesity (as a tautological argument), while retaining the cut-off of 0.5 for the W/Ht ratio; however this underlines the need to derive biologically rational cut-offs that would relate to different levels of risk for adult cardiovascular disease.

Total body muscle mass estimation from bioelectrical impedance analysis & simple anthropometric measurements in Indian men.

BACKGROUND & OBJECTIVE: Skeletal muscle mass represents about 30-40 per cent of the total body weight, and has important roles in function and metabolism. Although newer methods of measuring muscle mass are accurate and sophisticated, there is a need for methods that can be used in low resource settings. Existing methods of predicting muscle mass are based on mid upper arm circumference (MUAC) measurements, sometimes corrected for triceps skinfold fat. The present study was undertaken to develop predictive equations for estimating muscle mass from simple and non-invasive methods such as bioelectrical impedance (BIA) and anthropometric measurements (circumferences and skinfold thickness) in Indian men. METHODS: BIA measurements and anthropometric measurements were carried out on 67 normal, healthy men between the ages of 18 and 45 yr. True muscle mass was measured from 24 h creatinine excretion. Multiple linear regression with step-wise forward selection was used to predict total muscle mass using measurements like height(2)/impedence, height and weight and using arm muscle area (AMA), thigh muscle area (TMA) and calf muscle area (CMA). RESULTS: The prediction equation for muscle mass (kg) using height(2)/impedance and height was - 12.347+ (0.363 x height(2)/impedance) + (0.122 x height) [R(2) = 0.55; Standard error of estimate (SEE) = 2.58 kg], while the equation using appendicular muscle area was 10.122 + (0.23 x AMA)+ (0.049 x TMA) [R(2) 0.36; SEE 3.07 kg]. INTERPRETATION & CONCLUSION: This study provides prediction equations for estimating muscle mass in healthy Indian males from simple non invasive methods such as BIA and anthropometric measurements such as circumferences and skinfold thickness. Further studies need to be done on a larger sample size and using an external group to validate the equations.

Use of rice bran oil in patients with hyperlipidaemia.

BACKGROUND: The quantity and type of dietary fat is known to affect plasma lipid concentration and hence the choice of cooking oil is important to lower the risk of coronary heart disease. Rice bran oil, which was not popular worldwide, is slowly being recognized as a 'healthy' oil in India. We assessed if rice bran oil had hypolipidaemic effects in subjects with elevated lipid levels. METHODS: The study had a cross-over design with subjects (n = 14) randomly assigned to consume either rice bran oil or refined sunflower oil in their homes, for a period of 3 months (period 1). After a washout period of 3 weeks, they were crossed over to the other oil (period 2). The serum lipid values were estimated at the beginning, on day 45 and day 90 of each phase. Additional parameters assessed included anthropometry, dietary and physical activity patterns. RESULTS: The use of rice bran oil significantly reduced plasma total cholesterol and triglyceride levels compared with sunflower oil. The reduction in plasma LDL-cholesterol with rice bran oil was just short of statistical significance (p = 0.06). HDL-cholesterol levels were unchanged. CONCLUSION: The use of rice bran oil as the main cooking oil significantly reduced serum cholesterol and triglyceride levels. The use of rice bran oil together with dietary and lifestyle modifications may have implications for reducing the risk of cardiovascular disease.

Prediction of total body muscle mass from simple anthropometric measurements in young Indian males.

BACKGROUND & OBJECTIVES: The total body skeletal muscle mass plays a significant role in both health and disease states. Accurate measurement or prediction of muscle mass is useful in physiology, nutrition and clinical medicine. There are many prediction equations derived in the Western populations to estimate skeletal muscle mass, however, regression equations best fit the population they are derived from. There is hence a need to generate predictive equations for the Indian population. The objective of this study was to derive predictive equations for muscle mass from simple anthropometric measurements such as mid-arm circumference (MAC) and triceps skinfolds in a young Indian male population. METHODS: Anthropometric measurements of body weight, height, mid-arm circumference and skinfold measurements were carried out on 66 subjects with a wide range of body mass indices. Twenty four hour urine samples were collected over a 3 day period for estimating urinary creatinine excretion, from which the total body muscle mass was inferred. Linear regression was carried out between MAC and corrected arm muscle area (CAMA) with muscle mass obtained from urinary creatinine to derive a prediction equation for muscle mass. RESULTS: The prediction equation obtained for muscle mass (kg) using MAC alone was (1.641xMAC)-15.580 [r=0.72, standard error of estimate (SEE) 2.91kg] while the equation derived from CAMA alone was (0.496xCAMA)+10.183, (r=0.62, SEE=3.29kg). INTERPRETATION & CONCLUSION: A new prediction equation for the measurement of muscle mass was derived in young Indian men using simple anthropometric measurements such as mid-arm circumference and triceps skinfolds.