Prediction Equation for Physical Activity Energy Expenditure in 11-13-Year-Old Sri Lankan Children.

This study aimed to develop a regression equation to predict physical activity energy expenditure (PAEE) using accelerometry. Children aged 11-13 years were recruited and randomly assigned to validation (n = 54) and cross-validation (n = 25) groups. The doubly labelled water (DLW) technique was used to assess energy expenditure and accelerometers were worn by participants across the same period. A preliminary equation was developed using stepwise multiple regression analysis with sex, height, weight, body mass index, fat-free mass, fat mass and counts per minute (CPM) as independent variables. Goodness-of-fit statistics were used to select the best prediction variables. The PRESS (predicted residual error sum of squares) statistical method was used to validate the final prediction equation. The preliminary equation was cross-validated on an independent group and no significant (p > 0.05) difference was observed in the PAEE estimated from the two methods. Independent variables of the final prediction equation (PAEE = [0.001CPM] - 0.112) accounted for 70.6% of the variance. The new equation developed to predict PAEE from accelerometry was found to be valid for use in Sri Lankan children.

Development of a New Equation for the Prediction of Resting Metabolic Rate in Sri Lankan Adults.

Resting metabolic rate (RMR) is the key determinant of the energy requirement of an individual. Measurement of RMR by indirect calorimetry is not feasible in field settings and therefore equation-based calculations are used. Since a valid equation is not available for Sri Lankans, it is important to develop a new population-specific equation for field use. The study objective was to develop a new equation for the prediction of RMR in healthy Sri Lankans using a reference method, indirect calorimetry. RMR data were collected from fifty-seven (male 27) adults aged 19 to 60 years. They were randomly assigned to validation (n = 28) and cross-validation (n = 19) groups using the statistical package R (version 3.6.3). Height, weight, and RMR were measured. Multivariable fractional polynomials (MFP) were used to determine explanatory variables and their functional forms for the model. A variable shrinkage method was used to find the best fit predictor coefficients of the equation. The developed equation was cross-validated on an independent group. Weight and sex code (male = 1; female = 0) were identified as reliable independent variables. The new equation developed was RMR (kcal/day) = 284.5 + (13.2 x weight) + (133.0 x sex code). Independent variables of the prediction equation were able to predict 88.5% of the variance. Root mean square error (RMSE) of the prediction equation in validation and cross-validation was 88.11 kcal/day and 79.03 kcal/day, respectively. The equation developed in this study is suitable for predicting RMR in Sri Lankan adults.

A field tool for prediction of body fat in Sri Lankan women: skinfold thickness equation.

BACKGROUND: Valid skinfold thickness (SFT) equations for the prediction of body fat are currently unavailable for South Asian women and would be a potentially robust field tool. Our aim was to assess the validity of existing SFT equations against deuterium (2H2O) dilution and, if invalid, to develop and validate an SFT equation for % fat mass (%FM) in Sri Lankan women. METHODS: H2O dilution was used with Fourier transform infrared (FTIR) spectroscopy as the criterion method for the assessment of %FM in urban Sri Lankan women (30-45 years). This data was used to assess the validity of available SFT equations and to generate and validate a new SFT equation for the prediction of %FM against the criterion method. Women (n = 164) were divided into validation and cross-validation groups for the development and validation of the new equation. The level of agreement between the %FM calculated by the final derived prediction equation and the %FM obtained by 2H2O dilution was assessed using Pearson's correlation coefficient (R) and Bland Altman plots. Student's t test was used to assess over- or underestimation, and significance was set at p < 0.05. RESULTS: Existing equations significantly (p < 0.001) underestimated %FM compared with the 2H2O dilution method. The final equation obtained was %FM = 19.621 + (0.237*weight) + (0.259*triceps). When compared with 2H2O dilution, %FM by the equation was not significantly different. There was a significant (p < 0.001) correlation between %FM by the reference method and %FM by the equation. The limit of agreement by Bland Altman plot was narrow with a small mean positive bias. CONCLUSIONS: Existing SFT equations were not applicable to this population. The new equation derived was valid. We report a new SFT equation to predict %FM in women of South Asian ancestry suitable for field use.

Lifestyle patterns and dysglycaemic risk in urban Sri Lankan women.

Specific dietary patterns are associated with the risk of chronic disease. An in-depth understanding more reflective of lifestyle would be possible when assessing the synergistic effects of both diet and physical activity in pattern analysis. In the present study, we examined the biochemical markers of dysglycaemia and cardiometabolic risk in relation to lifestyle patterns using principal component analysis (PCA). Urban women (n 2800) aged 30-45 years were screened for dysglycaemia using cluster sampling from the Colombo Municipal Council area. All the 272 dysglycaemic women detected through screening and 345 randomly selected normoglycaemic women were enrolled. The International Physical Activity Questionnaire and a quantitative FFQ were used to assess physical activity and diet, respectively. Anthropometric measurements, bioelectrical impedance analysis and biochemical estimations were carried out. Lifestyle patterns were identified based on dietary and physical activity data using exploratory factor analysis. PCA was used for the extraction of factors. A total of three lifestyle patterns were identified. Women who were predominantly physically inactive and consumed snacks and dairy products had the greatest cardiometabolic risk, with a higher likelihood of having unfavourable obesity indices (increased waist circumference, fat mass percentage and BMI and decreased fat-free mass percentage), glycaemic indices (increased glycosylated Hb (HbA1c) and fasting blood sugar concentrations) and lipid profile (increased total cholesterol/TAG and decreased HDL-cholesterol concentrations) and increased high-sensitivity C-reactive protein concentrations. For the first time, we report lifestyle patterns and demonstrate the synergistic effects of physical activity/inactivity and diet and their relative association with cardiometabolic risk in urban women. Lifestyle pattern analysis greatly increases our understanding of high-risk behaviours occurring within real-life complexities.

Body composition in urban South Asian women; development of a bioelectrical impedance analysis prediction equation.

BACKGROUND: Assessment of body composition plays a significant role in combating chronic disease among South Asians. Accurate assessment of body composition by bioelectrical impedance analysis (BIA) requires population-specific equations which are currently unavailable for urban South Asian women. AIM: To assess validity of direct BIA assessment and selected equations for prediction of total body water (TBW), against Deuterium ((2)H2O) dilution and develop and validate a population-specific TBW equation for urban South Asian women. SUBJECTS AND METHOD: Data of 80 urban Sri Lankan women (30-45 years) were used for this analysis. Body composition was assessed by (2)H2O dilution (reference) and BIA. Available BIA equations were assessed for validity. A new TBW equation was generated and validated. RESULTS: Direct BIA measurements and other equations did not meet validation criteria in predicting TBW. TBW by the new equation (TBW = 3.443 + 0.342 × (height(2)/impedance) + 0.176 × weight) correlated (p < 0.001) with TBW by reference method. TBW using the new equation was not significantly different (25.30 ± 2.4 kg) from the reference (25.32 ± 2.7 kg). CONCLUSION: Direct use of TBW by instrument and existing equations are less suitable for this population. The new TBW equation is suitable for body composition assessment in urban South Asian women.

Body fat assessment in Sri Lankan adolescent girls; development of a simple field tool.

BACKGROUND: Development of accurate, simple measures of body fat is essential in developing countries due to the rising prevalence of overweight and obesity. Application of skin-fold thickness (SFT) to body fat prediction equations is an inexpensive method suitable for field settings. AIM: To determine percentage fat mass (%FM) of Sri Lankan adolescent girls using Fourier Transform Infrared spectrometry (FTIR) as a reference method and develop a SFT-prediction equation to estimate %FM. METHODS: Weight, height and SFT were measured and %FM determined by FTIR in 131 adolescent, post-menarcheal girls (15-19 years). SFT-measurements were applied to available body composition equations for validation in the population. A new equation for %FM was derived and validated. RESULTS: Mean %FM (FTIR) was 19.13 ± 8.2.Selected body composition prediction equations over-estimated %FM. The multiple regression procedure yielded a final equation consisting of two anthropometric and one demographic variable, % FM = 9.701 - (0.460)* age+(0.640)*TricepsSFT+(0.583)*Supra-iliacSFT. CONCLUSIONS: Existing SFT prediction-equations are unsuitable for predicting %FM in this population. The new equation utilizing one peripheral and one truncal skin-fold, is appropriate for prediction of %FM in this population and may be applicable to other South Asian/Asian-Indian adolescents following validation.