Predicting Energy Expenditure from Physical Activity, Heart Rate and Anthropometry in Female Indian Tea Pluckers
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The objective of this study was to test a methodological procedure for estimating energy expenditure for a population of Indian female tea pluckers. Subjects (N=40; age20-50y) working on a tea estate in West Bengal, India participated in the study. Each subject wore an Actigraph accelerometer, Polar heart rate monitor and Cosmed K4b2 indirect calorimeter during a 90-minute period to assess minute-by-minute physical activity (PA), heart rate (HR) and energy expenditure (EE), respectively. The testing period was meant to replicate a normal tea plucker’s work day which included 2 periods of rest, 3 periods of picking while carrying weight (0, 5, and 10kg) and 3 periods of walking while carrying weight (15,20, 25kg). An EE prediction equation was generated using a branched method that first distinguishes time during normal workday activities (picking, walking, resting) using accelerometer counts. Resting EE was estimated from age and weight, while minute-by-minute non-resting EE was estimated from HR and BMI. Rather than creating individually calibrated curves for each subject, individuals can be grouped based on BMI categories (<18.5, 18.5≥BMI≤24.5, >24.5) to predict EE during the work day. Predicted EE will be used to evaluate the efficiency of performing work (weight of tea plucked/kcal EE) relative to iron status in an independent sample of 248 tea pluckers. We conclude that energy expenditure can be accurately predicted with a branched equation based on PA, HR, age and BMI for a specific population participating in a known set of activities.
dissertation or thesis