PURPOSE: Physical activity questionnaires (PAQs) are considered the most cost-efficient method to estimate total energy expenditure (TEE) in epidemiological studies. However, relatively few PAQs have been validated using doubly labeled water (DLW) in women or in samples with diverse ethnic backgrounds. This study was conducted to validate the Arizona Activity Frequency Questionnaire (AAFQ) for estimation of TEE and physical activity energy expenditure (PAEE) over 1 month using DLW as a reference method. METHODS: Thirty-five relatively sedentary women completed the AAFQ before participating in an 8-d DLW protocol to measure TEE. TEE and PAEE were estimated from the AAFQ by calculating resting metabolic rate (RMR) using the equation of Mifflin et al. (AAFQmif), by measuring RMR using indirect calorimetry (AAFQic), and using MET conversion (AAFQmet). A predictive equation for TEE was generated. RESULTS: The mean +/- SD for TEE and PAEE from DLW were 9847 +/- 2555 kJ x d(-1) and 5578 +/- 2084 kJ x d(-1), respectively. Formulas using RMR to calculate the TEE and PAEE from the AAFQ tended to underestimate TEE and PAEE, whereas those that included only weight tended to overestimate TEE and PAEE. On the basis of the Mifflin et al. equation, the AAFQ tends to underestimate PAEE by 13%. This underestimation may be explained by the low lean body mass of the sample population and by effectiveness of the METs/RMR ratio in the obese. The following predictive equation was calculated: TEE (kJ x d(-1)) = (86.0 * average total daily METs) + (2.23 * RMRmif) - 6726. When the predictive equation is used, TEE calculated from the AAFQ is highly correlated with DLW TEE (adjusted r(2) = 0.70, P < 0.001). CONCLUSION: The AAFQ is an effective tool for the prediction of TEE and PAEE in epidemiological studies.
PURPOSE: Physical activity questionnaires (PAQs) are considered the most cost-efficient method to estimate total energy expenditure (TEE) in epidemiological studies. However, relatively few PAQs have been validated using doubly labeled water (DLW) in women or in samples with diverse ethnic backgrounds. This study was conducted to validate the Arizona Activity Frequency Questionnaire (AAFQ) for estimation of TEE and physical activity energy expenditure (PAEE) over 1 month using DLW as a reference method. METHODS: Thirty-five relatively sedentary women completed the AAFQ before participating in an 8-d DLW protocol to measure TEE. TEE and PAEE were estimated from the AAFQ by calculating resting metabolic rate (RMR) using the equation of Mifflin et al. (AAFQmif), by measuring RMR using indirect calorimetry (AAFQic), and using MET conversion (AAFQmet). A predictive equation for TEE was generated. RESULTS: The mean +/- SD for TEE and PAEE from DLW were 9847 +/- 2555 kJ x d(-1) and 5578 +/- 2084 kJ x d(-1), respectively. Formulas using RMR to calculate the TEE and PAEE from the AAFQ tended to underestimate TEE and PAEE, whereas those that included only weight tended to overestimate TEE and PAEE. On the basis of the Mifflin et al. equation, the AAFQ tends to underestimate PAEE by 13%. This underestimation may be explained by the low lean body mass of the sample population and by effectiveness of the METs/RMR ratio in the obese. The following predictive equation was calculated: TEE (kJ x d(-1)) = (86.0 * average total daily METs) + (2.23 * RMRmif) - 6726. When the predictive equation is used, TEE calculated from the AAFQ is highly correlated with DLW TEE (adjusted r(2) = 0.70, P < 0.001). CONCLUSION: The AAFQ is an effective tool for the prediction of TEE and PAEE in epidemiological studies.
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