2024 Adult Compendium of Physical Activities: A third update of the energy costs of human activities.

BACKGROUND: The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity (PA) across studies. The original version was updated in 2000, and again in 2011, and has been widely used to support PA research, practice, and public health guidelines. METHODS: This 2024 update was tailored for adults 19-59 years of age by removing data from those ≥60 years. Using a systematic review and supplementary searches, we identified new activities and their associated measured metabolic equivalent (MET) values (using indirect calorimetry) published since 2011. We replaced estimated METs with measured values when possible. RESULTS: We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers. We added 303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults. We added a Major Heading (Video Games). The 2024 Adult Compendium includes 1114 PAs (912 with measured and 202 with estimated values) across 22 Major Headings. CONCLUSION: This comprehensive update and refinement led to the creation of The 2024 Adult Compendium, which has utility across research, public health, education, and healthcare domains, as well as in the development of consumer health technologies. The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

Older Adult Compendium of Physical Activities: Energy costs of human activities in adults aged 60 and older.

PURPOSE: To describe the development of a Compendium for estimating the energy costs of activities in adults ≥60 years (OA Compendium). METHODS: Physical activities (PAs) and their metabolic equivalent of task (MET) values were obtained from a systematic search of studies published in 4 sport and exercise databases (PubMed, Embase, SPORTDiscus (EBSCOhost), and Scopus) and a review of articles included in the 2011 Adult Compendium that measured PA in older adults. MET values were computed as the oxygen cost (VO2, mL/kg/min) during PA divided by 2.7 mL/kg/min (MET60+) to account for the lower resting metabolic rate in older adults. RESULTS: We identified 68 articles and extracted energy expenditure data on 427 PAs. From these, we derived 99 unique Specific Activity codes with corresponding MET60+ values for older adults. We developed a website to present the OA Compendium MET60+ values: https://pacompendium.com. CONCLUSION: The OA Compendium uses data collected from adults ≥60 years for more accurate estimation of the energy cost of PAs in older adults. It is an accessible resource that will allow researchers, educators, and practitioners to find MET60+ values for older adults for use in PA research and practice.

2024 Wheelchair Compendium of Physical Activities: An update of activity codes and energy expenditure values.

PURPOSE: This paper presents an update of the 2011 Wheelchair Compendium of Physical Activities designed for wheelchair users and is referred to as the 2024 Wheelchair Compendium. The Wheelchair Compendium aims to curate existing knowledge of the energy expenditure for wheelchair physical activities (PAs). METHODS: A systematic review of the published energy expenditure of PA for wheelchair users was completed between 2011 and May 2023. We added these data to the 2011 Wheelchair Compendium data that was compiled previously in a systematic review through 2011. RESULTS: A total of 47 studies were included, and 124 different wheelchair PA reported energy expenditure values ranging from 0.8 metabolic equivalents for wheelchair users (filing papers, light effort) to 11.8 metabolic equivalents for wheelchair users (Nordic sit skiing). CONCLUSION: In introducing the updated 2024 Wheelchair Compendium, we hope to bridge the resource gap and challenge the prevailing narratives that inadvertently exclude wheelchair users from physical fitness and health PAs.

Energy Costs of Chair Sitting and Standing Video Exercises in Chinese Older Adults Over 60 Years.

Home-based video exercise interventions improve older adults' physiological performance and functional capacity. Little is known about the energy costs of video exercises in older adults. The Compendium of Physical Activities (PAs) has few items with PA metabolic equivalents (METs) in older adults. This study measured the energy costs of four chair and two standing exercises (sitting Tai Chi, Yoga, mobility ball, aerobics: standing, slow aerobics, and fast aerobics). Fifteen females and 14 males, 62-87 years (M ± SD, 73 ± 7.7 years), were categorized into three age groups (60-69, 70-79, 80-89). Oxygen uptake (VO2, ml·min-1·kg-1) and heart rate (HR, b·min-1) were measured by indirect calorimetry and heart rate monitor. MET values were calculated as standard- (activity VO2/3.5), rounded- (significant digit rounded to 0, 3, 5, 8), and corrected METs (individual resting metabolism). Results showed chair Yoga, Tai Chi, and mobility ball ranged from 2.0 to 2.8 rounded METs (light intensity). Chair- and standing aerobics ranged from 3.0 to 4.3 rounded METs (moderate intensity). Averaged HR ranged from 91.9 ± 12.7 b·min-1 to 115.4 ± 19.1 b·min-1 for all PAs. Corrected METs were higher than standard METs (P < .05). Standard METs were similar between age groups (P > .05). In conclusion, this study is unique as it measures the energy costs of sitting and standing video exercises that can be performed by older adults at home or in an exercise facility. Knowing the energy costs of PAs for older adults can provide exercises interventions to prevent sedentary lifestyles.

Energy Costs of Household and Eldercare Activities in Young to Middle-Aged Chinese Adults.

BACKGROUND: The 2011 Compendium of Physical Activities provides metabolic equivalent (MET) values for household and eldercare activities (physical activities [PAs]). METs are from published studies, estimated if values are not published, or combined with other PAs with different METs in a single entry. Some PAs are missing from the Compendium. This study measures the energy costs for 15 household and eldercare PAs with estimated METs, PAs in combined entries, and new PAs. METHODS: Participants were 30 adults (14 males and 16 females), ages 22-58 years (33.7 [11.2] y). PAs were measured in a laboratory for 8 minutes with a 4-minute rest between PAs. A portable indirect calorimeter measured oxygen uptake (in milliliters per kilogram per minute). Standard METs were computed as activity VO2/3.5 mL·kg-1·min-1. RESULTS: Cooking, meal tasks, laundry, light cleaning, and watering plants ranged from 1.8 to 2.3 METs. Sweeping, walking, and carrying groceries and boxes on the ground and stairs ranged from 3.0 to 5.5 METs. Eldercare ranged from 1.8 to 3.0 METs. Measured METs differed from estimated values by ±0.3 to 2.2 METs. Most measured METs were lower than estimated METs. CONCLUSION: Updating estimated METs with measured values and separating PAs from combined entries increases the accuracy of household and eldercare PAs presented in the Compendium.

Energy Cost of Reclining, Sitting, and Standing Activities in Chinese Adults.

The 2011 Compendium presents MET values for sedentary behaviors (SBs) and light-intensity physical activities (LIPAs). Some entries have estimated METs, others have multiple activities in a single entry, and newer activities are not in the Compendium. Accurate MET values are needed to increase the validity and generalizability of the Compendium. This study measured and analyzed SBs and LIPAs' energy costs in reclining, sitting, standing postures, and fidgeting. Indirect calorimetry measured the energy costs (VO2, ml·kg-1.min-1) in 11 males and seven females (30.7 ± 7.6 y). Two groups of 9 participants each completed 17 randomly assigned activities (9 in group 1; 8 in group 2) for 5 minutes with a 2-minute rest between tasks. Standard METs were calculated as VO2 ml·kg-1.min-1/3.5 ml·kg-1.min-1. Results showed mean MET values for doing nothing (recline: 1.3, sit: 1.3. stand: 1.3); Watching TV on a mobile phone (recline: 1.3, sit: 1.3); Reading (recline; 1.5, sit: 1.0); Writing (recline: 1.5, sit: 1.3, stand: 1.3); Texting or viewing websites on a mobile phone (recline: 1.3, sit: 1.3, stand: 1.3); Fidgeting (sit hands only: 1.5, sit feet only: 1.8, stand hands and feet: 2.0); Typing (stand: 1.3). Measured vs. Compendium METs were the same for five SBs and LIPAs, higher for three SBs and LIPAs (by 0.2 METs), and lower for one SB (by 0.3 METs). In conclusion, the activities ranged from 1.0 to 2.0 METs, categorized as sedentary and light-intensity. Increasing the accuracy of Compendium MET values increases its utility for the correct classification of SB and LIPAs.

Energy Cost Expression for a Youth Compendium of Physical Activities: Rationale for Using Age Groups.

PURPOSE: This study compared the accuracy of physical activity energy expenditure (PAEE) prediction using 2 methods of accounting for age dependency versus 1 standard (single) value across all ages. METHODS: PAEE estimates were derived by pooling data from 5 studies. Participants, 6-18 years (n = 929), engaged in 14 activities while in a room calorimeter or wearing a portable metabolic analyzer. Linear regression was used to estimate the measurement error in PAEE (expressed as youth metabolic equivalent) associated with using age groups (6-9, 10-12, 13-15, and 16-18 y) and age-in-years [each year of chronological age (eg, 12 = 12.0-12.99 y)] versus the standard (a single value across all ages). RESULTS: Age groups and age-in-years showed similar error, and both showed less error than the standard method for cycling, skilled, and moderate- to vigorous-intensity activities. For sedentary and light activities, the standard had similar error to the other 2 methods. Mean values for root mean square error ranged from 0.2 to 1.7 youth metabolic equivalent across all activities. Error reduction ranged from -0.2% to 21.7% for age groups and -0.23% to 18.2% for age-in-years compared with the standard. CONCLUSIONS: Accounting for age showed lower errors than a standard (single) value; using an age-dependent model in the Youth Compendium is recommended.

The influence of physical characteristics on the resting energy expenditure of youth: A meta-analysis.

OBJECTIVE: To examine the literature on resting energy expenditure (REE) of youth and determine the influence of age, sex, BMI, and body composition on REE. METHODS: A literature search was conducted using PubMed, BIOSIS Previews, NTIS, EMBASE, MEDLINE, and Pascal databases for studies with data on resting metabolic rate, REE, resting oxygen uptake (or VO2 ) in healthy children, youth, or adolescents (age = 1-18 years). Over 200 publications were identified; sixty-one publications met criteria and were included in the meta-analyses, resulting in 142 study population estimates (totaling 5,397 youth) of REE. RESULTS: Pooled mean was 1414 kcal·day-1 with a significant and moderate-to-high between-study heterogeneity [Q(140) = 7912.42, P < 0.001; I2 = 98.97%]. A significantly greater (P < 0.001) pooled mean kcal·day-1 was estimated for studies with male participants (1519 kcal·day-1 ) comparing to studies with female participants (1338 kcal·day-1 ). Age, height, and body mass resulted in the highest R2 of 86.4 for males and 83.9% for females. Fat free mass and body mass index (BMI) did not improve total R2 . CONCLUSIONS: These data suggest that using a linear equation including age, height, and body mass to estimate REE based on kcal·day-1 is more accurate than estimates based on body mass kcal·kg-1 ·h-1 . Further, if kcal·kg-1 ·h-1 is used, including a quadratic component for the physical characteristics improves the predictive ability of the equation. Regardless of the metric, separate equations should be used for each sex.

Energy Expenditure and Intensity of Classroom Physical Activity in Elementary School Children.

BACKGROUND: There is limited data regarding objectively measured energy cost and intensity of classroom instruction. Therefore, the purpose of current study was to objectively measure energy cost and subsequently calculate MET values using a portable indirect calorimeter (IC) for both normal classroom instruction (NCI) and active classroom instruction (ACI). METHODS: We assessed energy expenditure (EE) and intensity levels (METs) in elementary school children (17 boys and 15 girls) using an IC (COSMED K4b2). Independent t-tests were used to evaluate potential sex and grade level differences for age, BMI, VO2, EE, and METs. RESULTS: The average EE for NCI and ACI were 1.8 ± 0.4 and 3.9 ± 1.0, respectively. The average intensity level for NCI and ACI were 1.9 ± 0.4 and 4.2 ± 0.9 METs, respectively. CONCLUSIONS: PA delivered through ACI can elicit EE at a moderate intensity level. These results provide evidence for ACI as a convenient/feasible avenue for increasing PA in youth without decreasing instruction time.

Predicting resting energy expenditure in young adults.

PURPOSE: To develop and validate a REE prediction equation for young adults. METHODS: Baseline data from two studies were pooled (N=318; women=52%) and randomly divided into development (n=159) and validation samples (n=159). REE was measured by indirect calorimetry. Stepwise regression was used to develop an equation to predict REE (University of Kansas (KU) equation). The KU equation and 5 additional REE prediction equations used in clinical practice (Mifflin-St. Jeor, Harris-Benedict, Owens, Frankenfield (2 equations)) were evaluated in the validation sample. RESULTS: There were no significant differences between predicted and measured REE using the KU equation for either men or women. The Mifflin-St. Jeor equation showed a non-significant mean bias in men; however, mean bias was statistically significant in women. The Harris-Benedict equation significantly over-predicted REE in both men and women. The Owens equation showed a significant mean bias in both men and women. Frankenfield equations #1 and #2 both significantly over-predicted REE in non-obese men and women. We found no significant differences between measured REE and REE predicted by the Frankenfield #2 equations in obese men and women. CONCLUSION: The KU equation, which uses easily assessed characteristics (age, sex, weight) may offer better estimates of REE in young adults compared with the 5 other equations. The KU equation demonstrated adequate prediction accuracy, with approximately equal rates of over and under-prediction. However, enthusiasm for recommending any REE prediction equations evaluated for use in clinical weight management is damped by the highly variable individual prediction error evident with all these equations.

Nonexercise energy expenditure and physical activity in the Midwest Exercise Trial 2.

PURPOSE: This study aimed to examine compensatory changes in nonexercise energy expenditure (NEEx) and nonexercise physical activity (NEPA) in response to an aerobic exercise training program. METHODS: Ninety-two overweight/obese (body mass index, 25-39.9 kg·m) sedentary young adults (18-30 yr) completed a 10-month randomized clinical efficacy trial of aerobic exercise 5 d·wk at either 400 kcal per session (n = 37), 600 kcal per session (n = 37), or control (n = 18). Total daily energy expenditure (TDEE) and resting metabolic rate (RMR) were measured at months 0 and 10. NEPA was measured by an accelerometer at months 0, 3.5, 7, and 10. NEEx was calculated by the following formula: [(total daily energy expenditure × 0.9) - RMR] - net EEEx (EEEx-RMR). Mixed modeling was used to examine differences between groups (group effect), within groups (time effect), and group-time interaction for NEEx and NEPA. RESULTS: Within the exercise groups, there were no significant effects (all P > 0.05) of group, time, or group-time interaction for NEPA. In addition, there were no significant within- or between-group differences for change in NEEx. However, activity counts per minute were significantly higher (P < 0.001) in the 600-kcal-per-session group (346 ± 141 min·d) versus controls (290 ± 106 min·d) at month 7 and significantly higher (P < 0.001) in both the 600-kcal-per-session (345 ± 163 min·d) and 400-kcal-per-session groups (317 ± 146 min·d) versus controls (277 ± 116 min·d) at 10 months. CONCLUSIONS: A 10-month aerobic exercise training program in previously sedentary, overweight and obese young adults was not associated with compensatory decreases in NEEx or NEPA. Results suggest that overweight and obese individuals do not become less physically active or spend more time in sedentary pursuits in response to exercise.

Oxygen Cost of Performing Selected Adult and Child Care Activities.

Little is known about the oxygen cost of caring for infants and older adults. Many people perform these activities so it is useful to know the energy cost and if the activities are of sufficient intensity to contribute to meeting physical activity recommendations. The purpose of this study was to assess the oxygen cost of four care-related activities in the Compendium of Physical Activities. Nineteen participants (n = 10 women, n = 9 men; Age = 36.4 ± 13.6 y; % Fat = 34.1 ± 10.5; BMI = 28.1 ± 4.5 kg/m2) performed four activities: 1) pushing an infant in a stroller, 2) pushing an adult in a wheelchair, 3) carrying an infant, and 4) bathing and dressing an infant. The oxygen cost was assessed using a portable metabolic unit. Activities were performed in random order for 8 minutes. The oxygen cost and heart rates, respectively, for healthy adults during care related activities were 3.09 METs and 90 ± 8 beats per minute (bpm) for pushing an infant in a stroller, 3.69 METs and 97 ± 9 bpm for pushing an adult in a wheelchair, 2.37 METs and 85 ± 9 bpm for carrying an infant, and 2.00 METs and 87 ± 9 bpm for bathing and dressing an infant. Carrying an infant and bathing an infant are light-intensity physical activities and pushing a wheelchair or a stroller are moderate intensity activities. The latter activities are of sufficient intensity to meet health-related physical activity recommendations.