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 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.

How much did it cost to develop and implement an eHealth intervention for a minority children population that overlapped with the COVID-19 pandemic?

BACKGROUND: eHealth interventions using active video games (AVGs) offer an alternative method to help children exercise, especially during a pandemic where options are limited. There is limited data on costs associated with developing and implementing such interventions. OBJECTIVES: We quantified the costs of delivering an eHealth RCT intervention among minority children during COVID-19. METHODS: We categorized the total trial cost into five subcategories: intervention material development, advertising and recruitment, intervention delivery, personnel salaries, and COVID-19-related equipment costs. RESULTS: The total RCT cost was $1,927,807 (Direct: $1,227,903; Indirect: $699,904) with three visits required for each participant. The average cost per participant completing the RCT (79 participants/237 visits) was $24,403 (Direct: $15,543; Indirect: $8860). Due to no-shows and cancellations (198 visits) and dropouts before study completion (61 visits; 56 participants), 496 visits had to be scheduled to ensure complete data collection on 79 participants. If all 496 visits were from participants completing the three-visit protocol, that would correspond to 165 participants, bringing the average cost per participant down to $11,684 (Direct: $7442; Indirect: $4242). Of the subcategories, intervention material development accounted for the largest portion, followed by personnel salaries. While the direct COVID-19-specific cost constituted <1% of the entire budget, the indirect effects were much larger and significantly impacted the trial. CONCLUSION: RCTs typically involve significant resources, even more so during a pandemic. Future eHealth intervention investigators should budget and plan accordingly to prepare for unexpected costs such as recruitment challenges to increase flexibility while maximizing the intervention efficacy.

Stepping volume and intensity patterns in a multi-ethnic urban Asian population.

BACKGROUND: Accelerometer measured physical activity (PA) studies particularly in non-western populations are lacking. Therefore, this study investigated stepping activity in a multi-ethnic urban Asian population. METHODS: Adult participants from the Singapore Health Study 2 consented to accelerometer activity monitoring for 7-consecutive days. Mean daily step count, peak stepping intensity (i.e. cadence) over 1-min, 30-min and 60-min and time spent in each cadence band: 0 (non-movement), 1-19, 20-39, 40-59, 60-79, 80-99 and ≥ 100 steps/minute (moderate to vigorous PA) were calculated. RESULTS: A total of 713 participants (42% male, mean age 47.8 years) were included. Overall, the mean daily step count was 7549. Mean daily step count was significantly lower in Indians (7083 adjusted p = 0.02) but not Malays 7140 (adjusted p = 0.052) compared to Chinese (7745 steps). The proportion of Malays, Indians, and Chinese achieving < 5000 daily steps was 26%, 23% and 14%, respectively (p < 0.01). Regardless of ethnicity, approximately half of the recorded time was spent undertaking 0-steps/minute (7.9 h). CONCLUSIONS: Greater promotion of brisk walking is required in light of the low step volume and pace observed in this multi-ethnic Asian population. Ethnic differences in stepping activity were also identified which indicates a need for targeted ethnic specific health promotion interventions.

Associations of neighborhood social environment attributes and physical activity among 9-11 year old children from 12 countries.

We investigated whether associations of neighborhood social environment attributes and physical activity differed among 12 countries and levels of economic development using World Bank classification (low/lower-middle-, upper-middle- and high- income countries) among 9-11 year old children (N=6161) from the International Study of Childhood Obesity, Lifestyle, and the Environment (ISCOLE). Collective efficacy and perceived crime were obtained via parental/guardian report. Moderate-to-vigorous physical activity (MVPA) was assessed with waist-worn Actigraph accelerometers. Neighborhood environment by country interactions were tested using multi-level statistical models, adjusted for covariates. Effect estimates were reported by country and pooled estimates calculated across World Bank classifications for economic development using meta-analyses and forest plots. Associations between social environment attributes and MVPA varied among countries and levels of economic development. Associations were more consistent and in the hypothesized directions among countries with higher levels economic development, but less so among countries with lower levels of economic development.

Socioeconomic status indicators, physical activity, and overweight/obesity in brazilian children / Indicadores de nível socioeconômico, atividade física e sobrepeso/obesidade em crianças brasileiras

Objective: To analyze the associations between socioeconomic status (SES) indicators and physical activity and overweight/obesity in children. Methods: 485 children wore accelerometers for 7 days. Variables included time in sedentary behavior and moderate-to-vigorous physical activity (MVPA), and steps/day. Children were further categorized as meeting or not meeting guidelines of ≥60min/day MVPA and ≥12,000 steps/day. Body mass index (BMI) and body fat percentage (BF%) were measured using bioelectrical impedance. Overweight/obesity was defined as BMI >+1 SD and BF% ≥85th percentile. Parents answered questionnaires that questioned total annual household income, parental education level, parental employment status and automobile ownership. Results: Children averaged 59.5min/day in MVPA (44.1% met MVPA guidelines), and 9639 steps/day (18.4% met steps/day guidelines). 45.4% and 33% were overweight/obese classified by BMI and BF% respectively. Higher relative total annual household income level (Odds Ratio 0.31; 95% confidence interval=0.15-0.65), and relatively higher maternal (OR=0.38; 95%CI=0.20-0.72) and paternal (OR=0.36; 95%CI=0.17-0.75) education levels were associated with lower odds of children meeting MVPA guidelines. Household automobile ownership was associated with lower odds of children meeting MVPA (OR=0.48; 95%CI=0.31-0.75) and steps/day guidelines (OR=0.44; 95%CI=0.26-0.74). Conclusions: SES indicators were not associated with overweight/obesity, but higher SES was associated with lower odds of children meeting MVPA guidelines.

Objetivo: Analisar as associações entre indicadores de nível socioeconômico (NSE) e atividade física e sobrepeso/obesidade em crianças. Métodos: 485 crianças usaram acelerômetros por 7 dias. As variáveis incluíram o tempo em comportamentos sedentários e atividade física moderada a vigorosa (AFMV), e passos/dia. As crianças foram ainda classificadas como satisfazendo ou não o cumprimento das diretrizes de ≥60 min/dia MVPA e ≥12.000 passos/dia. Índice de massa corporal (IMC) e percentual de gordura corporal (%GC) foram medidos através de impedância bioelétrica. Sobrepeso/ obesidade foi definido como IMC>+1SD e um %GC≥percentil 85. Os pais responderam a questionários que questionavam o rendimento total anual das famílias, o nível de educação dos pais, situação de emprego dos pais e propriedade de automóvel. Resultados: As crianças mostraram uma média de 59,5 min/dia de AFMV (44,1% atingiram as diretrizes de AFVM), e 9.639 passos/dia (18,4% atingiram as diretrizes de passos/dia). 45,4% e 33% estavam com sobrepeso/obesidade classificada pelo IMC e %GC, respectivamente. Maior nível de renda familiar anual total (odds ratio 0,31; intervalo de confiança de 95%=0,15-0,65),e níveis relativamente mais elevados de educação materna (OR=0,38; IC95%=0,20-0,72) e paterno (OR=0,36; IC95%=0.17-0.75), foram associados com menor chance de crianças atingirem as diretrizes de AFVM. Propriedade de automóvel foi associada com menor chance de crianças atingirem as diretrizes de AFVM (OR=0,48; IC95%=0,31-0,75) e diretrizes de passos/dia (OR=0,44; IC95%=0,26-0,74). Conclusões: Os indicadores de NSE não foram associados com sobrepeso / obesidade, mas maior NES foi associado com menor chance de crianças atingirem diretrizes de AFVM.

[Socioeconomic status indicators, physical activity, and overweight/obesity in Brazilian children]. / Indicadores de nível socioeconômico, atividade física e sobrepeso/obesidade em crianças brasileiras.

OBJECTIVE: To analyze the associations between socioeconomic status (SES) indicators and physical activity and overweight/obesity in children. METHODS: 485 children wore accelerometers for 7 days. Variables included time in sedentary behavior and moderate-to-vigorous physical activity (MVPA), and steps/day. Children were further categorized as meeting or not meeting guidelines of ≥60min/day MVPA and ≥12,000 steps/day. Body mass index (BMI) and body fat percentage (BF%) were measured using bioelec-trical impedance. Overweight/obesity was defined as BMI>+1 SD and BF%≥85th percentile. Parents answered questionnaires that questioned total annual household income, parental education level, parental employment status and automobile ownership. RESULTS: Children averaged 59.5min/day in MVPA (44.1% met MVPA guidelines), and 9639 steps/day (18.4% met steps/day guidelines). 45.4% and 33% were overweight/obese classified by BMI and BF% respectively. Higher relative total annual household income level (Odds Ratio 0.31; 95% confidence interval=0.15-0.65), and relatively higher maternal (OR=0.38; 95%CI=0.20-0.72) and paternal (OR=0.36; 95%CI=0.17-0.75) education levels were associ-ated with lower odds of children meeting MVPA guidelines. Household automobile ownership was associated with lower odds of children meeting MVPA (OR=0.48; 95%CI=0.31-0.75) and steps/day guidelines (OR=0.44; 95%CI=0.26-0.74). CONCLUSIONS: SES indicators were not associated with overweight/obesity, but higher SES was associated with lower odds of children meeting MVPA guidelines.

Correlates of Total Sedentary Time and Screen Time in 9-11 Year-Old Children around the World: The International Study of Childhood Obesity, Lifestyle and the Environment.

PURPOSE: Previously, studies examining correlates of sedentary behavior have been limited by small sample size, restricted geographic area, and little socio-cultural variability. Further, few studies have examined correlates of total sedentary time (SED) and screen time (ST) in the same population. This study aimed to investigate correlates of SED and ST in children around the world. METHODS: The sample included 5,844 children (45.6% boys, mean age = 10.4 years) from study sites in Australia, Brazil, Canada, China, Colombia, Finland, India, Kenya, Portugal, South Africa, the United Kingdom, and the United States. Child- and parent-reported behavioral, household, and neighborhood characteristics and directly measured anthropometric and accelerometer data were obtained. Twenty-one potential correlates of SED and ST were examined using multilevel models, adjusting for sex, age, and highest parental education, with school and study site as random effects. Variables that were moderately associated with SED and/or ST in univariate analyses (p<0.10) were included in the final models. Variables that remained significant in the final models (p<0.05) were considered correlates of SED and/or ST. RESULTS: Children averaged 8.6 hours of daily SED, and 54.2% of children failed to meet ST guidelines. In all study sites, boys reported higher ST, were less likely to meet ST guidelines, and had higher BMI z-scores than girls. In 9 of 12 sites, girls engaged in significantly more SED than boys. Common correlates of higher SED and ST included poor weight status, not meeting physical activity guidelines, and having a TV or a computer in the bedroom. CONCLUSIONS: In this global sample many common correlates of SED and ST were identified, some of which are easily modifiable (e.g., removing TV from the bedroom), and others that may require more intense behavioral interventions (e.g., increasing physical activity). Future work should incorporate these findings into the development of culturally meaningful public health messages.

The descriptive epidemiology of sitting among US adults, NHANES 2009/2010.

OBJECTIVES: Using NHANES 2009/2010, to describe the amount of time a representative sample of the U.S. population spends sitting by age, sex, ethnicity, education, and body mass index. DESIGN: Cross-sectional analysis. METHODS: Participants (n=5911, ≥20 years) self-reported demographic variables and the amount of time they spend sitting on a typical day. Body mass index was calculated from measured height and weight. RESULTS: Mean self-reported sitting time was 285min/day for males and 281min/day for females. Mexican-Americans reported sitting less than both non-Hispanic Whites and non-Hispanic Blacks (all p<0.0001). Non-Hispanic White males reported sitting more than non-Hispanic Black males, while Non-Hispanic White females reported sitting more than Other Hispanic females (both p<0.0001). No significant differences were found between sexes in any age group. There was a trend for increased sitting time with increasing age for females (p for trend=0.0045), for all Mexican-American and Hispanic participants and non-Hispanic Black males (all p≤0.006) and with increasing education (p for trend <0.0001). At the College Graduate level, females reported sitting less than males (p<0.0001). Obese females reported sitting more than normal weight and overweight females (p=0.0008). There were no significant differences in sitting time by body mass index for males. CONCLUSIONS: Self-reported sitting time differed by ethnicity, age group, education and body mass index but there was no overall difference by sex. These results represent the most up to date prevalence of self-reported sitting for the US adult population. Certain groups should be targeted to reduce sitting time, for example those with higher educational attainment and obese females.