Dataset Information

Physical activity and daily steps cut offs points for overweight/obesity prevention among eight Latin American countries.

ABSTRACT: This study aims to establish cut-off points for the number of minutes of physical activity intensity and the number of daily steps that identify overweight/obesity in adolescents, adults, and older adults. This study examined data from 2737 participants. Physical activity intensity and the number of daily steps were assessed using GT3X+ ActiGraph model accelerometers. Body mass index, waist-to-height ratio, and waist-to-hip ratio were used as indicators of overweight/obesity. The cut-off points for moderate-to-vigorous physical activity for the prevention of overweight/obesity according to body mass index in women ranged from 15.1 to 30.2 min/day; in men, the values were from 15.4 to 33.8 min/day. The lowest cut-off point for daily steps was established in the adolescent group for women and men (7304 and 5162). The highest value in women was 11,412 (51-65 years) and 13,234 in men (18-30 years). Results from measurements different from BMI, show average cut-off points for moderate-to-vigorous physical activity and daily steps of 29.1/8348 and 43.5/10,456 according to waist-to-height ratio; and results of 29.3/11,900 and 44.3/11,056 according to the waist-to-hip ratio; in women and men respectively. A more specific recommendation of physical activity and daily steps adjusted by sex and age range is suggested to prevent overweight/obesity.

SUBMITTER: Ferrero-Hernandez P

PROVIDER: S-EPMC9637090 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Physical activity and daily steps cut offs points for overweight/obesity prevention among eight Latin American countries.

Ferrero-Hernández Paloma P Farías-Valenzuela Claudio C Jofré-Saldía Emilio E Marques Adilson A Kovalskys Irina I Gómez Georgina G Rigotti Attilio A Cortés Lilia Yadira LY García Martha Yépez MY Pareja Rossina G RG Herrera-Cuenca Marianella M Fisberg Mauro M Silva Danilo R DR Sadarangani Kabir P KP Ferrari Gerson G

Scientific reports 20221105 1

This study aims to establish cut-off points for the number of minutes of physical activity intensity and the number of daily steps that identify overweight/obesity in adolescents, adults, and older adults. This study examined data from 2737 participants. Physical activity intensity and the number of daily steps were assessed using GT3X+ ActiGraph model accelerometers. Body mass index, waist-to-height ratio, and waist-to-hip ratio were used as indicators of overweight/obesity. The cut-off points ...[more]

PMID: 36335253

Similar Datasets

Project description:BackgroundNovel influenza surveillance systems that leverage Internet-based real-time data sources including Internet search frequencies, social-network information, and crowd-sourced flu surveillance tools have shown improved accuracy over the past few years in data-rich countries like the United States. These systems not only track flu activity accurately, but they also report flu estimates a week or more ahead of the publication of reports produced by healthcare-based systems, such as those implemented and managed by the Centers for Disease Control and Prevention. Previous work has shown that the predictive capabilities of novel flu surveillance systems, like Google Flu Trends (GFT), in developing countries in Latin America have not yet delivered acceptable flu estimates.ObjectiveThe aim of this study was to show that recent methodological improvements on the use of Internet search engine information to track diseases can lead to improved retrospective flu estimates in multiple countries in Latin America.MethodsA machine learning-based methodology that uses flu-related Internet search activity and historical information to monitor flu activity, named ARGO (AutoRegression with Google search), was extended to generate flu predictions for 8 Latin American countries (Argentina, Bolivia, Brazil, Chile, Mexico, Paraguay, Peru, and Uruguay) for the time period: January 2012 to December of 2016. These retrospective (out-of-sample) Influenza activity predictions were compared with historically observed flu suspected cases in each country, as reported by Flunet, an influenza surveillance database maintained by the World Health Organization. For a baseline comparison, retrospective (out-of-sample) flu estimates were produced for the same time period using autoregressive models that only leverage historical flu activity information.ResultsOur results show that ARGO-like models' predictive power outperform autoregressive models in 6 out of 8 countries in the 2012-2016 time period. Moreover, ARGO significantly improves on historical flu estimates produced by the now discontinued GFT for the time period of 2012-2015, where GFT information is publicly available.ConclusionsWe demonstrate here that a self-correcting machine learning method, leveraging Internet-based disease-related search activity and historical flu trends, has the potential to produce reliable and timely flu estimates in multiple Latin American countries. This methodology may prove helpful to local public health officials who design and implement interventions aimed at mitigating the effects of influenza outbreaks. Our methodology generally outperforms both the now-discontinued tool GFT, and autoregressive methodologies that exploit only historical flu activity to produce future disease estimates.

Project description:BackgroundPhysical activity is a cornerstone in the prevention and treatment of obesity. There are relatively few studies that explore the effect of accelerometer-determined moderate-to-vigorous physical activity (MVPA) on neck circumference (NC), most of them confined to single high-income countries. The present study investigated the association of accelerometer-determined MVPA with NC in adolescents and adults from eight Latin American countries, which are mostly upper-middle income countries.MethodsThe sample consisted of 2370 participants (47.8% male) from the Latin American Study of Nutrition and Health, a multicenter cross-sectional nutrition and health surveillance study of a nationally representative sample from eight Latin American countries (Argentina, Brazil, Chile, Colombia, Costa Rica, Ecuador, Peru, and Venezuela). Times (min/day) in MVPA (defined as time accumulated at ≥1952 activity counts/min) was assessed by ActiGraph GT3X+ accelerometer over 7 days. NC for adolescent was categorized as abnormal if circumference was > 34.5 cm for boys and > 31.25 for girls, whereas for adults the cut-off points for abnormal were > 39 cm for men and > 35 cm women. Multilevel logistic models, including country and region as random effects and adjusted for sex, age, socioeconomic level, and educational level, were used to study the association between MVPA and NC.ResultsThe average time of MVPA was 34.88 min/day, ranging from 31.16 in Venezuela to 40.27 in Chile. Concerning NC, 37.0% of the sample was classified as having elevated NC. Chile was the country with the highest percentage of people with elevated NC (56.9%), and Colombia had the lowest percentage (24.8%). Overall, the MVPA (min/day) was associated with elevated NC (OR = 0.994, CI95% = 0.990-0.998). In Costa Rica and Peru, there were significant associations between MVPA and NC when analyzed by country.ConclusionsThe present study provided evidence of significant associations between MVPA and NC in adolescents and adults from Latin America, independent of sex, age, socioeconomic level, and educational level. This analysis of accelerometry data and NC represents the first examination of these associations in eight Latin America countries. Further research is required to understand the differences between countries in the observed associations.Trial registrationClinicalTrials.Gov NCT02226627 . Retrospectively registered on August 27, 2014.

Dataset Information

Physical activity and daily steps cut offs points for overweight/obesity prevention among eight Latin American countries.

Publications

Physical activity and daily steps cut offs points for overweight/obesity prevention among eight Latin American countries.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets