Correlates of Toddlers' Physical Activity Levels and Sedentary Behavior During Unstructured Outdoor Play in Early Childhood Education and Daycare Settings.

Despite recent research showing that early childhood education and daycare settings (ECEC) have an important role in promoting toddlers' physical activity (PA), crucial information gaps remain regarding toddlers' PA and sedentary behavior (SB) in these outdoor settings. We aimed in this study to: (a) analyze PA patterns and SB during unstructured outdoor play time in preschool and daycare environments using accelerometry and systematic observation; (b) provide concurrent accelerometry and observational data to help validate the Observational System for Recording Physical Activity in Children-Preschool Version (OSRAC-P); and (c) examine individual, social and environmental correlates of PA and SB during toddlers' unstructured outdoor play time. We found that: (a) toddlers displayed high amounts of PA with no sex, BMI, and/or age differences in PA and SB levels,; (b) environmental variables (e.

Role of Spanish Toddlers' Education and Care Institutions in Achieving Physical Activity Recommendations in the COVID-19 Era: A Cross-Sectional Study.

To our knowledge, there are no published studies that describe the physical activity (PA) levels and objectively measure them through accelerometry in toddlers (2-3 years old) attending early childhood education and care (ECEC) institutions during the COVID-19 pandemic. The aims of this study were two-fold: (a) to analyse toddlers' PA levels and sedentary behaviour (SB) during school hours in ECEC institutions, as well as the rate of adherence to specific recommendations on total PA (TPA) and moderate-vigorous PA (MVPA); and (b) to evaluate the characteristics correlates (age, gender, and body mass index -BMI) of young children and the school environment on toddlers' TPA, light PA (LPA), MVPA, and SB during school hours in ECEC institutions. PA was evaluated with ActiGraph accelerometers.

Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015-2016.

We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015-December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases.

Two-level resolution of relative risk of dengue disease in a hyperendemic city of Colombia.

Risk maps of dengue disease offer to the public health officers a tool to model disease risk in space and time. We analyzed the geographical distribution of relative incidence risk of dengue disease in a high incidence city from Colombia, and its evolution in time during the period January 2009-December 2015, identifying regional effects at different levels of spatial aggregations. Cases of dengue disease were geocoded and spatially allocated to census sectors, and temporally aggregated by epidemiological periods.

Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia.

The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015⁻2016 ZVD outbreak. We apply the integrated nested Laplace approximation (INLA) for parameter estimation, using the epidemiological week (EW) as a time measure. At the departmental level, the best model showed that the dengue or ZVD risk in one municipality was highly associated with risk in the same municipality during the preceding EWs, while at the city level, the final model selected established that the high risk of dengue or ZVD in one census sector was highly associated not only with its neighboring census sectors in the same EW, but also with its neighboring sectors in the preceding EW.

Relative risk estimation of dengue disease at small spatial scale.

Background: Dengue is a high incidence arboviral disease in tropical countries around the world. Colombia is an endemic country due to the favourable environmental conditions for vector survival and spread. Dengue surveillance in Colombia is based in passive notification of cases, supporting monitoring, prediction, risk factor identification and intervention measures.

Bayesian dynamic modeling of time series of dengue disease case counts.

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables.