Associations between daily ambient temperature and sedentary time among children 4-6 years old in Mexico City

How Societal Forces of Change Are Transforming Youth Physical Activity Promotion in North America

BACKGROUND

Climate change, increasing recognition of institutionalized discrimination, and the COVID-19 pandemic are large-scale, societal events (ie, forces of change) that affect the timing, settings, and modes of youth physical activity. Despite the impact that forces of change have on youth physical activity and physical activity environments, few studies consider how they affect physical activity promotion.

METHODS

The authors use 2 established frameworks, the ecological model of physical activity and the youth physical activity timing, how, and setting framework, to highlight changes in physical activity patterns of youth in North America that have resulted from contemporary forces of change.

RESULTS

North American countries-Canada, Mexico, and the United States-have faced similar but contextually different challenges for promoting physical activity in response to climate change, increasing recognition of institutionalized discrimination, and the COVID-19 pandemic. Innovative applications of implementation science, digital health technologies, and community-based participatory research methodologies may be practical for increasing and sustaining youth physical activity in response to these forces of change.

CONCLUSIONS

Thoughtful synthesis of existing physical activity frameworks can help to guide the design and evaluation of new and existing physical activity initiatives. Researchers, practitioners, and policymakers are encouraged to carefully consider the intended and unintended consequences of actions designed to respond to forces of change.

High-resolution spatiotemporal modeling of daily near-surface air temperature in Germany over the period 2000-2020

The commonly used weather stations cannot fully capture the spatiotemporal variability of near-surface air temperature (T_air), leading to exposure misclassification and biased health effect estimates. We aimed to improve the spatiotemporal coverage of T_air data in Germany by using multi-stage modeling to estimate daily 1 × 1 km minimum (T_min), mean (T_mean), maximum (T_max) T_air and diurnal T_air range during 2000-2020. We used weather station T_air observations, satellite-based land surface temperature (LST), elevation, vegetation and various land use predictors. In the first stage, we built a linear mixed model with daily random intercepts and slopes for LST adjusted for several spatial predictors to estimate T_air from cells with both T_air and LST available. In the second stage, we used this model to predict T_air for cells with only LST available. In the third stage, we regressed the second stage predictions against interpolated T_air values to obtain T_air countrywide. All models achieved high accuracy (0.91 ≤ R² ≤ 0.98) and low errors (1.03 °C ≤ Root Mean Square Error (RMSE) ≤ 2.02 °C). Validation with external data confirmed the good performance, locally, i.e., in Augsburg for all models (0.74 ≤ R² ≤ 0.99, 0.87 °C ≤ RMSE ≤ 2.05 °C) and countrywide, for the T_mean model (0.71 ≤ R² ≤ 0.99, 0.79 °C ≤ RMSE ≤ 1.19 °C). Annual T_mean averages ranged from 8.56 °C to 10.42 °C with the years beyond 2016 being constantly hotter than the 21-year average. The spatial variability within Germany exceeded 15 °C annually on average following patterns including mountains, rivers and urbanization. Using a case study, we showed that modeling leads to broader T_air variability representation for exposure assessment of participants in health cohorts. Our results indicate the proposed models as suitable for estimating nationwide T_air at high resolution. Our product is critical for temperature-based epidemiological studies and is also available for other research purposes.

Associations between weather conditions and physical activity and sedentary time in children and adolescents: A systematic review and meta-analysis

This systematic review and meta-analysis aimed to investigate the associations between weather conditions and physical activity (PA) and sedentary time (ST) in children and adolescents. A systematic search of six databases identified 11,816 articles, of which 26 studies were included in the review. Several weather conditions were included, such as rainfall, temperature, wind speed, day length, sunlight, humidity, snowfall, and clouds. Meta-analyses showed that higher temperatures were associated with more moderate-to-vigorous PA, while lower temperature and heavily rainfall was associated with longer ST. Children and adolescents showed more PA and less ST during favorable weather conditions. Future longitudinal and intervention studies on PA and ST should focus on how weather conditions promote or hinder these behaviors.

Seasons, weather, and device-measured movement behaviors: a scoping review from 2006 to 2020

BACKGROUND

This scoping review summarized research on (a) seasonal differences in physical activity and sedentary behavior, and (b) specific weather indices associated with those behaviors.

METHODS

PubMed, CINAHL, and SPORTDiscus were searched to identify relevant studies. After identifying and screening 1459 articles, data were extracted from 110 articles with 118,189 participants from 30 countries (almost exclusively high-income countries) on five continents.

RESULTS

Both physical activity volume and moderate-to-vigorous physical activity (MVPA) were greater in summer than winter. Sedentary behavior was greater in winter than either spring or summer, and insufficient evidence existed to draw conclusions about seasonal differences in light physical activity. Physical activity volume and MVPA duration were positively associated with both the photoperiod and temperature, and negatively associated with precipitation. Sedentary behavior was negatively associated with photoperiod and positively associated with precipitation. Insufficient evidence existed to draw conclusions about light physical activity and specific weather indices. Many weather indices have been neglected in this literature (e.g., air quality, barometric pressure, cloud coverage, humidity, snow, visibility, windchill).

CONCLUSIONS

The natural environment can influence health by facilitating or inhibiting physical activity. Behavioral interventions should be sensitive to potential weather impacts. Extreme weather conditions brought about by climate change may compromise health-enhancing physical activity in the short term and, over longer periods of time, stimulate human migration in search of more suitable environmental niches.