Bayesian spatial modeling of childhood overweight and obesity prevalence in Costa Rica.

BMC Public Health

Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.

Published: April 2023

AI Article Synopsis

  • Childhood overweight and obesity rates in Costa Rica are alarmingly high, necessitating targeted public health interventions based on geographic and socioeconomic factors.
  • A Bayesian spatial mixed model was used to analyze data from Costa Rica's 2016 Weight and Size Census and the 2011 National Census, revealing that education levels initially increase the likelihood of overweight and obesity but decrease after around 8 years of schooling.
  • The study found that areas with more commercial and tourist activities and specific geographic locations, such as the country's center and border regions, show higher prevalence rates of childhood obesity, highlighting the need for localized health strategies.

Article Abstract

Background: Childhood overweight and obesity levels are rising and becoming a concern globally. In Costa Rica, the prevalence of these conditions has reached alarming values. Spatial analyses can identify risk factors and geographical patterns to develop tailored and effective public health actions in this context.

Methods: A Bayesian spatial mixed model was built to understand the geographic patterns of childhood overweight and obesity prevalence in Costa Rica and their association with some socioeconomic factors. Data was obtained from the 2016 Weight and Size Census (6 - 12 years old children) and 2011 National Census.

Results: Average years of schooling increase the levels of overweight and obesity until reaching an approximate value of 8 years, then they start to decrease. Moreover, for every 10-point increment in the percentage of homes with difficulties to cover their basic needs and in the percentage of population under 14 years old, there is a decrease of 7.7 and 14.0 points, respectively, in the odds of obesity. Spatial patterns show higher values of prevalence in the center area of the country, touristic destinations, head of province districts and in the borders with Panama.

Conclusions: Especially for childhood obesity, the average years of schooling is a non-linear factor, describing a U-inverted curve. Lower percentages of households in poverty and population under 14 years old are slightly associated with higher levels of obesity. Districts with high commercial and touristic activity present higher prevalence risk.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10074779PMC
http://dx.doi.org/10.1186/s12889-023-15486-1DOI Listing

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