Differences in the prevalence of overweight, obesity and underweight among children from primary schools in rural and urban areas

Ann Agric Environ Med. 2016 Jun 2;23(2):341-4. doi: 10.5604/12321966.1203902.

Abstract

Introduction: Overweight adversely affects not only the health and development of children and adolescents but also their health in adulthood, increasing the risk of chronic non-communicable diseases and disabilities. The frequency of nutritional disorders among children and adolescents is increasing in many countries worldwide, including Poland.

Objective: To demonstrate differences in the nutritional well-being of school-age children depending on the school location: rural and urban areas.

Materials and methods: The study conducted in 2010 covered a total of 1,255 pupils, 627 girls and 628 boys, aged nine, from the area of five provinces of Poland: Pomorskie, Opolskie, Wielkopolskie, Podkarpackie and Masovian, representing the northern, southern, western, eastern and central regions of the country. Based on the height and weight measurements of children, the body mass index was calculated. The nutritional status was assessed according to the criteria of Cole et al.

Results: The prevalence of overweight and obesity in girls and boys in separate regions of the country (villages, cities with less than 100,000 residents and cities with more than 100,000 residents) did not differ significantly.

Conclusions: The prevalence of overweight and obesity among children from rural and urban areas of Poland is similar. Analysis of regional differences in the prevalence of obesity, overweight and underweight among children and adolescents may indicate the direction of national and local activities aiming to reduce the inequalities resulting from nutritional well-being.

MeSH terms

  • Body Mass Index
  • Child
  • Female
  • Humans
  • Male
  • Nutritional Status
  • Obesity / epidemiology*
  • Overweight / epidemiology*
  • Poland / epidemiology
  • Prevalence
  • Rural Population
  • Students / statistics & numerical data
  • Thinness / epidemiology*
  • Urban Population