Epidemiologic Model: Obesity in Children

Globally, obesity is a significant public health issue and health hazard that frequently first appears in childhood and causes substantial adverse health effects in later life (Klingelhöfer et al., 2021). Around 6.9% of girls and 9.3% of boys aged 5 to 19 worldwide suffered from obesity in 2022, which is a considerable rise over earlier decades (Lim, Xue, & Wang, 2020). It is the most challenging public health concern and has become a global pandemic. Obese children grow up to be obese adults and are more likely to develop diabetes and heart issues later in life, which are linked to higher rates of morbidity and early mortality (Balasundaram & Krishna, 2021).

Person: Individuals of all ages, genders, and socioeconomic backgrounds are impacted by childhood obesity. Children between the ages of 5 and 19 are more likely to be obese, and some ethnic groups, such as African American and Hispanic children, have higher rates than their White and Asian American counterparts (Skinner et al., 2018).

Place: Geographical location affects the frequency of childhood obesity. In the US, urban areas and those with less access to recreational opportunities and nutritious food tend to have higher rates. According to Di Cesare et al. (2019), childhood obesity is a significant public health concern in both developed and developing nations worldwide.

Time: Over the past several decades, there has been a significant rise in childhood obesity. For example, there has been a moderate increase in the prevalence of obesity in children aged 2-4 years and a minor increase in the proportion of overweight children aged five or under worldwide. The prevalence of severe obesity in children ages 2–5 has significantly increased in the United States between 2013 and 2014 (Skinner et al., 2018).

The random sampling approach guarantees that each child in the population has an equal chance of being chosen while gathering primary data on childhood obesity. It reduces selection bias and aids in obtaining a representative sample. To guarantee that particular subgroups are represented, stratified sampling necessitates separating the population into subgroups according to age, gender, or socioeconomic level. Measured height and weight are used to determine BMI, and the National Health and Nutrition Examination Survey (NHANES) provides extensive information on the nutritional status and general health of adults and children in the United States. The Youth Risk Behavior Surveillance System (YRBSS) also tracks youth health behaviors, such as dietary behaviors, food, and physical activity patterns (National, 2016). These data sources can enhance the completeness of case identification. However, because some surveys rely on self-reported data, which may create bias, they might not be able to capture some subpopulations (Skinner et al., 2018).

By guaranteeing a representative sample and sufficient representation of subgroups, random and stratified sampling techniques will improve the thoroughness of case identification. When defining obesity based on BMI percentiles, the direct measurements (such as height and weight) obtained through primary data methods offer specific and reliable information. Researchers can gain a thorough understanding of childhood obesity by integrating primary and secondary data sources, guaranteeing precise case identification and standardized diagnostic requirements..

References

Balasundaram, P., & Krishna, S. (2021). Obesity effects on child health.

Di Cesare, M., Sorić, M., Bovet, P., Miranda, J. J., Bhutta, Z., Stevens, G. A., ... & Bentham, J. (2019). The epidemiological burden of obesity in childhood: a worldwide epidemic requiring urgent action. BMC medicine, 17, 1-20.