Childhood obesity
Compose a focused paper that explains and describes your healthcare issue/topic from the scientific and mathematical/analytical perspectives of inquiry. (You will cover two perspectives in one paper.)
Address your general topic by forming and answering two levels of research questions for each inquiry.
Choose a “Level 1 Research Question/Writing Prompt” from both of the lists below to answer in the paper.
Compose a “Level 2 Research Question/Writing Prompt” for each kind of inquiry that provides detail, specificity, and focus to your inquiry, research, and writing.
State your research questions in the introduction of your paper.
Answer each research question and support your assertions with evidence (research) to form the body of your paper.
In the conclusion of the paper, briefly review the issues, research questions, answers, and insights.
Level 1 Research Questions/Writing Prompts
SCIENTIFIC Perspective of Inquiry
What are the anatomical, physiological, pathological, or epidemiological issues?
Which body systems are affected?
What happens at the cellular or genetic level?
Which chemical or biological issues are most important?
Level 1 Research Questions/Writing Prompts
MATHEMATICAL/ANALYTICAL Perspective of Inquiry
What are the economic issues involved?
Which economic theories or approaches best explain the issue?
What are the statistical facts related to the issue?
Which statistical processes used to study the issue provide for the best explanation or understanding?
Sample Solution
The prevalence of childhood obesity is one of the most pressing public health issues in the United States. Research suggests that there has been an alarming increase in childhood obesity over the past two decades, making it a critical issue to address. In order to understand this epidemic and develop effective interventions, it is important to analyze both scientific and mathematical aspects of the problem. The purpose of this paper is to explore two research questions: 1) What are some of the underlying causes of childhood obesity?; 2) How can mathematics be used to assess its impact on society?
Research suggests that there are numerous factors associated with rising rates of childhood obesity, such as unhealthy diet choices, lack of physical activity, genetic predispositions, socioeconomic status, family psychosocial dynamics and endocrine-disrupting chemicals (Dumas et al., 2017). Unhealthy diets high in sugar-sweetened beverages and processed foods have become increasingly accessible due do economic growth and modern food production practices (Wang & Kimm 2006). Additionally, technology advancements have created devices which enable people to remain sedentary for long periods without expending large amounts energy (Koplan et al., 2001). Moreover, social determinants such as poverty or living conditions can limit access to healthy food options or recreational activities (Evans et al., 2018). These environmental influences can often lead individuals towards unhealthy eating habits which result in weight gain.
Mathematical models provide a way for researchers to investigate how different risk factors interact with each other and contribute towards overall rates of child obesity (Gortmaker et al., 1996). Analytical models allow investigators to examine current trends by formulating hypotheses about how changes in individual behaviors may influence population level health outcomes. For example, Gortmaker’s dynamic model examined how changes in dietary patterns could affect future levels of overweight/obesity among adolescents over time (Gortmaker et al., 1996). Mathematical models also provide a way for researchers and policymakers alike to determine the cost effectiveness potential interventions strategies such as taxation policies aimed at curbing consumption soda or junk food products(Andreyeva & Chaloupka 2010).
This paper has discussed two research questions related understanding child obesities’s underlying causes from a scientific perspective while also exploring ways mathematical analysis can help assess its societal impacts. It has become clear that various environmental factors including but not limited poor diets availabilities create opportunities for children engage in unhealthful behaviors contributing higher levels adiposity. Mathematical modeling provides powerful tool measuring these effects by allowing us make predictions regarding their consequences population-level health outcome while evaluating efficacy possible intervention strategies targeting those at highest risk developing obesities early age.
