Research Questions and Definition of Variables Research Proposal

¶ … Interval # Ordinal # Nominal # Ratio

Childhood obesity has become a fundamental problem for policymakers in the United States. Obesity increases the risk of such health complications as Type II diabetes and cardiovascular diseases. As such, researchers have shifted their effort to studying the causes and risk factors for childhood obesity. This text presents a set of research questions and variables for a proposed study seeking to identify the causes of childhood obesity.

Childhood Obesity: Research Questions and Variables

Childhood obesity is becoming a serious health concern for parents and policymakers alike in the U.S. Empirical evidence indicates that the prevalence of overweight and obesity among children below has almost tripled over the last decade (Karnik & Kanekar, 2012). This increasing prevalence of obesity places our young generation at risk for cardiovascular diseases, type II diabetes, and other health complications associated with overweight (Karnik & Kanekar, 2012). For this reason, all stakeholders need to play their roles to identify the specific causes of childhood obesity, the risk factors, and the prevention/corrective measures that need to be taken to correct the situation. The research questions below are geared at identifying the risk factors and causes of obesity among school-going children.

RQ1: are there any noticeable differences in the obesity levels of male and female school-going children?

This question seeks to assess how significant gender is as a risk factor for childhood obesity. In other words, we will be interested in identifying whether girls (or boys for that matter) are more at risk for childhood obesity compared to boys (or girls). This explanation would make sex/gender the independent variable, and children's health statuses the dependent variable. Sex, in this case, would be measured as a qualitative discrete, nominal variable -- the children will be categorized as either 1) male or 2) female, but the numbers 1 and 2 are simply category labels and have no quantitative significance. They are simply identifiers of the different categories; as such, the two categories only differ qualitatively, but not quantitatively (Norman & Streiner, 2008). The dependent variable, obesity, on the other hand, will be defined in terms of the BMI (Body Mass Index). Healthy BMIs range between 26 and 29, and a BMI equal to or in excess of 30 is regarded as obese. BMI figures can take an infinite number of values between any two measures -- for instance, between 26 and 27, we could have 26.1, 26.2, 26.7, 26.75, and so on, which makes this a continuous variable, interval variable. We could record actual BMI values for all participating children and then compare them with their gender to determine who, between girls and boys, run higher risks of being obese. We cannot refer to this as a ratio variable because it would be impossible to report an BMI of zero (Norman & Streiner, 2008).

RQ2: What is the relationship between time spent watching TV and childhood obesity?

Experts have argued that the primary reason why more children are becoming obese is because they are spending a lot of time engaging in indoor activities such as watching television an playing video games, and consequently spending less and less time s on physical activities outside the house. This question seeks to assess how true this ideology is. We are interested in identifying how watching TV influences obesity; as such, time spent watching TV is the independent variable and childhood obesity the dependent variable. We could measure the time spent watching TV in terms of the total number of whole hours one spends watching television everyday between the time when they arrive from school and when they go to bed. We can expect responses like 1, 2, 3, 4, or 5 hours, which would make this a discrete variable. Additionally, we could categorize these whole hours as follows 1) less than 2 hours; 2) between 2 and 4 hours; and 3) over 4 hours, in which case we would have measured it as an ordinal variable because we can rightly say that a child in category (2) spends more time watching TV than one in category (1), although we cannot say by how much (Jekel, 2007). Childhood obesity, on the other hand, can be defined in terms of a child's BMI as stipulated in RQ1 above. RQ3: What is the relationship between the level of familial income and the risk of childhood obesity?

Research indicates that children from low-income families are more likely to be obese than their counterparts from affluent backgrounds. This is particularly because the former may not be in a position to afford healthy diets. This question seeks to assess how prominent a factor familial income is as a risk element for childhood obesity. Thus, familial income will be taken as the independent variable and childhood obesity as the dependent variable. We could measure familial income in terms of the total income of a child's parents and working siblings in a given month. We could expect figures such as $25,000, $28, 750, $30,000 and so on, which implies that we will measure it as a continuous, ratio variable because a measure of 0 would essentially represent zero income (Jekel, 2007). The 'childhood obesity' variable could be measured as a continuous, interval variable as in RQ 1 and 2 above. We could obtain estimated values for total familial income for individual participating children, and then compare these to their individual BMI scores to determine whether there are any noticeable differences.

RQ4: What is the difference in the childhood obesity rates between children in private school and those in public schools?