After reading a number of research studies, I wanted to conduct my own quantitative research on the subject. The primary goal was to ascertain whether education has an effect on obesity; whether it has no impact at all with different approach to measure the participants’ body weight. Some researches mentioned above used self-reported data to examine the relationship between socioeconomic status and obesity. For example, Ronald Strum’s (2002) article used self-reporting data collected from Healthcare for Communities (HCC) survey. However, according to Villanueva (2010) study, self-reported data collection methods are more likely to have an incorrect classification of obesity status; as the self-reported data (height and weight) was accepted as correct because people tend to underestimate their body size. Americans have a sliding scale when it comes to describing their own weight. This means that individuals underestimate or overestimate their own weight with respect to others. Therefore, the discrepancy between self-reported and objectively measured weight is likely to be less accurate or underestimated showing the prevalence of obesity in the United States.
I would like to conduct my research by using standardized measuring instruments to determine the BMI (body mass index) that will guarantee against the use of faulty data. Also, I will conduct a survey wherein I will use the quantitative method in my research which allowed me access to their height and weight. I will compare their height and weight to the BMI scale in order to decide whether the average physician would consider the individual to be obese or not.
This research project will investigate whether the individual with low education level is more likely to be obsese compared to someone who has higher education by conducting a survey ; without using respondent’s self-reported height and weight.
The research process will start by conducting a quantitative survey on sampled members of the society. The sample will be restricted to males and non-pregnant females, as it is expected that mother’s current body weight would not be an accurate measurement to determine whether she is ordinarily obese or not. Furthermore, the subjects of the research must be adults (21 and over) and individuals who are done with schooling because future variation in an academic standing may result in different data .For instance, currently enrolled students will not be subjected to the research because they are still studying even though they are officially adults. Therefore, an ideal research candidate for this survey will be an individual who is legally an adult, settled in life and with no ambitions of increasing the attained education level.
The sampled population will be divided into three subgroups, each consisting of 300 individuals. The socioeconomic status, with regard to their educational levels will be used as the determinant in this sample segmentation. The socioeconomic status of each member will be determined by a coding based on their education levels. There will be three socioeconomic levels: low education (less than high school, meaning less than ninth grade or no degree), medium education (high school, meaning 10th to 12th grades), and higher education (college or beyond college such as masters, doctoral, or professional). The three groups indicate low, medium, and high socioeconomic status respectively.
As America has a large population with different levels of education, it is impossible to distribute the survey questionnaire to all Americans throughout the 50 states to collect data. Also, it would ineffective to randomly select streets or given areas to select participants. Some areas in America are occupied by a specific population demographic. Streets such as Telegraph Avenue are dominated by students. Other localities in America are divided according to the economic status, race, and occupation of the residents. To tackle this challenge, a stratified probability sampling method will be applied. However, it is almost impossible to find exactly the same number of respondents at three different educational attainment levels at the same time and at the same place. I would randomly select participants then classify them by asking each respondent’s level of education till I have 300 individuals for each educational level. The final population sample will constitute of 300 individuals whose education levels do not overlap.
The grouping guarantees that subjects from each stratum are included in the final sample. The grouping strategy will save a lot of time, effort, and costs as the stratified sampling method generally does not require a large population size. Stratification has highest statistical precision compared to other survey techniques because of its lower variability within the different groups.
The body mass index (BMI) will be used as a parameter to ascertain the level of obesity in a subject. The calculation of the BMI involves comparison of the weight in kilograms and the height in meters. The weight is divided by the square of the height in order to obtain an exact figure. A BMI of 25 or more is considered overweight; 30 or more is considered obese (Desilver, 2013).
BMI data will be collected from a standardized public health centers where the survey respondents can easily examine weight and height of the respondents. Every respondent is required to measure his/her height and weight at the health center to get an objective calculation. Conducting the survey at a health center is apt because it is very important to measure each individual’s weight objectively without variation error. Also, a public health center is a place where everyone can visit despite their socioeconomic status. All individuals will be asked to take off their shoes and heavy outer clothing prior to measurement in order to get a precise weight.
Each of the participants’ will be subjected to a standardized questionnaire on their annual income, age, gender, and occupation. Most importantly, everyone will be required to select their right education groups: high, medium, low education levels. The questions about their weight and height will be open-ended. Factor like participant’s income and occupation will be considered for reference, but will not be used as driving determinants of obesity. The research process will strongly focus on establishing a relationship between education levels and body weight.
The respondents will not have an option to self-report their weights and heights other than done at the health center. The reason behind this is to avoid a potential danger of data manipulation and use of inaccurate scales. Scales from different manufacturers will give different results for the same individual. Using standardized measuring instruments to determine the BMI will guarantee against the use of faulty data.
Self-reported data collection methods tend to result in an underestimation of body mass index. According to Desilver, Americans have a sliding scale when it comes to describing their own weight. This means that individuals underestimate or overestimate their own weight with respect to others. Desilver estimates that only 31% of people said they are overweight, while 63% said their body sizes are “just about right”. This contradicts the National Health and Nutrition Examination Survey’s statistics that peg obesity in America at 68%.The timings of the survey will be flexible to accommodate all respondents at the healthcare.
Weight and height measurement will be conducted during work hours on business days. This will not disturb the normal operations of the public health center. As this research requires the respondents to go to a health center to get their height and weight measured; it would be time-consuming and money for them. Transportation cost would be involved in reaching the healthcare venue unless the center is walking-distance to the participants. Therefore appropriate compensation of $10 cash would be given to the respondents. Except those who would like offer voluntarily services. Some respondents might question the need to go to a health center and get their height and weight measured. Obesity is a one of the key contributing factors to rising national and personal healthcare costs. It is reported that obesity related illness expenditure can be around 35% of a person’s total expenditure and can even go up to 77% on the required medications.
Consequently, it is necessary to find accurate data to determine obesity in order to formulate an effective policy; to reduce rates of obesity and related diseases. To accomplish the above task it is essential to ask the individuals to go to a health center and provide correct data for a reliable research.
