Introduction
Analyzing the data collected requires a specific approach in which the research question is the vector that drives the entire course of the project. Postulating a research question based on the overall objective of the work determines precisely how the data will be analyzed, what statistical methods will be used, and what results are expected to be obtained. This paper explores the NHANES dataset for 2017-2018 (CDC, n.d.).
Data Collection
NHANES is a set of survey data that collects information from national surveys, which allows us to study giant sets and make judgments that are fair to the national community. This set contains extensive information on several measurable blocks, which includes demographic, dietary, examination, laboratory, and questionnaire data measuring various variables. This paper proposes to use this dataset to design the direction of the methodology of a potential project, formulate a research question, and construct a working hypothesis that can be tested using statistical tests.
Formulation of a Research Question
The construction of the research question should be based solely on areas of high interest to the field. Practically and theoretically, it is impractical to develop research vectors that have no benefit to either society or academic discourse. For this reason, the formulation of the research question should be given special attention. Variables describing laboratory outcomes for the population were chosen as the data set within NHANES. Since diabetes is a prevalent and gaining disease, the study of the laboratory variable of Insulin content was of particular practical and academic interest.
The Significance of a Research Question
The personal rationale for the choice is the increased attention to this disease, including identifying predictors of the development of an endocrine pathologic condition. Data on this variable were collected in August 2020 and provided information on three interest categories. First was the sample weight (WTSAF2YR) measured for men and women aged 12 to 150 years. Second was blood insulin content after fasting (LBXIN), measured in uU/mL. Third, the same content (LBDINSI) was measured in pmol/L. These three variables represented a continuous scale, ranked from minimum to maximum value.
Proposal of a Research Question
Given the data set studied and diabetes as a general area of interest, the research question can be formulated as follows: “Is there a relationship between a person’s weight and blood insulin content (pmol/L)?”. The formulation of this question links two variables, WTSAF2YR and LBDINSI, to each other and proposes to assess the significance of the relationship between them. In other words, a study built on this question is not experimental or longitudinal.
Still, it would have a cross-sectional, non-experimental design to examine the nature of the association between the two continuous variables. Given this, the null hypothesis could be “there is no relationship between a person’s weight and insulin content (pmol/L).” Then the alternative hypothesis should be formulated as “there is a relationship between a person’s weight and insulin content (pmol/L).” A statistical method that could be applied to the data could be Pearson correlation analysis to establish the direction and strength of the relationship between variables.
Conclusion
Postulating this research question and conducting a project according to it has high practical and clinical potential. The results of such a study would determine whether there is a relationship between insulin content in the blood and an individual’s weight, which makes sense when identifying predictors of diabetes. If, for example, insulin decreases with weight gain, this could indicate that obesity is a prerequisite for developing diabetes. The results will inform clinical recommendations and guidelines to improve public health and the quality of populational life.
Reference
CDC. (n.d.). NHANES questionnaires, datasets, and related documentation. Centers for Disease Control and Prevention. Web.
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