Gender and Cholesterol: Statistical Analysis of National Health & Nutrition Examination Survey Data Research Paper

Comparison of Men and Women in NHANES

Statistical analysis helps answer questions about the existence of differences between groups, even when those groups are represented by gender categories. For this assignment, demographic and dietary data were collected from the 2017-2018 NHANES population survey. The two data sets were merged using participant ID as a unifying factor: this way, assurance was achieved that records for respondents were collected accurately and matched to the same person.

The study built on a comparison of cholesterol content between two gender groups, men and women. In addition, additionally, the study sought to answer the question of age difference (demographic predictor) for the two gender groups. In other words, the current study was based on three variables: gender, age, and the participant’s blood cholesterol content.

Before proceeding to the analysis, attention should be paid to the descriptive statistics for the generated sample. Specifically, after data cleaning, the sample was represented by 7640 records. The sample represented 49.3% (n = 3763) men and 50.7% (n = 3877) women, and the mean age of the respondents was 35.09 (SD = 25.15) years. In terms of blood cholesterol content, the mean was 30.70 (SD = 96.29) mg.

Hypothesis Formulation and Testing

Based on the available data, two hypotheses were formed for each study:

• H₁₀: There is no difference in mean cholesterol levels between the two gender groups.
• H₁₁: There are differences in cholesterol content between women and men.
• H₂₀: Men and women have no differences in mean age.
• H₂₁: Of the two gender groups, on average, one appears to be older than the other.

As can be seen, all hypotheses were non-directional and could be tested using the t-test of independent samples (NU, 2023). Since all variables were continuous and gender was a nominal scale, a t-test of independent samples would allow for an assessment of the statistical significance of the mean values in the study variables between males and females.

Results of Hypothesis Testing

A t-test of independent samples was performed for each of the two studies, and the results allowed us to judge the differences between the groups. To test for differences in mean age, the results showed no statistically significant results, (t(7617.18) = -0.090, p =.928). This implies that there were no differences between men (M = 35.06, SD = 25.46) and women (M = 35.11, SD = 24.86) in the context of age; men were not older or younger than women, and vice versa.

Descriptive Statistics for Significant Differences

In contrast, with regard to cholesterol content, statistically significant differences were found between the two groups, (t(6768.09) = 6.38, p =.000). It followed that males (M = 37.86, SD = 111.04) had higher cholesterol content than females (M = 23.76, SD = 78.79).

Table 1. Results of descriptive statistics for the two gender groups in terms of cholesterol levels.

In other words, the first working hypothesis (H₁₁) was confirmed completely: the male and female samples did have different cholesterol contents. However, the second hypothesis (H₂₁) was not accepted, and no age difference was found between women and men. As a consequence, the findings raise the need to investigate additional factors influencing the higher cholesterol content in men, as well as to answer the question of whether this difference is normal. Performing additional tests is recommended to investigate and look for causal relationships.

Reference

NU. (2023). Statistics resources. National University. Web.