Chi-square Test is Most Appropriate for Comparing Diabetes Prevalence Between Doctors and Nurses
The chi-square test is the most appropriate statistical test to compare the prevalence of diabetes mellitus between doctors and nurses.
Understanding the Data Structure
The question presents categorical data in a 2×2 contingency table format:
- Two professional groups (doctors vs. nurses)
- Two health status categories (diabetic vs. non-diabetic)
The data shows:
- Doctors: 30 diabetic out of 100 total
- Nurses: 50 diabetic out of 200 total
Why Chi-square is the Correct Choice
Chi-square testing is specifically designed to analyze the relationship between categorical variables. In this scenario:
- Data type consideration: Both variables (profession and diabetes status) are categorical/nominal data
- Purpose of analysis: We're testing whether there's a significant association between profession and diabetes prevalence
- Contingency table structure: The data naturally fits into a 2×2 table format
Why Other Tests Are Not Appropriate
T-test (Option A): Inappropriate because t-tests compare means of continuous variables between groups. Our data consists of frequencies in categories, not continuous measurements.
ANOVA (Option B): Inappropriate because ANOVA compares means across three or more groups for continuous dependent variables. Our outcome is categorical (diabetic/non-diabetic), not continuous.
Correlation (Option D): Inappropriate because correlation measures the strength and direction of a linear relationship between two continuous variables. Our variables are categorical.
Statistical Approach
The chi-square test would analyze whether the proportion of diabetes differs significantly between doctors (30%) and nurses (25%). The calculation involves:
Creating a 2×2 contingency table:
| Group | Diabetic | Non-diabetic | Total | |----------|----------|--------------|-------| | Doctors | 30 | 70 | 100 | | Nurses | 50 | 150 | 200 | | Total | 80 | 220 | 300 |Calculating expected frequencies for each cell based on row and column totals
Comparing observed frequencies with expected frequencies
Clinical Relevance
Understanding the statistical difference in diabetes prevalence between healthcare worker groups could inform:
- Targeted occupational health interventions
- Workplace wellness programs
- Further research into occupational risk factors for diabetes among healthcare professionals
The chi-square test provides a straightforward approach to determine if the observed difference in diabetes prevalence (30% vs. 25%) is statistically significant or merely due to chance.