14.5 Example: Skipping breakfast
The data in Table 14.6 come from a study of Iranian children aged 6–18 years old (Kelishadi et al. 2017). From this table:
- The proportion of females who skipped breakfast is \(\hat{p}_F = 2\,383/6\,640 = 0.359\);
- The proportion of males who skipped breakfast is \(\hat{p}_M = 1\,944/6\,846 = 0.284\).
Also,
- \(\text{Odds}(\text{Skips breakfast, among F}) = 2\,383/4\,257 = 0.5598\);
- \(\text{Odds}(\text{Skips breakfast, among M}) = 1\,944/4\,902 = 0.3966\).
For example, about 55.98 females skip breakfast for every 100 females who eat breakfast. The odds ratio (OR) comparing the odds of skipping breakfast, comparing females to males, is
\[\begin{align*} \text{OR} &= \frac{\text{Odds}(\text{Skipping breakfast, for females})}{\text{Odds}(\text{Skipping breakfast, for males})}\\ &= \frac{0.5598}{0.3966} = 1.41; \end{align*}\] the odds of females skipping breakfast are \(1.41\) times the odds of males skipping breakfast. The data can then be summarised numerically (Table 14.7).
Skips breakfast | Doesn’t skip breakfast | Total | |
---|---|---|---|
Females | 2383 | 4257 | 6640 |
Males | 1944 | 4902 | 6846 |
Percentage | Odds | Sample size | |
---|---|---|---|
Females | 64.1 | 1.786 | 6640 |
Males | 71.6 | 2.522 | 6846 |
Odds ratio | 0.708 |