Confidence intervals (CIs) indicate the reliability of a statistical estimate or rate. A 95% confidence interval is interpreted as a range in which we can be 95% confident the true population value lies. Wide confidence intervals, suggest less reliable estimates than narrow confidence intervals. In general, the larger the population, the narrower the CI and hence, the more precise is the estimate. Confidence intervals can also be used as tests of statistical significance when comparing estimates – if the CIs for the estimates under comparison overlap, we can say the difference between the estimates is not statistically significant. For CCHS data, 95% CIs have been calculated using the “bootstrap method”.