**Core Concept:** Chendler's Index (CI) is a statistical tool used in epidemiological studies to measure the strength of association between two categorical variables. It is calculated as the ratio of the observed count to the expected count, multiplied by 100. CI helps determine if an association between two variables is significant or not.

**Why the Correct Answer is Right:** Chendler's Index is primarily used to assess the strength of association between two categorical variables, such as risk factors in a case-control study or exposure-outcome variables in a cohort study. The expected count is calculated based on the population distribution of both variables. If the observed count is significantly different from the expected count, the association is deemed significant.

**Why Each Wrong Option is Incorrect:**

A. Chendler's Index is not typically used to determine the prevalence of a disease or condition. While it can give an idea of the association between risk factors and a disease, it is not specifically designed to calculate disease prevalence.

B. Although CI is used to assess the strength of association, it is not primarily used to calculate the odds ratio (OR), which is often used to measure the strength of association between categorical variables in epidemiology.

C. Chendler's Index is used to determine the strength of association, not to measure the correlation coefficient (CC), which is used to quantify the relationship between continuous variables.

D. CI is used to assess the strength of association, not to calculate the relative risk (RR), which is used to measure the risk of an event occurring in a population.

**Clinical Pearl / High-Yield Fact:** CI is essential for epidemiological research, helping researchers understand the relationship between categorical variables and guiding decision-making about intervention strategies, public health policies, and risk assessment. By understanding the CI value, one can determine whether the observed association is statistically significant or not.