So, incidence and prevalence estimate two different entities. Prevalence is suited for long term conditions to give you an idea of the magnitude of the problem, and incidence provides you an idea of the force at which a condition is developing in the population. 

Concepts of Age-standardisation and Standardised Incidence Rate

Sometimes, we are interested to know whether difference in the age or other structures in the two populations might be influencing the difference in the rates we find. In order to assess this situation, we need age-specific rates of the two or more populations that we'd like to compare and another population whose age structure we know. This method is referred to as age-standardisation. This is particularly useful in situations where we investigate clusters of cases of diseases in environmental health. For example, imagine you have received reports that cancer incidence rate has increased in a particular township since the introduction of a new plant. How do you know that whether the rates that are being reported are really too high when compared with the rest of the country? This is where standardisation of the rates become an important concept to learn. 
We will first illustrate this concept using UK cancer data and then we will illustrate the point of standardised rates using data sets from the NZ Ministry of Health for cancer cases for the years 2013, 2014, and 2015. You can obtain the data sets from here. We will first illustrate by calculating age-standardised rates for breast cancers and then we will compare the ASRs for Leukemia, and melanoma, the two cancers that are linked to environmental variables. 
In order to calculate age standardised rates of diseases we need to conduct the following steps:
  1. Obtain or calculate the age-specific rates
  2. Obtain SEGI population or another standardised population. You can find SEGI population here (PDFdocument)
  3. Multiply each age-band of the age-specific rate with the number for the corresponding age band in the SEGI population
  4. Add up the numbers in the product column
  5. This number you obtained in step 4 is the age-standardised rate
We will illustrate this idea with an example. We have obtained data for all cancer incidence rates for UK between the years 2012-2014. Below, in Table 1, we have presented this data. You can see that for some age groups, cancer rates among women are lower than that for men, and for others, the rates are higher. How do we know whether, for all cancers, the rates are higher among men?