Purpose

This module covers two issues that commonly arise when researchers analyze population data: age standardization and population counts (estimated numbers of persons in the U.S. with a particular characteristic). Addressing these issues in NHANES analyses requires the use of Census population data. 

Age is one of the most common and important confounding factors in health studies.  Age can confound comparisons when the groups being compared have different age distributions and age is related to the outcome of interest (e.g. death or the prevalence of disease).  Age standardization is a method that allows you to take away the confounding effect of age in order to allow you to make fair comparisons.

To understand the public health impact of a problem, it is often helpful to calculate population counts in addition to the prevalence of a health condition. By quantifying the number of people with a particular condition, counts directly speak to the magnitude of a public health problem.

 

Task 1: Calculate Age-Standardized Estimates

This task addresses how to generate age-adjusted prevalence estimates and means.

• Key Concepts about Age Standardization
• How to Generate Age-Adjusted Prevalence Rates in SUDAAN
• OPTIONAL: How to Generate Age-Adjusted Means in SUDAAN
• How to Generate Age-Adjusted Prevalence Rates in SAS 9.2 Survey Procedures
• OPTIONAL: How to Generate Age-Adjusted Means in SAS 9.2 Survey Procedures
• How to Generate Age-Adjusted Prevalence Rates in Stata
• OPTIONAL: How to Generate Age-Adjusted Means in Stata
• Download Sample Code and Dataset

 

Task 2: Calculate Population Counts

This task addresses how to calculate the number (i.e. the count) of people with a certain condition or disease in the non-institutionalized U.S. population.

• Key Concepts about Population Counts
• How to Generate Population Counts in SUDAAN
• How to Generate Population Counts in SAS Survey Procedures
• How to Generate Population Counts in Stata
• Download Sample Code and Dataset