What Are Demographic Variables? 

First, let's consider the meaning of the words: Variables—quite simply—are anything that can change and be measured. Examples include age, gender, ethnicity, fertility rates, etc. Demography is the study of human populations. If your research interest has to do with how characteristics vary among individuals or groups of individuals, then you will be looking for demographic statistics.

Typically, we think of two broad classes of demographic statistics that are collected and used by researchers:

  1. Demographers explore changes in the structure of populations, such as in numbers of births and deaths, life expectancy, migration rates, and so on. The statistics describing these changes are together called "vital statistics" or "population statistics." For example, a demographer might analyze trends and projections of birth and death rates for Afghanistan:

  2. Demographic—or more broadly, sociodemographicstatistics refer to characteristics of a population, such as age, race, ethnicity, gender, sexual orientation, income, education, and marital status. These types of variables are often used to understand how these characteristics vary with respect to each other (e.g., how income varies by race or with respect to another variable under investigation). For example, a study tracking cancer incidence might collect data on the race, ethnicity, age, and/or gender of the research participants to understand whether and how occurrence of cancer varies by one or more of these demographic characteristics:

Keep in mind that while the statistics you analyze may suggest a potential relationship between the variables you select, this relationship does not necessarily imply causality—just because income is higher among whites than Blacks in the United States does not mean that being white causes income to increase; rather, it raises the question of why that inequity exists.

Statistics provide evidence of correlation and causation; alternatively, statistics can reveal that there is no evidence of correlation or causation. Further research and analysis are required to prove either.

Standardization and sociodemographic variables

In analyzing statistical results, it is important to make sure that "apples are being compared to apples"—meaning that an apple is defined clearly in both data collection and data reporting. When possible, variables should be defined in a way that's consistent with commonly used definitions or taxonomies. For example, in the United States, the Office of Management and Budget sets Standards for the Classification of Federal Data on Race and Ethnicity and many government agencies follow these in administering questionnaires and surveys. Use of such standards helps ensure comparability of results across surveys and time.