6.3: Vital Statistics
Some of the primary types of data that epidemiologists track are births and deaths. In many countries, these aptly named vital statistics are recorded by the government. In the U.S., hospitals and health professionals are required to report both births and deaths, as well as many different diseases and conditions (see Notifiable Conditions below), and most state departments of public health house these documents, along with marriage and divorce records. Birth and death certificate forms filled out by the healthcare professional also include some information pertinent to epidemiology; such as demographics, information about the parents, pregnancy and birth for birth certificates, and cause of death (and sometimes factors related to the cause) for death certificates.
There are some important terms used in tracking these vital statistics. The first might be natality, or the birth rate. Natality refers to the number of live births in a given time period relative to the number of people in a particular population. Fertility rate refers to the number of live births per number of women in the population of childbearing age, which is typically considered 15-44. Pregnancy and birth is possible outside of that range, but much more rare (National Vital Statistics System, 2023a). Natality and fertility of a specific population or comparisons over time can provide information whether or not a population is growing, what resources might be needed (i.e. for maternal and infant care), and changes in family planning or contraception use trends.
Mortality refers to the death rate for a particular population, disease, or condition being studied. Of course death is the 100% predictable end of every human life, but when and how death occurs is influenced by a variety of factors - some of which can be changed. Morbidity refers to the disease or condition rate - typically expressed as incidence (new cases) and prevalence (current cases). Studying the morbidity and mortality rates of different diseases or conditions can inform where public health efforts need to focus the most. For example, if the population in a specific neighborhood has a higher rate of cancers, that might prompt an investigation of environmental exposures to cancer-causing toxins (carcinogens) in that area. Or if one racial demographic has higher mortality rates from a specific disease than the overall average, perhaps outreach, healthcare access, and screenings for this group may need to be improved in order to catch the disease earlier, and provide better treatment options. The goal of public health related to morbidity and mortality is to extend the years of healthy life for all people, and reduce or eliminate preventable causes of disease, disability, and death.
One of the biggest factors related to increasing risk of death from any cause is age. The older we get, the higher the risk becomes. Therefore, mortality rates for a particular population may not always be comparable to another population due to age differences. For example, if we compare mortality rates in Florida to those in Alaska, it might seem that Florida has a substantially higher mortality rate. However, Florida is also home to many people over the age of 65, which could skew their death rate to be higher, due to more deaths occurring in aging populations. In 2020, older adults made up over 21% of Florida’s residents, and only 13% of Alaska’s. Instead of using the “crude” or absolute mortality rate then, an age-adjusted mortality rate will more accurately reflect these outcomes between different populations (Seabert et al., 2021). Age-adjusted mortality rates attempt to control mathematically for these differences and allow for the comparison of mortality rates between different populations. The mathematical methods used to calculate age-adjusted rates are beyond the scope of this text, but it is important to understand what these terms mean when comparing vital statistics.