4.7: Vital Statistics
- Page ID
- 124748
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)Some of the primary types of data that epidemiologists track are births and deaths. These data are named vital statistics and are recorded by the government. In the United States, hospitals and health professionals are required to report both births and deaths, as well as many different diseases and conditions. A list of reportable diseases to the Centers for Disease Control can be found here (Medline Plus, 2025). It is important to note that 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.
The following are important terms used in tracking vital statistics:
Natality refers to the number of live births in a given 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 (considered 15-44 years old). Pregnancy and birth are possible outside of that range, but they are much more rare (National Vital Statistics System, 2025).
Natality and fertility of a specific population or comparisons over time can provide information on 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.
Morbidity refers to the disease or condition rate - typically expressed as incidence (new cases) and prevalence (current cases).
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.
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 cancer, 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 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 the 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, McKenzie, & Pinger, R, 2022). 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.
To further understand the burden of disease, it is important to know how rate impacts a health problem (please note, the below rate explanation was a condensed summary from Riegelman & Kirkwood, 2025 p31). A rate is simply a measurement that compares two different quantities and is expressed via the numerator and denominator. In epidemiological studies, the numerator is a number of individuals that is also included in the denominator. When looking at a rate of an event, the numerator measures the times an event has happened, for example, breast cancer. The denominator measures the times the event has the possibility of happening. Many times, epidemiologists use the whole population as the denominator, but in certain circumstances, one would use only the at-risk population as the denominator. For instance, it would be appropriate to use the at-risk population, instead of the whole population, as the denominator when looking at a disease that is only found in a certain number of the population, and it is clearly understood and logic to exclude the other part of the population, for example when studying prostate cancer the denominator should include only the males portion of the population. In running an analysis of the burden of a disease, it is important to look at two different types of rates:
Incidence rates: The number of new cases of the disease in a certain period (Centers for Disease Control, 2022). Incidence rate is used to identify the cause of the problem, etiology. Mortality rate is also expressed via incidence rate. In a situation when most people who develop a disease die from it, as when people are diagnosed with pancreatic cancer (one of the known silent cancers), the incidence rate and mortality are similar. This comparison between mortality and incidence rate is important because it provides epidemiologists a probability of those who are diagnosed with the disease dying from it, and this is called fatality-rate. The fatality-rate for pancreatic cancer between 2014 and 2020 was 87% (National Institute of Health, 2024). Below is the equation used to calculate the incidence rate:
Incidence rates = number of new cases of a disease in a year/ number of people in the at-risk population
Prevalence rate: The number of cases of a disease present during a particular time (Centers for Disease Control, 2023). The prevalence rate is important in looking at the burden of disease because it provides us with the proportion of the people who have the disease in a certain period of time and therefore, it helps to identify the need for public health services. It is important to note that the limitation of prevalence rate is that, in some cases, the prevalence will be low because sometimes those that have the disease have it for a short period, such is the case with pancreatic cancer. Pancreatic cancer is a cancer that has subtle symptoms and many times is detected only during an autopsy (Rawla, Sunkara, & Gaduputi, 2019).
Prevalence rates = number of people living with a particular disease/number of people in the at-risk population
Reference:
Centers for Disease Control. (2022). Incidence. National Center for Health Statistics. https://www.cdc.gov/nchs/hus/sources.../incidence.htm
Centers for Disease Control. (2023). Prevalence. National Center for Health Statistics. https://www.cdc.gov/nchs/hus/sources...prevalence.htm
Medline. (2025). Reportable diseases. https://medlineplus.gov/ency/article/001929.htm
National Vital Statistical System. (2025). National Vital Statistics System. Birth Data. https://www.cdc.gov/nchs/nvss/births.htm
National Institute of Health. (2024). Cancer Stat Facts: Pancreatic Cancer. Surveillance, Epidemiolgy, and End Results Program. https://seer.cancer.gov/statfacts/html/pancreas.html
Rawla, P., Sunkara, T. & Gaduputi, V. (2019). Epidemiology of pancreatic cancer: global trends, etiology, and risk factors. World Journal of Oncology Feb 26;10(1):10-27 doi: 10.14740/wjon1166
Riegelman, R. & Kirkwood, B. (2025). Public Health 101 (4th). Jones & Bartlett Learning.
Seabert, D. McKenzie, J. F., & Pinger, R. R. (2022). An introduction to community & public health (10th). Jones & Bartlett Learning.