Person Years and Person Months in Research Studies

When scientists perform certain types of prospective studies they measure that time in person years or person months. (Prospective studies are studies that follow a large group of people over time.) Person years and person months are types of measurement take into account both the number of people in the study and the amount of time each person spends in the study. For example, a study that followed 1000 people for 1 year would contain 1000 person years of data. A study that followed 100 people for 10 years would also contain 1000 person years of data. The same amount of data would be collected, but it would be collected on fewer people being studied for a longer follow-up period.

Person years and person months are often used as a measurement of time in studies that analyze their data using Kaplan-Meier curves. This is also known as "survival analysis." Survival analysis allows scientists to estimate how long it takes for half of a population to have undergone an event. It is called survival analysis because the technique was initially developed to look at how various factors affected the length of life. However, today survival analysis is used by researchers across a number of fields - from economics to medicine. Survival analysis is more forgiving of certain types of data problems than other types of analysis. In particular, it is quite forgiving of people being lost to follow-up. That is because they can still contribute time to the study, even if they leave without experiencing an event.

A number of research studies looking at sexually transmitted diseases have used person years as a component of their analyses. A few examples are described below:

• A 2015 study looked at whether hepatitis C (HCV) infection increased the risk of deep vein thrombosis (DVT) and related health consequences. The study found that HCV infection did increase DVT risk but not the rate of pulmonary emboli (blood clots in the lungs.)
• A 2014 study looked at how often people living with HIV are long-term nonprogressors. The study found that even if people make it to 10 years post infection without progressing, most of them will eventually progress to AIDS without treatment.
• A 2013 study demonstrated that women presenting for infertility treatment are less likely to be able to get pregnant, without IVF, if they test positive for chlamydia than if they don't.

Time is an important component in all of these studies. In the infertility study, it didn't just matter if women got pregnant, it mattered how long it took. The association with time is even more explicit in the HIV study. It wanted to know how long it took for people to progress from HIV to AIDS.