When interpreting pulmonary function tests (PFTs), a patient’s test results are compared to a group of normal people in order to determine that patient’s percent predicted value for each result. Those normal values are based on a person’s age, height, and gender. Until recently, we also used race as one of those variables – but should we?
Height, age, and gender
Height is an important variable in PFT interpretation. Taller people have larger lungs than shorter people. In pulmonary function testing, the overall size of the lungs is measured by the total lung capacity, which is the total volume of air in the lungs. If a patient’s total lung capacity is below the 5th percentile of normal people of a similar height, that patient is considered to have restrictive lung disease. Interstitial lung disease, muscle weakness, pregnancy, and chest wall deformities are some of the common causes of restrictive lung disease. If we did not stratify normal populations by height, then shorter people would be incorrectly diagnosed with restrictive lung disease, which could trigger unnecessary expensive diagnostic testing to determine the cause of the restriction. The graph below shows the relationship between a normal person’s height and their total lung capacity. Normal for a 170 cm (5′ 6″) man is 6.0 liters whereas normal for a 190 cm (6′ 3″) man is 8.0 liters.
Age is another important variable in PFT interpretation. As a child grows older (and also taller), the child’s lung volume increases. But after adulthood, our lung become smaller as we age. For example, the average forced expiratory volume in 1 second (FEV1) at age 30 is 4.4 liters but the average FEV1 at age 70 is 3.2 liters.
We define obstructive lung disease as an FEV1/FVC ratio below the 5th percentile of normal. Once again, we see that what we consider to be normal changes with age. In addition, we see that there are also gender differences in what constitutes normal values. As people age, the normal FEV1/FVC decreases and for any given age, men have a lower FEV1/FVC than women. So, for example, the FEV1/FVC that we would define as obstructive lung disease for a man at age 20 would be 0.73 but for a man at age 80 would be 0.62. A 20-year-old woman would have obstructive lung disease with an FEV1/FVC of less than 0.76 whereas a 20-year-old man would not be considered obstructed until his FEV1/FVC is less than 0.73.
Race and ethnicity
In the past, race was also factored into the determination of normal PFT values. Not for nefarious reasons but for the simple fact that when large numbers of normal people were tested, there are racial differences in the average PFT values after age, gender and height were all accounted for. Last year, the American Thoracic Society recommended eliminating race in PFT interpretation because of a concern that it implied biological differences between people of different races and ethnicities but those changes are actually due to social and environmental factors as well as structural racism. So, should we stop using race and ethnicity in defining normal values in pulmonary function test interpretation?
What is a person’s race, anyway?
My grandmother’s mother was White and her father was Chinese. She was not allowed to attend Atlanta public schools because in the eyes of the school board she was considered Chinese if one of her parents was from China. Genetically, she was just as much White as she was Chinese. Similarly, if you ask 1,000 Americans if Barack Obama is White or Black, 999 of those Americans will say he is Black. His father was from Africa but his mother was Caucasian of Irish ancestry. Like my grandmother, he is genetically just as much White as he is Black. The point is that we assign race labels using social criteria as much as (or more than) true ancestral heritage. When those large numbers of healthy people were tested to determine normal values for PFTs, they were grouped by self-reported race and not by sending gene tests off to 23andMe to determine their genetic ancestry. In the melting pot that is the United States, the vast majority of us have very complex ancestry. Lumping everyone into categories of White, Black, Asian, Hispanic, Native American, etc. is often arbitrary and not very accurate.
But differences do exist…
There are clearly problems fitting many people into one specific race or ethnicity group. But for those people who do self-report themselves belonging to one group or another, there are racial and ethnic differences in normal values. The NHANES III normal values are most commonly used in pulmonary function test interpretation. The NHANES III data set indicates that for a 5′ 9″ 65-year-old man, the average forced vital capacity (FVC) is 4.60 liters for normal Whites, 4.52 liters for normal Hispanics, and 3.87 liters for normal Blacks. There are similar racial differences for women. The normal values were obtained by testing a large number of healthy non-smokers. A valid criticism of the NHANES III data set is that it stratified people into only three groups: White, Black, and Hispanic; other racial and ethnic groups were not included.
A second commonly used data set of normal pulmonary function test values is the Global Lung Initiative (GLI) that stratified people into five groups: Caucasian (Europe, Israel, Australia, USA, Canada, Mexican Americans, Brazil, Chile, Mexico, Uruguay, Venezuela, Algeria, Tunisia), Black (African American), Northeast Asian (North China & South Korea), Southeast Asian (South China, Taiwan, Hong Kong, and Thailand), and other/mixed. Using the GLI data set for a 65-year-old man who is 5′ 9″, the average normal FVC for Caucasian is 4.30 liters, Black 3.63 liters, Northeast Asian 4.13 liters, Southeast Asian 3.82 liters, and other/mixed 3.96 liters.
So, for any given height, gender, and age, normal people who identify as being Southeast Asian or Black have lower lung volumes than those who identify as being Northeast Asian, White, or Hispanic. But that does not mean that race biologically caused those differences. Instead, race and ethnicity may merely correlate with other factors that affect lung volumes.
Factors that correlate with race and ethnicity
When differences exist between people of different races or ethnicities, it does not necessarily mean that those differences are caused by the person’s race – it usually means that those differences are correlated with the person’s race. There is a big difference between causality and correlation. For example, say you are studying the incidence of vitamin D deficiency and you find that Whites in Norway have a higher rate of vitamin D deficiency than Hispanics from Guatemala. Race did not cause the vitamin D deficiency – living at a high latitude with little sunlight caused the vitamin D deficiency. Race merely correlated with vitamin D deficiency because of Hispanics in Guatemala live at a lower latitude than Whites in Norway. Here are some of the factors affecting pulmonary function that correlate with (but are not caused by) race and ethnicity.
Genetics. Lung volumes can be affected by a person’s genes. Just like all of the members of a family might have big ears, all of the members of a family might have big lung volumes. We often define race by skin color. But race is a poor surrogate for genetics and there is no good reason to believe that the genes that determine the amount of pigment in a person’s skin should also dictate the size of a person’s lung volumes.
Socioeconomic status. When English physician John Hutchinson invented the spirometer in 1846, he used it to show differences in lung function between people in different professions, which was a crude estimate of socioeconomic status. There are a lot of reasons why people from lower socioeconomic groups could have lower lung volumes than those from higher socioeconomic groups. Crowded living conditions can lead to more frequent childhood respiratory infections and greater exposure to environmental tobacco smoke. Air pollution in lower class residential areas can affect lung function. Poor nutrition in childhood can have a profound impact on both height and lung function in adulthood. Inadequate treatment of childhood asthma due to limited access to healthcare in childhood can result in lower pulmonary function values in adulthood. When we identify racial and ethnic differences in many health metrics, often what we are really identifying is the socioeconomic differences in those metrics, with race just being a reflection of socioeconomic status.
Maternal health. Maternal smoking during pregnancy, lower birth weight, and premature birth can all affect lung development in infancy. There are significant racial differences in access to maternal healthcare that can impact a child’s lung function.
Obesity. Body weight is not used as a demographic variable in PFT interpretation but obesity can have a profound effect on lung volumes, causing them to be lower. African American adults have a high prevalence of obesity (38.4%) compared with Hispanic American adults (32.6%) and White American adults (28.6%).
Occupation. Certain occupations can affect lung health and thus lung function. Exposure to airborne chemicals, toxins, and dusts can impact lung volumes and flow rates. These are often lower-paying occupations that disproportionately employ workers from minority races and ethnicities.
Altitude. People who live their entire lives at higher altitude have higher lung volumes than those who live at lower altitudes. Studies of inhabitants from Peru, Korea, and Tibet have found that people living at high altitudes have higher values for forced vital capacity (FVC) and forced expiratory volume in 1 second (FEV1). This is presumed to be an adaptive mechanism since people living in high altitudes with lower atmospheric PO2 levels must maintain a higher minute ventilation to maintain normal tissue oxygenation.
The danger of ignoring race and ethnicity in PFT interpretation
One of the arguments against using race and ethnicity in PFT interpretation is that by separating patients into different racial or ethnic groups, we are encouraging health disparities. However, an equal argument can be made that if we do not use race and ethnicity in PFT interpretation, we are actually causing health disparities.
Several years ago, I got a panicked call from a family medicine physician who had gotten a spirometry test that showed a low FVC interpreted as indicative of restrictive lung disease and he was worried he had interstitial lung disease. I obtained a new full set of pulmonary function tests and confirmed that both his FVC and total lung capacity were below the 5th percentile of normal, indicating restrictive lung disease. But he was from India and moved to the U.S. when he was a teenager. Our PFT machine utilized the NHANES data set that did not include a racial designation of Southeast Asian (or even just Asian) so he was compared to normal values for Whites. I told him that people from India normally have lower lung volumes compared to White people from the U.S. and that I believed that he was healthy. However, he was very anxious and ended up getting a high resolution chest CT and a cardiopulmonary exercise test just to prove that he did not have interstitial lung disease.
This case illustrates that if we do not use race and ethnicity in PFT interpretation, then we run the risk of incorrectly labeling many Southeast Asian and Black patients as having restrictive lung disease when in fact, they are normal. In addition, by including all racial and ethnic groups in the calculations of normal values, we end up with lower values for the 5th percentile of normal for White, Hispanic, and Northeast Asian patients. As a result, we can miss restrictive lung disease in these racial and ethnic groups.
PFTs are also used to determine life insurance premiums and suitability for certain occupations. I recently got an email from one of the nurses at our hospital whose son was unable to enter firefighter school because his FEV1 was too low (he is healthy with no known lung disease). Abnormal PFT values can keep a person from entering the military or becoming a commercial pilot. PFTs are used in disability determination, in pulmonary rehabilitation eligibility, and in pre-operative assessment for lung cancer surgery. By eliminating race and ethnicity, we could inadvertently prevent African Americans and Southeast Asians from getting certain jobs or getting needed lung cancer surgery. Similarly, we could make it more difficult for Northeast Asians and Whites to get disability benefits or get into pulmonary rehabilitation.
PFT interpretation is as much art as it is science
When I was a resident, one of my mentors who was a cardiologist told me that the non-cardiologist at a patient’s bedside could interpret that patient’s EKG better than the cardiologist reading that EKG who has never seen the patient. That is because tests such as EKGs are best interpreted in the context of the individual patient’s clinical presentation and the person in the best position to know that clinical presentation is the physician at the beside taking care of that patient (provided that the physician is well-trained in EKG interpretation).
Pulmonary function tests are similar in this way to EKGs. If a patient is 8 months pregnant or has severe scoliosis on physical exam and that patient’s PFTs have a computer interpretation of restrictive lung disease, I am not going to do an extensive work-up for interstitial lung disease because my physical exam shows me that the PFT changes are due to diaphragm limitation by a gravid uterus or to chest wall abnormalities caused by scoliosis. If we do not include race in the demographics entered into the PFT computer and the computer interpretation shows mild restrictive lung disease, I will be less concerned if I know that patient is from India.
Using race and ethnicity in PFT interpretation is a conundrum – we are damned if we do and damned if we don’t. At the workshop that led to the new American Thoracic Society guidelines, 30 out of 33 attendees recommended to eliminate race and ethnicity in PFT interpretation. For this reason, it is likely that in the near future, race/ethnic demographics will not be requested when entering data into PFT machines and those machines will use race-neutral data sets of normal people in the determination of percent predicted values. It will be incumbent on all of us who use pulmonary function tests to ensure that we do not create healthcare disparities in our attempt to eliminate healthcare disparities when race-neutral data sets are used.
February 10, 2024