Comments
Abstract
Rationale: Natural history of preserved ratio impaired spirometry (PRISm), often defined as FEV1/FVC ⩾lower limit of normal and FEV1 <80% of predicted value, is not well described.
Objectives: To investigate the natural history and long-term prognosis of the following PRISm trajectories: persistent PRISm trajectory (individuals with PRISm both young and middle-aged), normal to PRISm trajectory (individuals developing PRISm from normal spirometry in young adulthood), and PRISm to normal trajectory (individuals recovering from PRISm in young adulthood by normalizing spirometry while middle-aged).
Methods: We followed 1,160 individuals aged 20–40 years from the Copenhagen City Heart Study from 1976 to 1983 until 2001 to 2003 to determine their lung function trajectory; 72 had persistent PRISm trajectory, 76 had normal to PRISm trajectory, 155 had PRISm to normal trajectory, and 857 had normal trajectory. From 2001–2003 until 2018, we determined the risk of cardiopulmonary disease and death.
Measurements and Main Results: We recorded 198 admissions for heart disease, 143 for pneumonia, and 64 for chronic obstructive pulmonary disease as well as 171 deaths. Compared with individuals with normal trajectory, hazard ratios for individuals with persistent PRISm trajectory were 1.55 (95% confidence interval, 0.91–2.65) for heart disease admission, 2.86 (1.70–4.83) for pneumonia admission, 6.57 (3.41–12.66) for chronic obstructive pulmonary disease admission, and 3.68 (2.38–5.68) for all-cause mortality. Corresponding hazard ratios for individuals with normal to PRISm trajectory were 1.91 (1.24–2.95), 2.74 (1.70–4.42), 7.61 (4.21–13.72), and 2.96 (1.94–4.51), respectively. Prognosis of individuals with PRISm to normal trajectory did not differ from those with normal trajectory.
Conclusions: PRISm in middle-aged individuals is associated with increased risk of cardiopulmonary disease and all-cause mortality, but individuals who recover from PRISm during their adult life are no longer at increased risk.
The prevalence of preserved ratio impaired spirometry (PRISm) has been reported as high in current and former smokers in the general population and is associated with increased risk of developing chronic obstructive pulmonary disease and all-cause mortality. Nonetheless, individuals with PRISm also seem to display increased cardiovascular morbidity and mortality. However, the natural history of PRISm throughout adult life is still not well described.
In the general population, both individuals with persistent PRISm throughout adult life and those who develop PRISm from normal lung function from age 20 to 40 years experience an increased risk of cardiopulmonary disease and death; however, individuals who recover from PRISm during their adult life have a similar prognosis as those with normal lung function.
A substantial proportion of individuals in high-income and particularly low-income countries display preserved ratio impaired spirometry (PRISm), often defined as FEV1/FVC ⩾0.70 (or ⩾lower limit of normal [LLN]) and FEV1 <80% of the predicted normal value (1–12). However, the natural history of PRISm lung function trajectory is not well described. In particular, our knowledge of the long-term prognosis of individuals with PRISm regarding morbidity and mortality is based on relatively few studies with a limited follow-up time (2, 4, 5, 11, 12). In the U.S. COPDGene (COPD Genetic Epidemiology) cohort, which includes current and former smokers aged 45–80 years, PRISm was highly prevalent and associated with increased mortality after 5 years of follow-up (11). The study concluded that PRISm mainly represents a transitional state, as some individuals with PRISm normalized their lung function; however, as many as 22% developed Global Initiative for Obstructive Lung Disease (GOLD) stage 0, and 25% progressed to GOLD stages 1–4 chronic obstructive pulmonary disease (COPD). In another U.S. study based on the TESAOD (Tucson Epidemiological Study of Airway Obstructive Disease) cohort, the investigators reported that 32% of individuals with PRISm developed COPD during follow-up and concluded that PRISm was difficult to distinguish from obstructive lung disease (4). A recent Dutch study based on the Rotterdam cohort concluded that PRISm is associated with increased mortality and that the PRISm population encompasses at least three distinct clinical groups: one that developed COPD during a 5-year follow-up time, a second with high cardiovascular disease burden and early death, and a third with persistent PRISm and normal age-related lung function decline (12).
In the present analyses based on a sample from the general population, the Copenhagen City Heart Study, Denmark, we investigate the course of PRISm lung function trajectory throughout adult life during up to 42 years of follow-up. By using repeated spirometries during the first 25 years of follow-up, we are able to identify three distinct PRISm lung function trajectories: individuals with persistent PRISm both when aged 20–40 years (early adulthood) and 25 years later when middle-aged, those that normalize their lung function from PRISm in early adulthood to normal values when middle-aged, and those that develop PRISm when middle-aged from a normal lung function in early adulthood. After assigning individuals to these three PRISm lung function trajectories, we hypothesized that the long-term prognosis, including hospital admissions from cardiopulmonary disease and overall survival, would be different from that of individuals with normal lung function trajectory throughout their adult life.
The Copenhagen City Heart Study is an ongoing prospective cohort study of the general population in Denmark based on a random sample of 19,698 individuals aged 20–100 years living in the inner city of Copenhagen in 1976–1978 (13). At the first survey, 14,223 men and women participated (response rate: 74%), and the whole sample was reinvited to subsequent surveys in 1981–1983, 1991–1994, and 2001–2003. The fourth survey included 6,237 individuals (response rate: 50%). The study was approved by an institutional review board and a Danish ethical committee (approval number: KF100.2039/91) and was conducted according to the Declaration of Helsinki. Written informed consent was obtained from all participants.
In the present analyses, we included 1,160 individuals aged 20–40 years when they attended their initial survey in 1976–1978 or 1981–1983 and were followed until the last survey in 2001–2003 to determine their PRISm lung function trajectory. Hereafter, individuals were followed from the last survey in 2001–2003 until 2018 to determine the risk of clinical outcomes. At each survey, participants answered an extensive questionnaire concerning lifestyle, health topics, symptoms, and exposures and underwent a physical health examination. Blood samples were drawn and analyzed for markers of systemic inflammation, including hsCRP (high-sensitivity C-reactive protein) and fibrinogen, and white blood cell counts.
At both the 1976–1978 and 1981–1983 surveys, the same electronic spirometer was used (Monaghan M403) (14). The spirometer was calibrated daily with a 1-L syringe and weekly against a water-sealed Godard spirometer. Spirometry was performed in a sitting position without the use of a nose clip with at least three measurements. At least two measurements differing by less than 5% had to be produced as a criterion for correct performance. The highest values of FEV1 and FVC were used.
In the 2001–2003 survey, a dry wedge spirometer was used (Vitalograph, Maids Moreton). The spirometer was calibrated daily with a 1-L syringe. Spirometry was performed in a standing position without the use of a nose clip with at least three measurements. At least two measurements differing by less than 5% together with a correct visual appearance of the spirometry tracings had to be produced as a criterion for correct performance. The highest obtained values of both FEV1 and FVC were used.
In all surveys used in the present analyses, only prebronchodilator measurements were available.
PRISm was defined as a FEV1/FVC ⩾LLN and FEV1 <80% of the predicted normal value (15). LLN was defined as the fifth percentile of the predicted normal value for FEV1/FVC, calculated as the mean value minus 1.645 SDs. Individuals with airflow limitation, defined as FEV1/FVC <LLN, were excluded.
Participants were assigned into one of four mutually exclusive lung function trajectories (Figures 1 and 2): Normal trajectory was defined as FEV1/FVC ⩾LLN and FEV1 ⩾80% of predicted at the initial survey visit in 1976–1978 or 1981–1983 as well as at the last survey visit in 2001–2003; PRISm to normal trajectory was defined as FEV1/FVC ⩾LLN and FEV1 <80% of predicted at the initial survey visit in 1976–1978 or 1981–1983 and FEV1/FVC ⩾LLN and FEV1 ⩾80% of predicted at the last survey visit in 2001–2003; normal to PRISm trajectory was defined as FEV1/FVC ⩾LLN and FEV1 ⩾80% of predicted at the initial survey visit in 1976–78 or 1981–83 and FEV1/FVC ⩾LLN and FEV1 <80% of predicted at the last survey visit in 2001–2003; and persistent PRISm trajectory was defined as FEV1/FVC ⩾LLN and FEV1 <80% of predicted at the initial survey visit in 1976–1978 or 1981–1983 as well as the last survey visit in 2001–2003.
Figure 1. Outline of the study. Participants were assigned into one of four mutually exclusive lung function trajectories based on spirometry measured approximately 25 years apart (from the initial survey visit in 1976–1978 or 1981–1983 until the last survey visit in 2001–2003): normal trajectory, PRISm to normal trajectory, normal to PRISm trajectory, and persistent PRISm trajectory. After the last survey visit in 2001–2003, individuals were followed for risk of cardiopulmonary disease and all-cause mortality for up to 17 years of follow-up. PRISm = preserved ratio impaired spirometry.
[More] [Minimize]
Figure 2. Flowchart for the study population. PRISm = preserved ratio impaired spirometry.
[More] [Minimize]All-cause mortality was obtained from the national Danish Civil Registration System, which contains date of death and emigration for all residents in Denmark, recorded from 2001–2003 until December 13, 2018 (16). Cardiopulmonary disease was based on three morbidity outcomes of interest, defined as hospitalizations owing to 1) ischemic heart disease (IHD) (International Classification of Diseases [ICD]-10: I20-I25) and/or heart failure (ICD-10: I50), 2) pneumonia (ICD-10: J12-J18), and 3) COPD (ICD-10: J44) as the main or secondary discharge diagnosis on the basis of information obtained from the National Danish Patient Registry, which covers all public and private hospital contacts in Denmark, recorded from 2001–2003 until December 7, 2018 (17). The ICD-10 code J44 performs well in the Danish context: a previous validation study has shown a positive predictive value of 92% for the presence of clinical COPD (18). No individuals were lost to follow-up, and those who emigrated were censored at the date of emigration.
For continuous variables, ANOVA and Mann–Whitney U test were used to compare means and medians, respectively. For categorical variables with two or more levels, Fisher’s exact test was used. The annualized decline in FEV1 was estimated as the slope from the initial survey visit in 1976–1983 to the last survey visit in 2001–2003. The median follow-up time from the 2001–2003 survey was estimated by the reverse Kaplan–Meier method by reversing the event indicator so that the outcome of interest becomes whether subjects are censored or not (19). The median follow-up time represents the time that 50% of the participants would have been followed had there been no events. Death was considered a competing risk for each of the cardiopulmonary morbidity outcomes. The cumulative incidence was estimated by the Aalen-Johansen estimator (20) for the cardiopulmonary morbidity outcomes, and the survival function was estimated by the Kaplan–Meier estimator (with log-rank test) for all-cause mortality. The association between the lung function trajectories and cardiopulmonary morbidity outcomes was analyzed using cause-specific Cox regression (21) (a natural extension of the Cox proportional hazards regression to the setting with competing risks), and the association between the lung function trajectories and all-cause mortality was analyzed using Cox proportional hazards regression, all adjusted for age and sex. The underlying time scale for all clinical outcomes was time since the last survey visit in 2001–2003. The interaction between smoking status and lung function trajectories on all clinical outcomes was tested using the likelihood ratio test. Sensitivity analyses with additional adjustment for FEV1 as percent of predicted normal value and for other potential confounders related to cardiovascular disease were performed for IHD and/or heart failure outcome. In another sensitivity analysis, the fixed ratio (the GOLD criteria for COPD and restrictive ventilatory impairment) rather than LLN was used to define the lung function trajectories, and key analyses were performed for this classification. The key assumption of the Cox regression, the proportionality assumption, was tested with the score process test, as suggested by Lin, Wei, and Ying (22). Differences in survival (years lost) were estimated with restricted mean survival time adjusted for age and sex with a maximum survival of 17 years (23). All analyses were performed with R version 3.5.2 (R Foundation for Statistical Computing). A two-sided P value <0.05 was chosen to indicate statistical significance.
Characteristics at the initial survey visit in 1976–1978 or 1981–1983 and 25 years later at the last survey visit in 2001–2003 for the four lung function trajectories are given in Table 1. Individuals in the normal to PRISm trajectory and persistent PRISm trajectory had a higher cumulative smoking exposure, body mass index (BMI), increase in BMI, hsCRP, fibrinogen, and white blood cell counts and reported more often dyspnea, chronic bronchitis, and low physical activity than those in the normal trajectory and PRISm to normal trajectory at the last survey visit in 2001–2003, suggesting that smoking, systemic inflammation, overweight, and physical inactivity are all associated with both the development and maintenance of PRISm and that this condition is associated with a high burden of respiratory symptoms.
| Group 1: Normal (n = 857) | Group 2: PRISm to Normal (n = 155) | Group 3: Normal to PRISm (n = 76) | Group 4: Persistent PRISm (n = 72) | P Value Group 1 vs. Group 2 | P Value Group 1 vs. Group 3 | P Value Group 1 vs. Group 4 | P Value Group 2 vs. Group 3 | P Value Group 2 vs. Group 4 | P Value Group 3 vs. Group 4 | |
|---|---|---|---|---|---|---|---|---|---|---|
| Characteristics at initial survey visit in 1976–1978 or 1981–1983 | ||||||||||
| Sex, M | 421/857 (49) | 61/155 (39) | 40/76 (53) | 26/72 (36) | 0.029 | 0.63 | 0.037 | 0.067 | 0.66 | 0.049 |
| Age, yr | ||||||||||
| Mean | 32 ± 6 | 30 ± 6 | 35 ± 5 | 33 ± 6 | <0.001 | <0.001 | 0.71 | <0.001 | 0.001 | 0.015 |
| Range | 21 to 40 | 22 to 40 | 22 to 40 | 21 to 40 | — | — | — | — | — | — |
| FEV1 | ||||||||||
| Mean, L | 3.8 ± 0.8 | 2.9 ± 0.5 | 3.5 ± 0.7 | 2.7 ± 0.5 | <0.001 | 0.004 | <0.001 | <0.001 | 0.018 | <0.001 |
| Percent of predicted value | 95 ± 10 | 74 ± 6 | 89 ± 8 | 71 ± 6 | <0.001 | <0.001 | <0.001 | <0.001 | 0.002 | <0.001 |
| FVC | ||||||||||
| Mean, L | 4.4 ± 1.0 | 3.4 ± 0.7 | 4.1 ± 0.9 | 3.2 ± 0.7 | <0.001 | 0.058 | <0.001 | <0.001 | 0.012 | <0.001 |
| Percent of predicted value | 93 ± 11 | 75 ± 7 | 88 ± 10 | 72 ± 9 | <0.001 | 0.001 | <0.001 | <0.001 | 0.003 | <0.001 |
| FEV1/FVC | 0.87 ± 0.06 | 0.83 ± 0.06 | 0.85 ± 0.06 | 0.84 ± 0.06 | <0.001 | 0.014 | 0.001 | 0.13 | 0.53 | 0.45 |
| Smoking status | — | — | — | — | 0.40 | <0.001 | 0.14 | <0.001 | 0.065 | 0.15 |
| Never-smoker | 294/855 (34) | 62/155 (40) | 13/75 (17) | 21/72 (29) | — | — | — | — | — | — |
| Former smoker | 138/855 (16) | 24/155 (15) | 5/75 (7) | 7/72 (10) | — | — | — | — | — | — |
| Current smoker | 423/855 (49) | 69/155 (45) | 57/75 (76) | 44/72 (61) | — | — | — | — | — | — |
| Childhood smoking onset (<14 yr old) | 32/547 (6) | 2/91 (2) | 9/62 (15) | 5/50 (10) | 0.21 | 0.027 | 0.22 | 0.008 | 0.097 | 0.57 |
| Asthma | 10/837 (1) | 1/154 (1) | 0/74 (0) | 1/70 (1) | >0.99 | >0.99 | 0.59 | >0.99 | 0.53 | 0.49 |
| BMI, kg/m2 | 23.1 ± 3.1 | 22.9 ± 3.4 | 24.2 ± 3.8 | 23.7 ± 4.1 | 0.33 | 0.004 | 0.13 | 0.007 | 0.10 | 0.45 |
| Characteristics at last survey visit in 2001–2003 | ||||||||||
| Age, yr | ||||||||||
| Mean | 57 ± 7 | 54 ± 7 | 60 ± 6 | 57 ± 7 | <0.001 | 0.001 | 0.52 | <0.001 | 0.001 | 0.039 |
| Range | 41 to 66 | 42 to 65 | 42 to 65 | 44 to 65 | — | — | — | — | — | — |
| FEV1 | ||||||||||
| Mean, L | 3.1 ± 0.7 | 2.9 ± 0.6 | 2.3 ± 0.5 | 2.1 ± 0.5 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.010 |
| Percent of predicted value, % | 100 ± 12 | 93 ± 11 | 75 ± 6 | 70 ± 8 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
| FVC | ||||||||||
| Mean, L | 4.0 ± 0.9 | 3.6 ± 0.8 | 3.1 ± 0.7 | 2.7 ± 0.7 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | 0.005 |
| Percent of predicted value, % | 102 ± 12 | 95 ± 12 | 79 ± 7 | 74 ± 9 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
| FEV1/FVC | 0.79 ± 0.05 | 0.80 ± 0.05 | 0.76 ± 0.05 | 0.77 ± 0.05 | 0.12 | <0.001 | <0.001 | <0.001 | <0.001 | 0.38 |
| Decline in FEV1 | ||||||||||
| Mean, ml/yr | 25 ± 18 | −2 ± 17 | 47 ± 16 | 23 ± 14 | <0.001 | <0.001 | 0.34 | <0.001 | <0.001 | <0.001 |
| Median (IQR), ml/yr | 24 (14 to 34) | 2 (−9 to 10) | 43 (34 to 55) | 23 (17 to 30) | <0.001 | <0.001 | 0.50 | <0.001 | <0.001 | <0.001 |
| Percent of baseline value per year, %/yr | 0.7 ± 0.4 | −0.1 ± 0.6 | 1.3 ± 0.3 | 0.9 ± 0.5 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 | <0.001 |
| Frequent childhood respiratory infections* | 39/759 (5) | 6/135 (4) | 4/64 (6) | 9/60 (15) | >0.99 | 0.57 | 0.006 | 0.73 | 0.018 | 0.15 |
| Current smoker | 251/843 (30) | 43/153 (28) | 38/75 (51) | 28/72 (39) | 0.70 | <0.001 | 0.11 | 0.001 | 0.12 | 0.19 |
| Smoking history, median (IQR), pack-years | 7 (0 to 26) | 5 (0 to 24) | 30 (7 to 45) | 21 (0 to 41) | 0.29 | <0.001 | 0.002 | <0.001 | 0.002 | 0.18 |
| Dyspnea (mMRC ⩾ 2) | 53/855 (6) | 9/154 (6) | 13/76 (17) | 6/72 (8) | >0.99 | 0.002 | 0.45 | 0.009 | 0.57 | 0.14 |
| Previous exposure to dust/fumes | 105/857 (12) | 16/154 (10) | 14/76 (18) | 9/72 (13) | 0.59 | 0.15 | >0.99 | 0.099 | 0.65 | 0.37 |
| Chronic bronchitis | 87/855 (10) | 9/154 (6) | 15/76 (20) | 11/72 (15) | 0.10 | 0.019 | 0.17 | 0.002 | 0.025 | 0.52 |
| Asthma | 33/856 (4) | 9/154 (6) | 7/76 (9) | 8/72 (11) | 0.27 | 0.038 | 0.011 | 0.41 | 0.18 | 0.79 |
| BMI, kg/m2 | ||||||||||
| Mean | 26.2 ± 4.0 | 26.1 ± 4.3 | 28.4 ± 5.2 | 28.0 ± 5.8 | 0.65 | <0.001 | 0.001 | 0.001 | 0.006 | 0.70 |
| Increase | 3.1 ± 2.7 | 3.3 ± 2.8 | 4.1 ± 3.2 | 4.4 ± 4.0 | 0.59 | 0.002 | <0.001 | 0.033 | 0.012 | 0.62 |
| Education, yr | 10.2 ± 2.2 | 10.6 ± 3.4 | 9.2 ± 2.0 | 9.8 ± 2.1 | 0.045 | <0.001 | 0.19 | 0.001 | 0.073 | 0.069 |
| Low physical activity | 59/851 (7) | 8/154 (5) | 15/76 (20) | 12/72 (17) | 0.49 | <0.001 | 0.009 | 0.001 | 0.010 | 0.67 |
| High physical activity | 397/851 (47) | 63/154 (41) | 21/76 (28) | 16/72 (22) | 0.22 | 0.002 | <0.001 | 0.059 | 0.007 | 0.57 |
| Hypertension | 378/857 (44) | 58/155 (37) | 49/76 (64) | 44/72 (61) | 0.13 | 0.001 | 0.006 | <0.001 | 0.001 | 0.73 |
| Diabetes | 43/857 (5) | 5/154 (3) | 6/76 (8) | 5/72 (7) | 0.42 | 0.28 | 0.41 | 0.19 | 0.30 | >0.99 |
| Ischemic heart disease and/or heart failure | 5/857 (1) | 2/155 (1) | 4/76 (5) | 1/72 (1) | 0.29 | 0.004 | 0.38 | 0.093 | >0.99 | 0.37 |
| hsCRP, median (IQR), mg/L | 1.2 (0.6 to 3.0) | 1.4 (0.7 to 3.4) | 2.0 (1.0 to 4.6) | 2.7 (1.1 to 7.8) | 0.096 | <0.001 | <0.001 | 0.026 | <0.001 | 0.18 |
| Fibrinogen, median (IQR), μmol/L | 10.8 (9.2 to 12.8) | 10.8 (9.3 to 12.4) | 12.0 (10.2 to 13.7) | 12.0 (10.3 to 13.7) | 0.82 | 0.004 | 0.001 | 0.005 | 0.002 | 0.68 |
| WBC count, median (IQR), ×109 | 6.3 (5.2 to 7.4) | 6.3 (5.3 to 7.6) | 7.1 (6.1 to 8.8) | 7.1 (6.2 to 8.5) | 0.67 | <0.001 | <0.001 | 0.001 | 0.004 | 0.76 |
Individuals in the normal to PRISm trajectory and those in the persistent PRISm trajectory presented with similar clinical features at the last survey visit in 2001–2003, including FEV1/FVC, smoking status and history, previous exposure to dust/fumes, chronic bronchitis, asthma, BMI, increase in BMI, hypertension, diabetes, and markers of systemic inflammation. Although not statistically significant, both dyspnea and previous admissions for IHD/heart failure were numerically higher in the normal to PRISm trajectory versus persistent PRISm trajectory, but frequent childhood respiratory infections were numerically higher in the latter group. However, compared with individuals belonging to the normal to PRISm trajectory, those in the persistent PRISm trajectory were more likely younger and women, with lower FEV1 and FVC, and had an FEV1 decline of half the size during 25 years of follow-up (23 ml/yr vs. 47 ml/yr).
Individuals belonging to the two trajectories with normal lung function at the last survey visit in 2001–2003 were different from each other with respect to sex, age, education, FEV1, FVC, and FEV1 decline (25 ml/yr for the normal trajectory vs. −2 ml/yr for the PRISm to normal trajectory).
In absolute terms, the average loss/increase in FEV1 during the 25 years of follow-up was 622 ml in the normal trajectory, −23 ml in the PRISm to normal trajectory, 1,160 ml in the normal to PRISm trajectory, and 583 ml in the persistent PRISm trajectory.
During a median follow-up time of 16.3 years (interquartile range, 15.7–16.7) from 2001–2003 through 2018, we recorded 198 admissions for IHD/heart failure, 143 for pneumonia, and 64 for COPD among 1,160 participants. Figure 3 shows 1 minus the cumulative incidence and risk estimates for cardiopulmonary morbidity according to the four lung function trajectories.
Figure 3. The top panel shows 1 minus the cumulative incidence of cardiopulmonary admissions for the four lung function trajectories. The bottom panel shows the risk of cardiopulmonary admissions for the four lung function trajectories adjusted for age and sex. CI = confidence interval; COPD = chronic obstructive pulmonary disease; IHD = ischemic heart disease; PRISm = preserved ratio impaired spirometry.
[More] [Minimize]The risk of admission was the same for the normal trajectory compared with the PRISm to normal trajectory for all three cardiopulmonary morbidity outcomes. The two trajectories with PRISm in middle age showed similar risk of all three clinical outcomes, which was higher compared with the normal trajectory. Compared with individuals in the normal trajectory, the hazard ratio (HR) for IHD/heart failure admission was 0.59 (95% confidence interval [CI], 0.33–1.04) for individuals in the PRISm to normal trajectory, 1.91 (95% CI, 1.24–2.95) for individuals in the normal to PRISm trajectory, and 1.55 (95% CI, 0.91–2.65) for individuals in the persistent PRISm trajectory. Corresponding HRs were 1.14 (95% CI, 0.66–1.98), 2.74 (95% CI, 1.70–4.42), and 2.86 (95% CI, 1.70–4.83) for pneumonia admission and 0.66 (95% CI, 0.20–2.19), 7.61 (95% CI, 4.21–13.72), and 6.57 (95% CI, 3.41–12.66) for COPD admission, respectively.
During a median follow-up time of 16.4 years (interquartile range, 15.9–16.8), 171 deaths were recorded among 1,160 participants. Figure 4 shows survival and risk of all-cause mortality according to the four lung function trajectories. Kaplan–Meier curves show considerable discrepancies between the PRISm lung function trajectories with a log-rank test of P < 0.001. Although individuals in the PRISm to normal trajectory had similar survival as those in the normal trajectory, risk of all-cause mortality was substantially higher in the two trajectories with PRISm in middle age compared with the normal trajectory. Compared with individuals in the normal trajectory, the HR for all-cause mortality was 1.06 (95% CI, 0.61–1.83) for individuals in the PRISm to normal trajectory, 2.96 (95% CI, 1.94–4.51) for normal to PRISm trajectory, and 3.68 (95% CI, 2.38–5.68) for individuals in the persistent PRISm trajectory. The adjusted number of life years lost during follow-up compared with normal trajectory was 1.36 (95% CI, 0.38–2.33) for normal to PRISm trajectory and 2.19 (95% CI, 1.14–3.24) for persistent PRISm trajectory.
Figure 4. The top panel shows the survival for the four lung function trajectories. The middle panel shows the risk of all-cause mortality for the four lung function trajectories adjusted for age and sex. The bottom panel shows the difference in survival for the four lung function trajectories adjusted for age and sex. CI = confidence interval; PRISm = preserved ratio impaired spirometry.
[More] [Minimize]Adjustment for age, sex, and FEV1 as percent of predicted value slightly reduced the risk of IHD/heart failure admission for PRISm to normal trajectory compared with normal trajectory, with an HR of 0.52 (95% CI, 0.29–0.92). Even after adjustment for other potential confounders related to cardiovascular disease, including smoking history, physical activity, BMI, hypertension, and education, individuals in the PRISm to normal trajectory had a numerically lower risk of IHD/heart failure admission compared with individuals in the normal trajectory, with an HR of 0.74 (95% CI, 0.41–1.33). We found no evidence of an interaction between current smoking and the four lung function trajectories for IHD/heart failure admission (P = 0.54), pneumonia admission (P = 0.14), COPD admission (P = 0.89), or all-cause mortality (P = 0.12).
The number of individuals in each of the lung function trajectories was slightly higher when using the fixed ratio for FEV1/FVC instead of LLN to define the groups (see Table E1 in the online supplement), but results were similar for all endpoints (Figure E1 and Figure E2).
Selection bias is an obvious concern, as attendance at two surveys 25 years apart was chosen as an inclusion criterion for this study. Individuals aged 20–40 years identified with PRISm at their initial survey visit in 1976–1983 were at an increased risk of all-cause mortality before the last survey visit in 2001–2003 compared with individuals with normal lung function, with an age-adjusted HR of 1.74 (95% CI, 1.29–2.34). However, because of the age criterion of 20–40 years, less than 9% of the eligible individuals died before the last survey in 2001–2003. Correspondingly, compared with individuals with normal lung function, individuals with PRISm were not at an increased risk of admissions for IHD/heart failure, with an age-adjusted HR of 1.33 (95% CI, 0.92–1.93), or pneumonia, with an age-adjusted HR of 1.40 (95% CI, 0.86–2.27), but they were at an increased risk of admissions for COPD, with an age-adjusted HR of 2.96 (95% CI, 1.61–5.45). Furthermore, individuals with PRISm had only a 32% (95% CI, 6%–64%) higher risk of not participating in the last survey in 2001–2003 after 25 years of follow-up.
This study focused on the long-term prognosis of individuals from the general population with different PRISm lung function trajectories from early adulthood to middle age. We observed that individuals with persistent PRISm and those who developed PRISm in middle age from normal lung function in their early adulthood had significantly higher risk of mortality and hospital admissions from lung and heart disease than those with normal lung function throughout adult life. Importantly, individuals who recovered from PRISm by obtaining normal lung function while in middle age had a similar prognosis as those with normal lung function, suggesting that if the lung function recovers during early adulthood, previous history of PRISm does not seem to affect long-term morbidity and mortality.
The observation that small lung volumes are associated with poor survival is not new. Actually, it goes back more than 170 years to John Hutchinson, the inventor of the spirometer, and his pivotal findings that gave name to VC as the amount of air that could be expired from the lungs, inherently stating that this value reflects vitality and is related to survival (24). As reviewed by Godfrey and Jankowich, restrictive spirometry pattern, today often labeled as PRISm, has been associated with various disease outcomes, including diabetes, metabolic syndrome, hypertension, stroke, cardiovascular disease, and mortality (25). The present study confirms and expands these findings by including a dimension of the natural history of lung function trajectories, as the observation period of more than 40 years allowed us to allocate the participants into the relevant trajectory based on 25 years of observation from early adulthood until middle age.
Although we excluded individuals with airflow limitation, it is remarkable that the number of active smokers as well as the amount of tobacco exposure were substantially higher in the two trajectories with PRISm at the last survey visit than in the normal trajectory and PRISm to normal trajectory (Table 1). This suggests that smoking, in addition to causing airflow limitation, perhaps in combination with overweight/adiposity, may also be associated with restrictive lung function impairment. Our observation of the very high risk of admissions from COPD in the two trajectories with PRISm at the last survey visit is in line with previous observations that PRISm often precedes development of COPD (4, 9, 11, 12). Indeed, the results from the COPDGene cohort highlight that a substantial proportion of smokers, despite absence of airflow limitation, are still treated with COPD medications and experience COPD-like symptoms and exacerbation-like events (26).
Over the years, there has been an ongoing discussion of the pathophysiological mechanisms behind PRISm, including its poor prognosis. In addition to factors causing extrapulmonary restriction, such as obesity, kyphoscoliosis, or previous stroke, systemic inflammation has also been suggested as a possible link between PRISm and cardiopulmonary morbidity (2, 3, 27–29). In the present study, we also observed significantly higher levels of markers of systemic inflammation in the trajectories with PRISm at the last survey in 2001–2003, yet it is not clear whether this elevation plays any causal role for development of PRISm or merely reflects the high prevalence of smoking and high BMI in individuals with this condition. Systemic inflammation is, in particular, believed to play a role in morbidity from cardiovascular disease and is related to the presence of diabetes, which has also been associated with small lung volumes in the present cohort (30, 31). It has also been proposed that systemic inflammation associated with PRISm may be caused by exposure to air pollution, particularly in low-income countries (28). Participants of the present study all lived in the same geographical region with low levels of air pollution, and we could not demonstrate significant differences regarding exposure to occupational dust/fumes between the four lung function trajectories (Table 1).
Childhood respiratory infections have been associated with low lung function in middle-aged adults (32). However, the presence of PRISm in middle age may be more strongly related to other lifestyle factors such as obesity, smoking, and physical inactivity, whereas PRISm in early adulthood may be more strongly influenced by early-life events such as respiratory infections in the first years of life and maternal smoking during pregnancy (33). In line with this, we observed more frequent childhood respiratory infections among those with persistent PRISm, which was significantly higher than in those who developed PRISm in their late adulthood but had normal lung function when aged 20–40 years (Table 1).
Previous longitudinal observations of 0.5 to 20 years of duration have documented a transitional nature of PRISm (4, 5, 9, 11, 12). In addition to developing COPD, a substantial proportion of individuals normalized or did not worsen their spirometry—a phenomenon named as a beneficial transition (9). In fact, during the initial 25 years of follow-up in the present study, approximately twice as many individuals recovered from PRISm compared with those who continued to have PRISm (Figure 2). Perhaps the most important and encouraging finding in our study is that individuals who recovered from PRISm had a similar survival and morbidity as those in the normal lung function trajectory. The group experiencing this remarkable lung function recovery had the highest education, smoked less, and was more physically active than individuals in the two trajectories ending with PRISm. This suggests that a healthy lifestyle most likely played an important role for this group’s favorable development and good prognosis. Thus, although low maximally attained lung function in early adulthood is related to a higher risk of comorbidities and mortality later in life (34, 35), a recovery of lung function during the adult years is possible and seems to reflect a better prognosis. On the other hand, it is important to notice that a higher proportion of individuals with low lung function at the initial survey visit in 1976–1983 died before the last survey visit in 2001–2003 (Figure 2), which highlights the heterogeneity behind possible reversibility of low lung function in early adulthood and possibility of a catch up (36).
Some potential limitations in the present study should be considered. Importantly, the spirometry procedure applied in the 1976–1978 and the 1981–1983 surveys does not satisfy present recommendations. Today, we have no direct possibilities to evaluate these spirometries on an individual basis. In the early 1990s, the results for the whole cohort were evaluated by comparing the values of healthy and asymptomatic never-smokers with the reference values for normal subjects provided by the Danish Society of Respiratory Medicine, and a good agreement was found (37). However, as the measurement of FEV1 probably has a better repeatability than FVC, the low quality of the spirometry in the years 1976–1983 could lead to overestimation of the participants with PRISm and be responsible for a wrong assignment of some normal individuals to the PRISm to normal subgroup. This could explain the almost no change in FEV1 and improvement in FVC from the initial survey to the 2001–2003 survey in the latter group and make our results regarding this subgroup less valid. However, the PRISm to normal group showed a numerically lower risk of admission for IHD and/or heart failure compared with the normal group, and this suggests that these groups are not just the result of a low-quality spirometry measurement or participants performing poorly on the day of examination in 1976–1983. If so, the risk of admission would not be influenced more than 25 years later. A plausible scenario is that we have slightly underestimated FEV1 and FVC at the initial survey visit in 1976–1983 in the PRISm to normal group.
Another potential limitation is the fact that only prebronchodilator measurements were available; however, this should have less importance, as the main focus is on the individuals with a preserved ratio of FEV1 and FVC and not airflow limitation (8). Another potential limitation is a small number of individuals in the two trajectories with PRISm at the last survey visit in 2001–2003. Thus, our results should be interpreted with caution and repeated in another population with spirometry in accordance with present standards.
Selection bias is clearly a concern with an inclusion criterion of measurements 25 years apart, and although individuals with PRISm at the initial survey visit in 1976–1983 had a relatively higher mortality rate than individuals with normal lung function, the absolute mortality rates were quite low in both groups because of the fact that only individuals aged 20–40 years were included. Furthermore, individuals with PRISm at the initial survey visit in 1976–1983 had only a 32% higher risk of not participating at the last survey visit in 2001–2003 compared with those with normal lung function at the initial survey visit in 1976–1983.
In the general population, both individuals with persistent PRISm throughout adult life and those who develop PRISm from normal lung function when aged 20–40 years experience an increased risk of cardiopulmonary disease and all-cause mortality, but individuals who recover from PRISm during their adult life have similar risk as those with normal lung function.
| 1. | Mannino DM, Ford ES, Redd SC. Obstructive and restrictive lung disease and functional limitation: data from the Third National Health and Nutrition Examination. J Intern Med 2003;254:540–547. |
| 2. | Mannino DM, Holguin F, Pavlin BI, Ferdinands JM. Risk factors for prevalence of and mortality related to restriction on spirometry: findings from the First National Health and Nutrition Examination Survey and follow-up. Int J Tuberc Lung Dis 2005;9:613–621. |
| 3. | Scarlata S, Pedone C, Fimognari FL, Bellia V, Forastiere F, Incalzi RA. Restrictive pulmonary dysfunction at spirometry and mortality in the elderly. Respir Med 2008;102:1349–1354. |
| 4. | Guerra S, Sherrill DL, Venker C, Ceccato CM, Halonen M, Martinez FD. Morbidity and mortality associated with the restrictive spirometric pattern: a longitudinal study. Thorax 2010;65:499–504. |
| 5. | Iyer VN, Schroeder DR, Parker KO, Hyatt RE, Scanlon PD. The nonspecific pulmonary function test: longitudinal follow-up and outcomes. Chest 2011;139:878–886. |
| 6. | Mannino DM, McBurnie MA, Tan W, Kocabas A, Anto J, Vollmer WM, et al.; BOLD Collaborative Research Group. Restricted spirometry in the Burden of Lung Disease Study. Int J Tuberc Lung Dis 2012;16:1405–1411. |
| 7. | Meghji J, Nadeau G, Davis KJ, Wang D, Nyirenda MJ, Gordon SB, et al. Noncommunicable lung disease in Sub-Saharan Africa. A community-based cross-sectional study of adults in urban Malawi. Am J Respir Crit Care Med 2016;194:67–76. |
| 8. | Backman H, Eriksson B, Hedman L, Stridsman C, Jansson S-A, Sovijärvi A, et al. Restrictive spirometric pattern in the general adult population: methods of defining the condition and consequences on prevalence. Respir Med 2016;120:116–123. |
| 9. | Sood A, Petersen H, Qualls C, Meek PM, Vazquez-Guillamet R, Celli BR, et al. Spirometric variability in smokers: transitions in COPD diagnosis in a five-year longitudinal study. Respir Res 2016;17:147. |
| 10. | Siddharthan T, Grigsby M, Miele CH, Bernabe-Ortiz A, Miranda JJ, Gilman RH, et al. Prevalence and risk factors of restrictive spirometry in a cohort of Peruvian adults. Int J Tuberc Lung Dis 2017;21:1062–1068. |
| 11. | Wan ES, Fortis S, Regan EA, Hokanson J, Han MK, Casaburi R, et al.; COPDGene Investigators. Longitudinal phenotypes and mortality in preserved ratio impaired spirometry in the COPDGene study. Am J Respir Crit Care Med 2018;198:1397–1405. |
| 12. | Wijnant SRA, De Roos E, Kavousi M, Stricker BH, Terzikhan N, Lahousse L, et al. Trajectory and mortality of preserved ratio impaired spirometry: the Rotterdam Study. Eur Respir J 2020;55:1901217. |
| 13. | Marott JL, Ingebrigtsen TS, Çolak Y, Vestbo J, Lange P. Lung function trajectories leading to chronic obstructive pulmonary disease as predictors of exacerbations and mortality. Am J Respir Crit Care Med 2020;202:210–218. |
| 14. | Cox P, Miller L, Petty TL. Clinical evaluation of a new electronic spirometer. Chest 1973;63:517–519. |
| 15. | Løkke A, Marott JL, Mortensen J, Nordestgaard BG, Dahl M, Lange P. New Danish reference values for spirometry. Clin Respir J 2013;7:153–167. |
| 16. | Helweg-Larsen K. The Danish register of causes of death. Scand J Public Health 2011;39:26–29. |
| 17. | Schmidt M, Schmidt SAJ, Sandegaard JL, Ehrenstein V, Pedersen L, Sørensen HT. The Danish National Patient Registry: a review of content, data quality, and research potential. Clin Epidemiol 2015;7:449–490. |
| 18. | Thomsen RW, Lange P, Hellquist B, Frausing E, Bartels PD, Krog BR, et al. Validity and underrecording of diagnosis of COPD in the Danish National Patient Registry. Respir Med 2011;105:1063–1068. |
| 19. | Schemper M, Smith TL. A note on quantifying follow-up in studies of failure time. Control Clin Trials 1996;17:343–346. |
| 20. | Aalen OO, Johansen S. An empirical transition matrix for non-homogeneous Markov chains based on censored observations. Scand J Stat 1978;5:141–150. |
| 21. | Gerds TA, Scheike TH, Andersen PK. Absolute risk regression for competing risks: interpretation, link functions, and prediction. Stat Med 2012;31:3921–3930. |
| 22. | Lin DY, Wei LJ, Ying Z. Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 1993;80:557–572. |
| 23. | Tian L, Zhao L, Wei LJ. Predicting the restricted mean event time with the subject’s baseline covariates in survival analysis. Biostatistics 2014;15:222–233. |
| 24. | Petty TL. John Hutchinson’s mysterious machine revisited. Chest 2002;121:219S–223S. |
| 25. | Godfrey MS, Jankowich MD. The vital capacity is vital: epidemiology and clinical significance of the restrictive spirometry pattern. Chest 2016;149:238–251. |
| 26. | Woodruff PG, Barr RG, Bleecker E, Christenson SA, Couper D, Curtis JL, et al.; SPIROMICS Research Group. Clinical significance of symptoms in smokers with preserved pulmonary function. N Engl J Med 2016;374:1811–1821. |
| 27. | Leone N, Courbon D, Thomas F, Bean K, Jégo B, Leynaert B, et al. Lung function impairment and metabolic syndrome: the critical role of abdominal obesity. Am J Respir Crit Care Med 2009;179:509–516. |
| 28. | Jackson P, Siddharthan T. The global significance of PRISm: how data from low- and middle-income countries link physiology to inflammation. Eur Respir J 2020;55:2000184. |
| 29. | Wijnant SRA, Lahousse L, Brusselle GG. The global significance of PRISm: how data from low- and middle-income countries link physiology to inflammation. Eur Respir J 2020;55:2000354. |
| 30. | Engström G, Lind P, Hedblad B, Wollmer P, Stavenow L, Janzon L, et al. Lung function and cardiovascular risk: relationship with inflammation-sensitive plasma proteins. Circulation 2002;106:2555–2560. |
| 31. | Lange P, Groth S, Kastrup J, Mortensen J, Appleyard M, Nyboe J, et al. Diabetes mellitus, plasma glucose and lung function in a cross-sectional population study. Eur Respir J 1989;2:14–19. |
| 32. | Perret JL, Lodge CJ, Lowe AJ, Johns DP, Thompson BR, Bui DS, et al.; TAHS investigators. Childhood pneumonia, pleurisy and lung function: a cohort study from the first to sixth decade of life. Thorax 2020;75: 28–37. |
| 33. | Svanes C, Sunyer J, Plana E, Dharmage S, Heinrich J, Jarvis D, et al. Early life origins of chronic obstructive pulmonary disease. Thorax 2010;65:14–20. |
| 34. | Agustí A, Noell G, Brugada J, Faner R. Lung function in early adulthood and health in later life: a transgenerational cohort analysis. Lancet Respir Med 2017;5:935–945. |
| 35. | Vasquez MM, Zhou M, Hu C, Martinez FD, Guerra S. Low lung function in young adult life is associated with early mortality. Am J Respir Crit Care Med 2017;195:1399–1401. |
| 36. | Allinson JP, Hardy R, Donaldson GC, Shaheen SO, Kuh D, Wedzicha JA. Combined impact of smoking and early-life exposures on adult lung function trajectories. Am J Respir Crit Care Med 2017;196:1021–1030. |
| 37. | Lange P. Development and prognosis of chronic obstructive pulmonary disease with special reference to the role of tobacco smoking. An epidemiologic study. Dan Med Bull 1992;39:30–48. |
Supported by Boehringer Ingelheim. Boehringer Ingelheim was given the opportunity to review the manuscript for medical and scientific accuracy as well as intellectual property considerations in relation to the potential mention of Boehringer Ingelheim substances. They did not participate in the design and conduct of the study; collection, management, analysis, or interpretation of the data; in preparation or approval of the manuscript; or decision to submit the manuscript for publication. The Copenhagen City Heart Study was funded by Capital Region of Copenhagen, Danish Heart Foundation, Danish Lung Association, and Velux Foundation. J.V. is supported by the NIH Research Manchester Biomedical Research Centre.
Author Contributions: J.L.M. and P.L. had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept, study design, and acquisition of data: J.L.M. and P.L. Analysis and interpretation of data: all authors. First draft of the manuscript: J.L.M. and P.L. Critical revision of the manuscript for important intellectual content: all authors. Statistical analysis: J.L.M. Obtained funding: J.L.M., J.V., and P.L. Administrative, technical, and material support: J.L.M. and P.L. Study supervision: P.L. All authors revised and approved the final version to be published.
This article has an online supplement, which is accessible from this issue’s table of contents at www.atsjournals.org.
Originally Published in Press as DOI: 10.1164/rccm.202102-0517OC on July 7, 2021
Author disclosures are available with the text of this article at www.atsjournals.org.
