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Clinical Science

Association of Lung Function With HIV-Related Quality of Life and Health Care Utilization in a High-Risk Cohort

Raju, Sarath MD, MPHa; McCormack, Meredith C. MD, MHSa; Drummond, Michael Bradley MD, MHSb; Ramamurthi, Hema C. MBBSc; Merlo, Christian A. MD, MPHa; Wise, Robert A. MDa; Mehta, Shruti H. PhDc; Brown, Robert H. MD, MPHc; Kirk, Gregory D. MD, MPH, PhDa,c

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: October 1, 2020 - Volume 85 - Issue 2 - p 219-226
doi: 10.1097/QAI.0000000000002431



With increases in the effectiveness of combination antiretroviral therapy for treating HIV, age-related diseases, such as chronic obstructive pulmonary disease (COPD), have emerged as significant comorbidities.1,2 To date, multiple studies have demonstrated that people living with HIV (PLWH) are at increased risk for the development of COPD compared with uninfected individuals with similar risk factors.3,4 Notably, HIV is associated with an accelerated decline in lung function, including spirometric measurements and diffusing capacity (DLCO).5–7 Obstructive lung disease has been associated with both decreased quality of life (QOL) and increased all-cause mortality for PLWH.8,9 Several studies have demonstrated the association between spirometric measures, notably forced expiratory volume in 1 second (FEV1), and health-related QOL among HIV-uninfected individuals.10–12 In the general population, FEV1 predictably declines with age, whereas the incidence of obstructive lung disease rises.13 Among PLWH, those with higher HIV RNA levels have even greater rates of FEV1 decline, with increased risk for the early development of obstructive lung disease.14 The independent impact of spirometric impairment monitored over time, including decreased FEV1 and forced vital capacity (FVC), on patient-centered outcomes, including quality of life and health care utilization, in PLWH has not been fully established. For high-risk individuals with HIV in particular, it has been challenging to separate the impact of lung function from behaviors, including smoking and injection drug use (IDU), which may contribute to other comorbidities, QOL, and health care utilization.

Since 2007, the Study of HIV Infection in the Etiology of Lung Disease (SHIELD) has routinely performed spirometry measurements along with detailed clinical, laboratory, and patient-reported data collection every 6 months on a large cohort of HIV-infected and similar HIV-uninfected participants with a history of IDU in Baltimore, MD. The prevalence of cigarette smoking and respiratory symptoms has been notably high in this cohort. Using longitudinal data from the SHIELD, we aimed to (1) analyze the associations between declining FEV1 and airflow obstructions on both QOL and acute care events; (2) determine whether FEV1 or the presence of obstructive lung disease was a stronger predictor of these outcomes among PLWH versus HIV-uninfected participants; and (3) describe the relationship between markers of HIV disease (ie, HIV status and viral suppression), lung function, and patient-centered health outcomes (QOL and health care utilization).


Study Participants

Participants included in this analysis were restricted to SHIELD recruits from the AIDS Linked to the Intravenous Experience cohort (which had serial QOL data available) above the age of 30 years (recognizing that lung function will generally continue to rise among healthy adults until the age of 30 before subsequently declining with further aging)15 (see Figure 1 for STROBE diagram, Supplemental Digital Content, As part of routine study visits, HIV-infected and HIV-uninfected participants complete standardized interviewer- and computer-administered questionnaires, clinical examination, and spirometry. We analyzed spirometry, QOL, and health care utilization data collected between February 2009 and June 2017. The study was approved by the Institutional Review Board of Johns Hopkins University (NA_00020295); all participants provided written informed consent.

Data Collection

Prebronchodilator spirometry data were collected using KoKo pneumotachometers (Pulmonary Data Services, Louisville, CO) in accordance with American Thoracic Society guidelines.5,16 Percent predicted values were calculated using Global Lung Function Initiative reference equations. The presence of airflow obstruction in our analysis was determined based on a prebronchodilator FEV1/FVC ratio below the lower limit of normal, based on the Global Lung Function Initiative mixed-ethnic reference equations.17

Quality-of-life scores were determined using the Medical Outcomes Study-HIV (MOS-HIV) questionnaire, conducted by trained interviewers at study visits concurrent with spirometry measurement. The MOS-HIV questionnaire is a 35-item survey that assesses 10 dimensions of health to measure functional status and well-being in PLWH.18 Physical health (MOS PHS) and mental health (MOS MHS) summary scores are generated using regression-based weights of individual domains.19 Summary scores are standardized with a mean of 50 among the study population, with higher scores indicating better health status. The physical and mental health summary scores have been demonstrated to correlate with survival in longitudinal studies of HIV infection, with a 1-point increase or decrease in either summary score linked to a clinically significant change in mortality risk, when compared with other participants in the study population.20

Medical conditions, such as respiratory infections or clinical AIDS events, including emergency department (ED) and inpatient visits, occurring in the previous 6 months were identified through self-report and confirmed through a review of medical records. Information on smoking status, IDU, education, respiratory medications, and antiretroviral therapy was determined by self-report. During each visit, laboratory testing included HIV RNA levels, CD4+ T-cell counts, and antibodies to HIV-1 (on HIV-uninfected persons); antibodies to hepatitis C virus (anti-HCV) and HCV RNA was performed at study entry.

Statistical Analysis

Summary statistics of clinical and demographic characteristics were assessed for the overall cohort and stratified by HIV status. Data are presented as mean (SD) for normally distributed data and median (IQR) for non-normally distributed data. Normally distributed continuous variables were compared using the t test, whereas categorical variables were compared with Pearson's χ2 and Fisher's exact tests. In parallel, we analyzed 2 lung function abnormalities as exposures of interest including significant declines in FEV1 (based on change from baseline assessment) or the presence of airflow obstruction (either at baseline or follow-up assessment). Decreases in percent predicted FEV1 were modeled continuously, with results displayed for a 15-point change in percent predicted FEV1. A 15-point change was selected because it approximated the median decrease in FEV1% predicted [15.3 (7.3–21.7)] for PLWH in our study and provided ease of interpretation. This value also approximated the 5-year decrease observed in population-based studies of smokers and has additionally been used as the targeted meaningful difference for absolute change of FEV1% predicted in interventional trials for COPD.21–23 Our primary analysis focused on FEV1 and airflow obstruction, given the established associations between FEV1, obstructive lung disease, and QOL in the general population. Models for FVC using similar methods are presented here as a secondary analysis, whereas analyses with a decline in the FEV1 to FVC ratio modeled continuously are presented separately in an online Supplement Digital Content, To determine the independent influence of lung function abnormalities on QOL, we used multivariable linear regression models of the MOS PHS and MHS scores, with generalized estimating equations of population aggregate data to account for the correlation arising from repeated measures among participants, adjusted for age, sex, race, education, recent IDU, smoking history, HCV status, health insurance, and the presence of self-reported comorbid conditions (diabetes, hypertension, cerebrovascular accident, cardiovascular disease, renal disease, and obesity). To evaluate the effect of lung function on acute care events (both ED and inpatient visits), we used logistic regression models with generalized estimating equation and robust estimation of variance, adjusted for similar covariates. Models for acute care events were constructed with a lag structure designed to look at the relationship between lung function at the current study visit and odds of reporting acute care events at the next 6-month follow-up visit. Models of QOL scores were designed without a lag structure, as our hypothesis was that lung function would influence QOL contemporaneously. HIV-related markers (HIV serostatus, viral load, and CD4+ T-cell count) were analyzed as time-varying covariates, updated every 6 months. HIV viral load was modeled continuously and categorically at different clinical thresholds (<400, >400–100,000, and >100,000 copies/mL); 400 copies/mL was considered the lower limit of detection for the viral load assay. CD4+ T-cell counts were also modeled categorically at clinical thresholds (<200, 200–499, and >500 cells/μL; see Table 2, Supplemental Digital Content, For all analyses, we performed a separate sensitivity analysis that limited data to participants with 5 years of follow-up data, to evaluate any biases that may be introduced by differential follow-up time among cohort participants. These results are provided in an online Supplement Digital Content,

STATA 15.0 (Stata Corp., College Station, TX) was used for statistical analyses. A P value of <0.05 was considered as significant for our primary analysis and <0.10 for interaction terms and effect modification.24


Participant Characteristics

A total of 1499 participants contributed 10,825 spirometry measurements over a median follow-up time of 5.2 (IQR: 1.0–7.5) years. Of these, 465 participants (31.0%) were HIV-infected and 1264 (84.6%) were current smokers (Table 1). Participants were a median of 49.5 years old at baseline and predominantly African American (84.1%) and men (67.1%). Demographics and exposures were relatively similar between HIV-infected and HIV-uninfected participants. HIV-infected participants were less likely to be active injectors but had similar pack-years of smoking and levels of comorbidity. Health care utilization was common, with 656 (43.8%) having at least 1 inpatient hospitalization and 997 (66.0%) having an ED visit during the entire study follow-up period. The number of ED visits over the entire study follow-up period did not vary by HIV status, although HIV-infected participants were more likely to have been hospitalized (48.9% versus 41.5%, P = 0.004). At baseline, 186 (40.6%) of HIV-infected participants had HIV RNA levels ≤400 copies/mL, with a median (IQR) HIV RNA (log copies/mL) of 4.26 (3.45–4.75) for those with detectable virus. The median CD4 count of HIV-infected participants was 379 cells/mm3 (IQR: 234–569). Three hundred twenty-five (21.1%) participants had airflow obstruction during baseline prebronchodilator spirometry, and the presence of airflow obstruction did not substantially differ by HIV status (20.8% for HIV-infected participants compared with 21.3% for HIV-uninfected). The overall mean FEV1% predicted was 87.9% and lower among HIV-infected participants (85.6%) compared with HIV-uninfected (88.8%) (P < 0.001). The mean FVC% predicted was also lower for HIV-infected compared with HIV-uninfected participants (91.9% versus 95.0%, respectively) (P < 0.001).

TABLE 1. - Participant Characteristics at the Baseline Spirometry Visit*
Overall Cohort HIV Infected HIV Uninfected P
N (n = 1499) (465) (1034)
 Age, yr 49.5 (9.2) 50.5 (7.0) 49.1 (8.7) 0.003
 Male, n (%) 1006 (67.1) 310 (66.7) 696 (67.3) 0.82
 Race/ethnicity, n (%)
  Black 1261 (84.1) 427 (91.8) 834 (80.6) <0.001
 Smoking status, n (%) 0.012
  Current 1264 (84.6) 374 (80.6) 890 (86.3)
  Former 133 (8.9) 52 (11.2) 81 (7.9)
  Never 98 (6.6) 38 (8.2) 60 (5.8)
 Smoking, pack-years 23.7 (17.7) 23.0 (18.9) 23.9 (17.1) 0.89
 High school education, n (%) 656 (43.8) 181 (39.1) 475 (45.9) 0.007
 Recent IDU, n (%) 871 (58.1) 248 (53.3) 623 (60.3) 0.004
 # Comorbid conditions 0.57
  1 467 (31.2) 143 (30.9) 324 (31.4)
  2 384 (25.6) 126 (27.2) 258 (25.0)
  ≥3 288 (19.3) 80 (17.3) 208 (20.1)
HIV characteristics§
 HIV RNA <400 copies/mL, n (%) 186 (40.6)
 HIV RNA, copies/mLǁ 18,121 [2820–56,440]
 HIV RNA (log10 copies/mL)ǁ 4.26 [3.45–4.75]
 CD4 count, cells/mm3 379 [234–569]
Lung function
  Absolute, L 2.61 (0.76) 2.51 (0.72) 2.65 (0.78) <0.001
  % Predicted 87.9 (18.3) 85.6 (19.0) 88.8 (17.9)
  Decline in % predicted 13.7 [6.2–18.8] 15.3 [7.3–21.7] 13.1 [5.6–18.0] 0.45
  Absolute, L 3.52 (0.98) 3.39 (0.89) 3.57 (1.01) <0.001
  % Predicted 94.1 (17.1) 91.9 (16.9) 95.0 (17.0)
 FEV1/FVC ratio 74.7 (8.7) 74.7 (9.4) 74.7 (8.4) 0.91
  Airflow obstruction, n (%) 356 (24.1) 108 (23.8) 248 (24.3)
Acute care events during the study period
 Inpatient hospitalization, n (%) 656 (43.8) 227 (48.9) 429 (41.5) 0.004
 ED visit, n (%) 997 (66.0) 314 (67.5) 683 (66.2) 0.46
*Values presented as mean (SD) or median [IQR], unless indicated otherwise.
Reporting exposure within previous 6 months.
History of nonpulmonary comorbidities (diabetes, hypertension, cerebrovascular accident, cardiovascular disease, renal disease, and obesity).
§Among HIV-infected only.
ǁAmong HIV-infected participants with detectable viral load only.
Participants meeting criteria for airflow obstruction at the first spirometry visit.

Associations Between Lung Function and QOL Scores

In multivariable models, a 15-point decrease in percent predicted FEV1 was independently associated with lower MOS physical health scores [mean difference: −0.51, 95% confidence interval (CI): −0.75 to −0.26, P < 0.001] but not mental health scores (mean difference: −0.08, 95% CI: −0.15 to 0.30, P = 0.50), after adjusting for HIV status, age, gender, race, education, current IDU, smoking, comorbid conditions, health insurance status, and HCV (Table 2). The presence of airflow obstruction alone was not associated with a statistically significant change in either MOS summary score. In our overall model, HIV was similarly associated with worse physical health (mean difference: −1.80, 95% CI: −2.80 to −0.81, P < 0.001) but not mental health (mean difference: −0.26, 95% CI: −1.29 to 0.76, P = 0.61). Female gender, recent IDU, lack of a high school education, and an increased number of comorbid conditions were all associated with lower physical and mental health scores.

TABLE 2. - Association of a 15% Decline in FEV1% Predicted With MOS Physical Health and Mental Health QOL Scores*
Predictor Change in PHS Change in MHS
Mean Difference (95% CI) P Mean Difference (95% CI) P
Decrease in FEV1 −0.52 (−0.75 to −0.26) <0.001 −0.08 (−0.15 to 0.30) 0.50
Age (per 10 yr) −2.97 (−3.58 to −2.36) <0.001 −0.18 (−0.76 to 0.39) 0.53
Female gender −3.27 (−4.31 to −2.22) <0.001 −2.20 (−3.24 to −1.16) <0.001
Black race 3.78 (2.32 to 5.24) <0.001 5.35 (3.82 to 6.88) <0.001
High school education 1.53 (0.55 to 2.51) 0.002 2.24 (1.27 to 3.20) <0.001
Current smoker −0.14 (−1.10 to 0.83) 0.78 0.88 (−0.16 to 1.94) 0.098
Current IDU −1.47 (−1.96 to −0.98) <0.001 −2.31 (−2.82 to −1.80) <0.001
# Comorbid conditions −1.40 (−1.71 to −1.09) <0.001 −0.64 (−0.94 to −0.36) <0.001
HIV status −1.80 (−2.80 to −0.81) <0.001 −0.26 (−1.29 to 0.76) 0.61
*Bolded items are statistically significant with p values <0.05.
*Adjusted for age, sex, African American race, HIV status, current smoking status, pack-years, comorbidities (cardiac disease, hypertension, stroke, obesity, renal disease, and diabetes), HCV status, health insurance status, and IDU.

In continuous models, the association between physical health scores and cross-sectional assessment of FEV1% predicted was linear for both PLWH and HIV-uninfected participants (Fig. 1). Stratified by HIV status, declines in FEV1 appeared more strongly associated with worse physical health for PLWH (mean difference: −0.75, 95% CI: −1.14 to −0.34, P < 0.001) than in HIV-uninfected participants (mean difference: −0.38, 95% CI: −0.69 to −0.09, P = 0.011), although we did not detect a statistically significant interaction (P interaction = 0.374).

Predicted MOS physical health scores with 95% CIs for (A) PLWH and (B) HIV-uninfected participants. Adjusted for age, sex, African American race, smoking status (current smoking and pack-years), comorbidities (cardiac disease, hypertension, stroke, obesity, renal disease, and diabetes), HCV status, insurance status, injection drug use, and education.

Among PLWH, the level of HIV viremia strongly modified the association between FEV1 and physical health (P interaction = 0.010). The association between FEV1 declines and physical health scores demonstrated a dose–response increase with poorer virological control (Table 3). Declines in FEV1 appeared to be associated with a greater change in physical health for those with viral load >100,000 copies/mL (mean difference: −1.66, 95% CI: −3.11 to −0.39, P = 0.020) compared with those with an undetectable viral load (mean difference: −0.58, 95% CI: −1.06 to −0.12, P = 0.014; Table 3). Of note, the impact of FEV1 was seen even in models that adjusted concurrently for both decline in FEV1 and the presence of airflow obstruction (see Table 1, Supplemental Digital Content, By contrast, the presence of airflow obstruction was only independently associated with a significant decrease in physical health for those with the highest levels of HIV RNA (mean difference: −4.70, 95% CI: −8.60 to −0.80, P: 0.018; Table 3). A similar pattern was observed when decreases in the FEV1/FVC ratio were modeled continuously, with a statistically significantly association only observed for those with the poorest viremic control (see Tables 3 and 5, Supplemental Digital Content,

TABLE 3. - Association of Changes in Lung Function and MOS Physical Health Score Stratified by HIV Status*
HIV Strata Per 15% Decrease in FEV1% Predicted Presence of Airflow Obstruction Per 15% Decrease in FVC1% Predicted
Mean Change in PHS (95% CI) P Mean Change in PHS (95% CI) P Mean Change in PHS (95% CI) P
HIV negative −0.38 (−0.69 to −0.09) 0.011 0.11 (−0.51 to 0.73) 0.72 −0.61 (−0.93 to −0.29) <0.001
HIV positive (viral load <400) −0.58 (−1.06 to −0.12) 0.014 −1.15 (−2.34 to 0.05) 0.061 −0.76 (−1.26 to −0.25) 0.003
HIV positive (viral load >400–100000) −1.04 (−1.71 to −0.21) 0.012 −0.04 (−1.76 to 1.69) 0.97 −1.17 (−1.95 to −0.41) 0.003
HIV positive (viral load >100,000) −1.66 (−3.11 to −0.39) 0.020 −4.70 (−8.60 to −0.80) 0.018 −1.06 (−2.81 to 0.68) 0.233
*Bolded items are statistically significant with p values <0.05.
*Adjusted for age, sex, African American race, smoking status (current smoking and pack-years), comorbidities (cardiac disease, hypertension, stroke, obesity, renal disease, and diabetes), HCV status, IDU, health insurance coverage, and education.

Associations Between Lung Function and Acute Care Events

For the overall cohort, a 15-point decrease in percent predicted FEV1 was associated with increased odds of ED visits (OR: 1.09, 95% CI: 1.03 to 1.16, P = 0.005) and hospitalization (OR: 1.15, 95% CI: 1.07 to 1.25, P ≤ 0.001) in adjusted models. The presence of airflow obstruction was associated with increased odds of hospitalization (OR: 1.26, 95% CI: 1.05 to 1.51, P = 0.011) but not ED visits (P = 0.175). These associations appeared to be driven by HIV, with HIV status notably modifying the effect of FEV1 on odds of both ED visits (P interaction = 0.019) and hospitalizations (P interaction = 0.048).

For HIV-uninfected participants, neither changes in FEV1 nor the presence of airflow obstruction was associated with a statistically significant change in the odds of acute care events (Table 4). By contrast, among PLWH, a 15-point decline in percent predicted FEV1 was associated with increased odds of experiencing an ED visit (OR: 1.21, 95% CI: 1.09 to 1.34, P < 0.001) and hospitalization (OR: 1.26, 95% CI: 1.12 to 1.42, P < 0.001; Fig. 2). Airflow obstruction was also associated with increased odds of hospitalization (OR: 1.56, 95% CI: 1.15 to 2.11, P = 0.004) but not ED visits among PLWH. HIV RNA levels did not further modify the effect of lung function on acute care events in PLWH.

TABLE 4. - Association of Changes in Lung Function and Odds of Health Care Utilization Stratified by HIV Status
HIV Strata Per 15% Decrease in FEV% Predicted Presence of Airflow Obstruction
OR (95% CI) P OR (95% CI) P
Odds of the ED visit
 Overall cohort 1.09 (1.03 to 1.16) 0.005 1.10 (0.96 to 1.26) 0.175
 HIV negative 1.03 (0.96 to 1.11) 0.416 1.01 (0.84 to 1.21) 0.73
 HIV positive 1.21 (1.09 to 1.34) <0.001 1.26 (0.98 to 1.61) 0.070
Odds of hospitalization
 Overall cohort 1.15 (1.07 to 1.25) <0.001 1.26 (1.05 to 1.51) 0.011
 HIV negative 1.07 (0.97 to 1.18) 0.170 1.10 (0.86 to 1.41) 0.33
 HIV positive 1.26 (1.12 to 1.42) <0.001 1.56 (1.15 to 2.11) 0.004
*Bolded items are statistically significant with p values <0.05.
*Adjusted for age, sex, African American race, smoking status (current smoking and pack-years), comorbidities (cardiac disease, hypertension, stroke, obesity, renal disease, and diabetes), HCV status, health insurance coverage, IDU, and education.

Odds of acute care events associated with (A) a 15% decline in percent predicted of FEV1. B, Presence of airflow obstruction (FEV1/FVC < lower limit of normal). Presented as odds ratio (95% CI), stratified by HIV and viral suppression status [presented as odds ratio (95% CI)]. Adjusted for age, sex, African American race, smoking status (current smoking and pack-years), comorbidities (cardiac disease, hypertension, stroke, obesity, renal disease, and diabetes), HCV status, insurance status, injection drug use, and education.

Associations Between FVC, QOL, and Acute Care Events

Similar to patterns observed for FVC declines, a 15-point change in percent predicted FVC was associated with reduced physical health in a dose–response manner (Table 3), with the caveat that the strata with HIV RNA levels >100,000 copies/mL were not statistically significant. A statistically significant association for those with an undetectable viral load (mean difference: −0.76, 95% CI: −1.26 to −0.25, P = 0.003) was observed after controlling for similar covariates.

We additionally looked at the relationship between changes in FVC and odds of reporting acute care events (see Figure 2, Supplemental Digital Content, For PLWH, there was increased odds of both ED visits (OR: 1.22, 95% CI: 1.10 to 1.37, P < 0.001) and hospitalization (OR: 1.26, 95% CI: 1.12 to 1.42, P ≤ 0.001) associated with a 15-point decline in percent predicted of FVC (see Table 4, Supplemental Digital Content, Much like in models of FEV1, we did not detect a statistically significant association between changes in FVC and acute care events for HIV-uninfected participants.


We demonstrate, in a large cohort with significant risk for comorbid lung disease and HIV, followed for a median of 5 years with ≥10,000 spirometry measurements, that declines in lung function are linked to both worsened physical health and increased risk of health care utilization, even after adjusting for multiple high-risk behaviors and HIV-related comorbidities. Our analyses indicate that the potential impact of declining lung function is greater for those with uncontrolled viremia than uninfected individuals. This study also suggests that substantial declines in FEV1 may be more important than the presence of airflow obstruction alone. Our results further speak to the importance of monitoring lung function over time in the care of PLWH and developing interventions that influence the trajectory of lung function, particularly for those with poor virologic control.

This study demonstrates a clinically meaningful impact associated with changes in both FEV1 and FVC over time for PLWH. Studies have reported that a 1-point decrease in physical or mental health summary scores was associated with a 4% increase in the likelihood of death, compared with others in that study population.18,20 This suggests that, even among a cohort with a high prevalence of comorbid conditions and health care utilization, the decrease of 1.04 units in the MOS PHS seen for individuals with viral load >400 copies/mL, or 1.66 units for patients with high viral loads, associated with a decrease in FEV1 percent predicted, is of clinical importance and could be linked to worse outcomes. For the cohort as a whole, the impact of declining lung function on QOL was also notably greater than the underlying behaviors, such as smoking, that contribute to disease. We do note that for those who experience a slower rate of lung function decline over time, changes in FEV1 are still associated with lower physical health scores, but the clinical impact of this may be less profound.

Of note, a previous cross-sectional study from the SHIELD cohort that focused on the presence of COPD and its impact on HIV-associated quality of life demonstrated a link between COPD and lower MOS mental health scores.8 Our study however did not find this association. These contrasting results may be related to multiple factors including a longer follow-up time and adjusting for the development of additional comorbidities. This study does help expand previous work by demonstrating the impact of impaired spirometric measures on physical health, even without the presence of airflow obstruction. In recent years, there has been increased recognition of a population of smokers with Preserved Ratio Impaired Spirometry, defined as a reduced FEV1 in the setting of a preserved FEV1/FVC ratio.25,26 This phenomenon has been associated with increased respiratory symptoms and decreased quality of life in the COPDGene cohort.27 Similarly, in our cohort, declines in FEV1 may also represent a transitional state associated with increased physical impairment before the development of overt airflow obstruction. Declines in FVC may suggest the development of restrictive lung disease over time. Previous studies have demonstrated that respiratory infections in PLWH lead to permanent declines in FVC and worsened restriction among PLWH.28

Our analysis of acute care events highlights that decreased lung function is associated with worse health outcomes for PLWH than for uninfected participants, where no association was seen. These results prompt consideration of potential explanations as to why declining lung function may have a greater impact on those with uncontrolled HIV than uninfected participants. One theory may be that those with lower lung function have increased susceptibility to lower respiratory tract infections or exacerbations of underlying lung disease for PLWH.29 It is also possible that the decreases in lung function observed were driven by preceding respiratory illnesses and acute care events, as observed in previous studies, but we were unable to definitively determine this based on the data available. We do have concerns that lung disease remains undertreated among PLWH, as previous studies from SHIELD demonstrated that nearly 25% of those with severe COPD were not even aware of their diagnosis of COPD.30 Previous studies have also suggested that worsened pulmonary disease goes hand and hand with progression of other HIV-related comorbidities.31,32 Although we did adjust for the presence of several comorbidities, our analysis was unable to account for severity of disease in a number of important comorbidities, including cardiovascular disease and renal failure. The differing associations between declining lung function and acute care visits, seen by HIV status, may also reflect behavioral issues rather than biologic factors. HIV-infected participants with higher viral load may represent those more likely to participate in high-risk behavior and be less engaged with medical care. Our study was not able to determine whether variation in acute care utilization was related to lack of follow-up, under treatment of intrinsic lung disease or poor medication adherence. However, the number of ED visits reported for participants in our cohort did not differ by HIV status, and adjusting for variables that may introduce this bias (education, IDU, and health insurance status) did not affect our overall results.

The study does have a number of other limitations worth noting. Generalizability of our study results may be limited by our inner-city population with a history of IDU, in which smoking was nearly ubiquitous. We are unable to assess whether our results can easily be translated to other practice settings. However, the cohort represents an important population, often underrepresented in research, that is representative of an inner-city HIV population, with epidemiologically matched HIV-uninfected controls to provide appropriate comparison. The shared risk factors across the HIV subgroups in the cohort additionally attenuate the risk of unmeasured exposures accounting for the differences observed. We do note the differential follow-up time among participants as a potential limitation; however, the results were consistent in sensitivity analyses limited to participants with 5 years of follow-up data (see Tables 7 and 8, Supplemental Digital Content, The analysis of certain health outcomes was limited in our studies. We did not have complete data surrounding the etiology of each acute care event. As a result, we were not able to determine whether hospitalizations were specifically related to pulmonary complications. In a supplemental analysis, we did observe an association between decreases in FEV1 and pneumonia, which may suggest that lower respiratory tract infections contribute to the acute care events and lung function decline observed; however, this association did not significantly differ by HIV status (see Table 6, Supplemental Digital Content, Our study may also underestimate the association between airflow obstruction and quality of life, as those with airflow obstruction and COPD in our cohort tended to have mild disease. Modified Medical Research Council dyspnea scores were available in a smaller subset that noted those with airflow obstruction had a mean Modified Medical Research Council score of 0.93, which indicates mild dyspnea at baseline.33 The milder nature of COPD in this cohort may have underestimated the potential impact of obstructive lung disease. In terms of our measurements of pulmonary function, the absence of longitudinal data on DLCO is a limitation of our study. Previous studies of HIV-associated lung disease have noted that DLCO impairment was an independent predictor of dyspnea, and that over half of individuals with moderate to severe DLCO impairments had no evidence of airflow obstruction.34,35 Longitudinal analysis of the impact of DLCO impairments on HIV-related quality of life remains a key area for future study. Many of these limitations are countered by the large-scale nature of our study, with over 10,000 spirometry measurements and QOL assessments, which allows us to dissect the independent impact of impaired lung function.

In summary, we demonstrate that lung function remains an important marker of both physical health and health care utilization among PLWH. The association appears strongest in those with uncontrolled HIV disease and poor virologic control. Our study suggests that as the prevalence of HIV-related lung disease grows, monitoring lung function over time is of notable importance. Further work should be undertaken to help determine whether changes in lung function also correlates with progression of other HIV-related comorbidities. In screening for HIV-related lung disease, clinicians should evaluate for longitudinal changes in lung function, as measured by declines in FEV1 or FVC, rather than relying on single measurements of obstructive lung disease. Our work suggests that established interventions that have the potential to decrease the rate of lung function decline should be pursued among PLWH, such as smoking cessation programs, efforts to mitigate air pollutant exposure, early introduction of long-acting bronchodilators, and therapies to decrease the incidence of recurrent lower respiratory tract infections and exacerbations of the underlying respiratory disease.36–40 Interventions with the potential to slow the rate of lung function decline could ultimately have a significant impact on improving QOL and reducing health care utilization in this at-risk population.


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