Supplemental Digital Content
Adolescent age is an independent risk factor for abnormal spirometry among people living with HIV in Kenya
Engi F. Attia, Elizabeth Maleche Obimbo, T. Eoin West, Lilian Ndukwe-Wambutsi, Catherine Kiptinness, Anthony Cagle, Christine J. McGrath, Celestine K. Mugambi, Neveen G. El Antouny, Sherry Eskander, Michael H. Chung, Kristina Crothers
EXPANDED METHODS Study design and cohort
We prospectively enrolled HIV-infected adolescents (10-19 years old) and adults (≥20 years old) receiving routine medical care at the Coptic Hope Center for Infectious Diseases for this cross- sectional analysis. The Hope Center is an urban clinic that has provided free ART and
comprehensive care to >20,000 HIV-infected individuals according to Kenya Ministry of Health guidelines since 2004.1 The Hope Center serves a primarily poor, urban catchment area including slum settlements such as Kibera. A minority of individuals seeking care at the Hope Center travel into Nairobi from rural areas. We enrolled up to 10 consecutively eligible
individuals daily from January through March 2014. Individuals with acute respiratory infections, illness too severe to allow participation, recently diagnosed tuberculosis or who were pregnant were excluded. All participants signed written informed consent or assent in their preferred language (Kiswahili or English), and study questionnaires were also administered in the preferred language by trained study staff fluent in both Kiswahili and English. This study was approved by the Kenyatta National Hospital/University of Nairobi Ethics and Research Committee (P433/08/2013 and P154/03/2015), and the University of Washington Institutional Review Board (45675 and STUDY00001509).
Risk factor ascertainment
Standardized questionnaires administered in interview format assessed risk factors and
exposures. Participant responses were recorded in real time using Open Data Kit (ODK) Collect software on a tablet. ODK was programmed to not allow proceeding to the next question until there was a response for the current question.
Smoking status was classified as current (smoked within the past year), former (quit >1 year ago), or never (<100 lifetime cigarettes). Pack-years were calculated from daily average
cigarettes and years smoked. Indoor energy sources used for heating or cooking within the past year included combustible fuels consisting of biomass fuels (wood, charcoal), kerosene/paraffin, electricity, and gas. Participants could say yes to use of more than one of these sources of energy.
Respiratory disease history, including asthma, COPD and prior pulmonary infections, were also ascertained. We asked “Has a doctor or health care provider ever told you that you had
asthma?” with follow-up questions about asthma if they responded “yes”. The other possible responses were “no” and “don’t know”. Similarly, for COPD, we asked “Has a doctor or health care provider ever told you that you had chronic obstructive pulmonary disease (COPD), also known as emphysema or chronic bronchitis?” with the same answer choices and potential for follow-up questions. For prior pulmonary infections, we asked “Has a doctor or health care provider ever told you that you had pneumonia?” followed by “How many courses of antibiotics for pneumonia have you taken in the past year?” and “Have you been hospitalized for
pneumonia in the past year?”. We also asked “Has a doctor or health care provider ever told you that you had tuberculosis?” followed by “Did tuberculosis involve your lungs or chest?” and
“Are you taking or have you ever taken medications for tuberculosis?”
Known duration of HIV infection, CD4 cell counts, ART and co-trimoxazole use, and World Health Organization (WHO) Clinical HIV Stage were abstracted from Hope Center data. Nadir CD4 was defined as the lowest available CD4, and recent CD4 preceded the study visit by up to
120 days. WHO HIV Stage was determined at Hope Center enrollment. We also collected ART and co-trimoxazole use information directly from participants to cross-reference with Hope Center data. Participants who were 10-19 years old and also reported maternal or sibling HIV infection, no sexual debut and no intravenous drug use met criteria for perinatally-acquired HIV.
Clinical assessment
Standardized questionnaires also assessed respiratory symptoms. Breathlessness severity was characterized using the modified Medical Research Council (mMRC) Dyspnea Scale.2 Other respiratory symptoms were assessed using the Likert scale of the COPD Assessment Test (CAT).3-5 As this questionnaire is not validated in our population, we used it only to ascertain presence of symptoms rather than symptom severity or a CAT score.
Oxygen saturation was measured at rest and after sub-maximal exercise, consisting of a 4-flight stair climb (15 steps per flight). Tachypnea was defined based on age-appropriate normal resting respiratory rates for adolescents (10-12.9 years old: >25 breaths per minute [bpm]; 13- 15.9 years old: >23 bpm; ≥16 years old: >22 bpm) and as >22 bpm for adults.6 Height and weight were measured, and body mass index (BMI) was calculated. Low BMI was defined as BMI <18.5 kg/m2 for adults (underweight) and BMI-for-age Z-score <-2 for adolescents (wasted).
Stunted growth in adolescents was defined as height-for-age Z-score <-2. We calculated Z- scores using the WHO Child Growth Standards to standardize anthropometric measurements of adolescents in our cohort to values of adolescents of the same age and gender in a reference population generated by the WHO.7-9 Z-scores quantify how many standard deviations
anthropometric measurements from individuals in our cohort vary from the mean (Z-score=0 or 50th percentile) of this age- and gender-adjusted reference population.
Spirometry testing and interpretation
Spirometry was performed using the ultrasound-based ndd EasyOne® Spirometer (ndd Medical Technologies, Andover, MA, USA), which does not require calibration given the technology it uses to measure airflow.10 Forced expiratory volume in 1 second (FEV1) and forced vital
capacity (FVC) were measured before and 15 minutes after administration of 400 µg salbutamol via a dual-valved LiteAire® collapsible, disposable spacer (Thayer Medical Corporation, Tucson, AZ)11 in all participants according to American Thoracic Society (ATS)/European Respiratory Society (ERS) standards.12 Spirometry quality control included real-time visualization as well as remote review and quality scoring of spirograms by Spirometry 360, an internet-based quality feedback reporting system.13 Spirometry quality scores were based on ATS/ERS acceptability and reproducibility criteria.12,14 Spirometry results with no acceptable efforts were excluded from analyses. We used the highest FEV1 and FVC from acceptable efforts for each participant in these analyses.
We used Global Lung Initiative 2012 reference equations for African Americans to determine predicted FEV1 and FVC and to calculate FEV1/FVC less than the lower limit of normal (<LLN), FEV1 <LLN and FVC <LLN,15 as no validated Kenyan lung function reference populations are available. We defined airflow obstruction as FEV1/FVC <LLN. In our primary analyses, we considered abnormal spirometry to be present if any of these patterns was present pre- bronchodilator in order to allow comparisons of prevalence with other studies that generally have not administered bronchodilators uniformly. Bronchodilator responsiveness was identified if post-bronchodilator FEV1 or FVC increased by 200 mL and 12% among adults, and if FEV1
increased by >10% among adolescents.16,17
Chest CT scans
To characterize the substantial burden of respiratory abnormalities observed among
adolescents, we invited adolescents to undergo non-contrast high-resolution chest computed tomography (CT) scanning using a standardized protocol with a radiation dose of <3 mSv. CT exams were acquired during a breath-hold at end inspiration and exhalation using a
multidetector CT scanner calibrated daily at the Coptic Hospital/Hope Center (Siemens Definition Edge, Siemens Medical Solutions, Forsheim, Germany). To minimize radiation exposure, we limited field size, ensured appropriate patient positioning, tolerated a moderate noise level and used thyroid and abdominal/pelvic shielding.18 Urine pregnancy tests were used to confirm reported negative pregnancy status. CT scans were interpreted by a board-certified radiologist with expertise in thoracic radiologist blinded to clinical data. Parenchymal, airway and pulmonary vascular abnormalities were categorized using established Fleischner Society definitions.19 Emphysema severity was characterized semiquantitatively by visual inspection based on extent of involvement: 0 = none/negligible (0%); 1 = trace (1-10%); 2 = mild (11-25%);
3 = moderate (26-50%); 4 = severe (51-75%); 5 = very severe (>75%).20 Given the low
prevalence of emphysema, emphysema was defined as not present vs present (i.e., score of 0 vs score of 1-5). CT scans were not interpreted using quantitative software.
Statistical analysis
We compared baseline characteristics by age groups and by presence of abnormal spirometry, using χ2 or Fisher’s exact tests for categorical, t-tests with unequal variances for spirometry and Wilcoxon rank-sum tests for other continuous variables.
We generated bivariate logistic regression models to evaluate unadjusted associations between adolescent age and cofactors that we hypothesized a priori would be associated with abnormal spirometry (CD4 <200, WHO HIV Stage 3/4, ART, low BMI, combustible fuel use, cigarette smoking, ART, and prior pulmonary infections). We compared any abnormal spirometry pattern versus normal spirometry, airflow limitation (FEV1/FVC<LLN) versus normal spirometry,
FEV1<LLN versus normal spirometry, and FVC<LLN versus normal spirometry. To avoid
overfitting adjusted models that determined associations between adolescent age and abnormal spirometry, cofactors were retained if they did not co-vary or if they had substantive effects on other variables. We determined correlations between abnormal spirometry patterns and chest CT findings among adolescents.
Analyses were performed using Stata 14 (College Station, TX). P-values <0.05 were considered statistically significant.
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Figure S1. Study cohort
460 participants enrolled
459 participants eligible
455 completed all study procedures
1 participant discovered to be HIV-uninfected
after enrollment
4 participants did not complete interview AND
spirometry
427 included in analyses
28 did not perform acceptable pre- and
post-bronchodilator spirometry 468 potential
participants recruited 2 pregnant 1 too ill to participate
1 with recent pneumonia 1 with salbutamol
allergy
1 declined spirometry 1 declined consent 1 with time constraint
Table S1. Bivariate logistic regression models for associations of adolescent and other cofactors with abnormal spirometry patterns
Odds ratio (95% confidence interval) Any abnormal
spirometry
Airflow limitation
(FEV1/FVC <LLN) FEV1 <LLN FVC <LLN Adolescent age (10-19 years old) 3.29 (1.78 – 6.10)** 3.09 (1.46 – 6.51)* 3.43 (1.68 – 6.98)* 3.11 (1.35 – 7.18)*
Nadir CD4 <200 cells/µL 0.81 (0.50 – 1.31) 0.81 (0.44 – 1.48) 0.91 (0.51 – 1.64) 0.82 (0.41 – 1.63) Recent CD4 <200 cells/µL 1.41 (0.68 – 2.93) 1.21 (0.48 – 3.06) 1.70 (0.73 – 3.92) 1.52 (0.55 – 4.18) WHO HIV Stage 3/4 1.88 (1.15 – 3.08)* 1.71 (0.93 – 3.12)† 2.25 (1.25 – 4.07)* 2.41 (1.20 – 4.84)*
Low BMI 4.10 (1.95 – 8.60)** 3.04 (1.19 – 7.75)* 4.78 (2.10 – 10.9)** 5.93 (2.43 – 14.5)**
Indoor energy sources
Any combustible fuel 1.44 (0.70 – 2.96) 2.25 (0.78 – 6.51) 1.31 (0.56 – 3.06) 0.85 (0.36 – 2.03) Kerosene use 1.63 (1.00 – 2.63)* 1.63 (0.89 – 2.95) 1.84 (1.03 – 3.30)* 1.26 (0.65 – 2.48) Wood use 1.06 (0.52 – 2.16) 0.95 (0.38 – 2.37) 1.04 (0.44 – 2.45) 1.61 (0.67 – 3.98) Charcoal use 0.87 (0.53 – 1.40) 1.11 (0.60 – 2.05) 0.68 (0.38 – 1.20) 0.49 (0.25 – 0.96)*
Current/former cigarette smoking 1.10 (0.52 – 2.31) 1.77 (0.80 – 3.92) 0.65 (0.22 – 1.89) 0.46 (0.11 – 1.98) Smoking pack-years 1.04 (1.00 – 1.09)† 1.06 (1.01 – 1.11)* 1.02 (0.97 – 1.08) 0.99 (0.88 – 1.12) Current ART use 1.10 (0.55 – 2.23) 0.76 (0.35 – 1.67) 1.34 (0.54 – 3.30) 2.95 (0.69 – 12.7) Prior pneumonia 1.28 (0.75 – 2.17) 1.28 (0.67 – 2.46) 1.26 (0.67 – 2.37) 1.10 (0.51 – 2.35) Prior pulmonary tuberculosis 3.22 (1.93 – 5.39)** 2.97 (1.59 – 5.57)* 3.84 (2.11 – 6.99)** 4.61 (2.30 – 9.23)**
**p-value <0.001; *p-value <0.05; †p-value <0.1
Table S2. Adjusted logistic regression models for associations of adolescent age and cofactors with abnormal spirometry patterns
Odds ratio (95% confidence interval) Any abnormal
spirometry
Airflow limitation
(FEV1/FVC <LLN) FEV1 <LLN FVC <LLN Adolescent age (10-19 years old) 3.22 (1.48 – 6.98)* 3.68 (1.52 – 8.91)* 2.54 (1.00 – 6.44)† 1.78 (0.60 – 5.23)
Nadir CD4 <200 cells/µL -- -- -- --
Recent CD4 <200 cells/µL 1.31 (0.61 – 2.82) 1.22 (0.48 – 3.09) 1.67 (0.67 – 4.13) 1.40 (0.47 – 4.14) WHO HIV Stage 3/4 1.29 (0.71 – 2.33) 1.32 (0.64 – 2.71) 1.44 (0.70 – 2.96) 1.26 (0.53 – 3.00) Low BMI 1.76 (0.75 – 4.14) 1.42 (0.53 – 3.81) 2.31 (0.86 – 6.19)† 2.98 (1.02 – 8.70)*
Indoor energy sources
Any combustible fuel -- -- -- --
Kerosene use 1.77 (1.04 – 3.04)* 1.69 (0.89 – 3.21) 2.28 (1.15 – 4.51)* 1.56 (0.72 – 3.38)
Wood use -- -- -- --
Charcoal use -- -- -- --
Current/former cigarette smoking -- -- -- --
Smoking pack-years 1.05 (1.00 – 1.10)* 1.08 (1.02 – 1.14)* 1.03 (0.98 – 1.08) 0.97 (0.86 – 1.10)
Current ART use -- -- -- --
Prior pneumonia -- -- -- --
Prior pulmonary tuberculosis 3.15 (1.70 – 5.85)** 2.97 (1.41 – 6.23)* 3.92 (1.91 – 8.04)** 4.62 (2.00 – 10.7)**
**p-value <0.001; *p-value <0.05; †p-value <0.1
NOTE: n=408 in adjusted model for any abnormal spirometry; n=379 in adjusted model for airflow limitation (FEV1/FVC <LLN) and FEV1 <LLN; n=364 in adjusted model for FVC <LLN
“--" = not included in multivariable models