Adiposity and Interstitial Lung Abnormalities in Community-Dwelling Adults
2021; Elsevier BV; Volume: 160; Issue: 2 Linguagem: Inglês
10.1016/j.chest.2021.03.058
ISSN1931-3543
AutoresMichaela R. Anderson, John S. Kim, Matthew Allison, Jon T. Giles, Eric A. Hoffman, Jingzhong Ding, R. Graham Barr, Anna J. Podolanczuk,
Tópico(s)Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
ResumoBackgroundObesity is associated with restrictive ventilatory defects and a faster rate of decline in FVC. This association is not exclusively mediated by mechanical factors and may reflect direct pulmonary injury by adipose-derived mediators.Research QuestionIs adipose tissue involved in the pathogenesis of interstitial lung disease (ILD)?Study Design and MethodsWe evaluated the association of CT measures of pericardial, abdominal visceral, and abdominal subcutaneous adipose tissue with high-attenuation areas (HAAs) and interstitial lung abnormalities (ILAs) in a large multicenter cohort study of community-dwelling adults, using multivariable-adjusted models. We secondarily evaluated the association of adipose depot size with FVC and biomarkers of obesity and inflammation.ResultsIn fully adjusted models, every doubling in pericardial adipose tissue volume was associated with a 63.4-unit increase in HAA (95% CI, 55.5-71.3), 20% increased odds of ILA (95% CI, –2% to 50%), and a 5.5% decrease in percent predicted FVC (95% CI, –6.8% to –4.3%). IL-6 levels accounted for 8% of the association between pericardial adipose tissue and HAA. Every doubling in visceral adipose tissue area was associated with a 41.5-unit increase in HAA (95% CI, 28.3-54.7), 30% increased odds of ILA (95% CI, –10% to 80%), and a 5.4% decrease in percent predicted FVC (95% CI, –6.6% to –4.3%). IL-6 and leptin accounted for 17% and 18%, respectively, of the association between visceral adipose tissue and HAA.InterpretationGreater amounts of pericardial and abdominal visceral adipose tissue were associated with CT measures of early lung injury and lower FVC in a cohort of community-dwelling adults. Adipose tissue may represent a modifiable risk factor for ILD. Obesity is associated with restrictive ventilatory defects and a faster rate of decline in FVC. This association is not exclusively mediated by mechanical factors and may reflect direct pulmonary injury by adipose-derived mediators. Is adipose tissue involved in the pathogenesis of interstitial lung disease (ILD)? We evaluated the association of CT measures of pericardial, abdominal visceral, and abdominal subcutaneous adipose tissue with high-attenuation areas (HAAs) and interstitial lung abnormalities (ILAs) in a large multicenter cohort study of community-dwelling adults, using multivariable-adjusted models. We secondarily evaluated the association of adipose depot size with FVC and biomarkers of obesity and inflammation. In fully adjusted models, every doubling in pericardial adipose tissue volume was associated with a 63.4-unit increase in HAA (95% CI, 55.5-71.3), 20% increased odds of ILA (95% CI, –2% to 50%), and a 5.5% decrease in percent predicted FVC (95% CI, –6.8% to –4.3%). IL-6 levels accounted for 8% of the association between pericardial adipose tissue and HAA. Every doubling in visceral adipose tissue area was associated with a 41.5-unit increase in HAA (95% CI, 28.3-54.7), 30% increased odds of ILA (95% CI, –10% to 80%), and a 5.4% decrease in percent predicted FVC (95% CI, –6.6% to –4.3%). IL-6 and leptin accounted for 17% and 18%, respectively, of the association between visceral adipose tissue and HAA. Greater amounts of pericardial and abdominal visceral adipose tissue were associated with CT measures of early lung injury and lower FVC in a cohort of community-dwelling adults. Adipose tissue may represent a modifiable risk factor for ILD. FOR EDITORIAL COMMENT, SEE PAGE 400The prevalence of obesity is rapidly increasing in the United States and is expected to affect 40% of the population by 2030.1Finkelstein E.A. Khavjou O.A. Thompson H. et al.Obesity and severe obesity forecasts through 2030.Am J Prev Med. 2012; 42: 563-570Abstract Full Text Full Text PDF PubMed Scopus (767) Google Scholar Obesity, particularly visceral obesity, is associated with restrictive ventilatory defects in older adults2Leone N. Courbon D. Thomas F. et al.Lung function impairment and metabolic syndrome: the critical role of abdominal obesity.Am J Respir Crit Care Med. 2009; 179: 509-516Crossref PubMed Scopus (331) Google Scholar,3Kwack W.G. Kang Y.S. 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Clinical significance of MCP-1 levels in BALF and serum in patients with interstitial lung diseases.Eur Respir J. 1999; 14: 376-382Crossref PubMed Scopus (145) Google Scholar A better understanding of the role of obesity in lung injury and early fibrosis may identify a novel target for the prevention and treatment of interstitial lung disease (ILD). FOR EDITORIAL COMMENT, SEE PAGE 400 In states of obesity, adipocytes undergo hypertrophy to store excess fatty acids. Adipocyte hypertrophy results in recruitment of proinflammatory macrophages, and increased production of IL-6, leptin, and resistin.10Weisberg S.P. McCann D. Desai M. Rosenbaum M. Leibel R.L. Ferrante Jr., A.W. Obesity is associated with macrophage accumulation in adipose tissue.J Clin Invest. 2003; 112: 1796-1808Crossref PubMed Scopus (7006) Google Scholar, 11Maffei M. Halaas J. Ravussin E. et al.Leptin levels in human and rodent: measurement of plasma leptin and ob RNA in obese and weight-reduced subjects.Nat Med. 1995; 1: 1155-1161Crossref PubMed Scopus (3250) Google Scholar, 12Steppan C.M. Bailey S.T. Bhat S. et al.The hormone resistin links obesity to diabetes.Nature. 2001; 409: 307-312Crossref PubMed Scopus (3828) Google Scholar All of these mediators have been shown to contribute to lung injury in animal models of pulmonary fibrosis.7Chu S.G. Villalba J.A. Liang X. et al.Palmitic acid-rich high-fat diet exacerbates experimental pulmonary fibrosis by modulating endoplasmic reticulum stress.Am J Respir Cell Mol Biol. 2019; 61: 737-746Crossref PubMed Scopus (21) Google Scholar,13Le T.T. Karmouty-Quintana H. Melicoff E. et al.Blockade of IL-6 trans signaling attenuates pulmonary fibrosis.J Immunol. 2014; 193: 3755-3768Crossref PubMed Scopus (160) Google Scholar, 14Kim J.S. Anderson M.R. Podolanczuk A.J. et al.Associations of serum adipokines with subclinical interstitial lung disease among community-dwelling adults: the Multi-Ethnic Study of Atherosclerosis (MESA).Chest. 2020; 157: 580-589Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar, 15Bellmeyer A. Martino J.M. Chandel N.S. Scott Budinger G.R. Dean D.A. Mutlu G.M. Leptin resistance protects mice from hyperoxia-induced acute lung injury.Am J Respir Crit Care Med. 2007; 175: 587-594Crossref PubMed Scopus (88) Google Scholar However, a direct link between adiposity and lung injury, remodeling, and early fibrosis in humans has not been previously established. Prior work evaluating the association between BMI and early parenchymal lung injury is inconsistent. Greater BMI may be associated with increased high-attenuation areas,16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar but there is no consistent association between BMI and interstitial lung abnormalities.17Putman R.K. Hatabu H. Araki T. et al.Association between interstitial lung abnormalities and all-cause mortality.JAMA. 2016; 315: 672-681Crossref PubMed Scopus (204) Google Scholar BMI is a poor measure of adiposity.18Shah N.R. Braverman E.R. Measuring adiposity in patients: the utility of body mass index (BMI), percent body fat, and leptin.PLoS One. 2012; 7e33308Crossref PubMed Scopus (315) Google Scholar It varies significantly by sex and race/ethnicity19Heymsfield S.B. Peterson C.M. Thomas D.M. Heo M. Schuna Jr., J.M. Why are there race/ethnic differences in adult body mass index-adiposity relationships? A quantitative critical review.Obes Rev. 2016; 17: 262-275Crossref PubMed Scopus (150) Google Scholar and provides no insight into mechanistic links between obesity and early parenchymal lung injury. In contrast, CT scanning can measure adipose tissue depot size and has been used to establish mechanistic links between adiposity and other forms of lung injury.20Anderson M.R. Udupa J.K. Edwin E. et al.Adipose tissue quantification and primary graft dysfunction after lung transplantation: the Lung Transplant Body Composition study.J Heart Lung Transplant. 2019; 38: 1246-1256Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar We sought to determine whether adipose tissue depot size was associated with two CT measures of early lung injury and fibrosis, and FVC, in a large cohort of community-dwelling adults. We and others have previously used and validated both an automated, quantitative measure termed high-attenuation areas (HAAs) and a qualitative measure termed interstitial lung abnormalities (ILAs).16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar,21Hunninghake G.M. Hatabu H. Okajima Y. et al.MUC5B promoter polymorphism and interstitial lung abnormalities.N Engl J Med. 2013; 368: 2192-2200Crossref PubMed Scopus (253) Google Scholar,22Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High-attenuation areas on chest computed tomography and clinical respiratory outcomes in community-dwelling adults.Am J Respir Crit Care Med. 2017; 196: 1434-1442Crossref PubMed Scopus (38) Google Scholar Both measures have been used to identify novel risk factors for early ILD.14Kim J.S. Anderson M.R. Podolanczuk A.J. et al.Associations of serum adipokines with subclinical interstitial lung disease among community-dwelling adults: the Multi-Ethnic Study of Atherosclerosis (MESA).Chest. 2020; 157: 580-589Abstract Full Text Full Text PDF PubMed Scopus (7) Google Scholar,16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar,17Putman R.K. Hatabu H. Araki T. et al.Association between interstitial lung abnormalities and all-cause mortality.JAMA. 2016; 315: 672-681Crossref PubMed Scopus (204) Google Scholar,21Hunninghake G.M. Hatabu H. Okajima Y. et al.MUC5B promoter polymorphism and interstitial lung abnormalities.N Engl J Med. 2013; 368: 2192-2200Crossref PubMed Scopus (253) Google Scholar,22Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High-attenuation areas on chest computed tomography and clinical respiratory outcomes in community-dwelling adults.Am J Respir Crit Care Med. 2017; 196: 1434-1442Crossref PubMed Scopus (38) Google Scholar Here, we hypothesized that greater amounts of pericardial, abdominal visceral, and abdominal subcutaneous adipose tissue would be associated with increased HAAs, greater odds of ILAs, and reduced FVC. We secondarily hypothesized that the association between adipose depots and both HAAs and ILAs would be partially mediated through circulating markers of obesity (leptin, adiponectin, resistin) and inflammation (IL-6, C-reactive protein [CRP], tumor necrosis factor [TNF]-α). The National Heart, Lung, and Blood Institute-funded Multi-Ethnic Study of Atherosclerosis (MESA) is an ongoing multicenter prospective cohort study that enrolled 6,814 adults between the ages of 45 and 84 years without clinically evident cardiovascular disease. Enrollment occurred between 2000 and 2002, with six subsequent follow-up examinations (e-Table 1). MESA and its ancillary studies were approved by individual site institutional review boards (e-Appendix 1). All participants provided informed consent. Our primary exposure was pericardial adipose tissue (PAT) volume measured by cardiac CT imaging performed at MESA examination 1 (e-Table 1) on electron beam tomography scanners at three sites (Imatron C-150; Imatron, Inc.) and multidetector CT imaging at three sites (Volume Zoom [Siemens] or GE LightSpeed [GE Healthcare]), using previously published techniques.16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar,23Ding J. Kritchevsky S.B. Harris T.B. et al.The association of pericardial fat with calcified coronary plaque.Obesity (Silver Spring). 2008; 16: 1914-1919Crossref PubMed Scopus (119) Google Scholar PAT was defined as all tissue with the density of adipose (–190 to –30 Hounsfield units [HU]), located between 15 mm above and 30 mm below the superior extent of the left coronary artery, bordered anteriorly by the chest wall, and posteriorly by the aorta and bronchus using volume analysis software (GE Healthcare). This limited region of PAT highly correlates with total volume of PAT (r = 0.93) with high intra- and interobserver reliability (κ = 0.999 and 0.997, respectively).23Ding J. Kritchevsky S.B. Harris T.B. et al.The association of pericardial fat with calcified coronary plaque.Obesity (Silver Spring). 2008; 16: 1914-1919Crossref PubMed Scopus (119) Google Scholar Our secondary exposures were visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) cross-sectional areas. At examinations 2 and 3 (2002-2005; e-Table 1), a random subset of 1,947 participants underwent abdominal imaging for measures of aortic calcium, using the scanners noted above. Using previously described techniques to interrogate these scans,24Rao V.N. Zhao D. Allison M.A. et al.Adiposity and incident heart failure and its subtypes: MESA (Multi-Ethnic Study of Atherosclerosis).JACC Heart Fail. 2018; 6: 999-1007Crossref PubMed Scopus (52) Google Scholar abdominal adipose tissue cross-sectional area was measured at five locations between L2/L3 and L4/L5. Primary analyses were performed using areas at L4/L5, with sensitivity analyses performed at L3/L4.20Anderson M.R. Udupa J.K. Edwin E. et al.Adipose tissue quantification and primary graft dysfunction after lung transplantation: the Lung Transplant Body Composition study.J Heart Lung Transplant. 2019; 38: 1246-1256Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar,25McClellan T. Allen B.C. Kappus M. et al.Repeatability of computerized tomography-based anthropomorphic measurements of frailty in patients with pulmonary fibrosis undergoing lung transplantation.Curr Probl Diagn Radiol. 2017; 46: 300-304Crossref PubMed Scopus (7) Google Scholar All tissue within the peritoneal cavity with the density of adipose tissue was identified as VAT. All tissue with the density of adipose and located outside of the peritoneal cavity but not within the muscle was identified as SAT. Using previously described methods, imputation was used to estimate missing SAT area on scans in which the subcutaneous tissue was incompletely imaged.26Mongraw-Chaffin M. Allison M.A. Burke G.L. et al.CT-derived body fat distribution and incident cardiovascular disease: the Multi-Ethnic Study of Atherosclerosis.J Clin Endocrinol Metab. 2017; 102: 4173-4183Crossref PubMed Scopus (15) Google Scholar These imputed SAT measures were used in primary analyses. Sensitivity analyses were performed, including only subjects with completely imaged SAT. All biomarkers were measured in serum samples collected between 2004 and 2005 (examination 3, e-Table 1) and stored in a –80°C freezer. Inflammatory biomarkers (IL-6, TNF-α, CRP) were measured in fasting samples, using an ultrasensitive enzyme-linked immunosorbent assay for IL-6 (Quantikine HS human IL-6 immunoassay; R&D Systems), Bio-Rad Luminex flow cytometry for TNF-α (Millipore), and a particle-enhanced immune photometric assay (BNII nephelometer for CRP; Dade-Behring, Inc). Adipokines (adiponectin, leptin, resistin) were measured by Bio-Rad Luminex flow cytometry (Millipore) at the University of Vermont (Burlington, VT). We examined two validated CT phenotypes of early parenchymal lung injury and fibrosis: a quantitative phenotype (HAAs), and a qualitative phenotype (ILAs).16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar,22Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High-attenuation areas on chest computed tomography and clinical respiratory outcomes in community-dwelling adults.Am J Respir Crit Care Med. 2017; 196: 1434-1442Crossref PubMed Scopus (38) Google Scholar,27Washko G.R. Hunninghake G.M. Fernandez I.E. et al.Lung volumes and emphysema in smokers with interstitial lung abnormalities.N Engl J Med. 2011; 364: 897-906Crossref PubMed Scopus (354) Google Scholar HAA was measured as all voxels of lung tissue with attenuation values between –600 and –250 HU on examination 1 (cardiac CT imaging). This range captures ground-glass and reticular changes while excluding denser areas of consolidation, nodules, and vasculature.16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar ILA was visually assessed on examination 5 (full lung CT imaging) by one of five trained radiologists and defined according to Fleischner Society guidelines as the presence of ground glass, reticular changes, emphysematous cysts, honeycombing, or traction bronchiectasis affecting > 5% of any lung zone in a nondependent fashion.16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar,27Washko G.R. Hunninghake G.M. Fernandez I.E. et al.Lung volumes and emphysema in smokers with interstitial lung abnormalities.N Engl J Med. 2011; 364: 897-906Crossref PubMed Scopus (354) Google Scholar,28Hatabu H. Hunninghake G.M. Richeldi L. et al.Interstitial lung abnormalities detected incidentally on CT: a position paper from the Fleischner Society.Lancet Respir Med. 2020; 8: 726-737Abstract Full Text Full Text PDF PubMed Scopus (58) Google Scholar Radiologists were blinded to measures of adiposity. At examinations 3 and 4 (2004-2007; e-Table 1), spirometry was performed in accordance with the American Thoracic Society/European Respiratory Society guidelines.29Miller M.R. Hankinson J. Brusasco V. et al.American Thoracic Society/European Respiratory Society (ATS/ERS) Task Force. Standardisation of spirometry.Eur Respir J. 2005; 26: 319-338Crossref PubMed Scopus (10497) Google Scholar The distributions of adipose depot measures and serum biomarkers were right-skewed, and therefore they were log2 transformed. Changes in the outcome are reported per doubling of the predictor. The distribution of HAA was right-skewed; transformation to –1/HAA2Leone N. Courbon D. Thomas F. et al.Lung function impairment and metabolic syndrome: the critical role of abdominal obesity.Am J Respir Crit Care Med. 2009; 179: 509-516Crossref PubMed Scopus (331) Google Scholar for regression modeling purposes has been validated and is reported here as HAA.30Easthausen I. Podolanczuk A. Hoffman E. et al.Reference values for high attenuation areas on chest CT in a healthy, never-smoker, multi-ethnic sample: the MESA study.Respirology. 2020; 25: 855-862Crossref PubMed Scopus (6) Google Scholar We performed Spearman correlations between adipose tissue depot size and height, weight, and BMI to confirm validity. Given that nonlinear associations are often identified in studies of obesity,31Anderson M.R. Geleris J. Anderson D.R. et al.Body mass index and risk for intubation or death in SARS-CoV-2 infection: a retrospective cohort study.Ann Intern Med. 2020; 173: 782-790Crossref PubMed Scopus (75) Google Scholar,32Anderson M.R. Kolaitis N.A. Gao Y. et al.A nonlinear relationship between visceral adipose tissue and frailty in adult lung transplant candidates.Am J Transplant. 2019; 19: 3155-3161Crossref PubMed Scopus (12) Google Scholar we tested for nonlinear relationships between predictors and outcomes using generalized additive models with the "gam" function in R with a loess smoothing function. Associations appeared to be linear, and therefore we used linear regression to examine the cross-sectional associations of adipose tissue depots with HAA and FVC. We used logistic regression to examine the associations of adipose depots with ILA. HAA models were adjusted for factors known to influence HAA measurement, including the following: study site, imaged lung volume, and radiation dose (milliamperes). We adjusted for potential confounders including age, sex, race/ethnicity, height, smoking status, cigarette pack-years, and percent emphysema (percent voxels with density less than 950 HU) in fully adjusted models.16Podolanczuk A.J. Oelsner E.C. Barr R.G. et al.High attenuation areas on chest computed tomography in community-dwelling adults: the MESA study.Eur Respir J. 2016; 48: 1442-1452Crossref PubMed Scopus (77) Google Scholar A priori subgroup analyses were performed by sex, age (< 65 or ≥ 65 years), BMI, race, and smoking status using Wald and likelihood ratio tests. To account for mechanical effects of adiposity (ie, atelectasis), we performed sensitivity analyses that (1) included BMI in models of PAT, and (2) included both VAT and SAT in the same model for assessments of abdominal adipose depots. Given high correlations between these measures, their inclusion in the same model may result in bias, and these estimates should be interpreted with caution. We assessed the association between biomarkers of obesity (leptin, resistin, adiponectin) and inflammation (IL-6, CRP, TNF-α) with PAT volume and VAT area using Spearman correlations. For biomarkers that were significantly associated with adipose measures, we estimated the proportion of the total association explained by each biomarker, using multilevel mediation analyses with the ml_mediation package in STATA (StataCorp) with covariates noted above clustered by study site. All analyses were performed with STATA/IC version 15.1 (StataCorp), and R version 3.3.1 (R Foundation for Statistical Computing). A total of 6,814 subjects were enrolled in MESA and underwent cardiac CT imaging performed at examination 1. For 6,784 subjects, measures of both HAA and PAT were available (e-Fig 1). Forty-seven percent of the subjects were male, the median (interquartile range [IQR]) age was 62 (53-70) years, 39% were white, 22% were Hispanic, the median BMI was 27.6 kg/m2 (IQR, 24.5-31.2), 50% were never smokers, 36% were former smokers, and median pack-years was 15 (IQR, 5-32) (e-Table 2). A total of 1,923 subjects underwent abdominal CT imaging at examination 2 or 3, with available measures of HAA (e-Fig 1). VAT measurement was available on all abdominal scans, and SAT was completely imaged on 1,388 (86%) scans and imputed on 234 scans (14%). Subjects in the lowest tertile of PAT were less likely to be male or white, had lower weight and BMI, and lower rates of smoking (Table 1). Median PAT, VAT, and SAT values for the PAT cohort were 71 cm3 (IQR, 49-100), 137 cm2 (IQR, 97-193), and 236 cm2 (IQR, 170-310), respectively, and were similar among subjects with available ILA and FVC (e-Table 2). Subjects with available measures of abdominal VAT, ILA, and FVC appeared similar to the full cohort on baseline characteristics (e-Table 2).Table 1Baseline Characteristics by Tertile of Pericardial Adipose Tissue VolumeaMissing values: Smoking status on 22 subjects, and cigarette pack-years on 94 subjects.CharacteristicLowest Tertile of PAT (n = 2,262)Middle Tertile of PAT (n = 2,261)Highest Tertile of PAT (n = 2,261)Age, y57 (51-67)63 (54-70)65 (57-72)Sex (male)762 (34)986 (44)1,444 (64)Race White794 (35)803 (36)1,018 (45) Asian268 (12)320 (14)209 (9) Black833 (37)628 (28)423 (19) Hispanic367 (16)510 (23)611 (27)Weight, kg60 (69-79)76 (67-88)87 (77-99)Height, cm164 (158-171)165 (158-173)169 (161-176)BMI, kg/m224.8 (22.5-28.0)27.5 (25.5-30.8)30.2 (27.4-34.0)BMI category < 18.553 (2)5 (0)0 (0) 18.5-25.01,105 (49)601 (27)180 (8) 25.0-30.0778 (34)966 (43)910 (40) 30-35233 (10)468 (21)723 (32) > 3593 (4)221 (10)448 (20)Smoking status Never smoker1,239 (55)1,181 (52)981 (43) Former smoker700 (31)780 (35)995 (44) Current smoker316 (14)292 (13)278 (12)Pack-years12 (3-25)15 (5-31)20 (6-38)PAT volume, cm342 (34-49)71 (64-79)115 (100-142)VAT area, cm291 (65-117)133 (105-172)198 (154-245)SAT area, cm2217 (145-283)239 (172-320)253 (200-336)Continuous variables are reported as median (interquartile range); categorical variables are reported as No. (%). PAT = pericardial adipose tissue; SAT = abdominal subcutaneous adipose tissue; VAT = abdominal visceral adipose tissue.a Missing values: Smoking status on 22 subjects, and cigarette pack-years on 94 subjects. Open table in a new tab Continuous variables are reported as median (interquartile range); categorical variables are reported as No. (%). PAT = pericardial adipose tissue; SAT = abdominal subcutaneous adipose tissue; VAT = abdominal visceral adipose tissue. PAT was strongly correlated with abdominal VAT (ρ = 0.67), moderately correlated with BMI (ρ = 0.51) and weight (ρ = 0.49), and weakly correlated with abdominal SAT (ρ = 0.20) and height (ρ = 0.17) (e-Table 3). Abdominal VAT was moderately correlated with BMI (ρ = 0.61) and weight (ρ = 0.54), and weakly correlated with abdominal SAT (ρ = 0.33). Abdominal SAT was strongly correlated with BMI (ρ = 0.73) and moderately correlated with height (ρ = 0.46). Every doubling in PAT volume was associated with 63.4-unit higher HAA (fully adjusted 95% CI, 55.5-71.3; P < .001) (Table 2, Fig 1A), and every doubling in abdominal VAT area was associated with 41.5-unit higher HAA (fully adjusted 95% CI, 28.3-54.7; P < .001) (Fig 1D). Abdominal SAT area was not associated with HAA in base models (9.3 units; 95% CI, –9.4 to 28.1; P = .33) (e-Fig 2A) but was associated with HAA in fully adjusted models (56.1 units; 95% CI, 38.8-73.5; P < .001).Table 2Associations of Adipose Tissue Depots With High-Attenuation Areas, Interstitial Lung Abnormalities, and FVCModelNo.Change in HAA per Doubling PAT Volume95% CIP ValueNo.Odds of ILA per Doubling PAT Volume95% CIP ValueNo.Change in FVC per Doubling PAT Volume95% CIP ValuePAT Model 1aModel 1: HAA analyses adjusted for study site, imaged lung volume, and radiation dose; ILA and FVC analyses are unadjusted.6,78482.073.4 to 90.5< .0012,4231.41.2 to 1.6< .0011,415–4.1–5.2 to –2.9< .001 Model 2bModel 2: Model 1 + age at examination 1, sex, race, height, smoking status, percent emphysema, cigarette pack-years, and study site.6,69063.455.5 to 71.3< .0012,3941.20.98 to 1.5.071,400–5.5–6.8 to –4.3< .001 Model 3cModel 3: Model 2 + BMI (in PAT models), SAT (in VAT models), or VAT (in SAT models).6,69019.610.6 to 28.7< .0012,3941.31.01 to 1.6.041,400–4.3–5.8 to –2.7< .001No.Change in HAA per Doubling VAT Area95% CIP ValueNo.Odds of ILA per Doubling VAT Area95% CIP ValueNo.Change in FVC per Doubling VAT Area95% CIP ValueVAT Model 1aModel 1: HAA analyses adjusted for study site, imaged lung volume, and radiation dose; ILA and FVC analyses are unadjusted.1,92357.442.6 to 77.1< .0018611.41.03 to 1.9.031,419–4.1–5.2 to –3.0< .001 Model 2bModel 2: Model 1 + age at examination 1, sex, race, height, smoking status, percent emphysema, cigarette pack-years, and study site.1,83841.528.3 to 54.7< .0018441.30.9 to 1.8.211,404–5.4–6.6 to – 4.3< .001 Model 3cModel 3: Model 2 + BMI (in PAT models), SAT (in VAT models), or VAT (in SAT models).1,56222.15.2 to 38.9.017261.40.9 to 2.1.161,229–4.0-5.5 to –2.6< .001No.Change in HAA per Doubling SAT Area95% CIP ValueNo.Odds of ILA per Doubling SAT Area95% CIP ValueNo.Change in FVC per Doubling SAT Area95% CIP ValueSAT Model 1aModel 1: HAA analyses adjusted for study site, imaged lung volume, and radiation dose; ILA and FVC analyses are unadjusted.1,6229.3–9.4 to 28.1.337401.10.8 to 1.5.731,241–5.0–6.3 to –3.8< .001 Model 2bModel 2: Model 1 + age at examination 1, sex, race, height, smoking status, percent emphysema, cigarette pack-years, and study site.1,60556.138.8 to 73.5< .0017261.00.7 to 1.5.961,229–5.3–6.7 to –3.9< .001 Model 3
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