http://orcid.org/0000-0003-4597-7037
Figures
Abstract
Background
Decreased lung function is associated with non-alcoholic fatty liver disease (NAFLD), based on linking mechanisms such as insulin resistance and systemic inflammation However, its association with the risk of developing NAFLD is unclear. Our aim was to investigate whether baseline lung function is associated with incident NAFLD in middle-aged healthy Koreans.
Methods
A cohort study of 96,104 subjects (mean age: 35.7 years) without NAFLD were followed up from 2002 to 2015. NAFLD was diagnosed by ultrasound after the exclusion of other possible causes of liver diseases. Baseline percent predicted forced expiratory volume in one second (FEV1%) and forced vital capacity (FVC%) were categorized in quartiles. Adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) (using the highest quartile as reference) were calculated for incident NAFLD at follow-up, controlling for covariates and potential confounders.
Results
During 579,714.5 person-years of follow-up, 24,450 participants developed NAFLD (incidence rate, 42.2 per 1,000 person-years). The mean follow-up period was 5.9±3.4 years. Regardless of smoking history, the risk for incident NAFLD increased with decreasing quartiles of FEV1 (%) and FVC (%) in a dose-response manner (p for trend<0.001). In never smokers, the aHRs (95% CIs) for incident NAFLD were 1.15 (1.08–1.21), 1.11 (1.05–1.18), and 1.08 (1.02–1.14) in quartiles 1–3 for FEV1 (%) and 1.12 (1.06–1.18), 1.11 (1.05–1.18), and 1.09 (1.03–1.15) in quartiles 1–3 for FVC (%), compared with the highest quartile reference. Similar inverse association was present in smoke-exposed subjects (aHR for incident NAFLD were 1.14, 1.21, 1.13 and 1.17, 1.11, 1.09 across FEV1(%) and FVC(%) quartile in increasing order, respectively).
Citation: Song J-U, Jang Y, Lim S-Y, Ryu S, Song WJ, Byrne CD, et al. (2019) Decreased lung function is associated with risk of developing non-alcoholic fatty liver disease: A longitudinal cohort study. PLoS ONE 14(1): e0208736. https://doi.org/10.1371/journal.pone.0208736
Editor: Giovanni Targher, Universita degli Studi di Verona, ITALY
Received: September 22, 2018; Accepted: November 22, 2018; Published: January 23, 2019
Copyright: © 2019 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: Due to ethical restrictions imposed by the Institutional Review Board of Kangbuk Samsung Hospital, the patient data are not available for distribution outside of the Kangbuk Samsung Hospital. For additional information, please contact JiinAhn (Jiin57.ahn@samsung.com) or the Institutional Review Board of Kangbuk Samsung Hospital (contact information below). - Address: 29 Saemunan-ro, Jongno-Gu, Seoul, Korea (03181) - E-mail: irb.kbsmc@samsung.com - Telephone: 82-2-2001-1943, 1945 - Fax: 82-2-2001-1946.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Non-alcoholic fatty liver disease (NAFLD) is characterized by the presence of hepatic steatosis [1] and may progress over time to cirrhosis and hepatic failure [2]. NAFLD is associated with various extrahepatic complications such as cardio-metabolic diseases, chronic kidney disease, and sarcopenia [3–7], mediating increased low-grade systemic inflammation [8,9] which play a causal role in the development of NAFLD [8]. Recently, the relationship between lung function and cardio-metabolic conditions has also been highlighted. Previous studies have demonstrated that decreased lung function is associated with an increase in low-grade inflammation [10] and increased risk of diabetes, cardiovascular disease, and metabolic syndrome [11,12]. Accordingly, there might be possibility linking decreased lung function to an increased risk of NAFLD, in the light of sharing inflammatory process. Therefore, we hypothesize that decreased lung function could be contributed to the development of NAFLD.
Although cross-sectional studies have suggested that reduced lung function measured at a single point in time is strongly associated with NAFLD [13–16], no longitudinal studies have investigated the role of baseline lung function in the development of incident NAFLD among subjects who are free of NAFLD at baseline. Using longitudinal follow-up data from a health screening examination program in South Korea in which it is possible to identify subjects with NAFLD using liver ultrasound data, we investigated whether baseline lung function was associated with incident NAFLD over 13 years of follow-up.
Methods
Study design and population
The Kangbuk Samsung Health Study was a cohort study of South Koreans aged 18 years or older who underwent a comprehensive annual or biennial health examination at one of the Kangbuk Samsung Hospital Health Screening Centers located in Seoul and Suwon, South Korea, between 1 January 2002 and 31 December 2015. More than 80% of the participants were employees of various companies and local governmental organizations and their spouses. In South Korea, the Industrial Safety and Health Law requires employees to participate in annual or biennial health examinations, which are offered free of charge. The remaining participants voluntarily purchased screening exams at the health exam center. A total of 198,484 potential participants who completed a physical activity questionnaire and underwent a comprehensive health examination received at least three follow-up visits over the study period. The data from the first visit served as baseline data. Among these potential study subjects, we excluded participants that met the following criteria: a self-reported history and/or currently receiving medication for chronic liver disease (n = 25,331), including positive serologic markers for hepatitis B or C virus (n = 8,141); alcohol intake ≥30 g/day for men and ≥20 g/day for women (n = 17,219); history of malignancy (n = 2,112), cardiovascular-metabolic diseases or chronic pulmonary diseases including abnormal chest radiograph findings (n = 38,444); and currently receiving treatment with steroids or medication for diabetes, hyperlipidemia, or thyroid disease (n = 4,585). Specific details of comorbidities were not available because the medical history questionnaire only required yes/no responses. We also excluded participants with missing spirometric data or liver ultrasonography (n = 5,380). As some individuals met more than one of the above criteria for exclusion, 126,282 subjects were ultimately eligible for initial inclusion in the study. Of these, 23,666 (18.7%) had fatty liver on baseline ultrasound examination and an additional 6,512 subjects were excluded because of missing data for smoking habits. Finally, 96,104 subjects were included in the study (Fig 1).
The study was approved by the Institutional Review Board of the Kangbuk Samsung Hospital, which waived the requirement for informed consent as we used only de-identified data obtained as part of routine health screening examinations.
Data collection, anthropometric measurements, and laboratory tests
At each visit, standardized self-administered questionnaires were used to acquire information regarding demographic characteristics, smoking status, drinking habits, regular exercise, medical history, current regular use of medications, and any clinical symptoms. Smoking habits were classified as follows: non-smokers, ex-smokers (no current smoking but regular smoking in the past), and current smokers (at least one cigarette per day). Alcohol history was considered positive if the subject had used alcohol in the past, even if they had stopped drinking. The weekly frequency of physical activity was also assessed and regular exercise was defined as ≥ 3 times/week.
Physical characteristics and serum biochemical parameters were measured. Height and weight were determined by trained nurses using automated instruments, with individuals wearing a lightweight hospital gown and no shoes. Height was measured to the nearest 1 mm using a stadiometer with the participant standing barefoot. Body weight was measured to the nearest 0.1 kg on a bioimpedance analyzer (InBody 3.0 and Inbody 720, Biospace Co., Seoul, Korea) that was validated for reproducibility and accuracy of body composition measurements [17]. Body mass index (BMI) was calculated as the weight in kilograms divided by the height in meters squared (kg/m2). Blood pressure was also measured by trained nurses with a standard sphygmomanometer following at least 5 minutes of seated rest.
Venous blood was collected from the antecubital vein after at least a 10-h fast. Methods for measuring serum levels of glucose, lipid profiles, liver enzymes, insulin, and high-sensitivity C-reactive protein (hsCRP) have been described previously [18]. Insulin resistance was assessed with the HOMA-IR equation: fasting blood insulin (μ U/ml) × fasting blood glucose (mmol/l)/22.5. The Laboratory Medicine Department at Kangbuk Samsung Hospital has been accredited and participates annually in inspections and surveys by the Korean Association of Quality Assurance for Clinical Laboratories.
Ultrasuond examination and definition of NAFLD
Abdominal ultrasonography (Logic Q700 MR 3.5-MHz transducer; GE, Milwaukee, WI, USA) was conducted on all participants by 11 experienced radiologists who were unaware of the aims of the study and were blinded to the laboratory findings. Images were captured in a standard manner with the patient in the supine position with the right arm raised above the head. Fatty liver on ultrasonography was defined by an increase in echogenicity of the liver relative to the echogenicity of the renal cortex or spleen parenchyma [19]. The inter- and intra-observer reliability for fatty liver diagnosis was high (kappa statistics of 0.74 and 0.94 respectively) [20]. NAFLD was defined by the presence of fatty liver after the exclusion of excessive alcohol use (threshold of <30 g/d for men and <20 g/d for women) [21], or other identifiable causes of liver disease, as described in the exclusion criteria.
Measurement of pulmonary function
Spirometry was performed as recommended by the American Thoracic Society [22] using the Vmax22 system (Sensor-Medics, Yorba Linda, CA). A bronchodilator was not administered prior to spirometry. The highest forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) values from three or more tests with acceptable curves were used for further analyses. Spirometric values should be compared with the normal predictive values obtained from the same population using the same procedures, because FEV1 and FVC are affected by gender, age, height, weight and race [23]. In real practice, Morris equation, which is based on a study of American subjects [24], underestimate spirometric indices in koreans [25], because Asian people have larger lung volumes than Caucasians because they have shorter legs and longer upper bodies [26]. Therefore, the predicted values for FEV1 and FVC were calculated from the following equations obtained in a representative Korean population sample [25]:
The predicted FVC% (FVC [%]) and predicted FEV1% (FEV [%]) were calculated by dividing the FVC (L) and FEV1 (L) by the predicted FVC and FEV1, respectively.
Statistical Analyses
Continuous variables were presented as the mean ± standard deviations or median and interquartile range, and categorical variables were presented as the number and percentage. The baseline data stratified by incident NAFLD at follow-up and quartiles of baseline ventilator function were compared using t-test or Mann–Whitney U test for two-group comparisons, and by one-way analysis of variance (ANOVA) or Kruskal-Wallis tests for comparison between quartiles. Chi-square test or Fisher’s exact test was used for categorical variables.
The outcome of interest was the development of incident NAFLD. Follow-up for each participant extended from the baseline exam until the development of NAFLD or the last health exam conducted prior to 31 December 2015, whichever came first. Incidence rates were calculated as the number of incident cases divided by person-years of follow-up. As we could establish that NAFLD had developed between two visits but could not determine the precise timing of NAFLD development, we used a parametric proportional hazards model to take interval censoring into account (stpm command in STATA) [27]. Using these models, the baseline hazard function was parameterized with restricted cubic splines in log time with four degrees of freedom.
The primary analysis was based on quartiles of baseline ventilator function. To exclude the potential confounding effects of smoking on the decline of lung function, the analyses were performed separately in smoke-exposed and smoke-naïve subjects. We estimated the adjusted hazard ratios (aHR) with 95% confidence intervals (CI) for incident NAFLD in quartiles 1–3 of FVC (%) or FEV1 (%) at baseline, with the highest (4th) quartile as the reference group. Logistic regression analyses were adjusted for baseline potential demographics, including age, sex, BMI, alcohol intake, smoking, exercise, education level, center, and year of test. We used a continuous variable with the number of quartiles and tested its statistical significance in the regression models. We assessed the proportional hazards assumption by examining graphs of estimated log (−log) survival. We also conducted dose–response analyses. We estimated the aHR with 95% CI associated with an increase of 1 (%) of ventilator function parameters at baseline using lung function as a continuous variable in the regression models. All tests were two-sided, and statistical significance was defined as a p value<0.05 (two-tailed). Data were analyzed using STATA version 13.0 (StataCorp LP, College Station, TX).
Results
Table 1 summarizes the baseline characteristics of the enrolled subjects (n = 102,616). Mean age was 35.7 years and mean BMI was 22.0 kg/m2. Compared with the reference group, subjects in the incident NAFLD group were more likely to be men, to have smoked, and to drink alcohol, and had higher blood pressure, and higher levels of fasting glucose, total cholesterol, triglycerides, LDL-C, hepatic enzymes, insulin, HOMA-IR, and hsCRP and lower levels of HDL-C (Table 1). The mean FEV1 (%) and FVC (%) values were 86% and 85%. The baseline values of FVC (%) and FEV1 (%) in the incident NAFLD group were significantly lower than in the reference group. Furthermore, subjects in the incident NAFLD group showed a greater decline in both FEV1 (%) and FVC (%) over the study period (Table 1).
When analyzed by quartiles of FEV1 (%) and FVC (%) level in smoke-exposed subjects or never smokers (Tables 2 and 3, respectively), both smoke-exposed and never smokers with lower FVC (%) or FEV1 (%) were less likely to drink and had higher BMIs. With respect to metabolic parameters, the subjects in the higher FVC (%) or FEV1 (%) quartiles had lower blood pressure, lower levels of LDL cholesterol, and triglyceride, and higher levels of HDL cholesterol, regardless of smoking habits. In contrast to never smokers, there was no association between FVC (%) or FEV1 (%) levels and exercise in smoke-exposed subjects. Additionally, levels of HOMA IR and insulin did not reach statistical significance across FVC (%) quartiles in smoke-exposed subjects.
Table 4 shows the risk of developing NAFLD according to baseline FEV1 (%) and FVC (%) stratified by smoking habit. We identified 24,450 incident cases of NAFLD during 579,714.5 person-years of follow-up (incidence rate, 42.2 per 1000 person-years). The mean±SD follow-up period was 5.9±3.4 years. We analyzed the relationships between baseline spirometric values and incident NAFLD after adjusting for all potential confounding parameters at baseline. Regardless of smoking habit, a low baseline FEV1 (%) and FVC (%) was strongly associated with incident NAFLD. Compared with the highest quartile (the reference group) of FEV1 (%) at baseline, the aHRs (95% CIs) for incident NAFLD in quartiles 1–3 were 1.14 (1.06–1.22), 1.21 (1.15–1.28), and 1.13 (1.08–1.18) in smoke-exposed subjects and 1.15 (1.08–1.21), 1.11 (1.05–1.18), and 1.08 (1.02–1.14) in never smokers, respectively. Similarly, the lowest quartile of FVC (%) was also associated with a higher risk of developing NAFLD (aHR = 1.17 [1.12–1.23] in smoke-exposed subjects and aHR = 1.12 [1.06–1.18] in never smokers), compared with the highest quartile (Table 4 and Fig 2). The aHR for incident NAFLD associated with a 1% decrease when FEV1 (%) was introduced as a continuous variable in regression models was 1.07 (1.05–1.09) in smoke-exposed subjects and 1.003 (1.002–1.004) in never smokers. With respect to each 1% decrease in FVC (%), the aHR for incident NAFLD was 1.005 (1.003–1.006) in smoke-exposed subjects and 1.003 (1.001–1.004) in never smokers.
Smoke-exposed subjects (A,C) and never smokers (B,D) were dived into quartiles according to baseline precentage of predcited values (% predicted) for FEV1 or FVC. Rregardless of smoking status, adjusted hazard ratios for incident NAFLD increased with decreasing quartiles of FEV1 (%) (A,B) and FVC (%) (C,D) in a dose-response manner (p for trend<0.001). The reference values was set at the highest quartile of FEV1(%) and FVC(%). Models was adjusted for potential covariates and metabolic laboratory markers including age, sex, BMI, alcohol intake, smoking, exercise, education level, center, year of test. aHR, adjusted hazard ratio; FEV1, forced expiratory volume in 1s; FVC, forced vital capacity; NAFLD, nonalcoholic fatty liver disease.
Discussion
The novel result of our study was that decreased FEV1 (%) and FVC (%) were independently associated with incident NAFLD over 13 years of follow-up. To the best of our knowledge, our study is the first to describe the association between low levels of lung function at baseline and incident NAFLD (diagnosed by liver ultrasound) in subjects without liver fat by ultrasound examination at baseline.
In the current study, 24,450 subjects developed NAFLD during 579,714.5 person-years of follow-up, which represents an incidence rate of 42.2 per 1000 person-years and is consistent with previous data (31–86 per 1,000 person-years) [28]. The baseline prevalence of NAFLD was approximately 18.7%; this is a little lower than previously reported (36.4–47.8%) [13, 15, 16] but the Korean population is not as obese as populations in other parts of the world. In a previous cross-sectional Korean study investigating associations between lung function and NAFLD, NAFLD was determined using only the hepatic steatosis index or aminotransferase levels [14]. Because aminotransferase levels can be normal in individuals with NAFLD [29] and have poor sensitivity and specificity for identifying NAFLD, it is possible that the prevalence of NAFLD in that study was imprecise [14] The prevalence of NAFLD in our study may be lower because the mean age of enrolled subjects was younger (36 years) than in previous studies (>47 years) [13,15,16]. Additionally, some subjects in previous studies had diabetes (7.4–8.1%), hypertension (11.8–28.1%), or metabolic syndrome (>50%) [13,15,16], all of which are associated with an increased risk of NAFLD.
Our results support a close link between NAFLD and lung function impairment including COPD severity from previous studies [13,15,16,30–33]. We also demonstrated that the increased risk of NAFLD with decreased lung function is irrespective of whether the subjects were smokers or never smokers. Furthermore, emerging evidence has shown that both NAFLD and impaired lung function were commonly associated with cardio-metabolic comorbidities [5,34–36]. Therefore, NAFLD and impaired lung function could be associated not by chance but by pathobiological necessity [37]. However, our results should be interpreted with caution, because of this modest effect of baseline lung function on the development of NAFLD. In the actual population, various factors such as life style behaviors and metabolic comorbidities contributed more to the development of NAFLD [38,39]. Furthermore, lung function decline rate was not associated with NAFLD itself in recent longitudinal analysis [31], although some subjects in this study had a medical history of metabolic syndrome (9.4%), hypertension (14%), and diabetes (4.1%) which can be a risk of NAFLD and decreased lung function [11,35,36,40]. Considering the results of this study and ours, decreased lung function is strongly associated with NAFLD, but additional studies should be needed to clarify their precise interrelationship, especially on the issue whether NAFLD itself affects lung function.
In the present study, the risk of incident NAFLD was interestingly approximately the same in smoke exposed subjects and non-smokers, suggesting that decreased lung function itself rather than its etiology such as smoking increase the risk of incident NAFLD. The influence of smoking on development of NAFLD is controversial. Some studies reported that smoking was a risk factor for NAFLD [41,42], while another study expresses a conflicting results [43,44]. In recent meta-analysis regarding this controversy, interestingly, there was an association between smoking and NAFLD in former smokers and passive smokers, whereas there was not any correlation in current smokers [45]. An increase in body weight and BMI as a consequence of cessation of smoking [46] and higher concentration of harmful chemicals in side stream smoke than main stream smoke [47] could be an explanation for the development of NAFLD in former smoker and passive smokers, respectively. Of note, there is a body of evidence that smoking is an important factor for several metabolic disturbances [48] which are closely related to NAFLD [35]. Finally, smoking itself may act as a cofactor but not as a direct independent factor for NAFLD. Given indirect role of smoking for incident NAFLD, it seems to have a similar risk of incident NAFLD, regardless of smoking status, although the exact proportion of passive smokers among never smokers could not be evaluated in the current study.
The underlying mechanisms relating reduced lung function to development of NAFLD remain unclear. However, it is plausible that insulin resistance plays a role because it is closely associated with both NAFLD [49] and reduced lung function [50]. Interestingly, liver steatosis is also associated with insulin resistance in skeletal muscle [51], and decreased muscle mass is associated with an increased risk of NAFLD [7]. Insulin resistance in skeletal muscle reduces glucose utilization and induces abnormal fat metabolism, which may impair mitochondrial ATP production and reduce skeletal muscle strength [51,52]. As forced respiration during spirometry requires respiratory skeletal muscle contraction, a decline of lung function could be caused by decreased skeletal muscle strength and mass in subjects with NAFLD. Second, systemic inflammation may also mediate a link between reduced lung function and incident NAFLD. Cigarette smoking is the most widely recognized risk factors for decreased lung function [53]. And also, other environmental exposure such as occupational dusts, chemicals, urbanization, and particulate air pollution is associated with accelerated lung function decline [40]. Inhalation of noxious particulates from environmental pollution could cause airspace inflammation and the release of pro-inflammatory cytokines (such as interleukin [IL]-6) from alveolar macrophages, which may result in damage to the airways and a decline in lung function [54]. These inflammatory cytokines could enter the circulation and stimulate systemic inflammation [54]. Indeed, increased serum CRP (product by stimulating by IL-6), a marker of systemic inflammation, has been positively associated with lung function decline, regard less of smoking status [10]. These indicate that subjects with decreased lung function may have higher exposure to various environmental insults that lead to early perturbations of lung function and, in parallel, induce a low-grade inflammatory response. Also, hypoadiponectinemia related to systemic inflammation may have a role in the development of NAFLD [55] because adiponectin has anti-inflammatory effects via inhibition of tumor necrosis factor (TNF)-α and IL-6 [56]. This raises the possibility that lung inflammation might be a marker of risk susceptibility for the development of NAFLD.
There are several strengths and limitations of our study. A major strength of our study is that we describe the association between lung function tests at baseline and incident NAFLD over 13 years of follow-up in subjects without liver fat by ultrasound examination at baseline. Another major strength of our study is its large sample size, with subjects drawn from a healthy population without overt clinical disease. There are also several limitations of our study. First, our study used ultrasonography to detect incident fatty liver as the study endpoint. We did not perform liver biopsies to diagnose NAFLD as this is not feasible in a health screening program. Therefore, since ultrasound only semi-quantitatively assesses liver fat, and not inflammation or fibrosis, we are not able to comment on associations between non-alcoholic steatohepatitis (NASH) and lung function. That being said, many population-based epidemiologic studies have diagnosed fatty liver using ultrasonography because ultrasound is recognized as a reliable tool for this purpose and has acceptable diagnostic accuracy for diagnosing steatosis [57]. Second, there is the possibility of selection bias when recruiting participants, as the study participants consisted mostly of approximately middle-aged Korean adults in an urban community who were enrolled in health promotion screening at a single university hospital. Consequently, our participants were probably healthier individuals compared with other community-based cohorts of similarly aged subjects. As a result, our findings cannot be generalized to other populations or ethnic groups. Third, there is the possibility of sampling bias among subjects who participated in the present study due to differences in socio-economic status or healthier life style, both of which could affect lung function and NAFLD. Unfortunately, this information was not available in this study. Especially, the assessment for proportion of passive smokers, more detailed data on individual’s intensity and duration of physical activity which alters the risk of NAFLD [38,45] was limited to our study. These factors may influence on our results. Finally, the present study was not hospital-based. Lack of data on the concrete environmental exposures and predisposition factors such as inflammation-sensitive plasma proteins, which could affect the susceptibility for inflammation-mediated decline of lung function [58], are also potential limitations of the present study.
In conclusion, our results showed that decreased FEV1 (%) and FVC (%) were independently associated with incident NAFLD over 13 years of follow-up. Our study is the first to describe the association between low levels of lung function at baseline and incident NAFLD. As reduced lung function at baseline is an independent risk factor for the development of NAFLD in middle-aged healthy Korean population, clinicians are aware that patients with reduced lung function are at increased risk of NAFLD regardless of their smoking status.
Acknowledgments
We acknowledge the efforts of the health screening group at Kangbuk Samsung Hospital, Korea. CDB is supported in part by the Southampton National Institute for Health Research Biomedical Research Centre.
References
- 1. Fan JG, Farrell GC (2009) Epidemiology of non-alcoholic fatty liver disease in China. J Hepatol 50: 204–210. pmid:19014878
- 2. Adams LA, Angulo P (2005) Recent concepts in non-alcoholic fatty liver disease. Diabet Med 22: 1129–1133. pmid:16108837
- 3. Mantovani A, Zaza G, Byrne CD, Lonardo A, Zoppini G, Bonora E, et al. (2018) Nonalcoholic fatty liver disease increases risk of incident chronic kidney disease: A systematic review and meta-analysis. Metabolism 79: 64–76. pmid:29137912
- 4. Mantovani A, Byrne CD, Bonora E, Targher G (2018) Nonalcoholic Fatty Liver Disease and Risk of Incident Type 2 Diabetes: A Meta-analysis. Diabetes Care 41: 372–382. pmid:29358469
- 5. Targher G, Byrne CD, Lonardo A, Zoppini G, Barbui C (2016) Non-alcoholic fatty liver disease and risk of incident cardiovascular disease: A meta-analysis. J Hepatol 65: 589–600. pmid:27212244
- 6. Byrne CD, Targher G (2015) NAFLD: a multisystem disease. J Hepatol 62: S47–64. pmid:25920090
- 7. Hong HC, Hwang SY, Choi HY, Yoo HJ, Seo JA, Kim SG, et al. (2014) Relationship between sarcopenia and nonalcoholic fatty liver disease: the Korean Sarcopenic Obesity Study. Hepatology 59: 1772–1778. pmid:23996808
- 8. Nigam P, Bhatt SP, Misra A, Vaidya M, Dasgupta J, Chadha DS (2013) Non-alcoholic fatty liver disease is closely associated with sub-clinical inflammation: a case-control study on Asian Indians in North India. PLoS One 8: e49286. pmid:23326306
- 9. Van Gaal LF, Mertens IL, De Block CE (2006) Mechanisms linking obesity with cardiovascular disease. Nature 444: 875–880. pmid:17167476
- 10. Shaaban R, Kony S, Driss F, Leynaert B, Soussan D, Pin I, et al. (2006) Change in C-reactive protein levels and FEV1 decline: a longitudinal population-based study. Respir Med 100: 2112–2120. pmid:16650972
- 11. Kwon CH, Rhee EJ, Song JU, Kim JT, Kwag HJ, Sung KC (2012) Reduced lung function is independently associated with increased risk of type 2 diabetes in Korean men. Cardiovasc Diabetol 11: 38. pmid:22524685
- 12. Engstrom G, Hedblad B, Nilsson P, Wollmer P, Berglund G, Janzon L (2003) Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med 253: 574–581. pmid:12702035
- 13. Qin L, Zhang W, Yang Z, Niu Y, Li X, Lu S, et al. (2017) Impaired lung function is associated with non-alcoholic fatty liver disease independently of metabolic syndrome features in middle-aged and elderly Chinese. BMC Endocr Disord 17: 18. pmid:28330472
- 14. Kwak MS, Kim E, Jang EJ, Lee CH (2018) The association of non-alcoholic fatty liver disease with lung function: A survey design analysis using propensity score. Respirology 23: 82–88. pmid:28749019
- 15. Peng TC, Kao TW, Wu LW, Chen YJ, Chang YW, Wang CC, et al. (2015) Association Between Pulmonary Function and Nonalcoholic Fatty Liver Disease in the NHANES III Study. Medicine (Baltimore) 94: e907.
- 16. Jung DH, Shim JY, Lee HR, Moon BS, Park BJ, Lee YJ (2012) Relationship between non-alcoholic fatty liver disease and pulmonary function. Intern Med J 42: 541–546. pmid:22181832
- 17. Malavolti M, Mussi C, Poli M, Fantuzzi AL, Salvioli G, Battistini N, et al. (2003) Cross-calibration of eight-polar bioelectrical impedance analysis versus dual-energy X-ray absorptiometry for the assessment of total and appendicular body composition in healthy subjects aged 21–82 years. Ann Hum Biol 30: 380–391. pmid:12881138
- 18. Sung KC, Wild SH, Byrne CD (2014) Development of new fatty liver, or resolution of existing fatty liver, over five years of follow-up, and risk of incident hypertension. J Hepatol 60: 1040–1045. pmid:24445219
- 19. Mathiesen UL, Franzen LE, Aselius H, Resjo M, Jacobsson L, Foberg U, et al. (2002) Increased liver echogenicity at ultrasound examination reflects degree of steatosis but not of fibrosis in asymptomatic patients with mild/moderate abnormalities of liver transaminases. Dig Liver Dis 34: 516–522. pmid:12236486
- 20. Kim CW, Yun KE, Jung HS, Chang Y, Choi ES, Kwon MJ, et al. (2013) Sleep duration and quality in relation to non-alcoholic fatty liver disease in middle-aged workers and their spouses. J Hepatol 59: 351–357. pmid:23578884
- 21. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. (2012) The diagnosis and management of non-alcoholic fatty liver disease: practice guideline by the American Gastroenterological Association, American Association for the Study of Liver Diseases, and American College of Gastroenterology. Gastroenterology 142: 1592–1609. pmid:22656328
- 22. American Thoracic Society (1995) Standardization of Spirometry, 1994 Update. Am J Respir Crit Care Med 152: 1107–1136. pmid:7663792
- 23. (1991) Lung function testing: selection of reference values and interpretative strategies. American Thoracic Society. Am Rev Respir Dis 144: 1202–1218. pmid:1952453
- 24. Morris JF, Koski A, Johnson LC (1971) Spirometric standards for healthy nonsmoking adults. Am Rev Respir Dis 103: 57–67. pmid:5540840
- 25. Choi JK, Paek D, Lee JO (2005) Normal predictive values of spirometry in Korean population. Tuberc Respir Dis 58: 230–242.
- 26. Rode A, Shephard RJ (1973) Pulmonary function of Canadian Eskimos. Scand J Respir Dis 54: 191–205. pmid:4748670
- 27. Royston P, Parmar MK (2002) Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects. Stat Med 21: 2175–2197. pmid:12210632
- 28. Chalasani N, Younossi Z, Lavine JE, Diehl AM, Brunt EM, Cusi K, et al. (2012) The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 55: 2005–2023. pmid:22488764
- 29. Vernon G, Baranova A, Younossi ZM (2011) Systematic review: the epidemiology and natural history of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis in adults. Aliment Pharmacol Ther 34: 274–285. pmid:21623852
- 30. Moon SW, Kim SY, Jung JY, Kang YA, Park MS, Kim YS, et al. (2018) Relationship between obstructive lung disease and non-alcoholic fatty liver disease in the Korean population: Korea National Health and Nutrition Examination Survey, 2007–2010. Int J Chron Obstruct Pulmon Dis 13: 2603–2611. pmid:30214178
- 31. Lee CH, Choi SH, Chung GE, Park B, Kwak MS (2018) Nonalcoholic fatty liver disease is associated with decreased lung function. Liver Int.
- 32. Viglino D, Jullian-Desayes I, Minoves M, Aron-Wisnewsky J, Leroy V, Zarski JP, et al. (2017) Nonalcoholic fatty liver disease in chronic obstructive pulmonary disease. Eur Respir J 49.
- 33. Kwak MS, Kim E, Jang EJ, Lee CH (2017) The association of non-alcoholic fatty liver disease with lung function: A survey design analysis using propensity score. Respirology.
- 34. Piazzolla G, Castrovilli A, Liotino V, Vulpi MR, Fanelli M, Mazzocca A, et al. (2017) Metabolic syndrome and Chronic Obstructive Pulmonary Disease (COPD): The interplay among smoking, insulin resistance and vitamin D. PLoS One 12: e0186708. pmid:29065130
- 35. Ballestri S, Zona S, Targher G, Romagnoli D, Baldelli E, Nascimbeni F, et al. (2016) Nonalcoholic fatty liver disease is associated with an almost twofold increased risk of incident type 2 diabetes and metabolic syndrome. Evidence from a systematic review and meta-analysis. J Gastroenterol Hepatol 31: 936–944. pmid:26667191
- 36. Leone N, Courbon D, Thomas F, Bean K, Jego B, Leynaert B, et al. (2009) Lung function impairment and metabolic syndrome: the critical role of abdominal obesity. Am J Respir Crit Care Med 179: 509–516. pmid:19136371
- 37. Lonardo A, Nascimbeni F, Ponz de Leon M (2017) Nonalcoholic fatty liver disease and COPD: is it time to cross the diaphragm? Eur Respir J 49.
- 38. Kwak MS, Kim D (2018) Non-alcoholic fatty liver disease and lifestyle modifications, focusing on physical activity. Korean J Intern Med 33: 64–74. pmid:29202557
- 39. Angulo P (2002) Nonalcoholic fatty liver disease. N Engl J Med 346: 1221–1231. pmid:11961152
- 40. Miele CH, Grigsby MR, Siddharthan T, Gilman RH, Miranda JJ, Bernabe-Ortiz A, et al. (2018) Environmental exposures and systemic hypertension are risk factors for decline in lung function. Thorax.
- 41. Munsterman ID, Smits MM, Andriessen R, van Nieuwkerk CMJ, Bloemena E, Mulder CJJ, et al. (2017) Smoking is associated with severity of liver fibrosis but not with histological severity in nonalcoholic fatty liver disease. Results from a cross-sectional study. Scand J Gastroenterol 52: 881–885. pmid:28446050
- 42. Liu Y, Dai M, Bi Y, Xu M, Xu Y, Li M, et al. (2013) Active smoking, passive smoking, and risk of nonalcoholic fatty liver disease (NAFLD): a population-based study in China. J Epidemiol 23: 115–121. pmid:23399520
- 43. Xu CF, Yu CH, Xu L, Miao M, Li YM (2010) Is cigarette smoking an independent risk factor or a cofactor for nonalcoholic fatty liver disease? Hepatology 52: 803–804. pmid:20683979
- 44. Chavez-Tapia NC, Lizardi-Cervera J, Perez-Bautista O, Ramos-Ostos MH, Uribe M (2006) Smoking is not associated with nonalcoholic fatty liver disease. World J Gastroenterol 12: 5196–5200. pmid:16937532
- 45. Akhavan Rezayat A, Dadgar Moghadam M, Ghasemi Nour M, Shirazinia M, Ghodsi H, Rouhbakhsh Zahmatkesh MR, et al. (2018) Association between smoking and non-alcoholic fatty liver disease: A systematic review and meta-analysis. SAGE Open Med 6: 2050312117745223. pmid:29399359
- 46. Albanes D, Jones DY, Micozzi MS, Mattson ME (1987) Associations between smoking and body weight in the US population: analysis of NHANES II. Am J Public Health 77: 439–444. pmid:3493709
- 47. Schick S, Glantz S (2005) Philip Morris toxicological experiments with fresh sidestream smoke: more toxic than mainstream smoke. Tob Control 14: 396–404. pmid:16319363
- 48. Oh SW, Yoon YS, Lee ES, Kim WK, Park C, Lee S, et al. (2005) Association between cigarette smoking and metabolic syndrome: the Korea National Health and Nutrition Examination Survey. Diabetes Care 28: 2064–2066. pmid:16043763
- 49. Takamura T, Misu H, Ota T, Kaneko S (2012) Fatty liver as a consequence and cause of insulin resistance: lessons from type 2 diabetic liver. Endocr J 59: 745–763. pmid:22893453
- 50. Lazarus R, Sparrow D, Weiss ST (1998) Baseline ventilatory function predicts the development of higher levels of fasting insulin and fasting insulin resistance index: the Normative Aging Study. Eur Respir J 12: 641–645. pmid:9762793
- 51. Kato K, Takeshita Y, Misu H, Zen Y, Kaneko S, Takamura T (2015) Liver steatosis is associated with insulin resistance in skeletal muscle rather than in the liver in Japanese patients with non-alcoholic fatty liver disease. J Diabetes Investig 6: 158–163. pmid:25802723
- 52. Barzilay JI, Cotsonis GA, Walston J, Schwartz AV, Satterfield S, Miljkovic I, et al. (2009) Insulin resistance is associated with decreased quadriceps muscle strength in nondiabetic adults aged >or = 70 years. Diabetes Care 32: 736–738. pmid:19171728
- 53. Skogstad M, Kjaerheim K, Fladseth G, Gjolstad M, Daae HL, Olsen R, et al. (2006) Cross shift changes in lung function among bar and restaurant workers before and after implementation of a smoking ban. Occup Environ Med 63: 482–487. pmid:16551754
- 54. van Eeden SF, Tan WC, Suwa T, Mukae H, Terashima T, Fujii T, et al. (2001) Cytokines involved in the systemic inflammatory response induced by exposure to particulate matter air pollutants (PM(10)). Am J Respir Crit Care Med 164: 826–830. pmid:11549540
- 55. Polyzos SA, Toulis KA, Goulis DG, Zavos C, Kountouras J (2011) Serum total adiponectin in nonalcoholic fatty liver disease: a systematic review and meta-analysis. Metabolism 60: 313–326. pmid:21040935
- 56. Fantuzzi G (2005) Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 115: 911–919; quiz 920. pmid:15867843
- 57. Ballestri S, Nascimbeni F, Baldelli E, Marrazzo A, Romagnoli D, Targher G, et al. (2017) Ultrasonographic fatty liver indicator detects mild steatosis and correlates with metabolic/histological parameters in various liver diseases. Metabolism 72: 57–65. pmid:28641784
- 58. Engstrom G, Lind P, Hedblad B, Wollmer P, Stavenow L, Janzon L, et al. (2002) Lung function and cardiovascular risk: relationship with inflammation-sensitive plasma proteins. Circulation 106: 2555–2560. pmid:12427651