Association of Pulmonary Function Decline over Time with Longitudinal Change of Glycated Hemoglobin in Participants without Diabetes Mellitus
by
, , , ,
Wen-Hsien Lee
1,2,3,4
,
Da-Wei Wu
1,4,5,
Ying-Chih Chen
1,2,
Yi-Hsueh Liu
1,2,
Wei-Sheng Liao
1,2,
Szu-Chia Chen
1,3,4,6,
Chih-Hsing Hung
1,3,4,
Chao-Hung Kuo
1,3,4 and
Ho-Ming Su
1,2,3,4,* 1
Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
2
Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
3
Faculty of Medicine, College of Medicine, Kaohsiung Medical University, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
4
Research Center for Environmental Medicine, Kaohsiung Medical University, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
5
Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Kaohsiung Medical University Hospital, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
6
Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, 482 Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung 812, Taiwan
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2021, 11(10), 994; https://doi.org/10.3390/jpm11100994
Submission received: 14 August 2021
/
Revised: 20 September 2021
/
Accepted: 29 September 2021
/
Published: 30 September 2021
Abstract
Pulmonary damage and function impairment were frequently noted in patients with diabetes mellitus (DM). However, the relationship between lung function and glycemic status in non-DM subjects was not well-known. Here, we evaluated the association of longitudinal changes of lung function parameters with longitudinal changes of glycated hemoglobin (HbA1c) in non-DM participants. The study enrolled participants without prior type 2 DM, hypertension, and chronic obstructive pulmonary disease (COPD) from the Taiwan Biobank database. Laboratory profiles and pulmonary function parameters, including forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1), were examined at baseline and follow-up. Finally, 7055 participants were selected in this study. During a mean 3.9-year follow-up, FVC and FEV1 were significantly decreased over time (both p < 0.001). In the multivariable analysis, the baseline (unstandardized coefficient β = −0.032, p < 0.001) and longitudinal change (unstandardized coefficient β = −0.025, p = 0.026) of FVC were negatively associated with the baseline and longitudinal change of HbA1c, respectively. Additionally, the longitudinal change of FVC was negatively associated with the risk of newly diagnosed type 2 DM (p = 0.018). During a mean 3.9-year follow-up, our present study, including participants without type 2 DM, hypertension, and COPD, demonstrated that the baseline and longitudinal change of FVC were negatively and respectively correlated with the baseline and longitudinal change of HbA1c. Furthermore, compared to those without new-onset DM, participants with new-onset DM had a more pronounced decline of FVC over time.
1. Introduction
Type 2 Diabetes mellitus (DM) is a globally common disease and a major risk factor of cardiovascular mortality and morbidity [1]. Micro-vascular and macro-vascular complications in particular organs and tissues, such as heart, kidney, and retina, are well established in patients with type 2 DM [2]. The lung is another target of organ damage of DM, and pulmonary function decline is also frequently noted in patients with type 2 DM [3]. According to recent studies, hyperglycemia is associated with pulmonary functional damage in type 2 diabetic patients with chronic obstructive pulmonary disease (COPD) and asthma [4,5,6]. Pulmonary function deterioration is associated with elevated glycated hemoglobin (HbA1c), glucose variability, and abnormal glucose level in type 2 diabetic patients with hospitalization for COPD or asthma [5,6,7,8]. In addition, anti-glycemic control in patients with type 2 DM can improve their pulmonary function [9].
Standard pulmonary function parameters, such as forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1), are generally used to assess the pulmonary function in clinical practices [10]. Compared with type 2 diabetic patients with well glycemic control, type 2 diabetic patients with poor glycemic control had a lower predicted FVC, FVC, predicted FEV1, and FEV1 [7,11]. Similarly, compared with non-diabetic subjects, patients with type 2 DM also had a lower residual FVC and residual FEV1 [12]. Although pulmonary function decline and status of glycemic control were studied in type 2 diabetic participants, there were few studies investigating the relationship between pulmonary function decline over time and longitudinal change of glucose status in non-DM participates. Here, we studied the relationship between changes of pulmonary function over time and longitudinal change of HbA1c in subjects without type 2 DM.
2. Methods
2.1. Data Source
This longitudinal study data was analyzed from the Taiwan Biobank, a national database with adults aged from 30 to 70 years old without cancer in Taiwan since 2008 [13,14]. The demographic information, including age, gender, and history of hypertension and diabetes, was obtained from a face-to-face interview. Systolic blood pressures, body mass index, and overnight fasting blood chemistry parameters, including fasting blood glucose, total cholesterol, triglycerides, serum creatinine, glutamic-pyruvic transaminase (GPT), and HbA1C, were collected. Initially, we included 27,210 participants that had completed all above data at baseline and at around a 3.9-year follow-up. Then, we excluded participants with type 2 DM (n = 1449), hypertension (n = 3562), COPD (n = 5952), and restrictive lung disease (n = 1). We also excluded participants who could not complete standard pulmonary function tests at baseline and longitudinal follow-up (n = 9191). Finally, 7055 participants were included in the present study.
2.2. Ethics Statement
The study protocol was approved by the Institutional Review Board of Kaohsiung Medical University Hospital (KMUHIRB-E(I)-20180242), which was approved on 8 March 2018.
2.3. Spirometry Examinations
Well-trained technicians performed the standard spirometry measurements by using a MicroLab spirometer and Spida 5 software (Micro Medical Ltd., Rochester, Kent, UK) [15]. All participants received a pulmonary function test three times, including FEV1 and FVC. All tests meet standard quality criteria with differences within 5% or 100 mL, and the best result among the 3 pulmonary function tests was used for further analysis. FVC-predicted and FEV1-predicted were calculated by dividing the FVC and FEV1 by the counterpart values measured from the general population by spirometry software, respectively. All participants did not receive a bronchodilator test.
2.4. Definition of Type 2 DM
Type 2 DM is defined according to the guidelines of the American Diabetes Association [16]. Participants were considered to have newly-diagnosed type 2 DM if type 2 DM was recorded by face-to-face interview or their HbA1C was ≥6.5% at follow-up.
2.5. Statistical Analysis
All data were presented as mean ± standard deviation or number (percentage). The longitudinal change of laboratory data and pulmonary function tests between baseline and follow-up were analyzed by paired t-test. The difference of continuous variables between groups was analyzed by an independent sample t-test. Correlations of baseline HbA1c and longitudinal change of HbA1C were determined by linear regression analysis. Binary logistic regression analysis was used to determine the significant correlations of newly diagnosed type 2 DM. Significant variables in the univariable linear and logistic analyses were selected into multivariable linear regression analysis with stepwise selection and logistic regression analysis with forward selection, respectively. All statistical analyses were performed by SPSS 22.0. A p-value of less than 0.05 was considered to be statistically significant.
3. Results
The present study has 7055 participants enrolled (mean age 49.5 ± 10.1, male gender 35%, smoking 25.6%) without type 2 DM, hypertension, or chronic pulmonary diseases during a 3.9-year follow-up. Table 1 shows clinical, laboratory, and pulmonary function data for all 7055 study participants. Compared to the baseline variables, age, systolic blood pressure, body mass index, fasting blood glucose, HbA1c, total cholesterol, triglyceride, FVC-predicted, FVE1-predicted, and FVE1/FVC were significantly increased and FVC and FEV1 were significantly decreased at follow-up. In addition, baseline FEV1 and FVC were 3.05 ± 0.59 and 3.64 ± 0.67 L for men and 2.09 ± 0.43 and 2.49 ± 0.48 for women, respectively. The annular decline of FEV1 and FVC were 19.5 ± 97.0 and 56.7 ± 93.2 mL for all participants, respectively.
The univariable and multivariable linear regression analyses of baseline HbA1c are shown in Table 2. In univariable analysis, baseline HbA1c was significantly correlated with male gender, increased age, systolic blood pressure, body mass index, fasting blood glucose, GPT, total cholesterol, and triglyceride and decreased FVC and FEV1. In multivariable analysis, baseline HbA1c was significantly correlated with increased age, body mass index, fasting blood glucose, GPT, total cholesterol, and triglyceride and decreased of FVC (unstandardized coefficient β = −0.033, 95% confidence interval [CI], −0.043 to −0.024; p < 0.001).
Univariable and multivariable linear regression analyses of the longitudinal change of HbA1c are shown in Table 3. In univariable analysis, the longitudinal change of HbA1c was positively correlated with the longitudinal changes of age, body mass index, fasting blood glucose, GPT, total cholesterol, and triglyceride and negatively correlated with longitudinal changes of creatinine, FVC, and FEV1. In multivariable analysis, the longitudinal change of HbA1c was positively correlated with the longitudinal changes of body mass index, fasting blood glucose, total cholesterol, and triglyceride and negatively correlated with longitudinal changes of creatinine and FVC (unstandardized coefficient β = −0.025, 95% CI, −0.048 to −0.003, p = 0.026).
Univariable and multivariable linear regression analyses of longitudinal change of FVC are shown in Table 4. In univariable and multivariable analysis, the longitudinal change of FVC was negatively correlated with smoking, and the longitudinal changes were positively correlated with age, GPT, and HbA1c (in multivariable analysis, unstandardized coefficient β = −0.022, 95% CI, −0.044 to −0.001, p = 0.041).
Table 5 shows the comparison of longitudinal changes of clinical, laboratory, and pulmonary function data between participants with and without newly diagnosed type 2 DM. Compared to participants without newly diagnosed type 2 DM, participants with newly diagnosed type 2 DM had increased longitudinal changes of fasting blood glucose and HbA1c and decreased longitudinal changes of total cholesterol and FVC during the 3.9-year follow-up.
Table 6 shows the odds ratio of the longitudinal changes of parameters in association with newly diagnosed type 2 DM in univariable and multivariable logistic regression analyses. In the multivariable analysis, newly diagnosed type 2 DM was positively correlated with the longitudinal change of fasting blood glucose and negatively correlated with the longitudinal changes of total cholesterol and FVC (odds ratio = 0.625, 95% CI, 0.424 to 0.922, p = 0.018).
4. Discussion
Our present study was the first one to demonstrate the relationship between the longitudinal changes of HbA1c and pulmonary function parameters in participants without type 2 DM, hypertension, and COPD. We showed that baseline HbA1c was associated with baseline FVC and the longitudinal change of HbA1c was also associated with the longitudinal change of FVC. Furthermore, compared to those without new-onset DM, participants with new-onset DM had a more pronounced decline of FVC over time.
The annular decline of pulmonary function was correlated with an ethnic difference, age, gender, smoke habit, diabetes, hypertension, and COPD [17,18,19,20,21], so we only enrolled participants without prior diabetes, hypertension, and COPD. There were some population-based studies to evaluate the annular decline in FEV1 and FVC. A 15-year Doetinchem population-based cohort study showed the annular decline in FEV1 and FVC were 36.1 and 59.9 mL for men and 30.9 and 29.0 mL for women, respectively [18]. In Korea, a 3.8-year cohort study enrolled 8842 health subjects without prior pulmonary diseases showed the annular decline in FEV1 was 31.3 mL for men and 27.0 mL for women [22]. In Korea, another 8.95-year longitudinal study, which consisted of 35,129 health subjects without a history of pulmonary diseases, demonstrated the annular decline in FEV1 was 37.32 mL [23]. In our 3.9-year follow-up study, the annular decline in FEV1 and FVC were 19.5 and 56.7 mL for all participants, 30.0 and 70.7 mL for men, and 13.8 and 49.2 mL for women, respectively. Different from our study, the above previous studies did not exclude participants with a history of hypertension and diabetes [18,22,23], which might partially explain why the annular decline in FEV1 was relatively low in our present study.
Diabetic lung disease was an emerged issue for pulmonary organ damage and function impairment in the DM population. Compared to subjects with non-diabetes, significant lung function impairments were frequently found in patients with type 2 DM. In the Atherosclerosis Risk in Communities Study, compared with non-diabetic subjects, patients with type 2 DM had a significantly lower FEV1 (3.2 vs. 3.4 L for men; 2.3 vs. 2.5 L for women) and FVC (4.2 vs. 4.6 L for men; 3.0 vs. 3.3 L for women) and faster annular decline in FEV1 (49 vs. 47 mL) and FVC (64 vs. 58 mL) [24]. From the Korea National Health and Nutrition Survey database, compared with non-DM participants, type 2 DM had a significantly lower FEV1 (2.7 vs. 2.8 L) and FEV1/FVC (75.9 vs. 77.9%) [25]. The difference between DM and non-DM patients for the FEV1/FVC ratio was insignificant in a pooled meta-analysis [26]. The baseline FEV1 (3.05 L for men; 2.09 L for women) and FVC (3.64 L for men; 2.49 L for women) in our participants were similar to those in non-diabetic and healthy Asian adults [25,27]. Compared to those with non-newly diagnosed type 2 DM, our subjects with newly diagnosed type 2 DM similarly had a reduced FVC but comparable longitudinal changes of FEV1 and FEV1/FVC.
High glycemic status, in terms of high HbA1c, was associated with pulmonary dysfunction and increased risks of hospitalization for asthma and COPD in patients with type 2 DM [5,28,29]. In a cross-sectional study in Japan, a 1% increase in HbA1c was associated with a significant decrease in FEV1 and FVC (73 and 128 mL for men and 25 and 52 mL for women, respectively) [28]. Although HbA1c was negatively correlated with FEV1 and FVC in DM patients with good glycemic control, the correlation became insignificant in DM patients with poor glycemic control [30]. Zhang et al. showed the non-linear “L-shaped” association between HbA1c and pulmonary function in type 2 DM [30]. Similar to a previous study, we also showed that the increased baseline and longitudinal changes of HbA1c were significantly correlated with reduced baseline and longitudinal changes of FVC in the multivariable models adjusted by age, body mass index, and laboratory variables. Furthermore, 1 L decline in FVC over 3.9 years could increase the risk of newly diagnosed type 2 DM in the present cohort study by 37.5%.
The deterioration of lung function, including FEV1 and FVC, was found in patients with type 2 DM [31]. High HbA1C and uncontrolled glycemic state were associated with the decline of FEV1 and FVC in diabetic patients [31]. In the non-diabetic participants in Korea, Oh et al. showed that increased HbA1c was significantly correlated with lung impairment, including FEV1, FVC, and restrictive pulmonary pattern [32,33]. Smoking status could influence HbA1C, FEV1 and restrictive lung pattern, as shown in previous studies [33,34]. Differently from Oh’s study (smoking 36%), our present study showed a non-significant relationship with smoking, HbA1c, and FEV1. Our study result could be affected by participants with a relatively low percentage of smoking (25.6%).
The mechanism of pulmonary dysfunction in hyperglycemic status and overt DM was multifactorial [35], including insulin resistance, oxidative stress, elastic fibers remodeling, excessive pulmonary collagens expression, and smooth muscle dysfunction [36,37,38,39]. Singh et al. showed hyperinsulinemia-induced activation of β-catenin mediated pulmonary fibrosis and epithelial-mesenchymal transition in mice and human airway smooth muscle cells [36]. Cazzola et al. demonstrated hyperglycemia-induced hyper-responsiveness of isolated human bronchi and increased intra-cellular calcium release via a Rho/ROCK signal transduction pathway in human airway smooth muscle cells [39]. Clemmer et al. showed hyperglycemia was associated with increased pulmonary vascular permeability via the superoxide pathway in obese rats [37]. Südy et al. also found that increased pulmonary tissue viscoelasticity was associated with the alveolar collapse in diabetic rats [38]. The hyperglycemic effects on the airway and alveolar regions could result in an increase in pulmonary elastic fiber remodeling, and therefore, reduce pulmonary volume [36,37,38,39,40].
Study Limitations
There were several limitations in our longitudinal cohort study. First, air pollution and exercise habits were associated with pulmonary function [41,42]. There was no such data in the Taiwan Biobank. Second, compared to COPD patients with non-hyperlipidemia, COPD patients with hyperlipidemia were correlated with lower pulmonary volumes and higher FEV1 [43]. Although we adjusted the lipid profiles in multivariable analyses, we did not know the diary habit and lipid-lowering agents of our participants. Third, owing to the statistics of the Taiwan Biobank, the proportion of study participants coming back to follow up was only about 50%, which may result in sample bias. Thus, unequally followed participants could affect the interpretation of our results in the non-randomized study. Finally, inflammatory markers and insulin-resistant profiles were correlated with pulmonary function [44,45]. Such information was also lacking in this study.
5. Conclusions
During a mean 3.9-year follow-up, our present study, including participants without type 2 DM, hypertension, and COPD, demonstrated that the baseline and longitudinal changes of FVC were negatively and respectively correlated with the baseline and longitudinal change of HbA1c. Furthermore, compared to those without new-onset DM, participants with new-onset DM had a more pronounced decline of FVC over time.
Author Contributions
Conceptualization, W.-H.L. and H.-M.S.; Data curation, W.-H.L., D.-W.W., Y.-C.C. and W.-S.L.; Formal analysis, D.-W.W.; Funding acquisition, C.-H.H.; Investigation, Y.-C.C. and Y.-H.L.; Methodology, Y.-H.L. and H.-M.S.; Project administration, S.-C.C., C.-H.H. and C.-H.K.; Re-sources, S.-C.C.; Software, Y.-H.L. and W.-S.L.; Supervision, S.-C.C., C.-H.H., C.-H.K. and H.-M.S.; Validation, W.-H.L.; Writing—original draft, W.-H.L. and H.-M.S.; Writing—review & editing, H.-M.S. All authors have read and agreed to the published version of the manuscript.
Funding
This study was supported by grants from the Kaohsiung Municipal Siaogang Hospital, Taiwan (kmhk-109-10).
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Institutional Review Board of Kaohsiung Medical University Hospital (KMUHIRB-E(I)-20180242), which was approved on 8 March 2018.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
Data may be available upon request to interested researchers. Please send data requests to: Ho-Ming Su, MD. Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University.
Acknowledgments
All authors thank all researchers and participants at the Taiwan Biobank.
Conflicts of Interest
All authors declare that no competing financial interests or personal relationships that could have associate the summit in the present study.
References
- American Diabetes Association. 10. Cardiovascular disease and risk management: Standards of medical care in diabetes-2020. Diabetes Care 2020, 43, S111–S134. [Google Scholar] [CrossRef]
- Chawla, A.; Chawla, R.; Jaggi, S. Microvasular and macrovascular complications in diabetes mellitus: Distinct or continuum? Indian J. Endocrinol. Metab. 2016, 20, 546–551. [Google Scholar] [CrossRef]
- van den Borst, B.; Gosker, H.R.; Zeegers, M.P.; Schols, A.M. Pulmonary function in diabetes: A metaanalysis. Chest 2010, 138, 393–406. [Google Scholar] [CrossRef]
- Khateeb, J.; Fuchs, E.; Khamaisi, M. Diabetes and lung disease: A neglected relationship. Rev. Diabetes Stud. 2019, 15, 1–15. [Google Scholar] [CrossRef]
- Yang, G.; Han, Y.Y.; Forno, E.; Yan, Q.; Rosser, F.; Chen, W.; Celedon, J.C. Glycated hemoglobin a1c, lung function, and hospitalizations among adults with asthma. J. Allergy Clin. Immunol. Pract. 2020, 8, 3409–3415.e1. [Google Scholar] [CrossRef] [PubMed]
- Yang, C.J.; Liao, W.I.; Tang, Z.C.; Wang, J.C.; Lee, C.H.; Chang, W.C.; Hsu, C.W.; Tang, S.E.; Tsai, S.H. Glycated hemoglobin a1c-based adjusted glycemic variables in patients with diabetes presenting with acute exacerbation of chronic obstructive pulmonary disease. Int. J. Chron. Obstruct. Pulmon. Dis. 2017, 12, 1923–1932. [Google Scholar] [CrossRef] [PubMed][Green Version]
- Davis, W.A.; Knuiman, M.; Kendall, P.; Grange, V.; Davis, T.M.; Fremantle Diabetes, S. Glycemic exposure is associated with reduced pulmonary function in type 2 diabetes: The fremantle diabetes study. Diabetes Care 2004, 27, 752–757. [Google Scholar] [CrossRef] [PubMed]
- Islam, E.A.; Limsuwat, C.; Nantsupawat, T.; Berdine, G.G.; Nugent, K.M. The association between glucose levels and hospital outcomes in patients with acute exacerbations of chronic obstructive pulmonary disease. Ann. Thorac. Med. 2015, 10, 94–99. [Google Scholar] [PubMed]
- Gutierrez-Carrasquilla, L.; Sanchez, E.; Barbe, F.; Dalmases, M.; Lopez-Cano, C.; Hernandez, M.; Rius, F.; Carmona, P.; Hernandez, C.; Simo, R.; et al. Effect of glucose improvement on spirometric maneuvers in patients with type 2 diabetes: The sweet breath study. Diabetes Care 2019, 42, 617–624. [Google Scholar] [CrossRef]
- Johnson, J.D.; Theurer, W.M. A stepwise approach to the interpretation of pulmonary function tests. Am. Fam. Physician 2014, 89, 359–366. [Google Scholar] [PubMed]
- Kim, J.M.; Kim, M.K.; Joung, K.H.; Lee, J.H.; Kim, H.J.; Ku, B.J. Association between glycemic state and pulmonary function and effect of walking as a protective factor in subjects with diabetes mellitus. Ann. Transl. Med. 2019, 7, 530. [Google Scholar] [CrossRef] [PubMed]
- Walter, R.E.; Beiser, A.; Givelber, R.J.; O’Connor, G.T.; Gottlieb, D.J. Association between glycemic state and lung function: The framingham heart study. Am. J. Respir. Crit. Care Med. 2003, 167, 911–916. [Google Scholar] [CrossRef] [PubMed]
- Wen, W.L.; Wu, P.Y.; Huang, J.C.; Tu, H.P.; Chen, S.C. Different curve shapes of fasting glucose and various obesity-related indices by diabetes and sex. Int. J. Environ. Res. Public Health 2021, 18, 3096. [Google Scholar] [CrossRef]
- Lin, J.C.; Fan, C.T.; Liao, C.C.; Chen, Y.S. Taiwan biobank: Making cross-database convergence possible in the big data era. Gigascience 2018, 7, 1–4. [Google Scholar] [CrossRef]
- Miller, M.R.; Hankinson, J.; Brusasco, V.; Burgos, F.; Casaburi, R.; Coates, A.; Crapo, R.; Enright, P.; van der Grinten, C.P.; Gustafsson, P.; et al. Standardisation of spirometry. Eur. Respir. J. 2005, 26, 319–338. [Google Scholar] [CrossRef] [PubMed]
- American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of medical care in diabetes-2020. Diabetes Care 2020, 43, S14–S31. [Google Scholar] [CrossRef]
- Thomas, E.T.; Guppy, M.; Straus, S.E.; Bell, K.J.L.; Glasziou, P. Rate of normal lung function decline in ageing adults: A systematic review of prospective cohort studies. BMJ Open 2019, 9, e028150. [Google Scholar] [CrossRef]
- van Oostrom, S.H.; Engelfriet, P.M.; Verschuren, W.M.M.; Schipper, M.; Wouters, I.M.; Boezen, M.; Smit, H.A.; Kerstjens, H.A.M.; Picavet, H.S.J. Aging-related trajectories of lung function in the general population-the doetinchem cohort study. PLoS ONE 2018, 13, e0197250. [Google Scholar] [CrossRef] [PubMed]
- Tantucci, C.; Modina, D. Lung function decline in copd. Int. J. Chronic Obstruct. Pulmon. Dis. 2012, 7, 95–99. [Google Scholar] [CrossRef]
- Lee, J.; Kwon, D.; Lee, Y.; Jung, I.; Hyun, D.; Lee, H.; Ahn, Y.S. Hypertension is associated with increased risk of diabetic lung. Int. J. Environ. Res. Public Health 2020, 17, 7513. [Google Scholar] [CrossRef] [PubMed]
- Goldman, M.D. Lung dysfunction in diabetes. Diabetes Care 2003, 26, 1915–1918. [Google Scholar] [CrossRef]
- Leem, A.Y.; Park, B.; Kim, Y.S.; Chang, J.; Won, S.; Jung, J.Y. Longitudinal decline in lung function: A community-based cohort study in Korea. Sci. Rep. 2019, 9, 13614. [Google Scholar] [CrossRef] [PubMed]
- Ahn, K.M.; Lee, S.Y.; Lee, S.H.; Kim, S.S.; Park, H.W. Lung function decline is associated with serum uric acid in korean health screening individuals. Sci. Rep. 2021, 11, 10183. [Google Scholar] [CrossRef] [PubMed]
- Yeh, H.C.; Punjabi, N.M.; Wang, N.Y.; Pankow, J.S.; Duncan, B.B.; Cox, C.E.; Selvin, E.; Brancati, F.L. Cross-sectional and prospective study of lung function in adults with type 2 diabetes: The atherosclerosis risk in communities (aric) study. Diabetes Care 2008, 31, 741–746. [Google Scholar] [CrossRef]
- Lee, D.Y.; Nam, S.M. The association between lung function and type 2 diabetes in koreans. Osong Public Health Res. Perspect. 2020, 11, 27–33. [Google Scholar] [CrossRef]
- Diez-Manglano, J.; Asin Samper, U. Pulmonary function tests in type 2 diabetes: A meta-analysis. ERJ Open Res. 2021, 7, 7. [Google Scholar] [CrossRef] [PubMed]
- Wang, W.T.; Ko, H.K.; Lin, C.C.; Shu, J.H.; Hsu, H.C.; Liang, Y.; Hsu, P.F.; Lin, C.C.; Wang, Y.J.; Din, Y.Z.; et al. Spirometric reference values in heathy chinese adults in taiwan: The secular changes and comparison with other asian populations. J. Formos. Med. Assoc. 2020, 119, 290–299. [Google Scholar] [CrossRef]
- Kabeya, Y.; Kato, K.; Tomita, M.; Katsuki, T.; Oikawa, Y.; Shimada, A. Association of glycemic status with impaired lung function among recipients of a health screening program: A cross-sectional study in japanese adults. J. Epidemiol. 2014, 24, 410–416. [Google Scholar] [CrossRef] [PubMed]
- Chiu, H.T.; Li, T.C.; Li, C.I.; Liu, C.S.; Lin, W.Y.; Lin, C.C. Visit-to-visit glycemic variability is a strong predictor of chronic obstructive pulmonary disease in patients with type 2 diabetes mellitus: Competing risk analysis using a national cohort from the taiwan diabetes study. PLoS ONE 2017, 12, e0177184. [Google Scholar] [CrossRef]
- Zhang, R.H.; Zhou, J.B.; Cai, Y.H.; Shu, L.P.; Simo, R.; Lecube, A. Non-linear association between diabetes mellitus and pulmonary function: A population-based study. Respir. Res. 2020, 21, 292. [Google Scholar] [CrossRef]
- Maan, H.B.; Meo, S.A.; Al Rouq, F.; Meo, I.M.U.; Gacuan, M.E.; Alkhalifah, J.M. Effect of glycated hemoglobin (hba1c) and duration of disease on lung functions in type 2 diabetic patients. Int. J. Environ. Res. Public Health 2021, 18, 6970. [Google Scholar] [CrossRef] [PubMed]
- Oh, I.H.; Park, J.H.; Lee, C.H.; Park, J.S. The association of normal range glycated hemoglobin with restrictive lung pattern in the general population. PLoS ONE 2015, 10, e0117725. [Google Scholar] [CrossRef] [PubMed]
- Hong, J.W.; Ku, C.R.; Noh, J.H.; Ko, K.S.; Rhee, B.D.; Kim, D.J. Association between self-reported smoking and hemoglobin a1c in a korean population without diabetes: The 2011-2012 korean national health and nutrition examination survey. PLoS ONE 2015, 10, e0126746. [Google Scholar] [CrossRef]
- Simmons, M.S.; Connett, J.E.; Nides, M.A.; Lindgren, P.G.; Kleerup, E.C.; Murray, R.P.; Bjornson, W.M.; Tashkin, D.P. Smoking reduction and the rate of decline in fev(1): Results from the lung health study. Eur. Respir. J. 2005, 25, 1011–1017. [Google Scholar] [CrossRef]
- Kolahian, S.; Leiss, V.; Nurnberg, B. Diabetic lung disease: Fact or fiction? Rev. Endocr. Metab. Disord. 2019, 20, 303–319. [Google Scholar] [CrossRef]
- Singh, S.; Bodas, M.; Bhatraju, N.K.; Pattnaik, B.; Gheware, A.; Parameswaran, P.K.; Thompson, M.; Freeman, M.; Mabalirajan, U.; Gosens, R.; et al. Hyperinsulinemia adversely affects lung structure and function. Am. J. Physiol. Lung Cell Mol. Physiol. 2016, 310, L837–L845. [Google Scholar] [CrossRef]
- Clemmer, J.S.; Xiang, L.; Lu, S.; Mittwede, P.N.; Hester, R.L. Hyperglycemia-mediated oxidative stress increases pulmonary vascular permeability. Microcirculation 2016, 23, 221–229. [Google Scholar] [CrossRef] [PubMed]
- Sudy, R.; Schranc, A.; Fodor, G.H.; Tolnai, J.; Babik, B.; Petak, F. Lung volume dependence of respiratory function in rodent models of diabetes mellitus. Respir. Res. 2020, 21, 82. [Google Scholar] [CrossRef]
- Cazzola, M.; Calzetta, L.; Rogliani, P.; Lauro, D.; Novelli, L.; Page, C.P.; Kanabar, V.; Matera, M.G. High glucose enhances responsiveness of human airways smooth muscle via the rho/rock pathway. Am. J. Respir. Cell Mol. Biol. 2012, 47, 509–516. [Google Scholar] [CrossRef]
- Hollenbach, J.; Lopez-Rodriguez, E.; Muhlfeld, C.; Schipke, J. Voluntary activity modulates sugar-induced elastic fiber remodeling in the alveolar region of the mouse lung. Int. J. Mol. Sci. 2019, 20, 2438. [Google Scholar] [CrossRef]
- Adam, M.; Schikowski, T.; Carsin, A.E.; Cai, Y.; Jacquemin, B.; Sanchez, M.; Vierkotter, A.; Marcon, A.; Keidel, D.; Sugiri, D.; et al. Adult lung function and long-term air pollution exposure. Escape: A multicentre cohort study and meta-analysis. Eur. Respir. J. 2015, 45, 38–50. [Google Scholar] [CrossRef] [PubMed]
- Roman, M.A.; Rossiter, H.B.; Casaburi, R. Exercise, ageing and the lung. Eur. Respir. J. 2016, 48, 1471–1486. [Google Scholar] [CrossRef] [PubMed]
- Kahnert, K.; Lucke, T.; Huber, R.M.; Behr, J.; Biertz, F.; Vogt, A.; Watz, H.; Alter, P.; Fahndrich, S.; Bals, R.; et al. Relationship of hyperlipidemia to comorbidities and lung function in copd: Results of the cosyconet cohort. PLoS ONE 2017, 12, e0177501. [Google Scholar] [CrossRef]
- Lee, Y.B.; Kim, Y.S.; Lee, D.H.; Kim, H.Y.; Lee, J.I.; Ahn, H.S.; Sohn, T.S.; Lee, T.K.; Song, J.Y.; Yeo, C.D.; et al. Association between homa-ir and lung function in korean young adults based on the korea national health and nutrition examination survey. Sci. Rep. 2017, 7, 11726. [Google Scholar] [CrossRef] [PubMed]
- Aronson, D.; Roterman, I.; Yigla, M.; Kerner, A.; Avizohar, O.; Sella, R.; Bartha, P.; Levy, Y.; Markiewicz, W. Inverse association between pulmonary function and c-reactive protein in apparently healthy subjects. Am. J. Respir. Crit. Care Med. 2006, 174, 626–632. [Google Scholar] [CrossRef] [PubMed]
Table 1.
Clinical, laboratory, and pulmonary function data in all 7055 study participants.
| Parameters | Baseline | Follow-Up | p-Value | Longitudinal Change |
|---|---|---|---|---|
| Age (year) | 49.5 ± 10.1 | 53.4 ± 10.0 | <0.001 | 3.9 ± 1.3 |
| Systolic blood pressure (mmHg) | 114 ± 16 | 121 ± 18 | <0.001 | 8 ± 14 |
| Body mass index (kg/m2) | 23.7 ± 3.4 | 24.0 ± 3.5 | <0.001 | 0.3 ± 1.3 |
| Fasting blood glucose (g/dL) | 91.8 ± 7.8 | 93.1 ± 11.5 | <0.001 | 1.2 ± 10.3 |
| HbA1c (%) | 5.56 ± 0.34 | 5.70 ± 0.44 | <0.001 | 0.14 ± 0.36 |
| Creatinine (mg/dL) | 0.72 ± 0.28 | 0.71 ± 0.31 | 0.262 | 0.00 ± 0.13 |
| GPT (u/L) | 22.8 ± 18.0 | 22.9 ± 19.3 | 0.608 | 0.1 ± 20.9 |
| Total cholesterol (mg/dL) | 195.6 ± 34.5 | 198.1 ± 35.2 | <0.001 | 2.5 ± 29.1 |
| Triglyceride (mg/dL) | 109.8 ± 81.3 | 114.9 ± 82.2 | <0.001 | 5.1 ± 70.9 |
| Pulmonary function test | ||||
| FVC (L) | 2.89 ± 0.78 | 2.68 ± 0.76 | <0.001 | −0.21 ± 0.33 |
| FVC-predicted (%) | 108.1 ± 20.0 | 114.6 ± 22.8 | <0.001 | 6.5 ± 17.3 |
| FEV1 (L) | 2.42 ± 0.67 | 2.33 ± 0.68 | <0.001 | −0.09 ± 0.37 |
| FEV1-predicted (%) | 111.8 ± 21.6 | 112.1 ± 29.7 | <0.001 | 0.3 ± 27.8 |
| FEV1/FVC (%) | 83.8 ± 6.2 | 87.4 ± 9.9 | <0.001 | 3.6 ± 10.9 |
FVC, forced vital capacity; FEV1, forced expiratory volume in 1 s; GPT, glutamic-pyruvic transaminase; HbA1c, glycated hemoglobin.
Table 2.
Univariable and multivariable linear regression analyses for baseline HbA1c.
| Baseline HbA1c | ||||
|---|---|---|---|---|
| Univariable Analysis | Multivariable Analysis | |||
| Baseline Parameters | Unstandardized Coefficient β (95% CI) | p-Value | Unstandardized Coefficient β (95% CI) | p-Value |
| Age (year) | 0.010 (0.009, 0.011) | <0.001 | 0.005 (0.005, 0.006) | <0.001 |
| Male (%) | 0.036 (0.019, 0.052) | <0.001 | - | |
| Smoking (%) | 0.016 (−0.002, 0.034) | 0.088 | ||
| Systolic blood pressure (mmHg) | 0.004 (0.003, 0.004) | <0.001 | - | |
| Body mass index (kg/m2) | 0.019 (0.017, 0.022) | <0.001 | 0.011 (0.009, 0.013) | <0.001 |
| Fasting blood glucose (g/dL) | 0.017 (0.016, 0.018) | <0.001 | 0.014 (0.013, 0.015) | <0.001 |
| Creatinine (mg/dL) | 0.023 (−0.004, 0.051) | 0.100 | ||
| GPT (u/L) | 0.002 (0.002, 0.003) | <0.001 | 0.001 (<0.001, 0.001) | <0.001 |
| Total cholesterol (mg/dL) | 0.002 (0.002, 0.003) | <0.001 | 0.001 (<0.001, 0.001) | <0.001 |
| Triglyceride (mg/dL) | 0.001 (<0.001, <0.001) | <0.001 | <0.001 (<0.001, <0.001) | 0.008 |
| Pulmonary function test | ||||
| FVC (L) | −0.046 (−0.056, −0.036) | <0.001 | −0.033 (−0.043, −0.024) | <0.001 |
| FEV1 (L) | −0.053 (−0.065, −0.042) | <0.001 | - | |
| FEV1/FVC (%) | −0.001 (−0.002, 0.001) | 0.334 | - | |
CI: confidence interval; other abbreviations as in Table 1.
Table 3.
Univariable and multivariable linear regression analyses for longitudinal changes of HbA1c.
Table 3.
Univariable and multivariable linear regression analyses for longitudinal changes of HbA1c.
| Longitudinal Change of HbA1C | ||||
|---|---|---|---|---|
| Univariable Analysis | Multivariable Analysis | |||
| Longitudinal Changes of Parameters | Unstandardized Coefficient β (95% CI) | p-Value | Unstandardized Coefficient β (95% CI) | p-Value |
| Age (year) | 0.011 (0.004, 0.017) | 0.001 | - | |
| Systolic blood pressure (mmHg) | <0.001 (−0.001, 0.001) | 0.972 | ||
| Body mass index (kg/m2) | 0.037 (0.030, 0.043) | <0.001 | 0.027 (0.022, 0.033) | <0.001 |
| Fasting blood glucose (g/dL) | 0.017 (0.016, 0.017) | <0.001 | 0.016 (0.016, 0.017) | <0.001 |
| Creatinine (mg/dL) | −0.142 (−0.207, −0.076) | <0.001 | −0.173 (−0.231, −0.116) | <0.001 |
| GPT (u/L) | 0.001 (<0.001, 0.001) | <0.001 | - | |
| Total cholesterol (mg/dL) | 0.001 (<0.001, 0.001) | <0.001 | <0.001 (<0.001, 0.001) | 0.023 |
| Triglyceride (mg/dL) | <0.001 (<0.001, <0.001) | <0.001 | <0.001 (<0.001, 0.001) | 0.042 |
| Pulmonary function test | ||||
| FVC (L) | −0.032 (−0.058, −0.007) | 0.013 | −0.025 (−0.048, −0.003) | 0.026 |
| FEV1 (L) | −0.031 (−0.053, −0.008) | 0.008 | - | |
| FEV1/FVC (%) | <0.001 (−0.001, 0.001) | 0.764 | - | |
CI: confidence interval; other abbreviations as in Table 1.
Table 4.
Univariable and multivariable linear regression analyses for longitudinal changes of FVC.
| Longitudinal Change of FVC | ||||
|---|---|---|---|---|
| Univariable Analysis | Multivariable Analysis | |||
| Longitudinal Changes of Parameters | Unstandardized Coefficient β (95% CI) | p-Value | Unstandardized Coefficient β (95% CI) | p-Value |
| Age (year) | −0.017 (−0.023, −0.011) | <0.001 | −0.017 (−0.023, −0.011) | <0.001 |
| Smoking (baseline) | −0.059 (−0.077, −0.042) | <0.001 | −0.059 (−0.077, −0.042) | <0.001 |
| Systolic blood pressure (mmHg) | −0.001 (−0.001, <0.001) | 0.228 | ||
| Fasting blood glucose (g/dL) | 0.001 (−0.001, 0.001) | 0.637 | ||
| HbA1C (%) | −0.027 (−0.049, −0.006) | 0.013 | −0.022 (−0.044, −0.001) | 0.041 |
| Creatinine (mg/dL) | 0.006 (−0.054, 0.060) | 0.842 | ||
| GPT (u/L) | −0.001 (−0.001, <0.000) | 0.048 | −0.001 (−0.001, <0.000) | 0.035 |
| Total cholesterol (mg/dL) | 0.001 (<−0.001, 0.001) | 0.950 | ||
| Triglyceride (mg/dL) | −0.001 (<−0.001, 0.001) | 0.051 | ||
CI: confidence interval; other abbreviations as in Table 1.
Table 5.
Comparison of longitudinal changes of clinical, laboratory, and pulmonary function data between participants with and without newly diagnosed type 2 diabetes mellitus.
Table 5.
Comparison of longitudinal changes of clinical, laboratory, and pulmonary function data between participants with and without newly diagnosed type 2 diabetes mellitus.
| Longitudinal Changes of Parameters | With Newly Diagnosed Type 2 Diabetes Mellitus n = 271 (3.8%) | Without Newly Diagnosed Type 2 Diabetes Mellitus N = 6784 (96.2%) | p-Value |
|---|---|---|---|
| Age (year) | 4.1 ± 1.3 | 3.9 ± 1.3 | 0.086 |
| Systolic blood pressure (mmHg) | 9 ± 15 | 8 ± 14 | 0.193 |
| Body mass index (kg/m2) | 0.4 ± 1.3 | 0.3 ± 1.3 | 0.159 |
| Fasting blood glucose (g/dL) | 16.6 ± 34.8 | 0.6 ± 7.1 | <0.001 |
| HbA1c (%) | 0.92 ± 0.95 | 0.11 ± 0.27 | <0.001 |
| Creatinine (mg/dL) | 0.0 ± 0.1 | 0.0 ± 0.1 | 0.167 |
| GPT (u/L) | 1.8 ± 21.4 | 0.0 ± 20.1 | 0.187 |
| Total cholesterol (mg/dL) | −5.7 ± 40.1 | 2.8 ± 28.6 | <0.001 |
| Triglyceride (mg/dL) | −0.2 ± 120.7 | 5.3 ± 68.1 | 0.211 |
| Pulmonary function test | |||
| FVC (L) | −0.25 ± 0.29 | −0.21 ± 0.33 | 0.028 |
| FVC-predicted (%) | 8.3 ± 14.8 | 6.4 ± 17.4 | 0.071 |
| FEV1 (L) | −0.12 ± 0.31 | −0.09 ± 0.37 | 0.136 |
| FEV1-predicted (%) | 0.0 ± 17.8 | 0.3 ± 28.1 | 0.949 |
| FEV1/FVC (%) | 3.9 ± 9.0 | 3.6 ± 10.9 | 0.613 |
Abbreviations as in Table 1.
Table 6.
Odds ratio of longitudinal changes of parameters in association with newly diagnosed type 2 DM in univariable and multivariable logistic regression analyses.
Table 6.
Odds ratio of longitudinal changes of parameters in association with newly diagnosed type 2 DM in univariable and multivariable logistic regression analyses.
| Newly Diagnosed Type 2 Diabetes Mellitus | ||||
|---|---|---|---|---|
| Univariable Analysis | Multivariable Analysis | |||
| Longitudinal Changes of Parameters | Odds Ratio (95% CI) | p-Value | Odds Ratio (95% CI) | p-Value |
| Age (per 1 year) | 1.084 (0.989, 1.118) | 0.086 | ||
| Systolic blood pressure (per 1 mmHg) | 1.006 (0.997, 1.015) | 0.193 | ||
| Body mass index (per 1 kg/m2) | 1.068 (0.976, 1.169) | 0.155 | ||
| Fasting blood glucose (per 1 g/dL) | 1.102 (1.089, 1.115) | <0.001 | 1.103 (1.090, 1.117) | <0.001 |
| Creatinine (per 1 mg/dL) | 0.379 (0.114, 1.261) | 0.114 | ||
| GPT (per 1 u/L) | 1.003 (0.999, 1.007) | 0.180 | ||
| Total cholesterol (per 1 mg/dL) | 0.991 (0.987, 0.994) | <0.001 | 0.989 (0.985, 0.993) | <0.001 |
| Triglyceride (per 1 mg/dL) | 0.999 (0.997, 1.001) | 0.204 | ||
| Pulmonary function test | ||||
| FVC (per 1 L) | 0.669 (0.467, 0.957) | 0.028 | 0.625 (0.424, 0.922) | 0.018 |
| FEV1 (L) (per 1 L) | 0.791 (0.581, 1.076) | 0.136 | ||
| FEV1/FVC (per 1%) | 1.003 (0.992, 1.014) | 0.612 | ||
CI: confidence interval; other abbreviations as in Table 1.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Lee, W.-H.; Wu, D.-W.; Chen, Y.-C.; Liu, Y.-H.; Liao, W.-S.; Chen, S.-C.; Hung, C.-H.; Kuo, C.-H.; Su, H.-M. Association of Pulmonary Function Decline over Time with Longitudinal Change of Glycated Hemoglobin in Participants without Diabetes Mellitus. J. Pers. Med. 2021, 11, 994. https://doi.org/10.3390/jpm11100994
AMA Style
Lee W-H, Wu D-W, Chen Y-C, Liu Y-H, Liao W-S, Chen S-C, Hung C-H, Kuo C-H, Su H-M. Association of Pulmonary Function Decline over Time with Longitudinal Change of Glycated Hemoglobin in Participants without Diabetes Mellitus. Journal of Personalized Medicine. 2021; 11(10):994. https://doi.org/10.3390/jpm11100994
Chicago/Turabian StyleLee, Wen-Hsien, Da-Wei Wu, Ying-Chih Chen, Yi-Hsueh Liu, Wei-Sheng Liao, Szu-Chia Chen, Chih-Hsing Hung, Chao-Hung Kuo, and Ho-Ming Su. 2021. "Association of Pulmonary Function Decline over Time with Longitudinal Change of Glycated Hemoglobin in Participants without Diabetes Mellitus" Journal of Personalized Medicine 11, no. 10: 994. https://doi.org/10.3390/jpm11100994
APA StyleLee, W.-H., Wu, D.-W., Chen, Y.-C., Liu, Y.-H., Liao, W.-S., Chen, S.-C., Hung, C.-H., Kuo, C.-H., & Su, H.-M. (2021). Association of Pulmonary Function Decline over Time with Longitudinal Change of Glycated Hemoglobin in Participants without Diabetes Mellitus. Journal of Personalized Medicine, 11(10), 994. https://doi.org/10.3390/jpm11100994
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
