Association between insulin resistance and lung function change: Analysis from the community-based prospective Ansan-Ansung cohort in Korea

Background: Diabetes mellitus and hyperglycemia are associated with respiratory dysfunction. Although several studies have reported that insulin resistance is related to decreased lung function, the association between insulin resistance and lung function changes has been rarely studied. This study aimed to investigate the effect of insulin resistance on the annual lung function change using a large-scale prospective cohort. Methods: We analyzed a community-based prospective cohort in Korea comprising 7,536 participants whose serial lung functions were assessed. Exposure was baseline insulin resistance estimated with homeostatic model assessment-insulin resistance (HOMA-IR), and outcomes were annual changes in forced expiratory volume in 1 second (FEV1), functional vital capacity (FVC), and FEV1/FVC ratio. Results: In the multivariate linear regression, the increased in the logarithmic HOMA-IR was associated with a decrease in FEV1 (β: -0.23; 95% CI: -0.32 to -0.13; P < 0.001), and FVC (β: -0.29; 95% CI: -0.39 to -0.19; P < 0.001), but not in FEV1/FVC ratio (β: 0.05; 95% CI: 0.00 to 0.11; P = 0.051). In the generalized additive model plot, L-shaped association between HOMA-IR and changes in FEV1 and FVC were observed with a HOMA-IR threshold of 2.4. Age modulated the effect of HOMA-IR on the change in FEV1, and increased HOMA-IR was associated with decreased annual FEV1 change only in the older population. Conclusions: Insulin resistance was a novel risk factor for the decrease in FEV1 and FVC. The aging process may modulate the effect of insulin resistance on the decline in lung function. are expressed as mean ± standard deviation for normally distributed continuous variables, median and interquartile range for non-normally distributed variables and percentage for categorical variables. P-trend was analyzed normally distributed continuous variables by the linear regression, for non-normally distributed continuous variable by Jonckheere-Terpstra tests, and for categorical variables by Cochran-Armitage test for trend. *, †, and ‡ P < 0.05 when compared to < 1.05, 1.06–1.45, 1.45–2.03 groups of HOMA-IR, respectively, using Bonferroni post-hoc analysis of one-way ANOVA for normally distributed continuous variables, Mann-Whitney U tests for non-normally distributed continuous variable, and chi-square tests for categorical variables. Abbreviations: HOMA-IR, homeostatic model assessment for insulin resistance; BMI, body mass index; blood


Background
Diabetes mellitus is a prevalent chronic disease in modern society, with many experiencing diabetes and its complications [1,2].Lung function decline has been considered a major complication of diabetes [3][4][5].Several studies have found that diabetes and hyperglycemia are associated with the development of various pulmonary diseases, including chronic obstructive pulmonary disease, asthma, and interstitial lung disease [6][7][8].Therefore, good control of diabetes may prevent future lung diseases.
Increased insulin resistance has been associated with the future development of obesity, diabetes [9], cardiovascular diseases [10], neurologic impairment [11], and kidney dysfunction [12].Although several studies have reported the potential association between insulin resistance and decreased lung function, none of these studies have evaluated the longitudinal effect of insulin resistance on future lung function changes.The aging process can cause diverse physiological, immunological and structural changes in the respiratory system [13,14].Thus, analyzing consecutive measurements of lung function may help to interpret the effects of aging on insulin resistance and lung function changes.In addition, it can clarify a causal association between insulin resistance and lung function.
Since diabetes is associated with a future decline in lung function and insulin resistance is a fundamental pre-condition of diabetes, we hypothesized that increased insulin resistance may be associated with future decline in lung function.Therefore, this study aimed to investigate the association between insulin resistance and lung function change using data from a community-based prospective Ansan-Ansung cohort in Korea.

Participants
The Ansan-Ansung cohort comprise participants aged 40-69 years who lived in Ansan (urban) and Ansung (rural) areas, and this cohort was analyzed to determine the factors affecting the incidence of chronic diseases.Baseline measurements were performed between May 2001 and February 2003, and two subsequent lung function tests were performed biennially thereafter.More detailed information about the Ansan-Ansung cohort can be obtained in previous reports [15].Of the 10,030 participants, we excluded 134 missing smoking status, 188 missing socioeconomic status, and 316 missing metabolic disorders.Of the 9,392, participants, 1,856 with missing additional lung function test results were further excluded.Therefore, 7,536 participants were nally included in this analysis (Fig. 1).

Outcomes: Changes in lung function test
Lung function tests were performed using a spirometer (VMAX2130; Sensormedics Corporation, Yorba, CA, USA).Pre-bronchodilator values were measured 3 times by trained technicians and the best scores were recorded.Predicted values of functional vital capacity (FVC) and functional expiratory volume in 1 second (FEV1) were calculated using the Korean formula [17].The FEV1/FVC ratio was expressed as the percentage of FEV1 divided by FVC.Study outcomes were annual changes in FEV1, FVC, and FEV1/FVC ratio.These values were determined by calculating the regression coe cient using a least-square linear regression analysis, with FEV1, FVC, and FEV1/FVC ratio as functions of time in years.It was applied to all values of FEV1, FVC, and FEV1/FVC ratio that were obtained during the follow-up period.

Measurements and other de nitions
Trained investigators interviewed participants regarding their socioeconomic status and lifestyle habits using KoGES Baseline Core Questionnaire.High income was de ned as the highest quintile of monthly household income (≥ 3 million won a month).Blood pressure (BP) was de ned as the average BP on both arms using a standard mercury sphygmomanometer (Baumanometer-Standby; W. A. Baum Co., Inc., Copiague, NY, USA).Body mass index (BMI) was de ned by dividing the weight by the square of the height (kg/m 2 ).Waist circumference was measured at the narrowest point between the lower rib and the iliac crest (measured to the nearest 0.1 cm).All blood samples were examined after fasting for at least 8 hours.Hemoglobin level and white blood cell (WBC) count were analyzed using enzymatic methods with ADVIA 120 (Bayer Diagnostics, Tarrytown, NY, USA).Fasting glucose, hemoglobin A 1 c (HbA 1 c), triglyceride, high density lipoprotein (HDL) cholesterol, C-reactive protein (CRP), and serum creatinine levels were measured using ADVIA 1650 (Siemens, Tarrytown, NY, USA).Estimated glomerular ltration rate (eGFR) was de ned using the Chronic Kidney Disease Epidemiology Collaboration equation [18].

Statistical analyses
Normality of distribution of continuous variables was assessed using histogram and Q-Q plots.Mean ± standard deviation (SD) was used to express normally distributed continuous variables, whereas median with interquartile range (IQR) was used for non-normally distributed continuous variables.The P trend was analyzed using linear regression for the normally distributed continuous variables, the Jonckheere-Terpstra test for the non-normally distributed continuous variables, and the Cochran-Armitage test for categorical variables.
The simple associations between HOMA-IR and spirometric parameters were expressed using the locally weighted scatterplot smoothing (LOWESS) function.In multivariate analyses, covariates were chosen based on clinical and statistical relevance.The non-linear association between HOMA-IR and changes in FEV1 and FVC was analyzed using the multivariate generalized additive model (GAM) for Gaussian distributions with the "mgcv" package, and calculation of Akaike information criterion (AIC) was used for the model tting.In AIC, lower scores within the data set indicate a better model t [19].The threshold point of HOMA-IR was chosen based on the best t determined by AIC among the models.
In the subgroup analysis, clinically signi cant variables were chosen, and participants were divided by the median of variables.The modulatory effect was con rmed by adding the interaction term of variables de ning the subgroup to the multivariate linear regression analysis.To visualize potential interaction of age on the association between insulin resistance and annual lung function change, the LOWESS regression with interaction was implemented using the "predict3d" package.A P value < 0.05 was considered statistically signi cant.All statistical analyses were performed using R version 3.6.2(R Core Team 2019; R Foundation for Statistical Computing, Vienna, Austria).
The clinical characteristics of the study population according to HOMA-IR quartile are shown in Table 1.Although age was not associated with HOMA-IR quartile, increased HOMA-IR quartile was associated with decreased proportion of men.Although income and educational status were not associated with HOMA-IR quartile, increased HOMA-IR quartile was associated with a decreased rate of current or past smoking.With the increase of HOMA-IR quartile, BMI, systolic and diastolic BP, waist circumference, WBC count, and fasting glucose, HbA 1 c, triglyceride, hemoglobin, and CRP levels increased, whereas HDL cholesterol levels decreased.With the increase of HOMA-IR quartile, baseline percent-predicted FEV1 and percentpredicted FVC decreased, but FEV1/FVC increased.We explored the association between HOMA-IR and annual changes in lung function test (Fig. 2).As HOMA-IR increased, annual FEV1 and FVC change decreased, whereas annual FEV1/FVC ratio change increased.Although the negative association between HOMA-IR and annual changes in FEV1 and FVC was statistically signi cant, the association between HOMA-IR and FEV1/FVC ratio was nulli ed in the multivariate linear regression analysis (Table 2).In the multivariate GAM plot analysis, we identi ed that the association between HOMA-IR and annual change in FEV1 and FVC was L-shaped, and the lowest AICs were found in HOMA-IR 2.4, in both annual FEV1 and FVC (Fig. 3).There were no subgroups showing the effect modi cation between HOMA-IR and annual FVC change.However, participant age signi cantly modi ed the effect of HOMA-IR on annual FEV1 change (P for interaction < 0.001).Although HOMA-IR was not associated with annual FEV1 change in people aged < 50 years, increased HOMA-IR was signi cantly associated with decreased annual FEV1 change in individuals aged ≥ 50 years (Table 3).We also identi ed similar effect modi cation of age on the association between HOMA-IR and annual FEV1 change in the LOWESS regression plot with interaction (Fig. 4).

Discussion
Recently, decreased lung function has been suggested as a complication of insulin resistance.In their large-scale cross-sectional study, Lawlor et al. found that HOMA-IR decreased by 5% and 8% for a 1 SD increase in log FEV1 and FVC, respectively [20].Sagun et al. also showed that decreased percentpredicted FEV1 was correlated with increased insulin resistance (HOMA-IR ≥ 2.5) in an age-adjusted analysis (OR 0.97, 95% CI 0.94-1.00,P = 0.028) [21].However, most previous studies were crosssectional, and a causal association between insulin resistance and decreased lung function needed to be evaluated in a prospective cohort.Therefore, we conducted the current study using a prospective community-based cohort and found that increased insulin resistance was associated with a decline in lung function, particularly in the elderly population.
In the current study, we found that increased baseline HOMA-IR was associated with a decrease in FEV1 and FVC, but not in FEV1/FVC ratio, in the multivariate analysis after adjusting for possible confounders.
We also found an L-shaped association between HOMA-IR and annual changes in FEV1 and FVC using the multivariate GAM plot, and the suggested threshold of HOMA-IR for lung function decline was 2.4.As a surrogate marker of insulin resistance, several studies have shown that the cutoff value of HOMA-IR for the risk of developing type 2 diabetes mellitus and metabolic syndrome in the Korean population is approximately 2.5 [22][23][24].Our ndings, consistent with those of previous studies, indicated that a decline in lung function may be metabolic complication due to the systemic effects of insulin resistance.
There were two possible explanations for the potential pulmonary hazard of insulin resistance.First, chronic low-grade in ammation in adipose tissue contributes to the development of insulin resistance [25,26].Levels of cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6, are increased with insulin resistance and cause lung brosis and in ammation [27,28].Second, respiratory muscle weakness is related to insulin resistance.With insulin resistance, TNF-α and interferon-gamma cause muscle wasting through the degeneration of myotubes and modulation of myogenesis [29,30].
In subgroup analysis, age showed a statistically signi cant effect modi cation on the association between HOMA-IR and annual change in FEV1.Although HOMA-IR was not associated with annual change in FEV1 in the younger group, increased HOMA-IR was signi cantly related to decreased FEV1 in the older group (P for interaction < 0.001).
Insulin resistance is associated with chronic low-grade in ammation [25].The risk of chronic low-grade in ammation increased with the aging process [31,32].Lung function can decline with increased in ammation [33,34].Therefore, we assumed that increased chronic low-grade in ammation during the aging process may potentiate the metabolic hazard of insulin resistance in lung function decline.In this regard, early intervention to reduce insulin resistance in the elderly population may have a bene cial effect on future lung function preservation.
Several limitations should be considered when interpreting our ndings.First, two or fewer additional lung function measurements were performed in this study.Therefore, the rate of change in FEV1 and FVC only re ects short-term changes in lung function.Further studies performing more spirometric tests will be needed to clarify the long-term effect of insulin resistance on lung function.Second, our study was conducted in single ethnicity and selected areas.Therefore, the results should be elucidated cautiously in accordance with racial and regional differences.Despite these limitations, our study has several strengths.First, to the best of our knowledge, this is the rst study to investigate the association between insulin resistance and lung function using a large-scale prospective cohort based on the general population.Second, we calculated the threshold of HOMA-IR for lung function decline using a nonlinear analytic method.Finally, the interaction between age and insulin resistance to lung function changes was investigated and presented using visualization.
In conclusion, increased insulin resistance was independently associated with a decrease in FEV1 and FVC, particularly in the older population.The potential pulmonary hazard of insulin resistance needs to be con rmed in future interventional studies

Table 1
Clinical characteristics of the study population according to HOMA-IR quartile.
1.06-1.45,1.45-2.03groups of HOMA-IR, respectively, using Bonferroni post-hoc analysis of one-way ANOVA for normally distributed continuous variables, Mann-Whitney U tests for non-normally distributed continuous variable, and chi-square tests for categorical variables.Abbreviations: HOMA-IR, homeostatic model assessment for insulin resistance; BMI, body mass index; BP, blood pressure; HbA 1 c, hemoglobin A 1 c; HDL, high density lipoprotein; eGFR, estimated glomerular ltration rate; WBC, white blood cell; CRP, C-reactive protein; FEV1, forced expiratory volume in 1 second; FVC, functional vital capacity.Values are expressed as mean ± standard deviation for normally distributed continuous variables, median and interquartile range for non-normally distributed variables and percentage for categorical variables.P-trend was analyzed normally distributed continuous variables by the linear regression, for non-normally distributed continuous variable by Jonckheere-Terpstra tests, and for categorical variables by Cochran-Armitage test for trend.*, †, and ‡ meant P < 0.05 when compared to < 1.05, 1.06-1.45,1.45-2.03groups of HOMA-IR, respectively, using Bonferroni post-hoc analysis of one-way ANOVA for normally distributed continuous variables, Mann-Whitney U tests for non-normally distributed continuous variable, and chi-square tests for categorical variables.Abbreviations: HOMA-IR, homeostatic model assessment for insulin resistance; BMI, body mass index; BP, blood pressure; HbA 1 c, hemoglobin A 1 c; HDL, high density lipoprotein; eGFR, estimated glomerular ltration rate; WBC, white blood cell; CRP, C-reactive protein; FEV1, forced expiratory volume in 1 second; FVC, functional vital capacity.

Table 2
Association between log-transformed HOMA-IR and the annual lung function change., age and sex were added as covariates.Model 2 included high income, college graduate, smoking status, BMI, waist circumference, systolic and diastolic BP, triglyceride, HDL cholesterol, eGFR, WBC count, hemoglobin and CRP levels in addition to the covariates in the model 1.

Table 3
Subgroup analysis for the effects of HOMA-IR on the annual rates of changes in FEV1 and FVC.