A student’s t-test determined between-group differences in cross-sectional characteristics for continuous data with a normal distribution and non-normal distribution data after log-transformation. The chi-squared test was used for dichotomous and categorical data. Multiple logistic regression models were applied to assess the multivariable associations between diabetes and pulmonary function parameters. Where there was evidence of nonlinearity in Kernel-weighted local polynomial smoothing, a two-line piecewise linear model with a single change point was estimated by trying all possible values for the change point and choosing the value with the highest likelihood. Then, we applied a restricted cubic spline with three knots to explore the non-linear association. The first and last knots were placed at the step 1%- and 99%-point of the examined parameters, respectively, and the middle knot was placed at the point chosen by the two-line piecewise linear model. It should be emphasized that we included all participants in the analysis of nonlinearity. Partial mediation was assessed using the percent mediation calculated as the relative change in FEV1 and FVC associated with the occurrence of diabetes between the baseline model and the adjusted model (also called percent change [PC]) .
A two-sided p-value < 0.05 was considered statistically significant. All analyses were weighted to represent the US population and to account for the intricate survey design and performed in STATA (15.0) STATA Corporation, College Station, TX, USA).
Cross-sectional qualities of the players
The main clinical and pulmonary data of the 8584 participants who were eligible for this cross-sectional study according to the presence of glucose abnormalities are displayed in Table 1. The weighted proportions of prediabetes and diabetes were 29.5% and 10.1%, respectivelypared to participants with normal glucose metabolism, those with prediabetes and diabetes were significantly older and more likely to be male, Mexican American, and non-Hispanic Black, with a lower educational level, physically inactive, and with a greater average BMI. The ratio of current smokers did not differ between the groups. Regarding pulmonary function, participants with prediabetes and diabetes showed significantly lower FEV1 and FVC measurements than the controls. This progressive association persisted after adjustment for confounding variables such as age, sex, race, educational level, physical activity (MET score), smoking status, BMI and WC (Additional file 1: Table S1). Finally, once supplementary adjustments for C-reactive protein (CRP) and insulin resistance were performed, participants with diabetes continued to show significantly decreased FEV1 and FVC values, reinforcing the potential role of other mechanisms underlying this negative association.
After adjustment for age, sex, race, education, smoking, physical activity, BMI, and WC, associations between HbA1c and FEV1, as well as FVC, were L-shaped (Fig. 1). The change points for FEV1 and FVC were estimated to be approximately 7%. When participants with diabetes were classified according to their HbA1c value, the negative association between HbA1c and FEV1 [? 7.23 (? to ? 3.29)] and FVC [? 5.31 (? 8.65 to ? 1.97)] existed only in those with good metabolic control (HbA1c < 7.0%) (Additional file 1: Table S2). A similar non-linear association was also found in FPG as well as 2 h-PG.
Non-linear association between plasma glucose, insulin resistance, CRP and pulmonary function in participants without pulmonary comorbidities. Data were weighted estimates. The shadow area represents a 95% confidence interval. Pnon-linear was estimated by a two-line piecewise linear model. The model was adjusted for age, sex, race, education, smoking, physical activity, BMI and waist circumference
Furthermore, we found a non-linear association between insulin resistance and pulmonary function in FVC and borderline significance in FEV1, but not in FEV1/FVC ratio. The non-linear association between CRP and pulmonary function also existed with a change point estimated at 0.14 mg/dL.