"Observing Pulmonary Function Disparities in Diabetes Patients from Demographic and Hormonal Perspectives: A Study Based on NHANES Database"

"Observing Pulmonary Function Disparities in Diabetes Patients from Demographic and Hormonal Perspectives: A Study Based on NHANES Database" | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article "Observing Pulmonary Function Disparities in Diabetes Patients from Demographic and Hormonal Perspectives: A Study Based on NHANES Database" Jianyang Wu, Yuyuan Lin, Jianxin Xu, Jie Pan, Mengxin Lin, Zhiyang Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4763867/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Diabetes is a global public health issue commonly associated with various complications, including impaired lung function. Existing studies suggest that the relationship between diabetes and lung function varies significantly across age, racial, and gender groups. However, specific differences in lung function within these demographic characteristics have not been thoroughly investigated. This study aims to explore lung function disparities among diabetic patients using data from the 2009–2012 NHANES. Methods Data from 2009–2012 NHANES were analyzed, including 8087 participants with valid physical measurements and lung function data, of which 984 were diabetic. Multivariate linear regression was employed to assess the effects of factors such as age, gender, race, BMI, and smoking on lung function indicators (peak expiratory flow (PEF), forced expiratory volume in one second (FEV1), and forced vital capacity (FVC)). Additionally, lung function was compared between male diabetic patients with different testosterone levels and postmenopausal female diabetic patients using hormone therapy. Results The study found significant disparities in lung function among diabetic patients across different racial, age, and gender groups. Specifically, in terms of race, Black diabetic patients exhibited poorer lung function compared to White and Mexican American patients, particularly in FEV1 and FVC indices. Regarding age, participants under 50 showed higher PEF, FEV1, and FVC than those over 50. Gender-wise, males had higher PEF, FEV1, and FVC than females. Male diabetic patients with testosterone levels ≥ 16 ng/dL had significantly better lung function indicators than those with testosterone levels < 16 ng/dL, notably in FEV1 and FVC (P < 0.001). Postmenopausal female diabetic patients using hormone therapy showed significant improvement in lung function. Specifically, those using estrogen and progesterone therapy exhibited marked improvement in FVC (P = 0.024). Conclusion This study reveals significant impacts of gender, race, and hormone levels on lung function among diabetic patients, providing new insights for personalized treatment. Male patients and postmenopausal female patients using hormone therapy demonstrated better lung function, suggesting the potential consideration of testosterone and estrogen supplementation in clinical treatment. These findings underscore the importance of addressing gender and racial disparities in medical research, promoting more precise and effective medical practices. Diabetes mellitus Lung function Testosterone levels Hormone therapy Public health NHANES Figures Figure 1 Figure 2 Figure 3 Introduction Diabetes is a prevalent chronic disease affecting millions of people worldwide. In recent years, the global impact of diabetes has been expanding at an unprecedented rate. According to the World Health Organization, approximately 415 million adults globally have diabetes, a number that is expected to increase to over 700 million by 2025[ 1 ]. Diabetes not only affects blood sugar levels but is also closely associated with reduced lung function. Several cross-sectional studies have shown that compared to non-diabetic individuals, those with diabetes have lower FVC and FEV1[ 2 – 5 ]. This indicates that the negative impact of diabetes on the respiratory system may be more severe than previously anticipated. These data demonstrate that diabetes is not only a metabolic disease but also a systemic condition that significantly affects lung function. The rapid increase in the global diabetic population, coupled with the emerging complex relationship between diabetes and lung function, underscores the urgent need to delve deeper into this area. This is essential for developing more precise and effective treatment and prevention strategies. Although the exact mechanisms linking diabetes and lung function are still unclear, the relationship remains crucial due to its potential epidemiological and clinical implications. The rising incidence of diabetes, obesity, smoking, and heart failure can cumulatively and significantly impair lung function, leading to increased morbidity and mortality rates associated with poor lung function on a population level [ 6 ]. Several epidemiological and clinical studies have reported reduced lung function in adults with diabetes compared to non-diabetic adults. The decline in lung function among diabetic patients appears to be negatively correlated with blood glucose levels, diabetes duration, and severity and is independent of smoking status or obesity [ 2 , 4 , 7 – 11 ]. Although existing studies have initially revealed the negative impact of diabetes on lung function and its variations across race, age, and gender, most of these studies focus on single factors. They often lack a comprehensive analysis considering multiple demographic characteristics, lifestyle factors, and disease states. Therefore, this study aims to systematically evaluate the impact of diabetes on lung function across different races, ages, and genders by analyzing data from the NHANES database. Gender and hormone levels play an essential role in regulating respiratory system function. Testosterone and estrogen significantly impact lung function by influencing airway smooth muscle tone and pulmonary surfactant production [ 12 , 13 ]. There are differences in lung function between males and females, with males typically having higher PEF, FVC, and FEV1. Additionally, postmenopausal women may experience further reductions in lung function due to declining estrogen levels. However, the specific manifestations of these gender and hormone level differences in diabetic patients remain unclear. Racial differences are also important factors influencing diabetes and lung function. There are significant disparities in diabetes prevalence and complications among different racial groups. The differences in diabetes-related lung function decline among Black, White, and Mexican American populations have not been adequately studied. This study aims to systematically evaluate the impact of diabetes on lung function across different races, ages, genders, and hormone levels by deeply analyzing large-scale data from the NHANES database. Our goal is to fill gaps in existing research, provide a scientific basis for personalized treatment of diabetic patients, and offer strong support for the formulation of public health policies. Materials and Methods Data Source The NHANES database is a nationwide cross-sectional study aimed at assessing the health and nutritional status of the non-institutionalized U.S. population. These data are collected from a complex, multi-stage, stratified, clustered probability sample that ensures high representativeness of health-related data across the United States. Data were obtained through face-to-face interviews, mobile examinations, and laboratory tests. We selected NHANES data from 2009–2012, as consistent lung function tests were used during this period. The NHANES protocol was reviewed and approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all participants provided written informed consent. The public data used in our analysis can be accessed at https://www.cdc.gov/nchs/nhanes/ . Study Population The study included data from two cross-sectional cycles of NHANES (2009–2012). Out of 20293 participants aged 1 year or older, 8641 were excluded due to missing data on physical measurements, lung function tests, or total cholesterol (TCHOL) tests. We further excluded 3391 individuals as our study focused on non-pregnant adults aged 20 years and older. Additionally, 174 participants were excluded due to missing diabetes data. Ultimately, 8087 participants with complete data were included for quantitative analysis (Fig. 1 ). Variable Measurements and Definitions Diabetes was diagnosed based on the American Diabetes Association (ADA) criteria[ 14 ] and self-reported questionnaire responses. The criteria included: fasting blood glucose ≥ 7 mmol/L (125 mg/dL), a self-reported physician diagnosis of diabetes, or current use of diabetes medications to lower blood glucose levels. During the 2009–2012 NHANES period, spirometry was conducted on participants aged 6 to 79 years, excluding those with current chest pain, physical problems with forced exhalation, use of supplemental oxygen, recent eye, chest, or abdominal surgery, recent heart attack, stroke, tuberculosis exposure, coughing up blood, retinal detachment, lung collapse, or aneurysm history. Spirometry followed standard protocols using a dry-rolling seal spirometer (Ohio 822/827; Ohio Medical Instruments, Cincinnati, OH, USA). Participants were required to provide three acceptable maneuvers. For this study, we used only pre-bronchodilator spirometry data of quality A (exceeds American Thoracic Society data collection standards) or B (meets American Thoracic Society data collection standards). Predicted lung function was calculated using NHANES III equations [ 15 ]. Total testosterone was analyzed using ID-HPLC/MS/MS, which employs a triple quadrupole mass spectrometer with electrospray ionization in positive ion mode. Current smokers were defined as participants aged 20 years or older who reported smoking occasionally or daily in the past 7 days or had smoked over 100 cigarettes in their lifetime [ 16 ]. Alcohol consumption categories were defined as follows: current heavy drinking (≥ 3 drinks per day for women, ≥ 4 drinks per day for men, or binge drinking [≥ 4 drinks for women, ≥ 5 drinks for men on a single occasion] for ≥ 5 days per month); current moderate drinking (≥ 2 drinks per day for women, ≥ 3 drinks per day for men, or binge drinking ≥ 2 days per month); all other cases were classified as light drinking [ 17 ]. Statistical Analysis All analyses used weighted samples to account for the complex survey design, ensuring estimates representative of the U.S. population. A four-year weight variable was created to provide estimates over the four years by taking half of the two-year weights assigned to each person sampled from 2009 to 2012. All analyses were conducted using RStudio version 2023.10.31 and R version 4.3.2 for Mac. We employed linear regression to compare lung function indicators between diabetic and non-diabetic participants, adjusted for race, age, and gender, and to obtain mean values and comparisons of lung function among diabetic patients across different gender, age, and racial groups. The frequency distribution of lung function indicators adjusted for age and gender was obtained across different racial groups. We also compared lung function between male diabetic patients with different testosterone levels and postmenopausal female diabetic patients using hormone therapy. Results Baseline Characteristics of Participants Table 1 presents the weighted baseline characteristics of participants selected from the 2009–2012 NHANES who had valid physical measurements and lung function data. The 8087 NHANES participants represented 25.5 million non-institutionalized U.S. residents, stratified by the presence of diabetes. The analysis included 984 diabetic patients with a mean age of 56.92 ± 12.61 years, of whom 53.03% were male and 46.97% were female. The non-diabetic group comprised 7103 individuals with a mean age of 43.92 ± 15.10 years, 49.78% male and 50.22% female. Significant differences were observed between the diabetic and non-diabetic groups in terms of age, race, BMI, waist circumference, smoking, alcohol consumption, PEF, FEV1, FVC, total cholesterol, physical activity, and hypertension (p < 0.05). Table 1 Weighted baseline characteristics of participants No Diabetes (n = 7103) Diabetes (n = 984) P-trend Age (y) 43.92 (15.10) 56.94 (12.61) < 0.001 Gender (%) 0.150 Male 49.78 53.03 Female 50.22 46.97 Ethnicity (%) < 0.001 Mexican American 8.24 10.59 Non-Hispanic White 68.67 58.80 Non-Hispanic Black 10.24 16.08 BMI (kg/cm2) 28.14 (6.19) 33.06 (6.85) < 0.001 Height (cm) 169.48 (9.90) 168.12 (10.07) 0.015 Waist circumference (cm) 81.09 (20.05) 93.61 (21.78) < 0.001 Current smoker (%) 43.23 51.26 0.002 Alcohol (%) < 0.001 mild 59.17 74.42 moderate 24.78 17.07 Heavy 16.05 8.51 PEF (mL/s) 8431.45 (2189.37) 7429.84 (2250.745) < 0.001 FEV1 (mL) 3272.40 (893.51) 2659.09 (834.13) < 0.001 FVC (mL) 4188.07 (1077.06) 3492.42 (1034.11) < 0.001 TCHOL (mg/dL) 197.44 (39.79) 187.00 (47.14) < 0.001 Hypertension (%) < 0.001 yes 22.86 66.03 no 77.04 33.93 BMI, body mass index; PEF, peak expiratory flow; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; TCHOL, Total Cholesterol. All values are presented as proportion (%), or mean ± standard deviation. Prevalence of Diabetes Multivariable logistic regression analysis was conducted to estimate the prevalence of diabetes adjusted for age, gender, and race (Appendix Table 1). Compared to White participants, Black and Mexican American participants were more likely to have diabetes (P < 0.001): 13.3% of Black participants, 7.7% of White participants, and 11.1% of Mexican American participants. Males were also more likely to have diabetes than females (P = 0.02). The prevalence of diabetes was lower during adolescence, below 8% from ages 20 to 45, and increased with age, peaking around 60 years. Comparison of Lung Function Indices between Diabetic and Non-Diabetic Participants Using multiple linear regression, we compared the age and gender-adjusted mean PEF, FEV1, and FVC between diabetic and non-diabetic participants (Table 2 ). Diabetes had the greatest impact on lung function indices among White participants, a lesser impact among Black participants, and the smallest impact among Mexican American participants. In Model 1 adjusted for age, race, and gender, diabetic patients showed overall lower mean PEF, FEV1, and FVC compared to non-diabetic patients (598.1 mL, P < 0.001; 308.2 mL, P < 0.001; 412.3 mL, P < 0.001, respectively). Model 2, which additionally adjusted for body mass index, total cholesterol, smoking status, alcohol consumption, physical activity, and hypertension, yielded results consistent with Model 1. Regarding gender, male diabetic patients exhibited a more significant decline in lung function compared to female diabetic patients (Appendix Table 2 ). In terms of age, diabetic patients over 50 years old showed a more pronounced decline in lung function compared to those under 50 years old (Appendix Table 2 ). Table 2 Comparative mean PEF, FEV1 and FVC in diabetics and non-diabetics. Variable Diabetics Non diabetics Mean Difference P Value PEF, mL/s Black 6925.9 (6635.6–7216.2) 7981.9 (7833.8–8130.0) 431.5 (134.0–728.9) 0.009 White 7440.9 (7116.8–7765.0) 8514.5 (8385.8–8643.2) 814.8 (545.3–1084.3) < 0.001 Mexican-American 7949.7 (7390.6–8508.8) 8566.9 (8428.7–8705.2) 302.6 ((-88.8) − 694.0) 0.141 Model 1 Reference 598.1 (414.7–781.4) < 0.001 Model 2 Reference 563.3 (387.5–739.1) < 0.001 FEV1, mL Black 2360.1 (2261.7–2458.6) 2893.1 (2833.8–2952.3) 214.2 (125.7–302.7) < 0.001 White 2688.4 (2542.8–2834.1) 3333.7 (3282.6–3384.9) 392.5 (280.7–504.2) < 0.001 Mexican-American 2985.9 (2813.1–3158.8) 3376.7 (3335.3–3418.2) 185.3 (74.4–296.3) 0.003 Model 1 Reference 308.2 (235.0–381.4) < 0.001 Model 2 Reference 244.6 (181.1–308.1) < 0.001 FVC, mL Black 3038.6 (2927.0–3150.2) 3610.1 (3542.8–3677.4) 272.9 (174.0–371.8) < 0.001 White 3620.3 (3447.7–3793.0) 4325.5 (4275.2–4375.9) 517.8 (398.2–637.4) < 0.001 Mexican-American 3747.6 (3547.6–3947.6) 4166.5 (4114.7–4218.4) 231.5 (90.9–372.2) 0.003 Model 1 Reference 412.3 (334.5–490.1) < 0.001 Model 2 Reference 331.1 (260.9–401.3) < 0.001 Means (95% CIs) are given from a weighted analysis adjusted for age and gender unless otherwise indicated. Model 1 adjusted age, race and gender. Model 2 adjusted age, race, gender, BMI, TCHOL, smoke, alcohol, physical activity and hypertension. Lifestyle Habits The percentage of diabetic patients adjusted for age and gender was compared among alcohol consumption groups (Appendix Table 3). There were 102, 123, and 1506 Black participants categorized as heavy, moderate, and light drinkers, respectively. For White participants, these numbers were 178, 303, and 2907, and for Mexican American participants, 66, 163, and 1004. Interestingly, the average prevalence of diabetes was lower among heavy and moderate drinkers compared to light drinkers. The association between heavy drinking and diabetes differed significantly from that of light drinking (P = 0.06), while differences among alcohol consumption groups were otherwise not significant. Frequency Distribution of Lung Function Indices in Diabetic Participants For participants with diabetes, the distribution of PEF, FEV1, and FVC indicates minimal differences in PEF, with Mexican American participants showing an advantage in FEV1 followed by White and Black participants. Among Black participants, there is a downward shift in FEV1 and a noticeable upward shift in FVC (Fig. 2 ; Appendix Table 5). Comparison of Lung Function Indices among Diabetic Participants by Race, Gender, and Age We compared average lung function indices among diabetic participants across major racial groups using linear regression (Table 3 ). Among participants aged 50 and younger, there were 34, 24, and 30 male participants for Black, White, and Mexican American groups, respectively, and 147, 108, and 70 male participants aged 50 and older. For female participants, there were 31, 31, and 26 aged 50 and younger, and 103, 121, and 56 aged 50 and older for Black, White, and Mexican American groups, respectively. Compared to Black participants, White participants showed slightly higher mean PEF (mean difference 515.0 mL; P = 0.047), significantly higher FEV1 (328.3 mL; P = 0.001), and higher FVC (581.8 mL; P < 0.001). Compared to Black participants, Mexican American participants exhibited slightly higher mean PEF (1023.8 mL; P = 0.004), significantly higher FEV1 (709.0 mL; P < 0.001), and higher FVC (625.8 mL; P < 0.001). In terms of age, participants aged 50 and younger had higher maximum expiratory flow, FEV1, and FVC compared to those aged 50 and older. Regarding gender, males exhibited higher PEF, FVC, and FEV1 compared to females. Appendix Table 4 summarizes these variables across gender and 12 age groups for the three major racial groups. Table 3 Mean Lung Function Values, by Age, Gender, and Ethnic Group* Gender and Age Group PEF, mL/s Blacks Whites Mexican Americans Males < 50 y 8900.7 (7875.1–9926.3) 10133.4‖ (9363.8–10903.0) 9662.5‖ (8669.5–10655.4) Males ≥ 50 y 8174.1 (7793.4–8554.9) 8091.2‖ (7633.1–8549.2) 8584.3‖ (8081.3–9087.3) Females < 50 y 6868.6 (6188.1–7549.1) 6785.1‖ (6327.8–7242.5) 7155.5‖ (6554.7–7756.4) Females ≥ 50 y 5515.4 (5185.0–5845.8) 5974.3‖ (5580.7–6368.0) 5612.8‖ (5093.6–6131.9) All Reference 515.0§ (26.6–1003.4) 1023.8¶ (374.8–1672.8) Gender and Age Group FEV1, mL Blacks Whites Mexican Americans Males < 50 y 3244.7 (2890.4–3598.9) 3884.0§ (3518.8–4249.2) 3653.2‖ (3311.2–3995.3) Males ≥ 50 y 2702.2 (2599.1–2805.2) 2890.1‖ (2693.0–3087.2) 3078.2‡ (2942.0–3214.5) Females < 50 y 2346.9 (2142.5–2551.3) 2795.3¶ (2602.8–2987.8) 2861.1¶ (2695.0–3027.2) Females ≥ 50 y 1883.6 (1766.3–2000.9) 2058.8§ (1983.6–2134.0) 2125.7§ (1963.0–2288.5) All Reference 328.3¶ ( 149.4–507.2) 625.8‡ (427.7–823.9) Gender and Age Group FVC, mL Blacks Whites Mexican Americans Males < 50 y 4034.9 (3662.8–4407.0) 4909.5§ (4479.0–5340.0) 4495.6‖ (4101.4–4889.8) Males ≥ 50 y 3617.6 (3508.4–3726.7) 4049.4‖ (3842.8–4256.1) 4039.9‡ (3831.4–4248.4) Females < 50 y 2869.0 (2637.2–3100.8) 3497.2¶ (3239.3–3755.0) 3452.1¶ (3242.1–3662.2) Females ≥ 50 y 2421.2 (2296.7–2545.7) 2717.3§ (2622.3–2812.3) 2664.7§ (2462.3–2867.1) All Reference 581.8‡ (377.1- 786.5) 709.0‡ (481.7–936.3) * Means (95% CIs) are given from a weighted analysis adjusted for age and gender. ‡P 0.01 to 0.05 compared with black participants. ¶P ≥ 0.001 to = 16 ng/dL showing superior results in FEV1 and FVC (P < 0.001) (Table 4 ). Table 4 Comparative mean PEF, FEV1 and FVC in different testosterone levels. Variable Testosterone, ng/dL P Value =16 PEF, mL/s 7715.0 (6009.3–9420.7) 8463.4 (7973.1–8953.6) 0.372 FEV1, mL 2136.1 (1779.0 -2493.2) 2967.4 (2773.8 -3161.1) < 0.001 FVC, mL 3189.4(3103.3 -3275.4) 4020.2 (3828.9 -4211.6) < 0.001 We also studied postmenopausal female diabetic patients from 2009–2012, categorizing them based on whether they used any form of female hormones such as estrogen and progestin, excluding contraception or infertility treatments. Results indicated significant improvement in FVC among hormone users (P = 0.024)(Fig. 3 ). Discussion Diabetes and impaired lung function are both global public health concerns. Understanding their relationship can provide new insights into the prevention and management of these diseases [ 18 ]. Multiple studies have indicated a declining trend in lung function among adults with type 2 diabetes (T2DM) [ 2 , 4 , 7 – 10 , 19 – 23 ]. However, there remains insufficient research on the specific impact of diabetes on lung function and its variations across different demographic groups. In this study, we particularly focused on three key indices: forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF), After adjusting for age, race, and gender, diabetic patients showed overall lower mean PEF, FEV1, and FVC compared to non-diabetic patients. Regarding demographic characteristics, our report confirms that biological factors influencing the pathophysiology of diabetes vary by race or nationality [ 19 – 26 ]. In this study, we conducted multivariable logistic regression analyses to estimate diabetes prevalence adjusted for age, gender, and race. The results indicated that compared to White participants, both Black and Mexican American participants were more susceptible to diabetes, consistent with findings from a review published in The Lancet[ 26 ], which highlighted significantly higher diabetes diagnosis rates among certain racial and ethnic groups compared to Whites. This phenomenon may be intricately linked to income, education, occupation, housing, food security, social support, and other factors. Additionally, we found that males are more prone to diabetes than females. Moreover, the prevalence of diabetes is lower during adolescence, less than 8% from ages 20 to 45, increasing with age and peaking around 60 years. Current research indicates a higher incidence of diabetes among elderly Black individuals. The findings from population-based analyses for observing age, gender, and racial disparities are consistent [ 24 , 27 ]. We also studied differences in BMI and lifestyle habits related to diabetes prevalence. We found a correlation between higher BMI and diabetes prevalence, consistent with previous studies linking obesity to an increased risk of type 2 diabetes [ 27 – 31 ]. The mechanisms may involve interactions among insulin resistance, inflammation, adipokines, and genetics. Our study suggests that individuals can reduce their risk of diabetes by controlling their weight, thereby enhancing the prevention and management of the disease. Furthermore, smoking was found to be associated with diabetes prevalence, where not only active smokers but also childhood and adulthood exposure to secondhand smoke were linked to higher rates of type 2 diabetes[ 29 ]. Interestingly, our study on alcohol intake revealed that light drinkers had a higher prevalence of diabetes compared to moderate and heavy drinkers, although a study published in 2015 contradicts our conclusion, suggesting a link between heavy drinking and increased diabetes risk [ 30 ]. This contradiction may require consideration of multiple factors such as study design, data sources, sample characteristics, alcohol categorization, adjusted variables, and temporal differences to better understand the disparities between results and provide reasonable explanations. Future studies are needed to validate these findings and explore specific reasons for these differences. Previous meta-analytic studies have found a significant correlation between declining lung function and the incidence of T2DM [ 6 ], consistent with our study's results. We found that lung function indices (FEV1, FVC, PEF) in diabetes patients were significantly lower than in non-diabetic individuals, with older diabetes patients showing more severe declines in lung function indices compared to younger patients, a finding echoed in similar reports [ 11 , 31 ]. Elderly diabetes patients face a higher risk of pulmonary complications. Regarding gender, Males outperformed females in PEF, FVC, and FEV1. Our study of male diabetic patients in 2011–2012 revealed a significant impact of testosterone levels on lung function indices, further analysis indicated that testosterone levels significantly influence lung function in male diabetes patients. Specifically, male patients with testosterone levels ≥ 16 ng/dL exhibited significantly better FEV1 and FVC indices than those with levels < 16 ng/dL (P < 0.001). This suggests that higher testosterone levels may protect lung function in male diabetes patients to some extent. Additionally, we studied postmenopausal female diabetes patients from 2009 to 2012, showing that hormone use significantly improved FVC (P = 0.024). This indicates that hormone therapy with estrogen and progestin post-menopause may help improve lung function in female diabetes patients. Overall, our studies confirm the significant role of sex hormones in pulmonary health, a conclusion supported by previous research [ 12 ]. High levels of testosterone protect lung function by enhancing the strength and endurance of respiratory muscles, such as FEV1 and FVC. These findings provide new perspectives and potential intervention measures for managing lung function in diabetes patients. However, some studies have found a correlation between high testosterone levels and increased risk of certain pulmonary diseases (such as lung cancer), necessitating further research into the effects of testosterone on lung function. Nevertheless, these gender differences also manifest differently across different races. For example, significant FEV1 and PEF differences are observed between White males and females, whereas these differences are relatively minor among Black and Mexican individuals, possibly due to genetic backgrounds, environmental influences, socioeconomic status, cultural habits, and physiological and biological differences. Therefore, based on this study, healthcare professionals can guide more attention and resources toward elderly Black males, targeting disease prevention and management to reduce disease incidence and progression. It is also crucial to consider race and age factors in more personalized healthcare professionals, including providing information on diabetes risk factors, preventive measures, and early identification. This finding also promotes further research to explore the specific reasons and mechanisms for the higher susceptibility to diabetes among elderly Black individuals, seeking more effective prevention and treatment strategies. Overall, these findings can guide clinical practice and public health policies to better prevent and manage diabetes. Secondly, this study also revealed the significant influence of gender and gender-specific hormones on lung function in diabetes patients, which has important social implications. First, these findings provide new insights into the personalized treatment of diabetes patients. In male diabetes patients, those with higher testosterone levels exhibit better lung function, suggesting that testosterone levels could be considered an important indicator in evaluating lung function in clinical practice and even exploring appropriate testosterone supplementation to improve their lung function. Similarly, in postmenopausal female diabetes patients, hormone therapy with estrogen and progestin significantly improves lung function, suggesting consideration of the potential benefits of these hormone therapies in treatment plans. Overall, the impact of diabetes on lung function is a complex and multifactorial process. When discussing the relationship between diabetes and pulmonary abnormalities, this study emphasizes that this relationship is not merely the result of singular factors but rather a complex interplay of various biological, socio-economic, and environmental factors. This complexity is evident in significant differences observed among different races, ages, and genders, highlighting the need for tailored clinical interventions and offering ample exploration opportunities for future research. Furthermore, this study reveals the significant role of gender and gender-specific hormones in lung function among diabetic patients, which constitutes an innovative and practically valuable finding. Future research could further refine this area, such as by longitudinally tracking hormone level changes to observe their dynamic impact on lung function and exploring the effectiveness and safety of different hormone replacement therapies in improving lung function in diabetic patients. Moreover, considering the differences in disease manifestation and treatment response based on gender, clinical practice should prioritize gender-specific assessment and intervention strategies. Although this study offers valuable insights, there are limitations. Firstly, this study relies on self-reported diabetes status, which may introduce reporting biases. Secondly, the cross-sectional nature of NHANES data limits the ability to establish causal relationships. Future research should focus on longitudinal studies to better understand the progression of declining lung function in diabetes patients. Additionally, unmeasured variables may affect the results, warranting further research. Lastly, this study is limited to adults from three major racial groups in the United States, caution should be exercised when extrapolating study results to other populations. Conclusions In summary, this study provides a comprehensive analysis of data from the NHANES database to observe the differences in lung function among diabetic patients from demographic and hormone-level perspectives. It deepens our understanding of the complexity of diabetes-related declines in lung function. Despite certain limitations, this research offers crucial insights for future studies and clinical practice. Future research should further explore the specific mechanisms underlying the relationship between diabetes and lung function, the roles of demographic characteristics and hormones in this relationship, and effective prevention and treatment strategies. Declarations Data availability statement Publicly available datasets were analyzed in this study. This data can be found here: https://www.cdc.gov/nchs/nhanes/index.htm. Author contributions Jianyang Wu and Yuyuan Lin conceived the study, analyzed the data, and drafted the manuscript. Jianyang Wu and Yuyuan Lin contributed equally to this work. Mengxin Lin helped revise the manuscript critically for important intellectual content; Zhiyang Xu, Jie Pan, and Jianxin Xu supervised the project and reviewed the manuscript. All authors approved the final version as submitted, and agree to be accountable for all aspects of the work. Funding Not applicable. Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. The use of NHANES data was approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all data used in this study were anonymized and de-identified prior to analysis. This study does not involve any clinical trials, hence clinical trial registration is not applicable. Publisher’s note All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. References Collaboration NRF. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet (London England). 2016;387(10027):1513–30. AA L, ST RLDSDD. Lung function in type 2 diabetes: the Normative Aging Study. Respir Med. 2005;99(12):1583–90. HC Y, NM P, NY W, JS P, BB D, CE C, FL ES. 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(4):741–6. J PL. Copenhagen City Heart Study: longitudinal analysis of ventilatory capacity in diabetic and nondiabetic adults. Eur Respir J. 2002;20(6):1406–12. RE W, RJ AB, GT G, DJ OC. Association between glycemic state and lung function: the Framingham Heart Study. Am J Respir Crit Care Med. 2003;167(6):911–6. OL K, JA K, S G, LJ S. Systematic review of the association between lung function and Type 2 diabetes mellitus. Diabet medicine: J Br Diabet Association. 2010;27(9):977–87. DA L, GD SE. Associations of measures of lung function with insulin resistance and Type 2 diabetes: findings from the British Women's Heart and Health Study. Diabetologia. 2004;47(2):195–203. HC Y, NM P, NY W, JS P, BB D, FL B. Vital capacity as a predictor of incident type 2 diabetes: the Atherosclerosis Risk in Communities study. Diabetes Care. 2005;28(6):1472–9. RE W, RJ AB, GT G, DJ OC. Association between glycemic state and lung function: the Framingham Heart Study. Am J Respir Crit Care Med. 2003;167(6):911–6. TM D, WA MKPKHV. Reduced pulmonary function and its associations in type 2 diabetes: the Fremantle Diabetes Study. Diabetes Res Clin Pract. 2000;50(2):153–9. Yeh HC, Punjabi NM, Wang NY, Pankow JS, Duncan BB, Cox CE, Selvin E, Brancati FL. 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(4):741–6. EA T, VM M, YS P. Sex differences and sex steroids in lung health and disease. Endocr Rev. 2012;33(1):1–47. YY H, SF EF, E A-P WMLM. Testosterone-to-estradiol ratio and lung function in a prospective study of Puerto Rican youth. Annals allergy asthma immunology: official publication Am Coll Allergy Asthma Immunol. 2021;127(2):236–e242231. Association AD. Standards of medical care in diabetes–2010. Diabetes Care. 2010;33(Suppl 1):S11–61. JL H JR, KB O. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999;159(1):179–87. MM H, DD B-H JEE, JF T, GP R. Prevalence of neutropenia in the U.S. population: age, sex, smoking status, and ethnic differences. Ann Intern Med. 2007;146(7):486–92. DD PR, M PJCAAF, PS PVHS, AA K. Inverse Association of Telomere Length With Liver Disease and Mortality in the US Population. Hepatol Commun. 2022;6(2):399–410. Hsia CC, Raskin P. Lung function changes related to diabetes mellitus. Diabetes Technol Ther. 2007;9(Suppl 1):S73–82. C ALGSXM. Type 2 diabetes impairs pulmonary function in morbidly obese women: a case-control study. Diabetologia. 2010;53(6):1210–6. ES F, DM M, Health N, Study NESEF-u. Prospective association between lung function and the incidence of diabetes: findings from the National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. Diabetes Care. 2004;27(12):2966–70. G E, B H, P N, P W, G B, L J: Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med 2003, 253(5):574–81. V N, DG M, LC R, CC PR. Glycemic control and cardiopulmonary function in patients with insulin-dependent diabetes mellitus. Am J Med. 1997;103(6):504–13. WA D, M K, Study PKVGTMD. Glycemic exposure is associated with reduced pulmonary function in type 2 diabetes: the Fremantle Diabetes Study. Diabetes Care. 2004;27(3):752–7. KF AM, YJ RJF, CC C. Associations between trends in race/ethnicity, aging, and body mass index with diabetes prevalence in the United States: a series of cross-sectional studies. Ann Intern Med. 2014;161(5):328–35. Al-Khlaiwi T, Alsabih AO, Khan A, Habib SH, Sultan M, Habib SS. Reduced pulmonary functions and respiratory muscle strength in Type 2 diabetes mellitus and its association with glycemic control. Eur Rev Med Pharmacol Sci. 2021;25(23):7363–8. Endocrinology TLD. A widening racial and social gap in diabetes. lancet Diabetes Endocrinol. 2021;9(8):471. YJ C, AM K, MRG A, SH S, HS K, EW G, WY F. Prevalence of Diabetes by Race and Ethnicity in the United States, 2011–2016. JAMA. 2019;322(24):2389–98. MI MWAMAK, E I, N S-A M. Homogeneity in the association of body mass index with type 2 diabetes across the UK Biobank: A Mendelian randomization study. PLoS Med. 2019;16(12):e1002982. L ML, B dL-G TGF, MC B-R. F C-C: Childhood and adult secondhand smoke and type 2 diabetes in women. Diabetes Care. 2013;36(9):2720–5. C K. Alcohol Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis of More Than 1.9 Million Individuals From 38 Observational Studies. Diabetes Care. 2015;38(9):1804–12. Y WL, C NYMXLSMBW. Association of lung function and blood glucose level: a 10-year study in China. BMC Pulm Med. 2022;22(1):444. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4763867","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338710009,"identity":"188032e7-c6e5-4b90-86b9-f6e70300f2dc","order_by":0,"name":"Jianyang Wu","email":"","orcid":"","institution":"Department of Thoracic Surgery, The First Hospital of Putian, The School of Clinical Medicine, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianyang","middleName":"","lastName":"Wu","suffix":""},{"id":338710010,"identity":"889e7f23-ce63-46b5-ade6-3a5abb7728f5","order_by":1,"name":"Yuyuan Lin","email":"","orcid":"","institution":"Department of Oncology, Fujian Medical University Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuyuan","middleName":"","lastName":"Lin","suffix":""},{"id":338710011,"identity":"a7ce6a5c-162a-4096-8fc2-66c0744368dd","order_by":2,"name":"Jianxin Xu","email":"","orcid":"","institution":"Department of Thoracic Surgery, The First Hospital of Putian, The School of Clinical Medicine, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jianxin","middleName":"","lastName":"Xu","suffix":""},{"id":338710012,"identity":"c3132f31-1483-4c2a-b2d3-a5cbdb20d81d","order_by":3,"name":"Jie Pan","email":"","orcid":"","institution":"Department of General Surgery (Emergency Surgery), Fujian Medical University Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Pan","suffix":""},{"id":338710013,"identity":"f6028b48-97c0-472a-b518-2a380a05954e","order_by":4,"name":"Mengxin Lin","email":"","orcid":"","institution":"Department of Oncology, Fujian Medical University Union Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mengxin","middleName":"","lastName":"Lin","suffix":""},{"id":338710014,"identity":"9a735ff4-c5a9-45d6-ae38-f2c9aeb4e7ce","order_by":5,"name":"Zhiyang Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYHACNoYEEMXefOBAQoUNDz97A7FaeI4lPnhwJk1GsucAEVrAQMLH2PBhy2EbgxsO+NUb3Eh/9uBhm12efARbmkRiw3kehhsMjB8+5uDWIjkjId0gsS252PB28zGJxB23eRhnNzBLztyGWwu/RAJQZRtz4sY5x4C2nLnNwyxzgI2ZF48WNqB6IKpP3DgjxwzIOMfDJpGAXwu/RDJI1+HE+RI5xkAXHuDhIaRFsucZ0NhzxxM3gAI54UwyjwTPwWa8fjE4nv5M8kdZdeL89uYDB39U2NnbH28++OEjHi1gwAiMGoMDCG4DAfUg8IeBQZ4YdaNgFIyCUTAyAQDdllk41FPo+wAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Thoracic Surgery, The First Hospital of Putian, The School of Clinical Medicine, Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Zhiyang","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2024-07-18 16:07:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4763867/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4763867/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62730489,"identity":"d613d60a-8784-4b7d-8c81-72487f2ec087","added_by":"auto","created_at":"2024-08-18 23:17:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":135013,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of participants inclusion for study.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4763867/v1/ca5059b4602452cbb97b58d2.jpg"},{"id":62730488,"identity":"2a2d01a7-8c08-4877-b681-a8f9dfd6f7f0","added_by":"auto","created_at":"2024-08-18 23:17:54","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":63126,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of PEF, FEV1, and FVC in persons with DM \u0026nbsp;\u0026nbsp;age 50 years or older from 3 ethnic groups.\u003c/p\u003e\n\u003cp\u003e(A) PEF; (B) FEV1; (C) FVC.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4763867/v1/ab30b782e191a5a72b116fe7.jpg"},{"id":62730913,"identity":"a45e58e1-7567-4575-a9ec-213087f25ea2","added_by":"auto","created_at":"2024-08-18 23:25:54","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":24116,"visible":true,"origin":"","legend":"\u003cp\u003eCompare lung function measures based on the use of female hormones.\u003c/p\u003e\n\u003cp\u003ePEF, FEV1 and FVC were measured at 6189mL/s, 2123mL, \u0026nbsp;\u0026nbsp;and 2779mL, respectively, in postmenopausal women who had used sex hormones. \u0026nbsp;\u0026nbsp;In comparison, these values were 5769 mL/s, 2029 mL, and 2624 mL in \u0026nbsp;\u0026nbsp;menopausal women who had not used sex hormones. There was a statistically \u0026nbsp;\u0026nbsp;significant difference in FVC (P=0.024). (A) PEF; (B) FEV1; (C) FVC\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4763867/v1/c770fd9a5e9f2438406cdaf5.jpg"},{"id":85305412,"identity":"ae875576-3322-4229-841a-0735a62214ce","added_by":"auto","created_at":"2025-06-24 12:38:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1153866,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4763867/v1/04bf09be-802a-44dd-8500-563b6d7e404b.pdf"},{"id":62730914,"identity":"b8454481-02f3-41e5-942e-e09e1201d6a6","added_by":"auto","created_at":"2024-08-18 23:25:54","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":33138,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4763867/v1/73aa1856b79f8898f1ba9af3.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\"Observing Pulmonary Function Disparities in Diabetes Patients from Demographic and Hormonal Perspectives: A Study Based on NHANES Database\"","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiabetes is a prevalent chronic disease affecting millions of people worldwide. In recent years, the global impact of diabetes has been expanding at an unprecedented rate. According to the World Health Organization, approximately 415\u0026nbsp;million adults globally have diabetes, a number that is expected to increase to over 700\u0026nbsp;million by 2025[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Diabetes not only affects blood sugar levels but is also closely associated with reduced lung function. Several cross-sectional studies have shown that compared to non-diabetic individuals, those with diabetes have lower FVC and FEV1[\u003cspan additionalcitationids=\"CR3 CR4\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This indicates that the negative impact of diabetes on the respiratory system may be more severe than previously anticipated. These data demonstrate that diabetes is not only a metabolic disease but also a systemic condition that significantly affects lung function. The rapid increase in the global diabetic population, coupled with the emerging complex relationship between diabetes and lung function, underscores the urgent need to delve deeper into this area. This is essential for developing more precise and effective treatment and prevention strategies. Although the exact mechanisms linking diabetes and lung function are still unclear, the relationship remains crucial due to its potential epidemiological and clinical implications. The rising incidence of diabetes, obesity, smoking, and heart failure can cumulatively and significantly impair lung function, leading to increased morbidity and mortality rates associated with poor lung function on a population level [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral epidemiological and clinical studies have reported reduced lung function in adults with diabetes compared to non-diabetic adults. The decline in lung function among diabetic patients appears to be negatively correlated with blood glucose levels, diabetes duration, and severity and is independent of smoking status or obesity [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8 CR9 CR10\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Although existing studies have initially revealed the negative impact of diabetes on lung function and its variations across race, age, and gender, most of these studies focus on single factors. They often lack a comprehensive analysis considering multiple demographic characteristics, lifestyle factors, and disease states. Therefore, this study aims to systematically evaluate the impact of diabetes on lung function across different races, ages, and genders by analyzing data from the NHANES database.\u003c/p\u003e \u003cp\u003eGender and hormone levels play an essential role in regulating respiratory system function. Testosterone and estrogen significantly impact lung function by influencing airway smooth muscle tone and pulmonary surfactant production [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. There are differences in lung function between males and females, with males typically having higher PEF, FVC, and FEV1. Additionally, postmenopausal women may experience further reductions in lung function due to declining estrogen levels. However, the specific manifestations of these gender and hormone level differences in diabetic patients remain unclear.\u003c/p\u003e \u003cp\u003eRacial differences are also important factors influencing diabetes and lung function. There are significant disparities in diabetes prevalence and complications among different racial groups. The differences in diabetes-related lung function decline among Black, White, and Mexican American populations have not been adequately studied.\u003c/p\u003e \u003cp\u003eThis study aims to systematically evaluate the impact of diabetes on lung function across different races, ages, genders, and hormone levels by deeply analyzing large-scale data from the NHANES database. Our goal is to fill gaps in existing research, provide a scientific basis for personalized treatment of diabetic patients, and offer strong support for the formulation of public health policies.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eData Source\u003c/h2\u003e\n \u003cp\u003eThe NHANES database is a nationwide cross-sectional study aimed at assessing the health and nutritional status of the non-institutionalized U.S. population. These data are collected from a complex, multi-stage, stratified, clustered probability sample that ensures high representativeness of health-related data across the United States. Data were obtained through face-to-face interviews, mobile examinations, and laboratory tests. We selected NHANES data from 2009\u0026ndash;2012, as consistent lung function tests were used during this period. The NHANES protocol was reviewed and approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all participants provided written informed consent. The public data used in our analysis can be accessed at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/nchs/nhanes/\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003eStudy Population\u003c/h2\u003e\n \u003cp\u003eThe study included data from two cross-sectional cycles of NHANES (2009\u0026ndash;2012). Out of 20293 participants aged 1 year or older, 8641 were excluded due to missing data on physical measurements, lung function tests, or total cholesterol (TCHOL) tests. We further excluded 3391 individuals as our study focused on non-pregnant adults aged 20 years and older. Additionally, 174 participants were excluded due to missing diabetes data. Ultimately, 8087 participants with complete data were included for quantitative analysis (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003eVariable Measurements and Definitions\u003c/h2\u003e\n \u003cp\u003eDiabetes was diagnosed based on the American Diabetes Association (ADA) criteria[\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e] and self-reported questionnaire responses. The criteria included: fasting blood glucose\u0026thinsp;\u0026ge;\u0026thinsp;7 mmol/L (125 mg/dL), a self-reported physician diagnosis of diabetes, or current use of diabetes medications to lower blood glucose levels. During the 2009\u0026ndash;2012 NHANES period, spirometry was conducted on participants aged 6 to 79 years, excluding those with current chest pain, physical problems with forced exhalation, use of supplemental oxygen, recent eye, chest, or abdominal surgery, recent heart attack, stroke, tuberculosis exposure, coughing up blood, retinal detachment, lung collapse, or aneurysm history. Spirometry followed standard protocols using a dry-rolling seal spirometer (Ohio 822/827; Ohio Medical Instruments, Cincinnati, OH, USA). Participants were required to provide three acceptable maneuvers. For this study, we used only pre-bronchodilator spirometry data of quality A (exceeds American Thoracic Society data collection standards) or B (meets American Thoracic Society data collection standards). Predicted lung function was calculated using NHANES III equations [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]. Total testosterone was analyzed using ID-HPLC/MS/MS, which employs a triple quadrupole mass spectrometer with electrospray ionization in positive ion mode. Current smokers were defined as participants aged 20 years or older who reported smoking occasionally or daily in the past 7 days or had smoked over 100 cigarettes in their lifetime [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]. Alcohol consumption categories were defined as follows: current heavy drinking (\u0026ge;\u0026thinsp;3 drinks per day for women, \u0026ge;\u0026thinsp;4 drinks per day for men, or binge drinking [\u0026ge;\u0026thinsp;4 drinks for women, \u0026ge;\u0026thinsp;5 drinks for men on a single occasion] for \u0026ge;\u0026thinsp;5 days per month); current moderate drinking (\u0026ge;\u0026thinsp;2 drinks per day for women, \u0026ge;\u0026thinsp;3 drinks per day for men, or binge drinking\u0026thinsp;\u0026ge;\u0026thinsp;2 days per month); all other cases were classified as light drinking [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003eStatistical Analysis\u003c/h2\u003e\n \u003cp\u003eAll analyses used weighted samples to account for the complex survey design, ensuring estimates representative of the U.S. population. A four-year weight variable was created to provide estimates over the four years by taking half of the two-year weights assigned to each person sampled from 2009 to 2012. All analyses were conducted using RStudio version 2023.10.31 and R version 4.3.2 for Mac. We employed linear regression to compare lung function indicators between diabetic and non-diabetic participants, adjusted for race, age, and gender, and to obtain mean values and comparisons of lung function among diabetic patients across different gender, age, and racial groups. The frequency distribution of lung function indicators adjusted for age and gender was obtained across different racial groups. We also compared lung function between male diabetic patients with different testosterone levels and postmenopausal female diabetic patients using hormone therapy.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eBaseline Characteristics of Participants\u003c/h2\u003e\n \u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e presents the weighted baseline characteristics of participants selected from the 2009\u0026ndash;2012 NHANES who had valid physical measurements and lung function data. The 8087 NHANES participants represented 25.5 million non-institutionalized U.S. residents, stratified by the presence of diabetes. The analysis included 984 diabetic patients with a mean age of 56.92\u0026thinsp;\u0026plusmn;\u0026thinsp;12.61 years, of whom 53.03% were male and 46.97% were female. The non-diabetic group comprised 7103 individuals with a mean age of 43.92\u0026thinsp;\u0026plusmn;\u0026thinsp;15.10 years, 49.78% male and 50.22% female. Significant differences were observed between the diabetic and non-diabetic groups in terms of age, race, BMI, waist circumference, smoking, alcohol consumption, PEF, FEV1, FVC, total cholesterol, physical activity, and hypertension (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eWeighted baseline characteristics of participants\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo Diabetes (n\u0026thinsp;=\u0026thinsp;7103)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiabetes (n\u0026thinsp;=\u0026thinsp;984)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-trend\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.92 (15.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.94 (12.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEthnicity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic White\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Hispanic Black\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBMI (kg/cm2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.14 (6.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.06 (6.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeight (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e169.48 (9.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e168.12 (10.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWaist circumference (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81.09 (20.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.61 (21.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCurrent smoker (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAlcohol (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emild\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emoderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeavy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePEF (mL/s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8431.45 (2189.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7429.84 (2250.745)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1 (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3272.40 (893.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2659.09 (834.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFVC (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4188.07 (1077.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3492.42 (1034.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTCHOL (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e197.44 (39.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e187.00 (47.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003eBMI, body mass index; PEF, peak expiratory flow; FEV1, forced expiratory volume in one second; FVC, forced vital capacity; TCHOL, Total Cholesterol.\u003c/p\u003e\n \u003cp\u003eAll values are presented as proportion (%), or mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003ePrevalence of Diabetes\u003c/h2\u003e\n \u003cp\u003eMultivariable logistic regression analysis was conducted to estimate the prevalence of diabetes adjusted for age, gender, and race (Appendix Table\u0026nbsp;1). Compared to White participants, Black and Mexican American participants were more likely to have diabetes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001): 13.3% of Black participants, 7.7% of White participants, and 11.1% of Mexican American participants. Males were also more likely to have diabetes than females (P\u0026thinsp;=\u0026thinsp;0.02). The prevalence of diabetes was lower during adolescence, below 8% from ages 20 to 45, and increased with age, peaking around 60 years.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003eComparison of Lung Function Indices between Diabetic and Non-Diabetic Participants\u003c/h2\u003e\n \u003cp\u003eUsing multiple linear regression, we compared the age and gender-adjusted mean PEF, FEV1, and FVC between diabetic and non-diabetic participants (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Diabetes had the greatest impact on lung function indices among White participants, a lesser impact among Black participants, and the smallest impact among Mexican American participants. In Model 1 adjusted for age, race, and gender, diabetic patients showed overall lower mean PEF, FEV1, and FVC compared to non-diabetic patients (598.1 mL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 308.2 mL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; 412.3 mL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, respectively). Model 2, which additionally adjusted for body mass index, total cholesterol, smoking status, alcohol consumption, physical activity, and hypertension, yielded results consistent with Model 1. Regarding gender, male diabetic patients exhibited a more significant decline in lung function compared to female diabetic patients (Appendix Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of age, diabetic patients over 50 years old showed a more pronounced decline in lung function compared to those under 50 years old (Appendix Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparative mean PEF, FEV1 and FVC in diabetics and non-diabetics.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiabetics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNon diabetics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Difference\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003ePEF, mL/s\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6925.9 (6635.6\u0026ndash;7216.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7981.9 (7833.8\u0026ndash;8130.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e431.5 (134.0\u0026ndash;728.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7440.9 (7116.8\u0026ndash;7765.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8514.5 (8385.8\u0026ndash;8643.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e814.8 (545.3\u0026ndash;1084.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican-American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7949.7 (7390.6\u0026ndash;8508.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8566.9 (8428.7\u0026ndash;8705.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302.6 ((-88.8) \u0026minus;\u0026thinsp;694.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e598.1 (414.7\u0026ndash;781.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e563.3 (387.5\u0026ndash;739.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eFEV1, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2360.1 (2261.7\u0026ndash;2458.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2893.1 (2833.8\u0026ndash;2952.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e214.2 (125.7\u0026ndash;302.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2688.4 (2542.8\u0026ndash;2834.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3333.7 (3282.6\u0026ndash;3384.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e392.5 (280.7\u0026ndash;504.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican-American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2985.9 (2813.1\u0026ndash;3158.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3376.7 (3335.3\u0026ndash;3418.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e185.3 (74.4\u0026ndash;296.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e308.2 (235.0\u0026ndash;381.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e244.6 (181.1\u0026ndash;308.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eFVC, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3038.6 (2927.0\u0026ndash;3150.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3610.1 (3542.8\u0026ndash;3677.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e272.9 (174.0\u0026ndash;371.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3620.3 (3447.7\u0026ndash;3793.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4325.5 (4275.2\u0026ndash;4375.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e517.8 (398.2\u0026ndash;637.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican-American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3747.6 (3547.6\u0026ndash;3947.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4166.5 (4114.7\u0026ndash;4218.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e231.5 (90.9\u0026ndash;372.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e412.3 (334.5\u0026ndash;490.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModel 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e331.1 (260.9\u0026ndash;401.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eMeans (95% CIs) are given from a weighted analysis adjusted for age and gender unless otherwise indicated.\u003c/p\u003e\n \u003cp\u003eModel 1 adjusted age, race and gender.\u003c/p\u003e\n \u003cp\u003eModel 2 adjusted age, race, gender, BMI, TCHOL, smoke, alcohol, physical activity and hypertension.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eLifestyle Habits\u003c/h2\u003e\n \u003cp\u003eThe percentage of diabetic patients adjusted for age and gender was compared among alcohol consumption groups (Appendix Table\u0026nbsp;3). There were 102, 123, and 1506 Black participants categorized as heavy, moderate, and light drinkers, respectively. For White participants, these numbers were 178, 303, and 2907, and for Mexican American participants, 66, 163, and 1004. Interestingly, the average prevalence of diabetes was lower among heavy and moderate drinkers compared to light drinkers. The association between heavy drinking and diabetes differed significantly from that of light drinking (P\u0026thinsp;=\u0026thinsp;0.06), while differences among alcohol consumption groups were otherwise not significant.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eFrequency Distribution of Lung Function Indices in Diabetic Participants\u003c/h2\u003e\n \u003cp\u003eFor participants with diabetes, the distribution of PEF, FEV1, and FVC indicates minimal differences in PEF, with Mexican American participants showing an advantage in FEV1 followed by White and Black participants. Among Black participants, there is a downward shift in FEV1 and a noticeable upward shift in FVC (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e; Appendix Table 5).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eComparison of Lung Function Indices among Diabetic Participants by Race, Gender, and Age\u003c/h2\u003e\n \u003cp\u003eWe compared average lung function indices among diabetic participants across major racial groups using linear regression (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Among participants aged 50 and younger, there were 34, 24, and 30 male participants for Black, White, and Mexican American groups, respectively, and 147, 108, and 70 male participants aged 50 and older. For female participants, there were 31, 31, and 26 aged 50 and younger, and 103, 121, and 56 aged 50 and older for Black, White, and Mexican American groups, respectively.\u003c/p\u003e\n \u003cp\u003eCompared to Black participants, White participants showed slightly higher mean PEF (mean difference 515.0 mL; P\u0026thinsp;=\u0026thinsp;0.047), significantly higher FEV1 (328.3 mL; P\u0026thinsp;=\u0026thinsp;0.001), and higher FVC (581.8 mL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared to Black participants, Mexican American participants exhibited slightly higher mean PEF (1023.8 mL; P\u0026thinsp;=\u0026thinsp;0.004), significantly higher FEV1 (709.0 mL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and higher FVC (625.8 mL; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n \u003cp\u003eIn terms of age, participants aged 50 and younger had higher maximum expiratory flow, FEV1, and FVC compared to those aged 50 and older. Regarding gender, males exhibited higher PEF, FVC, and FEV1 compared to females. Appendix Table 4 summarizes these variables across gender and 12 age groups for the three major racial groups.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean Lung Function Values, by Age, Gender, and Ethnic Group*\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender and Age\u003c/p\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003ePEF, mL/s\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBlacks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhites\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMexican Americans\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8900.7 (7875.1\u0026ndash;9926.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10133.4‖ (9363.8\u0026ndash;10903.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9662.5‖ (8669.5\u0026ndash;10655.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8174.1 (7793.4\u0026ndash;8554.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8091.2‖ (7633.1\u0026ndash;8549.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8584.3‖ (8081.3\u0026ndash;9087.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6868.6 (6188.1\u0026ndash;7549.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6785.1‖ (6327.8\u0026ndash;7242.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7155.5‖ (6554.7\u0026ndash;7756.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5515.4 (5185.0\u0026ndash;5845.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5974.3‖ (5580.7\u0026ndash;6368.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5612.8‖ (5093.6\u0026ndash;6131.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e515.0\u0026sect; (26.6\u0026ndash;1003.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1023.8\u0026para; (374.8\u0026ndash;1672.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender and Age\u003c/p\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFEV1, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlacks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican Americans\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3244.7 (2890.4\u0026ndash;3598.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3884.0\u0026sect; (3518.8\u0026ndash;4249.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3653.2‖ (3311.2\u0026ndash;3995.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2702.2 (2599.1\u0026ndash;2805.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2890.1‖ (2693.0\u0026ndash;3087.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3078.2\u0026Dagger; (2942.0\u0026ndash;3214.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2346.9 (2142.5\u0026ndash;2551.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2795.3\u0026para; (2602.8\u0026ndash;2987.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2861.1\u0026para; (2695.0\u0026ndash;3027.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1883.6 (1766.3\u0026ndash;2000.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2058.8\u0026sect; (1983.6\u0026ndash;2134.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2125.7\u0026sect; (1963.0\u0026ndash;2288.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e328.3\u0026para; ( 149.4\u0026ndash;507.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e625.8\u0026Dagger; (427.7\u0026ndash;823.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender and Age\u003c/p\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eFVC, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlacks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhites\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexican Americans\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4034.9 (3662.8\u0026ndash;4407.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4909.5\u0026sect; (4479.0\u0026ndash;5340.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4495.6‖ (4101.4\u0026ndash;4889.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3617.6 (3508.4\u0026ndash;3726.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4049.4‖ (3842.8\u0026ndash;4256.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4039.9\u0026Dagger; (3831.4\u0026ndash;4248.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026lt;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2869.0 (2637.2\u0026ndash;3100.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3497.2\u0026para; (3239.3\u0026ndash;3755.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3452.1\u0026para; (3242.1\u0026ndash;3662.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemales\u0026thinsp;\u0026ge;\u0026thinsp;50 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2421.2 (2296.7\u0026ndash;2545.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2717.3\u0026sect; (2622.3\u0026ndash;2812.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2664.7\u0026sect; (2462.3\u0026ndash;2867.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAll\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e581.8\u0026Dagger; (377.1- 786.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e709.0\u0026Dagger; (481.7\u0026ndash;936.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"4\"\u003e\n \u003cp\u003e* Means (95% CIs) are given from a weighted analysis adjusted for age and gender.\u003c/p\u003e\n \u003cp\u003e\u0026Dagger;P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 compared with black participants.\u003c/p\u003e\n \u003cp\u003e\u0026sect;P\u0026thinsp;\u0026gt;\u0026thinsp;0.01 to \u0026lt;\u0026thinsp;0.05 compared with black participants.\u003c/p\u003e\n \u003cp\u003e‖P\u0026thinsp;\u0026gt;\u0026thinsp;0.05 compared with black participants.\u003c/p\u003e\n \u003cp\u003e\u0026para;P\u0026thinsp;\u0026ge;\u0026thinsp;0.001 to \u0026lt;\u0026thinsp;0.01 compared with black participants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eFurther investigation among male diabetic patients in 2011\u0026ndash;2012 showed significant differences in lung function indices based on testosterone levels, with those\u0026thinsp;\u0026gt;\u0026thinsp;=\u0026thinsp;16 ng/dL showing superior results in FEV1 and FVC (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eComparative mean PEF, FEV1 and FVC in different testosterone levels.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTestosterone, ng/dL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;16\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026gt;=16\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePEF, mL/s\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7715.0 (6009.3\u0026ndash;9420.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8463.4 (7973.1\u0026ndash;8953.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFEV1, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2136.1 (1779.0 -2493.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2967.4 (2773.8 -3161.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFVC, mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3189.4(3103.3 -3275.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4020.2 (3828.9 -4211.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eWe also studied postmenopausal female diabetic patients from 2009\u0026ndash;2012, categorizing them based on whether they used any form of female hormones such as estrogen and progestin, excluding contraception or infertility treatments. Results indicated significant improvement in FVC among hormone users (P\u0026thinsp;=\u0026thinsp;0.024)(Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDiabetes and impaired lung function are both global public health concerns. Understanding their relationship can provide new insights into the prevention and management of these diseases [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Multiple studies have indicated a declining trend in lung function among adults with type 2 diabetes (T2DM) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, there remains insufficient research on the specific impact of diabetes on lung function and its variations across different demographic groups. In this study, we particularly focused on three key indices: forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF), After adjusting for age, race, and gender, diabetic patients showed overall lower mean PEF, FEV1, and FVC compared to non-diabetic patients.\u003c/p\u003e \u003cp\u003eRegarding demographic characteristics, our report confirms that biological factors influencing the pathophysiology of diabetes vary by race or nationality [\u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23 CR24 CR25\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In this study, we conducted multivariable logistic regression analyses to estimate diabetes prevalence adjusted for age, gender, and race. The results indicated that compared to White participants, both Black and Mexican American participants were more susceptible to diabetes, consistent with findings from a review published in The Lancet[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], which highlighted significantly higher diabetes diagnosis rates among certain racial and ethnic groups compared to Whites. This phenomenon may be intricately linked to income, education, occupation, housing, food security, social support, and other factors. Additionally, we found that males are more prone to diabetes than females. Moreover, the prevalence of diabetes is lower during adolescence, less than 8% from ages 20 to 45, increasing with age and peaking around 60 years. Current research indicates a higher incidence of diabetes among elderly Black individuals. The findings from population-based analyses for observing age, gender, and racial disparities are consistent [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also studied differences in BMI and lifestyle habits related to diabetes prevalence. We found a correlation between higher BMI and diabetes prevalence, consistent with previous studies linking obesity to an increased risk of type 2 diabetes [\u003cspan additionalcitationids=\"CR28 CR29 CR30\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The mechanisms may involve interactions among insulin resistance, inflammation, adipokines, and genetics. Our study suggests that individuals can reduce their risk of diabetes by controlling their weight, thereby enhancing the prevention and management of the disease. Furthermore, smoking was found to be associated with diabetes prevalence, where not only active smokers but also childhood and adulthood exposure to secondhand smoke were linked to higher rates of type 2 diabetes[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Interestingly, our study on alcohol intake revealed that light drinkers had a higher prevalence of diabetes compared to moderate and heavy drinkers, although a study published in 2015 contradicts our conclusion, suggesting a link between heavy drinking and increased diabetes risk [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This contradiction may require consideration of multiple factors such as study design, data sources, sample characteristics, alcohol categorization, adjusted variables, and temporal differences to better understand the disparities between results and provide reasonable explanations. Future studies are needed to validate these findings and explore specific reasons for these differences.\u003c/p\u003e \u003cp\u003ePrevious meta-analytic studies have found a significant correlation between declining lung function and the incidence of T2DM [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], consistent with our study's results. We found that lung function indices (FEV1, FVC, PEF) in diabetes patients were significantly lower than in non-diabetic individuals, with older diabetes patients showing more severe declines in lung function indices compared to younger patients, a finding echoed in similar reports [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Elderly diabetes patients face a higher risk of pulmonary complications. Regarding gender, Males outperformed females in PEF, FVC, and FEV1. Our study of male diabetic patients in 2011\u0026ndash;2012 revealed a significant impact of testosterone levels on lung function indices, further analysis indicated that testosterone levels significantly influence lung function in male diabetes patients. Specifically, male patients with testosterone levels\u0026thinsp;\u0026ge;\u0026thinsp;16 ng/dL exhibited significantly better FEV1 and FVC indices than those with levels\u0026thinsp;\u0026lt;\u0026thinsp;16 ng/dL (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This suggests that higher testosterone levels may protect lung function in male diabetes patients to some extent. Additionally, we studied postmenopausal female diabetes patients from 2009 to 2012, showing that hormone use significantly improved FVC (P\u0026thinsp;=\u0026thinsp;0.024). This indicates that hormone therapy with estrogen and progestin post-menopause may help improve lung function in female diabetes patients. Overall, our studies confirm the significant role of sex hormones in pulmonary health, a conclusion supported by previous research [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. High levels of testosterone protect lung function by enhancing the strength and endurance of respiratory muscles, such as FEV1 and FVC. These findings provide new perspectives and potential intervention measures for managing lung function in diabetes patients. However, some studies have found a correlation between high testosterone levels and increased risk of certain pulmonary diseases (such as lung cancer), necessitating further research into the effects of testosterone on lung function. Nevertheless, these gender differences also manifest differently across different races. For example, significant FEV1 and PEF differences are observed between White males and females, whereas these differences are relatively minor among Black and Mexican individuals, possibly due to genetic backgrounds, environmental influences, socioeconomic status, cultural habits, and physiological and biological differences.\u003c/p\u003e \u003cp\u003eTherefore, based on this study, healthcare professionals can guide more attention and resources toward elderly Black males, targeting disease prevention and management to reduce disease incidence and progression. It is also crucial to consider race and age factors in more personalized healthcare professionals, including providing information on diabetes risk factors, preventive measures, and early identification. This finding also promotes further research to explore the specific reasons and mechanisms for the higher susceptibility to diabetes among elderly Black individuals, seeking more effective prevention and treatment strategies. Overall, these findings can guide clinical practice and public health policies to better prevent and manage diabetes. Secondly, this study also revealed the significant influence of gender and gender-specific hormones on lung function in diabetes patients, which has important social implications. First, these findings provide new insights into the personalized treatment of diabetes patients. In male diabetes patients, those with higher testosterone levels exhibit better lung function, suggesting that testosterone levels could be considered an important indicator in evaluating lung function in clinical practice and even exploring appropriate testosterone supplementation to improve their lung function. Similarly, in postmenopausal female diabetes patients, hormone therapy with estrogen and progestin significantly improves lung function, suggesting consideration of the potential benefits of these hormone therapies in treatment plans.\u003c/p\u003e \u003cp\u003eOverall, the impact of diabetes on lung function is a complex and multifactorial process. When discussing the relationship between diabetes and pulmonary abnormalities, this study emphasizes that this relationship is not merely the result of singular factors but rather a complex interplay of various biological, socio-economic, and environmental factors. This complexity is evident in significant differences observed among different races, ages, and genders, highlighting the need for tailored clinical interventions and offering ample exploration opportunities for future research.\u003c/p\u003e \u003cp\u003eFurthermore, this study reveals the significant role of gender and gender-specific hormones in lung function among diabetic patients, which constitutes an innovative and practically valuable finding. Future research could further refine this area, such as by longitudinally tracking hormone level changes to observe their dynamic impact on lung function and exploring the effectiveness and safety of different hormone replacement therapies in improving lung function in diabetic patients. Moreover, considering the differences in disease manifestation and treatment response based on gender, clinical practice should prioritize gender-specific assessment and intervention strategies.\u003c/p\u003e \u003cp\u003eAlthough this study offers valuable insights, there are limitations. Firstly, this study relies on self-reported diabetes status, which may introduce reporting biases. Secondly, the cross-sectional nature of NHANES data limits the ability to establish causal relationships. Future research should focus on longitudinal studies to better understand the progression of declining lung function in diabetes patients. Additionally, unmeasured variables may affect the results, warranting further research. Lastly, this study is limited to adults from three major racial groups in the United States, caution should be exercised when extrapolating study results to other populations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this study provides a comprehensive analysis of data from the NHANES database to observe the differences in lung function among diabetic patients from demographic and hormone-level perspectives. It deepens our understanding of the complexity of diabetes-related declines in lung function. Despite certain limitations, this research offers crucial insights for future studies and clinical practice. Future research should further explore the specific mechanisms underlying the relationship between diabetes and lung function, the roles of demographic characteristics and hormones in this relationship, and effective prevention and treatment strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePublicly available datasets were analyzed in this study. This data can be found here: https://www.cdc.gov/nchs/nhanes/index.htm.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJianyang Wu and Yuyuan Lin conceived the study, analyzed the data, and drafted the manuscript. Jianyang Wu and Yuyuan Lin contributed equally to this work. Mengxin Lin helped revise the manuscript critically for important intellectual content; Zhiyang Xu, Jie Pan, and Jianxin Xu supervised the project and reviewed the manuscript. All authors approved the final version as submitted, and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The use of NHANES data was approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board, and all data used in this study were anonymized and de-identified prior to analysis. This study does not involve any clinical trials, hence clinical trial registration is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u0026rsquo;s note\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors, and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCollaboration NRF. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet (London England). 2016;387(10027):1513\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAA L, ST RLDSDD. Lung function in type 2 diabetes: the Normative Aging Study. Respir Med. 2005;99(12):1583\u0026ndash;90.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHC Y, NM P, NY W, JS P, BB D, CE C, FL ES. 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(4):741\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ PL. Copenhagen City Heart Study: longitudinal analysis of ventilatory capacity in diabetic and nondiabetic adults. Eur Respir J. 2002;20(6):1406\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRE W, RJ AB, GT G, DJ OC. Association between glycemic state and lung function: the Framingham Heart Study. Am J Respir Crit Care Med. 2003;167(6):911\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOL K, JA K, S G, LJ S. Systematic review of the association between lung function and Type 2 diabetes mellitus. Diabet medicine: J Br Diabet Association. 2010;27(9):977\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDA L, GD SE. Associations of measures of lung function with insulin resistance and Type 2 diabetes: findings from the British Women's Heart and Health Study. Diabetologia. 2004;47(2):195\u0026ndash;203.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHC Y, NM P, NY W, JS P, BB D, FL B. Vital capacity as a predictor of incident type 2 diabetes: the Atherosclerosis Risk in Communities study. Diabetes Care. 2005;28(6):1472\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRE W, RJ AB, GT G, DJ OC. Association between glycemic state and lung function: the Framingham Heart Study. Am J Respir Crit Care Med. 2003;167(6):911\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTM D, WA MKPKHV. Reduced pulmonary function and its associations in type 2 diabetes: the Fremantle Diabetes Study. Diabetes Res Clin Pract. 2000;50(2):153\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeh HC, Punjabi NM, Wang NY, Pankow JS, Duncan BB, Cox CE, Selvin E, Brancati FL. 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(4):741\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEA T, VM M, YS P. Sex differences and sex steroids in lung health and disease. Endocr Rev. 2012;33(1):1\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYY H, SF EF, E A-P WMLM. Testosterone-to-estradiol ratio and lung function in a prospective study of Puerto Rican youth. Annals allergy asthma immunology: official publication Am Coll Allergy Asthma Immunol. 2021;127(2):236\u0026ndash;e242231.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAssociation AD. Standards of medical care in diabetes\u0026ndash;2010. Diabetes Care. 2010;33(Suppl 1):S11\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJL H JR, KB O. Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999;159(1):179\u0026ndash;87.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMM H, DD B-H JEE, JF T, GP R. Prevalence of neutropenia in the U.S. population: age, sex, smoking status, and ethnic differences. Ann Intern Med. 2007;146(7):486\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDD PR, M PJCAAF, PS PVHS, AA K. Inverse Association of Telomere Length With Liver Disease and Mortality in the US Population. Hepatol Commun. 2022;6(2):399\u0026ndash;410.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHsia CC, Raskin P. Lung function changes related to diabetes mellitus. Diabetes Technol Ther. 2007;9(Suppl 1):S73\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC ALGSXM. Type 2 diabetes impairs pulmonary function in morbidly obese women: a case-control study. Diabetologia. 2010;53(6):1210\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eES F, DM M, Health N, Study NESEF-u. Prospective association between lung function and the incidence of diabetes: findings from the National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. Diabetes Care. 2004;27(12):2966\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eG E, B H, P N, P W, G B, L J: Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med 2003, 253(5):574\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eV N, DG M, LC R, CC PR. Glycemic control and cardiopulmonary function in patients with insulin-dependent diabetes mellitus. Am J Med. 1997;103(6):504\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWA D, M K, Study PKVGTMD. Glycemic exposure is associated with reduced pulmonary function in type 2 diabetes: the Fremantle Diabetes Study. Diabetes Care. 2004;27(3):752\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKF AM, YJ RJF, CC C. Associations between trends in race/ethnicity, aging, and body mass index with diabetes prevalence in the United States: a series of cross-sectional studies. Ann Intern Med. 2014;161(5):328\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAl-Khlaiwi T, Alsabih AO, Khan A, Habib SH, Sultan M, Habib SS. Reduced pulmonary functions and respiratory muscle strength in Type 2 diabetes mellitus and its association with glycemic control. Eur Rev Med Pharmacol Sci. 2021;25(23):7363\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEndocrinology TLD. A widening racial and social gap in diabetes. lancet Diabetes Endocrinol. 2021;9(8):471.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYJ C, AM K, MRG A, SH S, HS K, EW G, WY F. Prevalence of Diabetes by Race and Ethnicity in the United States, 2011\u0026ndash;2016. JAMA. 2019;322(24):2389\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMI MWAMAK, E I, N S-A M. Homogeneity in the association of body mass index with type 2 diabetes across the UK Biobank: A Mendelian randomization study. PLoS Med. 2019;16(12):e1002982.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL ML, B dL-G TGF, MC B-R. F C-C: Childhood and adult secondhand smoke and type 2 diabetes in women. Diabetes Care. 2013;36(9):2720\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eC K. Alcohol Consumption and the Risk of Type 2 Diabetes: A Systematic Review and Dose-Response Meta-analysis of More Than 1.9 Million Individuals From 38 Observational Studies. Diabetes Care. 2015;38(9):1804\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eY WL, C NYMXLSMBW. Association of lung function and blood glucose level: a 10-year study in China. BMC Pulm Med. 2022;22(1):444.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetes mellitus, Lung function, Testosterone levels, Hormone therapy, Public health, NHANES","lastPublishedDoi":"10.21203/rs.3.rs-4763867/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4763867/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDiabetes is a global public health issue commonly associated with various complications, including impaired lung function. Existing studies suggest that the relationship between diabetes and lung function varies significantly across age, racial, and gender groups. However, specific differences in lung function within these demographic characteristics have not been thoroughly investigated. This study aims to explore lung function disparities among diabetic patients using data from the 2009\u0026ndash;2012 NHANES.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eData from 2009\u0026ndash;2012 NHANES were analyzed, including 8087 participants with valid physical measurements and lung function data, of which 984 were diabetic. Multivariate linear regression was employed to assess the effects of factors such as age, gender, race, BMI, and smoking on lung function indicators (peak expiratory flow (PEF), forced expiratory volume in one second (FEV1), and forced vital capacity (FVC)). Additionally, lung function was compared between male diabetic patients with different testosterone levels and postmenopausal female diabetic patients using hormone therapy.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe study found significant disparities in lung function among diabetic patients across different racial, age, and gender groups. Specifically, in terms of race, Black diabetic patients exhibited poorer lung function compared to White and Mexican American patients, particularly in FEV1 and FVC indices. Regarding age, participants under 50 showed higher PEF, FEV1, and FVC than those over 50. Gender-wise, males had higher PEF, FEV1, and FVC than females. Male diabetic patients with testosterone levels\u0026thinsp;\u0026ge;\u0026thinsp;16 ng/dL had significantly better lung function indicators than those with testosterone levels\u0026thinsp;\u0026lt;\u0026thinsp;16 ng/dL, notably in FEV1 and FVC (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Postmenopausal female diabetic patients using hormone therapy showed significant improvement in lung function. Specifically, those using estrogen and progesterone therapy exhibited marked improvement in FVC (P\u0026thinsp;=\u0026thinsp;0.024).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study reveals significant impacts of gender, race, and hormone levels on lung function among diabetic patients, providing new insights for personalized treatment. Male patients and postmenopausal female patients using hormone therapy demonstrated better lung function, suggesting the potential consideration of testosterone and estrogen supplementation in clinical treatment. These findings underscore the importance of addressing gender and racial disparities in medical research, promoting more precise and effective medical practices.\u003c/p\u003e","manuscriptTitle":"\"Observing Pulmonary Function Disparities in Diabetes Patients from Demographic and Hormonal Perspectives: A Study Based on NHANES Database\"","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-18 23:17:49","doi":"10.21203/rs.3.rs-4763867/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"793c2a5b-57ab-41d0-9c8e-e4aa35e2702e","owner":[],"postedDate":"August 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-24T12:38:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-18 23:17:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4763867","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4763867","identity":"rs-4763867","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}