Skip to main content
Journal of Korean Medical Science logoLink to Journal of Korean Medical Science
. 2024 Jan 29;39(6):e51. doi: 10.3346/jkms.2024.39.e51

Increased Apolipoprotein B/Apolipoprotein A-I Ratio Is Associated With Decline in Lung Function in Healthy Individuals: The Kangbuk Samsung Health Study

Jonghoo Lee 1,*, Hye Kyeong Park 2,*, Min-Jung Kwon 3, Soo-Youn Ham 4, Hyun-Il Gil 5, Si-Young Lim 5, Jae-Uk Song 5,
PMCID: PMC10876430  PMID: 38374625

Abstract

Background

Lung dysfunction and high apolipoprotein B/apolipoprotein A-I (apoB/apoA-I) ratio are both recognized risk factors for cardiovascular disease. However, few studies have examined the association between the apoB/ApoA-I ratio and lung function. Therefore, we investigated whether this ratio is associated with decreased lung function in a large healthy cohort.

Methods

We performed a cohort study on 68,418 healthy Koreans (34,797 males, mean age: 38.1 years) who underwent a health examination in 2019. ApoB/apoA-I ratio was categorized into quartiles. Spirometric values at the fifth percentile in our population were considered the lower limit of normal (LLN), which was used to define lung function impairment. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs), using the lowest quartile as the reference, were estimated to determine lung function impairment.

Results

Mean apoB/apoA-I ratio was 0.67 ± 0.21. Subjects with the highest quartile of this ratio had the lowest predicted forced expiratory volume in one second (FEV1%) and forced vital capacity (FVC%) after controlling for covariates (P < 0.001). However, FEV1/FVC ratio was not significantly different among the four quartiles (P = 0.059). Compared with the lowest quartile (Q1, reference), the aORs (95% CI) for FEV1% < LLN across increasing quartiles (from Q2 to Q4) were 1.216 (1.094–1.351), 1.293 (1.156–1.448), and 1.481 (1.311–1.672) (P for trend < 0.001), respectively. Similarly, the aORs for FVC% < LLN compared with the reference were 1.212 (1.090–1.348), 1.283 (1.147–1.436), and 1.502 (1.331–1.695) with increasing quartiles (P for trend < 0.001). However, the aORs for FEV1/FVC < LLN were not significantly different among groups (P for trend = 0.273).

Conclusion

High apoB/apoA-I ratio was associated with decreased lung function. However, longitudinal follow-up studies are required to validate our findings.

Keywords: Apolipoprotein A-I, Apolipoprotein B, ApoB/A-I Ratio, Lung Function, Healthy Population, Spirometry

Graphical Abstract

graphic file with name jkms-39-e51-abf001.jpg

INTRODUCTION

Lung dysfunction is associated with many comorbidities and mortality from cardiovascular-metabolic diseases (CVMDs) and all other death causes.1,2,3,4,5,6 Furthermore, it often precedes overt disease manifestations.7 Therefore, early detection and treatment of modifiable risk factors for lung dysfunction could prevent various diseases and their complications.

Apolipoprotein A1 (apoA-I) is a major constituent of high-density lipoprotein (HDL), an antiatherogenic lipoprotein, while apolipoprotein B (apoB) is present in atherogenic lipoproteins including very-low-density lipoprotein (VLDL), intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL), and lipoprotein(a).8 Thus, apoB/apoA-I ratio is theoretically an ideal indicator of atherogenic lipid disturbance. Elevation of atherogenic lipoproteins promotes inflammation, which can lead to CVMDs9 and lung dysfunction.10 Furthermore, there is epidemiologic evidence to indicate that apoB/apoA-I ratio is strongly associated with CVMDs and insulin resistance (IR),11,12 which are associated closely with lung dysfunction.1,3,4

Taken together, apoB/apoA-I ratio might be associated with lung function. However, most studies on the apoB/apoA-I ratio have been performed in the context of CVMDs. Consequently, the association between apoB/apoA-I ratio and lung function remains obscure. Our aim was to assess the association between the apoB/apoA-I ratio and lung function in a large cohort of healthy Koreans.

METHODS

Study design and population

The present cohort study included 214,551 participants who underwent comprehensive health examinations in 2019. This study involved the partial utilization of data from our previously published research,13 and employed similar research methods. Consequently, current study encompass certain aspects of the content found in our preceding research.13 In South Korea, annual or biennial employee health screenings are required by the Industrial Safety and Health Law and are provided free of charge. Most of the examinees (more than 80% of participants) in this study are employees or family members of various companies or local governmental organizations. The remaining participants voluntarily registered for screening examinations.

Inclusion criteria were participants aged 18 years or older with recorded spirometry and apoB/apoA-I ratios (n = 162,401). Among this cohort, we excluded subjects with missing medical history data and/or data about smoking habits or alcohol consumption (n = 13,329). We additionally excluded participants with either a self-reported history and/or those patients currently receiving treatment for any medical conditions and subjects with metabolic syndrome as proposed by previous reports.14,15 After the exclusion of 93,983 participants, 68,418 participants were ultimately included in the analysis (Fig. 1).

Fig. 1. Flow chart of study participants. Details of comorbidities were unavailable because the medical history questionnaire only required yes/no responses. As some individuals had more than one exclusion criterion, 73,795 participants were ultimately included in the analysis.

Fig. 1

COPD = chronic obstructive pulmonary disease, BA = bronchial asthma, HBsAg = hepatitis B virus surface antigen, HCV-Ab = hepatitis C virus antibody, MS = metabolic syndrome, HDL = high-density lipoprotein.

Data collection, anthropometric measurements, and laboratory tests

The comprehensive health-screening program collects socio-demographic data, anthropometric measurements, behavioral factors, and laboratory data. Standardized self-administered questionnaires were used to ascertain information on demographic characteristics, medical history, medication use, smoking habits, alcohol intake (g/day), exercise frequency, any clinical symptoms, and education level. Smoking status was classified as nonsmokers, ex-smokers or current smokers. Average alcohol consumption was calculated based on the frequency and amount of alcohol consumed per drinking day and then categorized as none, non-heavy (< 20 g ethanol/day), or heavy (≥ 20 g ethanol/day). Weekly frequency of moderate physical activity (defined as more than 30 minutes of activity per day inducing slight breathlessness) was also assessed, and regular exercise was defined as ≥ 3 times/week.16 Education level was categorized as less than college graduate or college graduate or more.16

Physical characteristics and serum biochemical parameters were measured by trained nurses as reported previously.16,17 Obesity was defined as a body mass index (BMI) ≥ 25 kg/m2.18 Blood pressure (BP) was measured with a standard sphygmomanometer after at least 5 minutes of seated rest. Measurements were performed twice at 5 minutes intervals and averaged for analysis.

Blood samples were obtained after participants had fasted for at least 10 hours. Methods for measuring serum levels of liver enzymes, creatinine, lipid profiles, glucose, glycated hemoglobin (HbA1c), insulin, and high-sensitivity C-reactive protein (hsCRP) have been described previously.16,17 Inter- and intra-assay coefficients of variation for quality control specimens were < 5% for the blood variables. IR was assessed using the homeostasis model assessment of insulin resistance (HOMA-IR) equation19: Fasting Blood Insulin (μU/mL) × Fasting Blood Glucose (mmol/L)/22.5. Serum apoB and apoA-I concentrations were determined by an immunoturbidometric method using a Cobas 8000 c702 clinical analyzer (Roche Diagnostics, Tokyo, Japan). Limit of detection was 3 mg/dL for both reagents. Intra- and inter assay coefficients of variation were 1.1–4.9% and 1.2–4.7% for the low level quality control materials and 0.8–2.5% and 0.9–3.2% for the high level quality control materials, respectively.

Lung function measurement

Spirometry was performed as recommended by the American Thoracic Society/European Respiratory Society guidelines,20 using the Vmax22 system (Sensor-Medics, Yorba Linda, CA, USA). forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) were obtained under a pre-bronchodilatory setting. The highest FEV1 and FVC values from three or more tests with acceptable curves were used for analyses. Predicted values for FEV1 and FVC were calculated using equations for a representative Korean population sample.21 To calculate the predicted FVC% (FVC%) and predicted FEV1% (FEV1%), we divided the measured value (L) by the predicted value (L) and converted the quotient into a percentage. The ratio of FEV1 to FVC (FEV1/FVC) was also calculated, using the actual measurements. Spirometric values at the fifth percentile in our population were considered the lower limit of normal (LLN) range, as in a previous study.22 Impaired lung function was defined as FEV1% or FVC% less than LLN, and obstructive lung function (OLF) was defined as FEV1/FVC < LLN.23

Statistical analyses

Data are presented as means ± standard deviations or medians and interquartile ranges for continuous variables and as numbers (%) for categorical variables. The normality of continuous variables was assessed with the Kolmogorov-Smirnov test. Baseline continuous variables were stratified by quartile of apoB/apoA-I ratio and compared using one-way analysis of variance or the Kruskal-Wallis tests. The χ2 test or Fisher’s exact test was used to compare categorical variables among groups. To determine the relationships between the apoB/apoA-I ratio and lung function parameters, Pearson’s correlation coefficients was used. In addition, analysis of covariance was performed to assess the significance of differences in mean values of lung function parameters between study groups. Post hoc analysis was performed using the Bonferroni correction to compare mean spirometric values among study groups.

To analyze the significance of differences among groups according to quartile of apoB/apoA-I ratio, all covariates were transformed into categorical variables: high or low and with or without. Differences among four groups were tested using the chi square test or Fisher’s exact test. Using binary logistic regression analysis, adjusted odds ratios (aORs) with 95% confidence intervals (CIs) were estimated to determine the risk for lung dysfunction in quartiles 2–4 of the apoB/apoA-I ratio, with the lowest (1st) quartile as the reference group. We used three models to progressively adjust for potential confounders: model 1 was adjusted for age, sex, BMI, smoking status, heavy alcohol intake, regular exercise, and education level; model 2 was adjusted as for model 1 plus for mean BP (MBP), glucose, HbA1c, HOMA-IR, total cholesterol (TC), triglycerides (TG), HDL cholesterol, and LDL cholesterol; model 3 was adjusted as in model 2 plus for hsCRP and variables with P < 0.050 in univariate analyses. Because FVC(L) and FEV1(L) were strongly correlated (r = 0.943, P < 0.001), these parameters were assessed separately to avoid confounding effects. All tests were two-sided, and P values < 0.050 were considered statistically significant. Data were analyzed using IBM SPSS Statistics 24.0 (IBM Corp., Armonk, NY, USA).

Ethics statement

Ethics approvals for the study protocol and analyses of the data were obtained from the Institutional Review Board of Kangbuk Samsung Hospital (KBSMC 20223-07-046), and the requirement for informed consent was waived due to the use of de-identified data. The study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki, and followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.

RESULTS

Baseline characteristics of participants

Baseline characteristics of the 68,418 eligible subjects (50.9% male, 38.1 ± 7.0 years) are shown in Table 1. Mean BMI and apoB/apoA-I ratio were 23.0 ± 3.1 kg/m2 and 0.67 ± 0.21, respectively. When analyzed by quartiles of apoB/apoA-I ratio, we observed positive relationships between apoB/apoA-I ratio quartiles and age, BMI, hepatic enzyme levels, creatinine, TC, TG, LDL cholesterol, fasting glucose (FBS), HbA1c, HOMA-IR, hsCRP, BP and male sex, while there was a negative relationship between apoB/apoA-I ratio quartiles and HDL cholesterol (all P < 0.001). Regarding spirometric values, there was significant negative correlation between apoB/apoA-I ratio and all the spirometric values (FEV1(L), r = −0.253; FEV1%, r = −0.232; FVC(L), r = −0.299; FVC1%, r = −0.215 and FEV1/FVC ratio, r = −0.168 (all P < 0.001)). Furthermore, values of FEV1, FEV1%, FVC, FVC%, and FEV1/FVC ratio decreased significantly across increasing quartiles of apoB/apoA-I ratio (P < 0.001).

Table 1. Baseline characteristics of study participants by quartile of apoB/apoA-I ratio.

Characteristics All subjects (N = 68,418) Q1 ≤ 0.5135 (n = 17,084) Q2 (0.5136–0.6444) (n = 17,109) Q3 (0.6445–0.8050) (n = 17,118) Q4 (≥ 0.8051) (n = 17,107) P value
Age, yr 38.1 ± 7.0 36.26 ± 6.5 37.6 ± 6.8 38.8 ± 7.0 39.8 ± 7.0 < 0.001
Sex (male) 34,797 (50.9) 3,880 (22.7) 9,843 (40.0) 10,338 (60.4) 13,736 (80.3) < 0.001
Waist circumference, cm (n = 68,414) 79.6 ± 9.0 74.0 ± 7.5 77.6 ± 8.2 81.5 ± 8.3 85.4 ± 7.8 < 0.001
BMI, kg/m2 23.0 ± 3.1 21.3 ± 2.6 22.4 ± 2.8 23.5 ± 2.9 24.7 ± 2.8 < 0.001
Smoking, pack-years (n = 68,361) 2.74 ± 5.92 1.16 ± 3.82 1.96 ± 4.84 3.17 ± 6.28 4.67 ± 7.46 < 0.001
Amount of alcohol consumption, g/day 11.94 ± 18.91 10.92 ± 18.22a 10.94 ± 18.76a 12.24 ± 18.72 13.64 ± 19.80 < 0.001
Moderate physical activity frequency, times/week (n = 68,274) 0.86 ± 1.42 0.86 ± 1.47a,b,c 0.90 ± 1.46a,d 0.87 ± 1.41b,d 0.83 ± 1.34c < 0.001
High education (≥ college graduate) (n = 67,351) 56,721 (84.2) 13,857 (82.2) 14,166 (83.9) 14,275 (84.9) 14,423 (85.9) < 0.001
Total bilirubin, mg/dL (n = 68,409) 0.79 ± 0.36 0.76 ± 0.36 0.78 ± 0.36 0.81 ± 0.36 0.83 ± 0.36 < 0.001
ALT, U/L (n = 68,273) 16 (12–24) 13 (11–18) 15 (11–20) 17 (13–25) 23 (16–32) < 0.001
Serum creatinine, mg/dL 0.79 ± 0.17 0.71 ± 0.15 0.76 ± 0.17 0.82 ± 0.17 0.87 ± 0.16 < 0.001
Total cholesterol, mg/dL 191 ± 30 172 ± 25 184 ± 26 195 ± 27 212 ± 29 < 0.001
Triglycerides, mg/dL 86 (63–119) 66 (52–85) 76 (59–100) 93 (70–123) 121 (91–160) < 0.001
HDL cholesterol, mg/dL 63 ± 16 79 ± 15 67 ± 12 59 ± 10 49 ± 9 < 0.001
LDL cholesterol, mg/dL 122 ± 30 92 ± 18 114 ± 17 130 ± 19 152 ± 24 < 0.001
Fasting glucose, mg/dL 92.2 ± 8.2 90.3 ± 7.6 91.5 ± 8.1 93.0 ± 8.3 93.8 ± 8.2 < 0.001
HbA1c, % (n = 68,415) 5.4 ± 0.3 5.3 ± 0.3 5.4 ± 0.3 5.4 ± 0.3 5.5 ± 0.4 < 0.001
HOMA-IR (n = 68,392) 1.29 (0.90–1.81) 1.13 (0.79–1.57) 1.21 (0.85–1.69) 1.36 (0.95–1.89) 1.51 (1.08–2.05) < 0.001
hsCRP, mg/L (n = 68,001) 0.04 (0.03–0.07) 0.03 (0.02–0.05) 0.04 (0.02–0.06) 0.04 (0.03–0.08) 0.06 (0.03–0.10) < 0.001
Systolic BP, mmHg 107 ± 11 104 ± 10 106 ± 11 109 ± 11 111 ± 11 < 0.001
Diastolic BP, mmHg 69 ± 9 66 ± 8 68 ± 8 70 ± 9 72 ± 8 < 0.001
MBP 82 ± 9 79 ± 8 80 ± 9 83 ± 9 85 ± 9 < 0.001
Apo B, mg/dL 97 ± 23 72 ± 12 89 ± 11 103 ± 13 123 ± 17 < 0.001
ApoA-I, mg/dL 149 ± 24 169 ± 24 153 ± 19 143 ± 17 129 ± 16 < 0.001
ApoB/apoA-I ratio 0.67 ± 0.21 0.43 ± 0.06 0.58 ± 0.04 0.72 ± 0.05 0.96 ± 0.14 < 0.001
Measured FEV1(L) 3.31 ± 0.68 3.56 ± 0.64 3.40 ± 0.69 3.22 ± 0.69 3.06 ± 0.61 < 0.001
FEV1% 98.48 ± 10.69 99.56 ± 10.87 98.93 ± 10.77 98.25 ± 10.58 97.18 ± 10.37 < 0.001
Measured FVC(L) 4.01 ± 0.87 4.37 ± 0.80 4.14 ± 0.87 3.87 ± 0.87 3.64 ± 0.77 < 0.001
FVC% 98.86 ± 10.67 99.79 ± 10.95 99.25 ± 10.78 98.74 ± 10.56 97.66 ± 10.27 < 0.001
FEV1(L)/FVC(L) ratio 0.830 ± 0.059 0.846 ± 0.060 0.835 ± 0.060 0.823 ± 0.057 0.815 ± 0.053 < 0.001

Data are presented as means ± standard deviations, medians (interquartile ranges), or numbers of subjects with percentages in parentheses. We recorded subject numbers with available clinical parameters. Unless otherwise indicated, the available subject number was 68,418.

MBP = Diastolic BP (Average Systolic BP − Average Diastolic BP)/3.

ApoB/apoA-I = apolipoprotein B/apolipoprotein A-I, BMI = body mass index, ALT = alanine aminotransferase, HDL = high-density lipoprotein, LDL = low-density lipoprotein, HbA1c = hemoglobin A1c, HOMA-IR = homeostasis model assessment of insulin resistance, hsCRP = high-sensitivity C-reactive protein, BP = blood pressure, MBP = mean blood pressure, FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity, FEV1% = percent predicted forced expiratory volume in 1 second, FVC% = percent predicted forced vital capacity.

P values for one-way analysis of variance test. a,b,c,dThe same letter denotes no significant differences between the designated groups in post hoc analysis. Otherwise, differences among groups were significant after post hoc analyses (Bonferroni).

Lung function according to quartile of apoB/apoA-I ratio

A comparison of lung function parameters between study groups after adjusting for age, sex, BMI, smoking (pack-years), alcohol consumption (g/day), moderate physical activity frequency (times/week), MBP, glucose, HbA1c, HOMA-IR, lipid profiles, hepatic enzymes, creatinine, and hsCRP is provided in Table 2. The highest quartile group had the lowest FEV1(L), FEV1%, FVC(L), and FVC% values (P < 0.001). All these spirometric values were significantly different among groups (P < 0.001). However, FEV1/FVC ratio was similar among the four groups.

Table 2. Adjusted mean values of lung function parameters according to quartile of apolipoprotein B/apolipoprotein A-I ratio.

Characteristics Category P value by ANCOVA Adjusted P valuea
Q1 (≤ 0.5135) (n = 17,084) Q2 (0.5136–0.6444) (n = 17,109) Q3 (0.6445–0.8050) (n = 17,118) Q4 (≥ 0.8051) (n = 17,107) Q1 vs. Q2 Q1 vs. Q3 Q1 vs. Q4 Q1 vs. Q3 Q1 vs. Q4 Q1 vs. Q4
FEV1(L) 3.365 ± 0.004 3.343 ± 0.004 3.292 ± 0.004 3.237 ± 0.004 < 0.001 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
FEV1% 99.430 ± 0.087 98.806 ± 0.081 98.278 ± 0.081 97.424 ± 0.086 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001 < 0.001
FVC(L) 4.090 ± 0.005 4.058 ± 0.005 3.982 ± 0.005 3.906 ± 0.005 < 0.001 < 0.001 < 0.001 < 0.001 0.001 < 0.001 0.023
FVC% 99.741 ± 0.085 99.173 ± 0.080 98.746 ± 0.080 97.822 ± 0.085 < 0.001 0.016 < 0.001 < 0.001 0.001 < 0.001 < 0.001
FEV1(L)/FVC(L) ratio 0.831 ± 0.001 0.830 ± 0.001 0.829 ± 0.001 0.830 ± 0.001 0.059 1.000 0.382 1.000 0.763 1.000 0.694

Data are presented as adjusted means ± standard errors. The multivariable model was adjusted for age, sex, body mass index and continuous variables with P < 0.05 in univariate analyses, comprising smoking (pack-years), alcohol consumption (g/day), moderate physical activity frequency (times/week), mean blood pressure, glucose, hemoglobin A1c, homeostasis model assessment of insulin resistance, insulin, lipid profiles, liver enzymes, creatinine, and high-sensitivity C-reactive protein.

FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity, FEV1% = percent predicted forced expiratory volume in 1 second, FVC% = percent predicted forced vital capacity.

aAdjusted P value using Bonferroni correction.

Comparison of clinical and laboratory parameters between four groups stratified by quartile of apoB/apoA-I ratio

A comparison of clinical and laboratory characteristics among the four groups divided by quartiles of apoB/apoA-I ratio is provided in Table 3. Subjects in higher apoB/apoA-I ratio quartiles were male, older, more obese and more likely to smoke, and more subjects were highly educated. Furthermore, the prevalence of unfavorable metabolic parameters such as lipid profiles, FBS, HbA1c and HOMA-IR increased with increasing quartile of apoB/apoA-I ratio (P < 0.001). A significant increase in the prevalence of high MBP and hsCRP values according to quartile of apoB/apoA-I ratio was also observed (P < 0.001). The proportions of subjects with impaired lung function were also significantly higher in the highest quartile group than the other groups (P < 0.001). In contrast, more subjects exercised regularly in the lower apoB/apoA-I ratio quartiles.

Table 3. Comparison of demographic and clinical parameters among the four groups stratified by quartile of apolipoprotein B/apolipoprotein A-I ratio.

Characteristics All subjects (N = 68,418) Q1 (≤ 0.5135) (n = 17,084) Q2 (0.5136–0.6444) (n = 17,109) Q3 (0.6445–0.8050) (n = 17,118) Q4 (≥ 0.8051) (n = 17,107) P value
Age (≥ 38 yr) 33,301 (47.2) 6,462 (37.8) 7,594 (44.4) 8,717 (50.9) 9,528 (55.7) < 0.001
Sex (male) 34,797 (50.9) 3,880 (22.7) 9,843 (40.0) 10,338 (60.4) 13,736 (80.3) < 0.001
High waist circumferencea (n = 68,414) 13,494 (19.7) 1,672 (9.8) 2,652 (15.5) 3,932 (23.0) 5,238 (30.6) < 0.001
BMI (≥ 25 kg/m2) (obese) 16,095 (23.5) 1,427 (8.4) 2,714 (15.9) 4,671 (27.3) 7,283 (42.6) < 0.001
Current smokers 8,958 (13.1) 1,150 (6.7) 1,719 (10.0) 2,522 (14.7) 3,567 (20.9) < 0.001
Heavy alcohol intake (> 20 g/day) 11,417 (16.3) 2,427 (14.2) 2,466 (14.4) 2,914 (17.0) 3,340 (19.5) < 0.001
Regular exercise (≥ 3 times/week) (n = 68,274) 9,223 (13.5) 2,395 (14.0) 2,464 (14.4) 2,312 (13.5) 2,052 (12.0) < 0.001
Higher education (≥ college education) (n = 67,351) 56,721 (84.2) 13,857 (82.2) 14,166 (83.9) 14,275 (84.9) 14,423 (85.9) < 0.001
Elevated bilirubin (> 1.9 mg/dL) (n = 68,409) 959 (1.4) 231 (1.4) 235 (1.4) 251 (1.5) 242 (1.4) 0.816
Elevated ALT (> 40 U/L) (n = 68,273) 4,550 (6.7) 343 (2.0) 545 (3.2) 1,137 (6.7) 2,525 (14.8) < 0.001
Elevated serum creatinine (> 1.2 mg/dL) 141 (0.2) 16 (0.1) 14 (0.1) 46 (0.3) 65 (0.4) < 0.001
Hypercholesterolemia (≥ 220 mg/dL) 10,567 (15.4) 550 (3.2) 1,278 (7.5) 2,641 (15.4) 6,098 (35.6) < 0.001
Hypertriglyceridemia (≥ 150 mg/dL) 8,786 (12.8) 493 (2.9) 944 (5.5) 2,229 (13.0) 5,120 (29.9) < 0.001
Low HDL cholesterolb 13,091 (19.1) 148 (0.9) 712 (4.2) 2,848 (16.6) 9,383 (54.8) < 0.001
Hyper LDL cholesterol (≥ 159 mg/dL) 7,056 (10.3) 6 (0.0) 133 (0.8) 1,079 (6.3) 5,838 (34.1) < 0.001
Hyperglycemia at fasting (≥ 100 mg/dL) 7,899 (11.5) 1,291 (7.6) 1,665 (9.7) 2,342 (13.7) 2,601 (15.2) < 0.001
HbA1c (≥ 6.5) (n = 68,415) 144 (0.2) 11 (0.1) 23 (0.1) 44 (0.3) 66 (0.4) < 0.001
HOMA-IR ≥ 90th percentilec (n = 68,392) 6,888 (10.1) 1,004 (5.9) 1,384 (8.1) 2,000 (11.7) 2,500 (14.6) < 0.001
Elevated hsCRP (> 0.5 mg/L) (n = 68,001) 1,531 (2.3) 253 (1.5) 331 (1.9) 389 (2.3) 558 (3.3) < 0.001
MBPd (≥ 83 mmHg) 28,494 (41.6) 4,642 (27.2) 5,95 (34.7) 7,975 (46.6) 9,942 (58.1) < 0.001
FEV1% < LLNe 2,985 (4.4) 662 (3.9) 704 (4.1) 734 (4.3) 885 (5.2) < 0.001
FVC% < LLNe 3,081 (4.5) 735 (4.3) 736 (4.3) 753 (4.4) 857 (5.0) 0.003
FEV1(L)/FVC(L) ratio < LLNe 3,249 (4.7) 529 (3.1) 715 (4.2) 913 (5.3) 1,092 (6.4) < 0.001

Data are presented as means ± standard deviations, medians, and interquartile ranges, or the number of subjects with percentages in parentheses. We recorded subject numbers with available clinical parameters. Unless otherwise indicated, the available subject number was 73,795.

BMI = body mass index, ALT = alanine aminotransferase, HDL = high-density lipoprotein, LDL = low-density lipoprotein, HbA1c = hemoglobin A1c, HOMA-IR = homeostasis model assessment of insulin resistance, hsCRP = high-sensitivity C-reactive protein, MBP = mean blood pressure, FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity, FEV1% = percent predicted forced expiratory volume in 1 second, FVC% = percent predicted forced vital capacity, LLN = lower limit of normal.

aHigh waist circumference was defined as > 90 cm in males and > 85 cm in females.

bLow HDL was defined as < 40 mg/dL in males and < 50 mg/dL in females.

cThe value of HOMA-IR ≥ 90th percentile was 2.38.

dMBP = Diastolic BP (Average Systolic blood pressure − Average Diastolic blood pressure)/3.

eThe value of LLN was 81%, 82% and 73% in FEV1%, FVC% and FEV1(L)/FVC(L) ratio, respectively.

ORs for lung dysfunction by quartile of apoB/apoA-I ratio

To investigate the effect of apoB/apoA-I ratio on lung dysfunction, multiple logistic regression analysis was performed (Table 4). According to the fully adjusted logistic regression analysis, the aORs (95% CIs) for having FEV1% < LLN were 1.216 (1.094–1.351), 1.293 (1.156–1.448), and 1.481 (1.311–1.672) in respective quartiles 2–4 of the apoB/apoA-I ratio (P for trend < 0.001) Similarly, the aORs for having FVC% < LLN increased with increasing quartile of apoB/apoA-I ratio in a dose-dependent manner (P for trend < 0.001). However, the differences in aORs for OLF among groups were not statistically significant (P for trend = 0.273).

Table 4. Multiple logistic regression analysis of impaired lung function by quartile of apolipoprotein B/apolipoprotein A-I ratio.

Characteristics Model 1 Model 2 Model 3
OR (95% CI) P value P for trend OR (95% CI) P value P for trend OR (95% CI) P value P for trend
FEV1% < LLN < 0.001 < 0.001 < 0.001
Q1 (≤ 0.5135) (reference) 1.000 1.000 1.000
Q2 (0.5136–0.6444) 1.229 (1.109–1.361) < 0.001 1.220 (1.099–1.355) < 0.001 1.216 (1.094–1.351) < 0.001
Q3 (0.6445–0.8050) 1.326 (1.190–1.476) < 0.001 1.305 (1.167–1.460) < 0.001 1.293 (1.156–1.448) < 0.001
Q4 (≥ 0.8051) 1.507 (1.343–1.691) < 0.001 1.488 (1.319–1.679) < 0.001 1.481 (1.311–1.672) < 0.001
FVC% < LLN < 0.001 < 0.001 < 0.001
Q1 (≤ 0.5135) (reference) 1.000 1.000 1.000
Q2 (0.5136–0.6444) 1.263 (1.139–1.400) < 0.001 1.225 (1.102–1.362) < 0.001 1.212 (1.090–1.348) < 0.001
Q3 (0.6445–0.8050) 1.367 (1.228–1.522) < 0.001 1.303 (1.165–1.458) < 0.001 1.283 (1.147–1.436) < 0.001
Q4 (≥ 0.8051) 1.603 (1.431–1.796) < 0.001 1.520 (1.349–1.713) <0.001 1.502 (1.331–1.695) < 0.001
FEV1(L)/FVC(L) ratio < LLN 0.154 0.203 0.273
Q1 (≤ 0.5135) (reference) 1.000 1.000 1.000
Q2 (0.5136–0.6444) 1.026 (0.773–1.363) 0.857 1.030 (0.769–1.381) 0.841 1.005 (0.745–1.355) 0.975
Q3 (0.6445–0.8050) 1.174 (0.824–1.673) 0.373 1.164 (0.804–1.685) 0.422 1.122 (0.769–1.636) 0.551
Q4 (≥ 0.8051) 1.393 (0.997–1.947) 0.052 1.376 (0.971–1.949) 0.072 1.357 (0.952–1.935) 0.092

Model 1 was adjusted for age, sex, body mass index, smoking status, heavy alcohol intake, regular exercise, and education level. Model 2 was adjusted as in Model 1 plus for metabolic components including MBP, glucose, hemoglobin A1c, homeostasis model assessment of insulin resistance, total cholesterol, triglycerides, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. Model 3 was adjusted as in Model 2 plus high-sensitivity C-reactive protein and variables with a P value < 0.05 in the univariate analyses.

MBP = Diastolic Blood Pressure (Average Systolic Blood Pressure − Average Diastolic Blood Pressure)/3.

FEV1% = percent predicted forced expiratory volume in 1 second, FVC% = percent predicted forced vital capacity, LLN = lower limit of normal, FEV1 = forced expiratory volume in 1 second, FVC = forced vital capacity, MBP = mean blood pressure.

DISCUSSION

In our study, apoB/apoA-I ratio was associated with decreased FEV1 and FVC without OLF, in a large healthy population. To the best of our knowledge, this is the first study to investigate the effect of the apoB/apoA-I ratio on lung function in healthy subjects.

Dyslipidemia may have an adverse effect on lung function due to the associated LDL cholesterol-related endogenous oxidative burden and a decrease in anti-inflammatory activity with low HDL level.24,25 However, previous studies have reported mixed findings regarding the impact of dyslipidemia on lung function; some studies reported that dyslipidemia adversely affects lung function in population-based studies1,26 while other studies reported the opposite in patients with chronic obstructive pulmonary disease or other medical diseases.27,28,29 Furthermore, a recent meta-analysis stated that dyslipidemia was not related to lung function.30 However, careful consideration is required when assessing the relationship between dyslipidemia and lung function; previous studies included patients with preexisting CVMDs and pulmonary diseases, which are closely associated with both dyslipidemia25,31,32 and lung dysfunction.2,3,4,5,32 Additionally, reverse causality, whereby clinical disease causes cholesterol lowering, can result in a paradoxical association between LDL cholesterol and lung function in patients with medical diseases.33 And, HDL cholesterol can also become dysfunctional with a reduction in both cholesterol efflux and anti-inflammatory properties in the setting of disease, making it unable to protect tissue from the inflammatory effects of LDL cholesterol.24 Therefore, inclusion of patients with clinical diseases could have distorted the magnitude of the association between lung function and dyslipidemia.

In addition, differences in measurement of laboratory values may have contributed to the discrepant findings regarding the association between dyslipidemia and lung function. First, atherogenic cholesterol (LDL, IDL and VLDL concentrations) is a measure of the cholesterol content of lipoproteins. Because VLDL and IDL also have atherogenic potential, LDL cholesterol levels alone do not reflect the precise number of atherogenic lipoproteins.34 Second, there may be measurement error in LDL cholesterol, because it is routinely calculated using the Friedewald equation, which may give incorrect results under various circumstances.34 Lastly, the interaction between LDL cholesterol and HDL cholesterol should be considered to estimate the role of dyslipidemia in lung dysfunction. Taken together, LDL cholesterol and HDL cholesterol per se may not be adequate biomarkers of lung dysfunction. In contrast to lipoproteins, apoB is a better predictor of the precise number of atherogenic lipoproteins such as VLDL, IDL, and LDL, which each carry a single apo B molecule.34 ApoA-I has a strong association with HDL levels and represents the total amount of antiatherogenic particles present.34 Moreover, assays for apolipoproteins are standardized and accurate compared to those for LDL and HDL cholesterol. Consequently, the apoB/apoA-I ratio could be an ideal indicator of the interaction between atherogenic and antiatherogenic lipid particles and be able to capture most types of dyslipidemia by contrast to isolated lipid profiles, because a decreased apoA-I value potentiates the impact of apoB at all levels of apoB.35 Therefore, the apoB/apoA-I ratio in apparently healthy subjects can provide more valuable information about the effects of dyslipidemia on lung function than isolated lipid profiles.

Our findings are similar to the results of a previous study.36 However, in the previous study, FEV1 was inversely correlated with apoB/apoA-I ratio only in patients with atopy and asthma. Subjects with asthma could develop diaphragmatic weakness or other respiratory muscle impairment related to decreased lung function.37 Furthermore, dyslipidemia could be associated with an increased risk of asthma.38 This may have resulted in overestimation of the effect of the apoB/apoA-I ratio on lung function. Additionally, the previous study adjusted for only a few variables In contrast, we only included asymptomatic healthy subjects and minimized potential confounders. Thus, our results are more generalizable to the general population than those of the previous study.

Although the precise mechanisms by which the apoB/apoA-I ratio affects lung function remain unclear, the most likely mechanisms involve IR. A high apoB/apoA-I ratio is one of the key features of IR or metabolic syndrome,39 both of which are related to lung dysfunction.1,3,4,32 Increased lipolysis in peripheral adipose tissue in IR states and subsequent increased free fatty acid flux to the liver causes increased hepatic TG-rich VLDL production along with increased apoB level.40 Furthermore, IR results in TG enrichment of HDL particles along with release of lipid-poor apoA-I, which is degraded by proximal renal tubular cells.40 Therefore, IR states leads to a high apoB/apoA-I ratio. IR reduces glucose utilization and induces abnormal fat metabolism in skeletal muscles, possibly reducing skeletal muscle strength.41 As forced respiration during spirometry requires respiratory skeletal muscle contraction, IR could be an explanatory mechanism for our findings. Second, systemic inflammation could be an important mediator of high apoB/apoA-I ratio and lung dysfunction. High apoB/apoA-I ratio is linked to visceral fat accumulation,17 which is characterized by increased proinflammatory adipokines,32,39 leading to damage to the airways and a decline in lung function.32 Lastly, disruption of homeostatic maintenance of alveolar lipids can alter pulmonary (innate and adaptive) immune responses to the environment, increasing susceptibility to pathogens in the lung.25 Despite hypothetical mechanisms by which the apoB/apoA-I ratio affects lung function, we found no association between apoB/apoA-I ratio and OLF. Thus, our findings indicated a non-specific pattern that reflect reduced effort, a restrictive impairment, or an early consequence of small airway disease.23 However, our result is less likely caused by reduced effort, considering our study participant characteristics to be highly educated and asymptomatic. Therefore, our findings have important clinical implications, given the clinical significance of restrictive ventilatory impairment10,11 and small airway disease.42

Our study has several strengths and limitations. We showed that high apoB/apoA-I ratio was associated with decreased lung function, even in healthy individuals, supporting previous studies to show the importance of CVMDs for decreased lung function.2,3,4,5 Other strengths of our study are its large sample size, homogeneous population without overt clinical disease, and adjustments for multiple confounding factors. However, there are also several limitations to our study. First, neither causal relationships nor the underlying mechanisms linking apoB/apoA-I ratio and lung dysfunction could be determined because of the cross-sectional design of this study. Second, our results were obtained in a middle aged Korean health screening cohort. Therefore, these findings cannot be generalized to other racial or ethnic populations. Third, it is possible that some subjects had undetected CVMDs and pulmonary diseases because of the questionnaire-based collection of medical histories. Furthermore, lack of information on family history of these diseases might affect the outcomes because of a possible risk of cardiovascular and respiratory diseases in offspring.43,44 This may be significant, as these subclinical diseases can contribute to lung dysfunction, especially among individuals with dyslipidemia.1,2,3,4,5,25,31,32,45 Fourth, our LLN values were classified as the bottom 5% of the study population because those for a Korean population have not been decided till now. Thus, our LLN values might be different from those defined as the 5th percentile of a normal healthy Korean population.23 Therefore, our finding should be validated by future study using LLN values from a normal healthy population.23 Finally, our findings may have been affected by regression dilution bias, because a single measurement contains noise (i.e., random error), relative to the usual, long-term average level.

In conclusion, we found that high apoB/apoA-I ratio was associated with decreased lung function. This finding supports the importance of CVMD risk for reduced lung function. However, longitudinal follow-up studies and prospective interventional studies are needed to validate our findings.

ACKNOWLEDGMENTS

We would like to thank the staff members of Kangbuk Samsung Health Study for their hard work, dedication, and continuing support.

Footnotes

Funding: This work was supported by a research grant from Jeju National University Hospital in 2023.

Disclosure: The authors have no potential conflicts of interest to disclose.

Data Availability Statement: The data are not publicly available outside of the hospital because of Institutional Review Board restrictions (data were not collected in a way that could be distributed widely). However, the analytical methods are available from the corresponding author upon request.

Author Contributions:
  • Conceptualization: Song JU.
  • Data curation: Song JU.
  • Formal analysis: Lee J, Park HK, Song JU.
  • Funding acquisition: Lee J.
  • Investigation: Song JU.
  • Methodology: Lee J, Park HK, Kwon MJ, Song JU.
  • Project administration: Lee J, Song JU.
  • Resources: Song JU.
  • Software: Lee J, Song JU.
  • Supervision: Song JU.
  • Validation: Kwon MJ, Ham SY, Lim SY, Song JU.
  • Visualization: Ham SY, Gil HI, Song JU.
  • Writing - original draft: Lee J, Park HK, Song JU.
  • Writing - review & editing: Lee J, Park HK, Kwon MJ, Ham SY, Gil HI, Lim SY, Song JU.

References

  • 1.Leone N, Courbon D, Thomas F, Bean K, Jégo B, Leynaert B, et al. Lung function impairment and metabolic syndrome: the critical role of abdominal obesity. Am J Respir Crit Care Med. 2009;179(6):509–516. doi: 10.1164/rccm.200807-1195OC. [DOI] [PubMed] [Google Scholar]
  • 2.Sin DD, Wu L, Man SF. The relationship between reduced lung function and cardiovascular mortality: a population-based study and a systematic review of the literature. Chest. 2005;127(6):1952–1959. doi: 10.1378/chest.127.6.1952. [DOI] [PubMed] [Google Scholar]
  • 3.Engström G, Hedblad B, Nilsson P, Wollmer P, Berglund G, Janzon L. Lung function, insulin resistance and incidence of cardiovascular disease: a longitudinal cohort study. J Intern Med. 2003;253(5):574–581. doi: 10.1046/j.1365-2796.2003.01138.x. [DOI] [PubMed] [Google Scholar]
  • 4.Lim SY, Rhee EJ, Sung KC. Metabolic syndrome, insulin resistance and systemic inflammation as risk factors for reduced lung function in Korean nonsmoking males. J Korean Med Sci. 2010;25(10):1480–1486. doi: 10.3346/jkms.2010.25.10.1480. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bae MS, Han JH, Kim JH, Kim YJ, Lee KJ, Kwon KY. The relationship between metabolic syndrome and pulmonary function. Korean J Fam Med. 2012;33(2):70–78. doi: 10.4082/kjfm.2012.33.2.70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Mannino DM, Buist AS, Petty TL, Enright PL, Redd SC. Lung function and mortality in the United States: data from the First National Health and Nutrition Examination Survey follow up study. Thorax. 2003;58(5):388–393. doi: 10.1136/thorax.58.5.388. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Çolak Y, Afzal S, Nordestgaard BG, Lange P, Vestbo J. Importance of early COPD in young adults for development of clinical COPD: findings from the Copenhagen General Population Study. Am J Respir Crit Care Med. 2021;203(10):1245–1256. doi: 10.1164/rccm.202003-0532OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Davidson MH. Apolipoprotein measurements: is more widespread use clinically indicated? Clin Cardiol. 2009;32(9):482–486. doi: 10.1002/clc.20559. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Ross R. Atherosclerosis--an inflammatory disease. N Engl J Med. 1999;340(2):115–126. doi: 10.1056/NEJM199901143400207. [DOI] [PubMed] [Google Scholar]
  • 10.Shaaban R, Kony S, Driss F, Leynaert B, Soussan D, Pin I, et al. Change in C-reactive protein levels and FEV1 decline: a longitudinal population-based study. Respir Med. 2006;100(12):2112–2120. doi: 10.1016/j.rmed.2006.03.027. [DOI] [PubMed] [Google Scholar]
  • 11.Walldius G, Jungner I. The apoB/apoA-I ratio: a strong, new risk factor for cardiovascular disease and a target for lipid-lowering therapy--a review of the evidence. J Intern Med. 2006;259(5):493–519. doi: 10.1111/j.1365-2796.2006.01643.x. [DOI] [PubMed] [Google Scholar]
  • 12.Jung CH, Hwang JY, Shin MS, Yu JH, Kim EH, Bae SJ, et al. Association of apolipoprotein b/apolipoprotein A1 ratio and coronary artery stenosis and plaques detected by multi-detector computed tomography in healthy population. J Korean Med Sci. 2013;28(5):709–716. doi: 10.3346/jkms.2013.28.5.709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Lee J, Park HK, Kwon MJ, Ham SY, Gil HI, Lim SY, et al. The impact of insulin resistance on the association between metabolic syndrome and lung function: the Kangbuk Samsung Health Study. Diabetol Metab Syndr. 2023;15(1):65. doi: 10.1186/s13098-023-01042-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Kim BY, Kang SM, Kang JH, Kang SY, Kim KK, Kim KB, et al. 2020 Korean Society for the Study of Obesity guidelines for the management of obesity in Korea. J Obes Metab Syndr. 2021;30(2):81–92. doi: 10.7570/jomes21022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Jung CH, Lee WJ, Song KH. Metabolically healthy obesity: a friend or foe? Korean J Intern Med. 2017;32(4):611–621. doi: 10.3904/kjim.2016.259. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Chang Y, Kim BK, Yun KE, Cho J, Zhang Y, Rampal S, et al. Metabolically-healthy obesity and coronary artery calcification. J Am Coll Cardiol. 2014;63(24):2679–2686. doi: 10.1016/j.jacc.2014.03.042. [DOI] [PubMed] [Google Scholar]
  • 17.Hwang YC, Ahn HY, Kim WJ, Park CY, Park SW. Increased apoB/A-I ratio independently associated with type 2 diabetes mellitus: cross-sectional study in a Korean population. Diabet Med. 2012;29(9):1165–1170. doi: 10.1111/j.1464-5491.2012.03622.x. [DOI] [PubMed] [Google Scholar]
  • 18.World Health Organization. The Asia-Pacific Perspective: Redefining Obesity and Its Treatment. Geneva, Switzerland: World Health Organization; 2000. [Google Scholar]
  • 19.Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985;28(7):412–419. doi: 10.1007/BF00280883. [DOI] [PubMed] [Google Scholar]
  • 20.Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. Eur Respir J. 2005;26(2):319–338. doi: 10.1183/09031936.05.00034805. [DOI] [PubMed] [Google Scholar]
  • 21.Choi HS, Park YB, Yoon HK, Lim SY, Kim TH, Park JH, et al. Validation of previous spirometric reference equations and new equations. J Korean Med Sci. 2019;34(47):e304. doi: 10.3346/jkms.2019.34.e304. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Hong Y, Ra SW, Shim TS, Lim CM, Koh Y, Lee SD, et al. Poor interpretation of pulmonary function tests in patients with concomitant decreases in FEV1 and FVC. Respirology. 2008;13(4):569–574. doi: 10.1111/j.1440-1843.2008.01274.x. [DOI] [PubMed] [Google Scholar]
  • 23.Stanojevic S, Kaminsky DA, Miller MR, Thompson B, Aliverti A, Barjaktarevic I, et al. ERS/ATS technical standard on interpretive strategies for routine lung function tests. Eur Respir J. 2022;60(1):2101499. doi: 10.1183/13993003.01499-2021. [DOI] [PubMed] [Google Scholar]
  • 24.Gordon EM, Figueroa DM, Barochia AV, Yao X, Levine SJ. High-density lipoproteins and apolipoprotein A-I: potential new players in the prevention and treatment of lung disease. Front Pharmacol. 2016;7:323. doi: 10.3389/fphar.2016.00323. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Gowdy KM, Fessler MB. Emerging roles for cholesterol and lipoproteins in lung disease. Pulm Pharmacol Ther. 2013;26(4):430–437. doi: 10.1016/j.pupt.2012.06.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Cirillo DJ, Agrawal Y, Cassano PA. Lipids and pulmonary function in the Third National Health and Nutrition Examination Survey. Am J Epidemiol. 2002;155(9):842–848. doi: 10.1093/aje/155.9.842. [DOI] [PubMed] [Google Scholar]
  • 27.Huerta-Ramírez S, Paniagua-Pérez A, Castro-Serna D, Ledesma-Velázquez A, Rubio-Guerra A, Vargas-Ayala G. Effect of the components of the metabolic syndrome on pulmonary function. The unexpected role of high-density lipoprotein cholesterol. Cir Cir. 2018;86(2):175–181. doi: 10.24875/CIRU.M18000030. [DOI] [PubMed] [Google Scholar]
  • 28.Freyberg J, Landt EM, Afzal S, Nordestgaard BG, Dahl M. Low-density lipoprotein cholesterol and risk of COPD: Copenhagen General Population Study. ERJ Open Res. 2023;9(2):00496-2022. doi: 10.1183/23120541.00496-2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Kahnert K, Lucke T, Huber RM, Behr J, Biertz F, Vogt A, et al. Relationship of hyperlipidemia to comorbidities and lung function in COPD: results of the COSYCONET cohort. PLoS One. 2017;12(5):e0177501. doi: 10.1371/journal.pone.0177501. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Fang NN, Wang ZH, Li SH, Ge YY, Liu X, Sui DX. Pulmonary function in metabolic syndrome: a meta-analysis. Metab Syndr Relat Disord. 2022;20(10):606–617. doi: 10.1089/met.2022.0045. [DOI] [PubMed] [Google Scholar]
  • 31.Arvanitis M, Lowenstein CJ. Dyslipidemia. Ann Intern Med. 2023;176(6):ITC81–ITC96. doi: 10.7326/AITC202306200. [DOI] [PubMed] [Google Scholar]
  • 32.Baffi CW, Wood L, Winnica D, Strollo PJ, Jr, Gladwin MT, Que LG, et al. Metabolic syndrome and the lung. Chest. 2016;149(6):1525–1534. doi: 10.1016/j.chest.2015.12.034. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Iribarren C, Reed DM, Chen R, Yano K, Dwyer JH. Low serum cholesterol and mortality. Which is the cause and which is the effect? Circulation. 1995;92(9):2396–2403. doi: 10.1161/01.cir.92.9.2396. [DOI] [PubMed] [Google Scholar]
  • 34.Andrikoula M, McDowell IF. The contribution of ApoB and ApoA1 measurements to cardiovascular risk assessment. Diabetes Obes Metab. 2008;10(4):271–278. doi: 10.1111/j.1463-1326.2007.00714.x. [DOI] [PubMed] [Google Scholar]
  • 35.Walldius G, de Faire U, Alfredsson L, Leander K, Westerholm P, Malmström H, et al. Long-term risk of a major cardiovascular event by apoB, apoA-1, and the apoB/apoA-1 ratio-Experience from the Swedish AMORIS cohort: a cohort study. PLoS Med. 2021;18(12):e1003853. doi: 10.1371/journal.pmed.1003853. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Barochia AV, Kaler M, Cuento RA, Gordon EM, Weir NA, Sampson M, et al. Serum apolipoprotein A-I and large high-density lipoprotein particles are positively correlated with FEV1 in atopic asthma. Am J Respir Crit Care Med. 2015;191(9):990–1000. doi: 10.1164/rccm.201411-1990OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Visser E, de Jong K, van Zutphen T, Kerstjens HA, Ten Brinke A. Muscle function in moderate to severe asthma: association with clinical outcomes and inflammatory markers. J Allergy Clin Immunol Pract. 2023;11(5):1439–1447.e3. doi: 10.1016/j.jaip.2022.12.043. [DOI] [PubMed] [Google Scholar]
  • 38.Lim JE, Kim HM, Kim JH, Baek HS, Han MY. Association between dyslipidemia and asthma in children: A systematic review and multicenter cohort study using a common data model. Clin Exp Pediatr. 2023;66(8):357–365. doi: 10.3345/cep.2023.00290. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Sniderman AD, Faraj M. Apolipoprotein B, apolipoprotein A-I, insulin resistance and the metabolic syndrome. Curr Opin Lipidol. 2007;18(6):633–637. doi: 10.1097/MOL.0b013e3282f0dd33. [DOI] [PubMed] [Google Scholar]
  • 40.Rashid S, Patterson BW, Lewis GF. Thematic review series: patient-oriented research. What have we learned about HDL metabolism from kinetics studies in humans? J Lipid Res. 2006;47(8):1631–1642. doi: 10.1194/jlr.R600008-JLR200. [DOI] [PubMed] [Google Scholar]
  • 41.Barzilay JI, Cotsonis GA, Walston J, Schwartz AV, Satterfield S, Miljkovic I, et al. Insulin resistance is associated with decreased quadriceps muscle strength in nondiabetic adults aged >or=70 years. Diabetes Care. 2009;32(4):736–738. doi: 10.2337/dc08-1781. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.McDonough JE, Yuan R, Suzuki M, Seyednejad N, Elliott WM, Sanchez PG, et al. Small-airway obstruction and emphysema in chronic obstructive pulmonary disease. N Engl J Med. 2011;365(17):1567–1575. doi: 10.1056/NEJMoa1106955. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Gyawali S, López-Cervantes JP, Johannessen A, Gislason T, Holm M, Janson C, et al. Maternal and paternal tuberculosis is associated with increased asthma and respiratory symptoms in their offspring: a study from Northern Europe. Front Allergy. 2023;4:1193141. doi: 10.3389/falgy.2023.1193141. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Weijmans M, van der Graaf Y, Reitsma JB, Visseren FL. Paternal or maternal history of cardiovascular disease and the risk of cardiovascular disease in offspring. A systematic review and meta-analysis. Int J Cardiol. 2015;179:409–416. doi: 10.1016/j.ijcard.2014.11.017. [DOI] [PubMed] [Google Scholar]
  • 45.Pellegrino R, Viegi G, Brusasco V, Crapo RO, Burgos F, Casaburi R, et al. Interpretative strategies for lung function tests. Eur Respir J. 2005;26(5):948–968. doi: 10.1183/09031936.05.00035205. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Korean Medical Science are provided here courtesy of Korean Academy of Medical Sciences

RESOURCES