Abstract
Background/Objectives: Oxidative stress, an imbalance between oxidants and antioxidants, is known to affect pulmonary function (PF), thereby leading to the development of chronic obstructive pulmonary disease (COPD). However, data on the associations of serum vitamin A and E concentrations with PF parameters and COPD are inconsistent. The present cross-sectional study aimed to investigate these associations, considering inflammatory status. Participants/Methods: This study included 2005 male and female adults aged ≥40 years who had participated in a population-based national survey. Spirometry without a bronchodilator was conducted to yield PF parameters, such as forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and the FEV1/FVC ratio, which were used to define COPD. Serum vitamin A (retinol) and E (α-tocopherol) concentrations were assayed. Multivariable regression analysis was performed after adjusting for potential confounding variables. Results: Serum vitamin A concentration was positively associated with FEV1 (p for trend < 0.01) among all participants. In addition, the odds ratio (95% confidence interval) of the highest serum vitamin A concentration tertile for the prevalence of COPD, which was defined by the FEV1/FVC ratio < 0.7, was 0.53 (0.31, 0.90) compared with that of the lowest tertile (p for trend < 0.05). Analysis stratified by a cutoff point of 1 mg/L serum high-sensitivity C-reactive protein (hs-CRP) revealed that such associations with FEV1 and COPD prevalence were stronger in participants with lower hs-CRP levels (p for trend < 0.05). In contrast, serum vitamin E concentration was associated with neither PF parameters nor COPD prevalence. Conclusions: These findings suggest that serum vitamin A concentration may be important in preventing the progressive decline in PF parameters that results in COPD. Further epidemiological investigations are warranted to evaluate the causal associations of antioxidant vitamin status with PF parameters and COPD.
Keywords: vitamin A, vitamin E, pulmonary function tests, chronic obstructive pulmonary disease
1. Introduction
Chronic obstructive pulmonary disease (COPD) is a common pulmonary disease characterized by progressive airflow limitation, leading to breathing difficulties. The global prevalence of COPD was estimated to be approximately 10% among adults aged 30–79 years in 2019 [1]. Similarly, the prevalence of COPD was reportedly 12.9% among Korean adults aged ≥40 years [2]. In older adults aged ≥70 years, both reports estimated a notable prevalence more than double the overall prevalence [1,2]. As the older population increases, COPD is emerging as a significant and escalating public health problem worldwide.
Smoking, air pollution, and occupational exposure to dust or smoke are well-known major factors for the increased risk of developing COPD [1,3]. These risk factors presumably induce an imbalance between oxidants and antioxidants, thereby aggravating oxidative stress, which is ostensibly integral to the pathogenesis of COPD [4]. In contrast, endogenous and exogenous (dietary) antioxidants exert protective effects against oxidative stress; therefore, antioxidant status is further expected to be positively associated with pulmonary function (PF) and inversely associated with the risk of COPD [4]. In fact, a meta-analysis analyzing accumulated data on the association of dietary antioxidants with COPD symptoms and outcomes observed a significantly inverse association for vitamins C and E, but no association for vitamin A [5]. Epidemiological data on the association of the blood concentrations of these vitamins, which are objective markers of vitamin status, with PF and COPD prevalence are inconsistent [6,7,8,9,10,11,12,13]. Discrepancies in these findings may partly emanate from a lack of the following considerations: features of impaired PF (obstructive or non-obstructive patterns), inflammatory status, dietary supplementation, and the adjustment of total energy intake, which appear to be a potential confounder because COPD is accompanied by an energy imbalance owing to a reduced dietary intake and an increased resting energy expenditure [14].
The present study focused on serum vitamin A (retinol) and E (α-tocopherol) concentrations because these two antioxidant vitamins were exclusively analyzed in a national survey, whose data we utilized, to investigate their associations with PF parameters and COPD based on the evaluation of obstructive and non-obstructive patterns. In this analysis, the concentration of serum high-sensitivity C-reactive protein (hs-CRP), which is a marker of systemic inflammation, was considered as a confounder and an effect modifier, and dietary supplementation and total energy intake as confounding variables.
2. Participants and Methods
2.1. Participants
The study participants were male and female adults aged ≥40 years from the Korea National Health and Nutrition Examination Survey (KNHANES) conducted in the 7th survey period (2016–2018). The KNHANES, a population-based, cross-sectional survey that employs a complex stratified sampling design, is conducted by the Korea Disease Control and Prevention Agency (https://knhanes.kdca.go.kr/knhanes/ (accessed on 20 August 2024)). KNHANES participants comprised noninstitutionalized Korean citizens residing in South Korea who had signed an informed consent form [15]. In a total of 21,273 participants from the 7th KNHANES (n = 7042 in 2016, n = 7167 in 2017, and n = 7064 in 2018), 12,225 were eligible adults aged ≥ 40 years. After excluding individuals who had not undergone PF testing (n = 3830) or had not reported ≥ 8 h of fasting before blood sample collection for serum vitamin A and E concentration assays (n = 5597), those who had been diagnosed with chronic diseases (n = 422), such as COPD (n = 21), asthma (n = 70), pulmonary tuberculosis (n = 102), lung cancer (n = 4), stroke (n = 38), cardiovascular disease (n = 59), renal failure (n = 4), liver cirrhosis (n = 11), and cancer (n = 113), by a physician were excluded to eliminate the effects of chronic diseases on serum vitamin concentrations. In addition, individuals who had been found to have non-obstructive lung disease (restrictive pattern PF) based on the PF test (n = 294) or had not reported information (missing data) on smoking, alcohol consumption, or other confounding variables (n = 77) were excluded. Finally, data for 2005 participants (829 men and 1176 women) were analyzed. The present study was approved by the Institutional Review Board of Kookmin University (approval number: KMU-202102-HR-260).
2.2. Definition of Pulmonary Function Parameters
In the KNHANES, only participants aged ≥40 years underwent PF testing; the procedure and quality control has been described in a report [16]. Briefly, trained personnel conducted PF testing using a spirometer (a dry rolling seal spirometer was used until June 2016, after which a Vyntus™ SPIRO spirometer [CareFusion, San Diego, CA, USA] was employed) without a bronchodilator (post-bronchodilator testing was not performed in the KNHANES) and generated PF parameters, including forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and the FEV1/FVC ratio, which were utilized as analysis outcomes. In the KNHANES, three PF classifications were defined based on the test results as follows: (1) normal PF (FEV1/FVC ≥ 0.7 and FVC ≥ 80% of the predicted value), (2) a restrictive pattern of impaired PF (FEV1/FVC ≥ 0.7 and FVC < 80% of the predicted value), and (3) an obstructive pattern of impaired PF (FEV1/FVC < 0.7) [17]. Among the participants who had been diagnosed with impaired PF, those with an obstructive pattern were exclusively included and considered as COPD cases [18].
2.3. Serum Vitamin A and E and High-Sensitivity C-Reactive Protein Assay
Serum concentrations of vitamins A (retinol) and E (α-tocopherol) were assayed using the Agilent 1200 high-pressure liquid chromatography (HPLC) system (Agilent, Santa Clara, CA, USA) and HPLC reagent kits (Chromsystems, Gräfelfing, Germany) and hs-CRP levels using the Cobas Analyzer (Roche Diagnostics, Indianapolis, IN, USA) by a commercial laboratory that performed quality control tests [19].
2.4. Potential Confounding Variables and an Effect Modifier
Data on demographic and health-related characteristics including age, sex, residential district, educational level, household income level, body mass index (BMI) calculated by dividing body weight (kg) by the square of the height (m), smoking status, alcohol consumption, coffee consumption, regular physical activity (defined based on the performance of medium-intensity physical activity for ≥2 h 30 min per week or that of high-intensity physical activity for ≥1 h 15 min), total calorie intake, and dietary supplementation (vitamins, minerals, and functional foods) were collected from questionnaire-based data, and considered to be potential confounding variables in the analysis. In addition, serum hs-CRP concentration was used as a confounder and an effect modifier in the analysis because it was reportedly associated with antioxidant status and COPD [20,21].
2.5. Statistical Analysis
According to the serum vitamin A and E concentration tertile groups, descriptive statistics were obtained with consideration of sampling weight and presented as the mean ± standard error (SE) or percentage. Statistical differences between groups were evaluated using analysis of variance and the chi-square test for continuous and categorical variables, respectively. To analyze the associations between serum vitamin concentrations and PF parameters, linear regression analysis was performed with consideration of sampling weight and potential confounding variables to obtain regression coefficient estimates and their SEs. To satisfy the normality assumption, each PF parameter was squared and fitted as a dependent variable in the model based on the variable transformation results. In the multivariable models, age, BMI, total calorie intake, and hs-CRP level were fitted as continuous variables, while sex, residential district (rural, urban), educational level (middle school or lower, high school or higher), household income level (low and lower-middle, upper-middle and high), smoking status (abstainer, current smoker [two categories: <20, ≥20 pack-years]), alcohol consumption (abstainer, drinker), coffee consumption (non-consumer, consumer), regular physical activity (no, yes), and dietary supplementation (no, yes) were fitted as categorical variables. Additionally, multivariable association analysis, stratified by serum hs-CRP level (≤1, >1 mg/L), was conducted. To analyze the association between serum vitamin concentrations and COPD prevalence, logistic regression analysis was performed with consideration of sampling weight and previously mentioned potential confounding variables to obtain odds ratios (ORs) and 95% confidence intervals (CIs).
Statistical analyses were performed using SAS v.9.4 software (SAS Institute Inc., Cary, NC, USA). Statistical significance was set at p < 0.05.
3. Results
3.1. Characteristics of the Study Participants
Among 2005 study participants, 224 (weighted prevalence: 9.9%) were observed to have impaired PF, especially obstructive pattern PF. The study participants were compared among serum vitamin A and E concentration tertiles (Table 1). Participants in the lowest serum vitamin A tertile were more likely to be women, leaner, current non-smokers, and current non-drinkers of alcohol, as well as to consume fewer calories and exhibit higher serum hs-CRP concentrations. However, those in the lowest serum vitamin E tertile were more likely to be men, consume fewer dietary supplements, and exhibit lower serum hs-CRP concentrations.
Table 1.
Characteristics of 2005 study participants according to the tertiles of serum vitamin A (retinol) and E (α-tocopherol) concentrations.
| Variables | All | Serum Vitamin A Tertiles (T) [Median] | p Value | Serum Vitamin E Tertiles (T) [Median] | p Value | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1st T [0.37] | 2nd T [0.51] | 3rd T [0.69] | 1st T [10.09] | 2nd T [13.54] | 3rd T [18.43] | |||||
| Age, years | 54.0 ± 0.25 | 53.2 ± 0.45 | 54.7 ± 0.41 | 54.3 ± 0.42 | 0.091 | 53.5 ± 0.46 | 53.5 ± 0.46 | 54.6 ± 0.37 | 0.067 | |
| Men, % | 48.5 | 28.4 | 49.4 | 66.2 | <0.001 | 52.8 | 50.1 | 42.6 | <0.01 | |
| Residential district | Urban | 85.9 | 86.0 | 87.3 | 84.5 | 88.4 | 84.1 | 85.1 | 0.097 | |
| Rural | 14.1 | 14.0 | 12.8 | 15.6 | 11.6 | 16.0 | 14.9 | |||
| Educational level | ≤Middle school | 26.1 | 23.7 | 28.4 | 26.2 | 0.233 | 25.6 | 22.7 | 30.2 | <0.05 |
| ≥High school | 73.9 | 76.3 | 71.6 | 73.8 | 74.5 | 77.3 | 69.8 | |||
| Low household income level 1, % | 35.2 | 34.9 | 37.4 | 33.4 | 0.375 | 37.4 | 32.2 | 35.8 | 0.240 | |
| Body mass index, kg/m2 | 24.1 ± 0.08 | 23.8 ± 0.14 | 24.1 ± 0.13 | 24.4 ± 0.15 | <0.01 | 23.9 ± 0.16 | 24.1 ± 0.13 | 24.3 ± 0.13 | 0.129 | |
| Current smoker, % | 20.1 | 8.9 | 17.3 | 33.1 | <0.001 | 21.7 | 18.0 | 20.6 | 0.362 | |
| Pack-years of cigarettes 2 | 18.8 ± 0.6 | 16.6 ± 1.39 | 18.1 ± 1.04 | 20.0 ± 0.86 | 0.767 | 19.5 ± 1.11 | 18.4 ± 0.91 | 18.2 ± 1.02 | 0.311 | |
| Current alcohol drinker, % | 57.7 | 45.8 | 56.9 | 69.4 | <0.001 | 58.7 | 59.2 | 55.2 | 0.378 | |
| Coffee consumer, % | 57.5 | 54.1 | 58.9 | 59.4 | 0.166 | 58.8 | 56.5 | 57.2 | 0.759 | |
| Regular physical activity 3, % | 47.0 | 47.2 | 47.0 | 46.7 | 0.989 | 44.9 | 47.8 | 48.3 | 0.494 | |
| Total energy intake, kcal/day | 2042.6 ± 24.34 | 1904.9 ± 38.29 | 2029.3 ± 40.6 | 2181.5 ± 43.73 | <0.001 | 2073.0 ± 41.12 | 2057.3 ± 41.54 | 1996.6 ± 39.73 | 0.154 | |
| Dietary supplementation, % | 55.5 | 55.3 | 55.5 | 55.5 | 0.982 | 47.1 | 57.2 | 62.5 | <0.001 | |
| Serum hs-CRP, mg/L | 1.06 ± 0.05 | 1.33 ± 0.13 | 0.92 ± 0.05 | 0.93 ± 0.05 | <0.001 | 0.89 ± 0.06 | 1.05 ± 0.07 | 1.25 ± 0.11 | <0.001 | |
| Impaired pulmonary disease, % | 9.94 | 10.07 | 9.82 | 9.93 | 0.990 | 11.51 | 8.14 | 10.13 | 0.169 | |
Abbreviations: hs-CRP, high-sensitivity C-reactive protein. Values are presented as the mean ± standard error or %. 1 Participants whose household income is lower than median; 2 calculated in current smokers; 3 defined based on the performance of medium-intensity physical activity for ≥2 h 30 min per week or that of high-intensity physical activity for ≥1 h 15 min.
3.2. Associations between Serum Vitamin Concentrations and PF Parameters
Table 2 shows the associations of serum vitamin A and E concentrations with PF parameters. Positive associations of serum vitamin A concentration with FEV1 (p for trend < 0.01) and FVC (p for trend = 0.061) were observed in the multivariable models. However, no associations between serum vitamin E concentration and PF parameters were observed.
Table 2.
Associations of serum vitamin concentrations with lung function parameters among all participants.
| Variables | Estimates ± SEs across Vitamin Concentration Tertiles (T) | p for Trend across the Tertiles | ||
|---|---|---|---|---|
| 1st T | 2nd T | 3rd T | ||
| Across serum vitamin A concentration | ||||
| FEV1 | ||||
| Age- and sex-adjusted model | Reference | 0.0150 ± 0.0241 | 0.0614 ± 0.0271 * | < 0.05 |
| Multivariable model | Reference | 0.0165 ± 0.0238 | 0.0710 ± 0.0274 ** | < 0.01 |
| FVC | ||||
| Age- and sex-adjusted model | Reference | −0.0171 ± 0.0267 | 0.0555 ± 0.0312 | 0.057 |
| Multivariable model | Reference | −0.0156 ± 0.0265 | 0.0560 ± 0.0321 | 0.061 |
| FEV1/FVC | ||||
| Age- and sex-adjusted model | Reference | 0.0088 ± 0.0056 | 0.0057 ± 0.0066 | 0.456 |
| Multivariable model | Reference | 0.0089 ± 0.0056 | 0.0092 ± 0.0067 | 0.204 |
| Across serum vitamin E concentration | ||||
| FEV1 | ||||
| Age- and sex-adjusted model | Reference | 0.0607 ± 0.0244 * | 0.0006 ± 0.0253 | 0.823 |
| Multivariable model | Reference | 0.0493 ± 0.0243 * | −0.0086 ± 0.0263 | 0.580 |
| FVC | ||||
| Age- and sex-adjusted model | Reference | 0.0390 ± 0.0303 | −0.0031 ± 0.0276 | 0.805 |
| Multivariable model | Reference | 0.0297 ± 0.0301 | −0.0112 ± 0.0286 | 0.596 |
| FEV1/FVC | ||||
| Age- and sex-adjusted model | Reference | 0.0113 ± 0.0058 | 0.0008 ± 0.0059 | 0.960 |
| Multivariable model | Reference | 0.0101 ± 0.0058 | 0.0001 ± 0.0058 | 0.843 |
Abbreviations: FEV1, forced expiratory volume in one second; FVC, forced vital capacity. The multivariate models include age, sex, body mass index, residential district (urban, rural), educational level (≤middle school, ≥high school), household income level (low, high), smoking status (abstainer, current smoker [two categories: <20, ≥20 pack-years]), alcohol consumption (abstainer, current drinker), coffee consumption (non-consumer, consumer), regular physical activity (no, yes), dietary supplementation (no, yes), total energy intake, and serum hs-CRP levels. * p < 0.05 and ** p < 0.01.
3.3. Associations between Serum Vitamin Concentrations and PF Parameters Stratified by Serum hs-CRP Levels
As shown in Table 3, which displays the association results stratified by serum hs-CRP level, serum vitamin A concentration was significantly associated with FEV1 exclusively in participants with hs-CRP levels ≤ 1 mg/L, indicating a low systemic inflammatory state (p for trend < 0.05). However, stratified analysis revealed no associations between serum vitamin E concentration and PF parameters.
Table 3.
Multivariable associations between serum vitamin A and E concentrations and pulmonary function parameters according to serum hs-CRP levels.
| Variables | Estimates ± SEs across Vitamin Concentration Tertiles (T) | p for Trend across the Tertiles | ||
|---|---|---|---|---|
| 1st T | 2nd T | 3rd T | ||
| Across serum vitamin A concentration | ||||
| hs-CRP ≤ 1 mg/L | ||||
| FEV1 | Reference | 0.0194 ± 0.0271 | 0.0702 ± 0.0307 * | <0.05 |
| FVC | Reference | −0.0118 ± 0.0312 | 0.0619 ± 0.0384 | 0.082 |
| FEV1/FVC | Reference | 0.0104 ± 0.0058 | 0.0081 ± 0.0069 | 0.470 |
| hs-CRP > 1 mg/L | ||||
| FEV1 | Reference | 0.0313 ± 0.0462 | 0.0767 ± 0.0601 | 0.206 |
| FVC | Reference | 0.0197 ± 0.0501 | 0.0595 ± 0.0582 | 0.302 |
| FEV1/FVC | Reference | 0.0021 ± 0.0228 | 0.0240 ± 0.0165 | 0.206 |
| Across serum vitamin E concentration | ||||
| hs-CRP ≤ 1 mg/L | ||||
| FEV1 | Reference | 0.0269 ± 0.0271 | 0.0136 ± 0.0280 | 0.701 |
| FVC | Reference | 0.0205 ± 0.0348 | 0.0031 ± 0.0334 | 0.988 |
| FEV1/FVC | Reference | 0.0043 ± 0.0061 | 0.0019 ± 0.0060 | 0.592 |
| hs-CRP > 1 mg/L | ||||
| FEV1 | Reference | 0.0812 ± 0.0547 | −0.0422 ± 0.0581 | 0.410 |
| FVC | Reference | 0.0509 ± 0.0598 | −0.0598 ± 0.0547 | 0.241 |
| FEV1/FVC | Reference | 0.0630 ± 0.0191 ** | 0.0157 ± 0.0221 | 0.410 |
Abbreviations: hs-CRP, high-sensitivity C-reactive protein; FEV1, forced expiratory volume in one second; FVC, forced vital capacity. The multivariate models include age, sex, body mass index, residential district (urban, rural), educational level (≤middle school, ≥high school), household income level (low, high), smoking status (abstainer, current smoker [two categories: <20, ≥20 pack-years]), alcohol consumption (abstainer, current drinker), coffee consumption (non-consumer, consumer), regular physical activity (no, yes), dietary supplementation (no, yes), total energy intake, and serum hs-CRP levels. * p < 0.05 and ** p < 0.01.
3.4. Associations between Serum Vitamin Concentrations and COPD with Results Stratified by Serum hs-CRP Level
Table 4 shows the associations of serum vitamin A and E concentrations with the prevalence of spirometry-defined COPD. Similar to the results depicted in Table 2, serum vitamin A concentration was significantly associated with a lower COPD prevalence across all participants in the multivariable model (p for trend < 0.05). Compared with the bottom serum vitamin A concentration tertile group, the top tertile group yielded a lower OR (0.53 (95% CI: 0.31, 0.90)) for COPD. According to the association results stratified by serum hs-CRP level, participants with a low systemic inflammatory state of this marker (≤1 mg/L) exclusively exhibited a relatively low COPD prevalence; their ORs (95% CI) were 0.55 (0.34, 0.91) and 0.51 (0.30, 0.88) for the second and third tertile groups, respectively. However, such a low prevalence was not observed among those with serum hs-CRP levels > 1 mg/L. Meanwhile, serum vitamin E concentration and COPD prevalence were not associated.
Table 4.
Associations between serum vitamin concentrations and prevalence of chronic obstructive pulmonary disease.
| Variables | OR (95% CI) across Vitamin Concentration Tertiles (T) | p for Trend across the Tertiles | ||
|---|---|---|---|---|
| 1st T | 2nd T | 3rd T | ||
| Across serum vitamin A concentration | ||||
| Number of cases/noncases | 69/614 | 76/584 | 79/583 | 0.055 |
| Age and sex-adjusted model for all | Reference | 0.63 (0.40, 1.00) | 0.59 (0.37, 0.96) * | <0.05 |
| Multivariable model for all | Reference | 0.63 (0.39, 1.02) | 0.53 (0.31, 0.90) * | <0.05 |
| Multivariable model for hs-CRP ≤ 1 mg/L | Reference | 0.55 (0.34, 0.91) * | 0.51 (0.30, 0.88) * | 0.450 |
| Multivariable model for hs-CRP > 1 mg/L | Reference | 0.87 (0.34, 2.25) | 0.71 (0.27, 1.90) | 0.055 |
| Across serum vitamin E concentration | ||||
| Number of cases/noncases | 83/585 | 66/603 | 75/593 | |
| Age and sex-adjusted model for all | Reference | 0.70 (0.46, 1.08) | 1.10 (0.73, 1.65) | 0.574 |
| Multivariable model for all | Reference | 0.79 (0.49, 1.25) | 1.22 (0.78, 1.91) | 0.324 |
| Multivariable model for hs-CRP ≤ 1 mg/L | Reference | 0.91 (0.56, 1.46) | 1.10 (0.69, 1.74) | 0.482 |
| Multivariable model for hs-CRP > 1 mg/L | Reference | 0.67 (0.24, 1.91) | 0.76 (0.28, 2.04) | 0.605 |
Abbreviations: OR, odds ratio; CI, confidence interval; hs-CRP, high-sensitivity C-reactive protein. The multivariate models include age, sex, body mass index, residential district (urban, ruraleducational level (≤middle school, ≥high school)), household income level (low, high), smoking status (abstainer, current smoker [two categories: <20, ≥20 pack-years]), alcohol consumption (abstainer, current drinker), coffee consumption (non-consumer, consumer), regular physical activity (no, yes), dietary supplementation (no, yes), total energy intake, and serum hs-CRP levels. * p < 0.05.
4. Discussion
This cross-sectional study analyzed nationwide survey data to investigate the associations of serum vitamin A and E concentrations with PF parameters and COPD prevalence in middle-aged and older adults. Overall, serum vitamin A concentration exhibited significantly positive associations with FEV1 and a low prevalence of COPD. In particular, analyses stratified by serum hs-CRP level revealed that participants with serum hs-CRP levels ≤1 mg/L, which indicate a low inflammatory state and were observed in 76% of the study participants, displayed such associations. However, serum vitamin E concentration exhibited no association with PF parameters and COPD prevalence.
Oxidative stress, which is caused by the production of reactive oxygen species (ROS), thus overwhelming antioxidant capacity, has been proposed as a potential mechanism in the pathogenesis of COPD. ROS, including the superoxide anion, hydrogen peroxide, the hydroxyl radical, and single oxygen, are produced endogenously via metabolic reactions; furthermore, they are generated by exogenous sources such as cigarette smoke and air pollutants [4]. In pulmonary tissue, increased levels of oxidative stress are accompanied by inflammation, damage epithelial cells, and induce extracellular matrix degradation, leading to irreversible injury and the development of fibrosis [22]. However, because endogenous (e.g., glutathione, coenzyme Q10, superoxide dismutase, catalase, and glutathione peroxidase) and dietary exogenous antioxidants, including vitamins A and E, can scavenge ROS, thereby diminishing oxidative stress, they presumably play a protective role in preventing PF decline and COPD development [5].
Epidemiological data on the association of serum vitamin A and E concentrations with PF remain inconsistent [6,7,8,9,10]. Certain population-based, cross-sectional studies have observed a significant association of PF parameters with serum retinol [8] and β-carotene concentrations [7,8]; nevertheless, others have not [6,9]. Regarding investigations on serum vitamin E, particularly α-tocopherol, no associations [6,10], positive associations [7,8], and an inverse association [9] with PF parameters have been reported. Concerning the association with COPD, conflicting data have been generated by case–control studies, which performed PF testing to diagnose COPD [11,12]. A national survey involving American adults found that those who had reported a diagnosis of COPD were likely to have lower serum α-carotene, β-carotene, and α-tocopherol concentrations [13]. Data from large sample-size studies on such associations with COPD, especially cases diagnosed via PF testing, remain limited.
The current study is based on the same national survey (the KNHANES, conducted during the 2016–2018 period) data used in an earlier study [9] that exclusively included older adults; nonetheless, our study extended the scope of the study participants to adults aged ≥ 40 years. In addition, a broader range of confounding variables, including total calorie intake, dietary supplementation, and serum hs-CRP concentration, was considered in the multivariable models. The aforementioned previous study observed no association with serum vitamin A (retinol) concentration and an inverse association with serum vitamin E (α-tocopherol) concentration when PF parameters were fitted as dependent variables [9]. We speculated that the sample size limited to older adults may reduce statistical power, and that residual confounding from unadjusted factors, such as inadequate dietary intake or dietary supplementation, accompanied by severe PF impairment in older adults, may influence the previous results yielded by Chang et al. [9]. Our findings wherein serum retinol concentrations were associated with PF parameters and COPD prevalence are consistent with those of previous studies [8,11]. The results revealing no association with serum α-tocopherol concentration are consistent with those obtained by Hanson et al. [10], but not with the results of the other studies [7,8,13].
The current study conducted a novel investigation into the associations of serum vitamin A and E concentrations with PF parameters and COPD prevalence according to the serum hs-CRP level. Hs-CRP is reportedly a useful biochemical marker for determining COPD severity [21]. Patients with COPD exhibit increased oxidative stress accompanied by airway inflammation [23]. To mitigate oxidative-stress-induced lung damage, enzymatic and non-enzymatic antioxidant (e.g., vitamins A and E) defense mechanisms in the lungs are requisite to protecting against COPD [4]. Our findings indicate that higher serum vitamin A concentrations may help maintain PF in individuals with lower serum hs-CRP levels, but not among those with an elevated inflammatory state. These findings potentially imply that the antioxidant defense mechanism cannot overcome oxidative lung damage in patients with advanced PF impairment accompanied by a high inflammatory state.
The strengths of this study include the use of spirometry measures for outcomes, the analysis of data from a large-scale population-based survey, and the consideration of an extensive range of potential confounding variables. Notwithstanding, this study has certain limitations. First, serum from a single blood draw was assayed for retinol and α-tocopherol concentrations; moreover, other isoforms of vitamins A and E, especially β-carotene and several other carotenoids, γ-tocopherol, and δ-tocopherol, were not examined. Second, the results of the association for vitamin A with the FEV1/FVC ratio and COPD are inconsistent, possibly because of some outliers of the FEV1/FVC ratio, which might lead to a lack of statistical significance. Third, causal inference was limited by the study’s cross-sectional nature. Fourth, possible residual confounding caused by unmeasured variables cannot be ruled out. Finally, the generalization of this study’s findings is limited because the study participants were exclusively Koreans aged ≥40 years.
5. Conclusions
In summary, the current study found serum retinol concentration to be positively associated with PF parameters and a relatively low COPD prevalence when confounding variables, including serum hs-CRP level, total energy intake, and dietary supplementation, were considered. Such associations were exclusively observed in individuals with serum CRP level ≤ 1 mg/L. However, we were unable to observe a significant association with serum α-tocopherol concentration. Further epidemiological studies are warranted to generate data on causal inference regarding the associations of the serum concentrations of vitamin A and E, including their various isoforms, which more reliably reflect antioxidant status in the human body. Meanwhile, maintaining proper vitamin A status is an important public health message for adults at a high risk of COPD.
Author Contributions
Conceptualization, W.N. and I.B.; formal analysis, W.N.; data curation, W.N. and I.B.; writing—original draft preparation, W.N. and I.B.; writing—W.N. and I.B.; supervision, I.B.; funding acquisition, I.B. All authors have read and agreed to the published version of the manuscript.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of Kookmin University (approval number: KMU-202102-HR-260, 23 March 2021).
Informed Consent Statement
Written informed consent has been obtained from the participants involved in the study.
Data Availability Statement
All data are publicly available (https://knhanes.kdca.go.kr/knhanes/ (accessed on 20 August 2024)).
Conflicts of Interest
The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Funding Statement
This work was supported by the National Research Foundation of Korea Grant funded by the Korean Government (RS-2024-00336637).
Footnotes
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References
- 1.Adeloye D., Song P., Zhu Y., Campbell H., Sheikh A., Rudan I., NIHR RESPIRE Global Respiratory Health Unit Global, regional, and national prevalence of, and risk factors for, chronic obstructive pulmonary disease (COPD) in 2019: A systematic review and modelling analysis. Lancet Respir. Med. 2022;10:447–458. doi: 10.1016/S2213-2600(21)00511-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Kim S.H., Lee H., Kim Y., Rhee C.K., Min K.H., Hwang Y.I., Kim D.K., Park Y.B., Yoo K.H., Moon J.-Y. Recent Prevalence of and Factors Associated with Chronic Obstructive Pulmonary Disease in a Rapidly Aging Society: Korea National Health and Nutrition Examination Survey 2015–2019. J. Korean Med Sci. 2023;38:e108. doi: 10.3346/jkms.2023.38.e108. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Safiri S., Carson-Chahhoud K., Noori M., Nejadghaderi S.A., Sullman M.J.M., Heris J.A., Ansarin K., Mansournia M.A., Collins G.S., Kolahi A.-A., et al. Burden of chronic obstructive pulmonary disease and its attributable risk factors in 204 countries and territories, 1990–2019: Results from the Global Burden of Disease Study 2019. BMJ. 2022;378:e069679. doi: 10.1136/bmj-2021-069679. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Kirkham P.A., Barnes P.J. Oxidative stress in COPD. Chest. 2013;144:266–273. doi: 10.1378/chest.12-2664. [DOI] [PubMed] [Google Scholar]
- 5.Seyedrezazadeh E., Pour Moghaddam M., Ansarin K., Jafarabadi M.A., Sharifi A., Sharma S., Kolahdooz F. Dietary Factors and Risk of Chronic Obstructive Pulmonary Disease: A Systemic Review and Meta-Analysis. Tanaffos. 2019;18:294–309. [PMC free article] [PubMed] [Google Scholar]
- 6.Grievink L., Smit H., Veer P.V., Brunekreef B., Kromhout D. Plasma concentrations of the antioxidants beta-carotene and α-tocopherol in relation to lung function. Eur. J. Clin. Nutr. 1999;53:813–817. doi: 10.1038/sj.ejcn.1600854. [DOI] [PubMed] [Google Scholar]
- 7.Hu G., Cassano P.A. Antioxidant nutrients and pulmonary function: The Third National Health and Nutrition Examination Survey (NHANES III) Am. J. Epidemiol. 2000;151:975–981. doi: 10.1093/oxfordjournals.aje.a010141. [DOI] [PubMed] [Google Scholar]
- 8.Schünemann H.J., Grant B.J.B., Freudenheim J.L., Muti P., Browne R.W., Drake J.A., Klocke R.A., Trevisan M. The relation of serum levels of antioxidant vitamins C and E, retinol and carotenoids with pulmonary function in the general population. Am. J. Respir. Crit. Care Med. 2001;163:1246–1255. doi: 10.1164/ajrccm.163.5.2007135. [DOI] [PubMed] [Google Scholar]
- 9.Chang S.W., Kim M.B., Kang J.W. High serum folate level is positively associated with pulmonary function in elderly Korean men, but not in women. Sci. Rep. 2022;12:4523. doi: 10.1038/s41598-022-08234-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Hanson C., Lyden E., Furtado J., Campos H., Sparrow D., Vokonas P., Litonjua A.A. Serum tocopherol levels and vitamin E intake are associated with lung function in the normative aging study. Clin. Nutr. 2016;35:169–174. doi: 10.1016/j.clnu.2015.01.020. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Caram L.M.O., Amaral R.A.F., Ferrari R., Tanni S.E., Correa C.R., Paiva S.A.R., Godoy I. Serum Vitamin A and Inflammatory Markers in Individuals with and without Chronic Obstructive Pulmonary Disease. Mediat. Inflamm. 2015;2015:862086. doi: 10.1155/2015/862086. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Kodama Y., Kishimoto Y., Muramatsu Y., Tatebe J., Yamamoto Y., Hirota N., Itoigawa Y., Atsuta R., Koike K., Sato T., et al. Antioxidant nutrients in plasma of Japanese patients with chronic obstructive pulmonary disease, asthma-COPD overlap syndrome and bronchial asthma. Clin. Respir. J. 2017;11:915–924. doi: 10.1111/crj.12436. [DOI] [PubMed] [Google Scholar]
- 13.Zheng L., Yu X., Xia Z., Guo Y., Dai Y. The Associations Between Serum Vitamins and Carotenoids with Chronic Obstructive Pulmonary Disease: Results from the NHANES. Int. J. Chronic Obstr. Pulm. Dis. 2023;18:2985–2997. doi: 10.2147/COPD.S432995. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rawal G., Yadav S. Nutrition in chronic obstructive pulmonary disease: A review. J. Transl. Intern. Med. 2015;3:151–154. doi: 10.1515/jtim-2015-0021. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Kweon S., Kim Y., Jang M.-J., Kim Y., Kim K., Choi S., Chun C., Khang Y.-H., Oh K. Data resource profile: The Korea National Health and Nutrition Examination Survey (KNHANES) Int. J. Epidemiol. 2014;43:69–77. doi: 10.1093/ije/dyt228. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Korea Disease Control and Prevention Agency . Project Final Result Report: Education and Quality Control of Pulmonary Function Test in the 7th 2nd Year National Health and Nutrition Examination Survey 2017. Korea Disease Control and Prevention Agency; Cheongju, Republic of Korea: 2017. [(accessed on 20 August 2024)]. Available online: https://www.prism.go.kr/homepage/entire/researchDetail.do?researchId=1351000-201700231&menuNo=I0000002. [Google Scholar]
- 17.Korea Disease Control and Prevention Agency . Guideline for Raw Data Use of the Seventh Korea National Health and Nutrition Examination Survey (KNAHNES VII), 2016–2018. Korea Disease Control and Prevention Agency; Cheongju, Republic of Korea: 2020. [(accessed on 20 August 2024)]. Available online: https://knhanes.kdca.go.kr/knhanes/sub03/sub03_06_02.do. [Google Scholar]
- 18.Chung K.S., Park H.J., Leem A.Y., Lee S.H., Song J.H., Park M.S., Kim Y.S., Kim S.K., Chang J., Chung K.S. Comorbidities in obstructive lung disease in Korea: Data from the fourth and fifth Korean National Health and Nutrition Examination Survey. Int. J. Chronic Obstr. Pulm. Dis. 2015;10:1571–1582. doi: 10.2147/COPD.S85767. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Korea Disease Control and Prevention Agency . Project Final Result Report: Clinical Laboratory Test for the Seventh Korea National Health and Nutrition Examination Survey (2016–2018) Korea Disease Control and Prevention Agency; Cheongju, Republic of Korea: 2016. [(accessed on 20 August 2024)]. Available online: https://scienceon.kisti.re.kr/srch/selectPORSrchReport.do?cn=TRKO201900000133. [Google Scholar]
- 20.Julia C., Galan P., Touvier M., Meunier N., Papet I., Sapin V., Cano N., Faure P., Hercberg S., Kesse-Guyot E. Antioxidant status and the risk of elevated C-reactive protein 12 years later. Ann. Nutr. Metab. 2014;65:289–298. doi: 10.1159/000363194. [DOI] [PubMed] [Google Scholar]
- 21.Dahl M., Vestbo J., Lange P., Bojesen S.E., Tybjaerg-Hansen A., Nordestgaard B.G. C-reactive protein as a predictor of prognosis in chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 2007;175:250–255. doi: 10.1164/rccm.200605-713OC. [DOI] [PubMed] [Google Scholar]
- 22.Kinnula V.L., Fattman C.L., Tan R.J., Oury T.D. Oxidative stress in pulmonary fibrosis: A possible role for redox modulatory therapy. Am. J. Respir. Crit. Care Med. 2005;172:417–422. doi: 10.1164/rccm.200501-017PP. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Drost E.M., Skwarski K.M., Sauleda J., Soler N., Roca J., Agusti A., MacNee W. Oxidative stress and airway inflammation in severe exacerbations of COPD. Thorax. 2005;60:293–300. doi: 10.1136/thx.2004.027946. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data are publicly available (https://knhanes.kdca.go.kr/knhanes/ (accessed on 20 August 2024)).
