Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
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Advances in Clinical and Experimental Medicine

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doi: 10.17219/acem/175815

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

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Wang H, Ge C, Zhang Z, Geng Z, Zhang L. Effects of physical activity and sedentary behavior on serum vitamin D in patients with chronic obstructive pulmonary disease [published online as ahead of print on March 20, 2024]. Adv Clin Exp Med. 2024. doi:10.17219/acem/175815

Effects of physical activity and sedentary behavior on serum vitamin D in patients with chronic obstructive pulmonary disease

Huijun Wang1,A, Chunguang Ge2,B, Zhipeng Zhang3,C, Zhangyan Geng4,C, Lihai Zhang5,D,E,F

1 General Practice, Liaocheng People’s Hospital, China

2 Liaocheng Vocational and Technical College, China

3 Department of Respiratory Medicine, Jiyang District People’s Hospital, China

4 Department of Geriatrics, First Hospital of Hebei Medical University, Shijiazhuang, China

5 Department of Respiratory and Critical Care, First Hospital of Hebei Medical University, Shijiazhuang, China

Graphical abstract


Graphical abstracts

Abstract

Background. Chronic obstructive pulmonary disease (COPD) is a complex, heterogeneous disease with multiple extrapulmonary manifestations, among which vitamin D deficiency and insufficiency are very common in COPD and are associated with the health status and clinical outcomes of COPD patients.

Objectives. This paper aims to analyze the impact of leisure-time physical activity (LTPA) and daily sitting time (DST) and their interactions on serum vitamin D in patients with COPD.

Materials and methods. Participants aged ≥40 years from the National Health and Nutrition Examination Survey (NHANES) in the USA from 2007 to 2012 who had undergone pulmonary function tests and vitamin D tests were selected as the study participants. Participants’ LTPA and DST were assessed using the General Practice Assessment Questionnaire (GPAQ). Multivariate logistic regression analysis was used to analyze the relationship between serum vitamin D, LTPA, DSA and the combination of the 2 in patients with COPD, and the results were expressed as odds ratio (OR) and 95% confidence interval (95% CI).

Results. This study included 1,448 samples. The mean vitamin D concentration of the samples was (68.27 ±26.78) nmol/L; 360 participants (24.86%) had vitamin D deficiency and 539 participants (37.22%) had vitamin D insufficiency. Vitamin D and 25(OH)D3 expression levels differed across the 4 groups (150 min/week and DST > 8 h revealed the highest vitamin D expression levels, while LTPA 8 h showed the lowest. Vitamin D was weakly correlated with FEV1, FVC, BMI, age, and LTPA (p < 0.01), but not with DST. Body mass index (BMI) was weakly positively correlated with DST (r = 0.142, p < 0.01).

Conclusions. Serum physical activity and DST independently affect vitamin D levels in COPD patients; therefore, increasing physical activity and minimizing DST may help improve vitamin D levels and prevent vitamin D deficiency.

Key words: physical activity, sedentary behavior, vitamin D, chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a clinical syndrome characterized by chronic respiratory symptoms, abnormal lung structure and impaired lung function.1 It is a prevalent condition globally and is associated with significant morbidity and mortality. Despite its high incidence, COPD is frequently underdiagnosed, resulting in delayed recognition until the disease has reached an advanced stage. Over the last 2 decades, the treatment options for COPD have expanded considerably, including new oral and inhaled medications and innovative surgical and bronchoscopic procedures.2 External environmental factors (such as smoking, exposure to harmful particles, lower respiratory tract infection, and occupational exposure) and internal factors (such as genetic variation, epigenetic factors and population aging) lead to multiple mechanisms involved in the pathogenesis of COPD, which include oxidative stress, protease and antiprotease imbalance, immune inflammation, apoptosis, as well as systemic and lung damage and repair.3, 4 Owing to the initial oxidative and inflammatory events described above, COPD is linked to several changes in the respiratory airways, in particular the remodeling of alveolar and airways epithelium, mucoid plug formation, increased density of inflammatory cells, smooth muscle hyperplasia, and fibrosis.5 These changes are considered to be the part of the tissue regeneration and repair processes that further increase mucus production and lead to emphysematous destruction of the gas-exchanging surface of the lung.6 These airway changes manifest as clinical symptoms, including dyspnea and a persistent cough, with or without sputum production. Usually, spirometry is recommended as the subsequent diagnostic test, or a postbronchodilator FEV1/FVC ratio of less than 0.70 is used for further confirmation.7

While COPD is curable and the cure varies from case to case, the dietary and lifestyle changes are also considered indispensable for a quick recovery. While there is a lack of definitive data, the existing scientific evidence suggests that certain foods and nutrients, particularly those with antioxidant and anti-inflammatory properties, as well as when consumed in a balanced dietary pattern, are linked to improved pulmonary function, slower decline in lung function and a decreased risk of COPD. Understanding the impact of diet on COPD can equip healthcare professionals with an evidence-based framework to provide patients with valuable guidance to improve their respiratory wellbeing.8 It is also worth noting that nutritional deficiencies need to be assessed and replenished to achieve an effective treatment outcome either via dietary or pharmacological means.

Among several nutritional deficiencies, vitamin D has been extensively reported. Vitamin D deficiency and insufficiency are very common and are associated with the health status and clinical outcomes of patients with COPD.9, 10 Moreover, vitamin D is a potential modality for the treatment of COPD due to its anti-inflammatory and antioxidant properties, as well as its ability to modulate the immune response.11, 12 Although some recent studies suggest that vitamin D supplementation may benefit patients with COPD, the results are inconsistent13, 14 and the best way to prevent abnormal vitamin D metabolism in patients with COPD has not been determined.

Vitamin D plays a significant role in preventing inflammation and modulating molecular signaling pathways associated with tissue remodeling.15 Inflammation is a complex immune response involving the activation of various signaling molecules and cellular processes. Vitamin D has been shown to have anti-inflammatory properties by modulating the expression and function of inflammatory mediators, such as cytokines and chemokines.16, 17 It can inhibit the production of pro-inflammatory cytokines while promoting the synthesis of anti-inflammatory cytokines, thereby helping to maintain a balanced immune response and dampening excessive inflammation. Moreover, vitamin D has been shown to influence molecular signaling pathways involved in tissue remodeling. Tissue remodeling refers to the process of structural changes in tissues that occur in response to injury, repair or chronic diseases. Vitamin D can regulate the expression of genes involved in extracellular matrix synthesis and degradation and cell proliferation and differentiation. It can also influence the activity of enzymes and signaling molecules implicated in tissue remodeling processes, such as matrix metalloproteinases (MMPs) and transforming growth factor-beta (TGF-β)18 It has also been found to be effective in various lung inflammatory diseases.19 By exerting anti-inflammatory effects and modulating molecular signaling related to tissue remodeling, vitamin D helps maintain tissue homeostasis and prevent excessive tissue damage. However, it is important to note that the specific mechanisms and effects of vitamin D in these processes are still an area of active research, and further studies are needed to fully understand its role in preventing inflammation and tissue remodeling.

The connection between physical activity, sedentary behavior and serum vitamin D levels in patients with chronic obstructive pulmonary disease (COPD) lies in the impact of lifestyle factors on vitamin D synthesis. Inactivity and prolonged sedentary behavior can contribute to reduced exposure to sunlight, which is essential for the body’s production of vitamin D. This deficiency in physical activity and excessive sedentary time may consequently lead to lower serum vitamin D levels in COPD patients.20, 21 Recent studies have shown that physical activity in patients with COPD is affected by a variety of extrapulmonary factors (such as skeletal muscle dysfunction, depressive symptoms and nutritional status).22, 23 Regular exercise training and rehabilitation can alleviate the above extrapulmonary complications syndrome24; in the general population, serum vitamin D is related to physical activity, and adequate physical activity is a protective factor for maintaining normal vitamin D levels.25, 26 However, there is limited epidemiological evidence on the effects of physical activity and sedentary behavior on serum vitamin D in patients with COPD. Therefore, there is an ongoing scientific effort to explore the role of vitamin D in COPD and reduce the disease burden.

Objectives

This study aims to analyze the impact of leisure-time physical activity (LTPA) and daily sitting time (DST), as well as their interactions, on serum vitamin D in patients with COPD. Additionally, the study suggests ways of preventing abnormal vitamin D metabolism in patients with COPD. The aim of this study is to propose the inclusion of vitamin D status in the diagnosis and treatment of COPD, and to pave the way for further research on need of vitamin D interventions and the development of physical activity standards for routine COPD treatment.

Materials and methods

Study design and setting

This study involves 3 cycles of data retrieved from the National Health and Nutrition Examination Survey (NHANES) conducted between 2007 to 2012 and published by the Centers for Disease Control and Prevention (CDC).

Participants

Among the 48,407 samples in 3 cycles, this study included participants older than 40 years and whose lung function met the diagnostic criteria for COPD,17 while excluding those lacking data on vitamin D, physical activity time and DST. All NHANES protocols were approved by the National Center for Health Statistics Ethics Review Board. Written informed consent was obtained from all participants. The datasets used contained no personally identifiable information, so they were not subject to ethical review. Demographic data, spirometry, disease information, dietary data, laboratory and questionnaire data associated with disease definitions were collected and merged from different NHANES files.

Variables

According to the current studies, the following variables were chosen as confounding factors measured in the baseline survey. Demographic characteristics included age (40–60, >60), sex (male or female), race/ethnicity (Mexican American, other Hispanic, non-Hispanic White, non-Hispanic Black, and other race), education level (high school or less, some college and college graduate or higher), family poverty–income ratio (total family income divided by poverty line: <1.3, from 1.3 to <3.5 or ≥3.5); body mass index (BMI; calculated as weight [kg] divided by height [m2] which was separated into 3 groups BMI <25, BMI range from 25.0 to 29.9 or BMI ≥30); lung function test27; smoking status (never, former, current)28; comorbidities included asthma, congestive heart failure, coronary heart disease, diabetes, cancer, and arthritis. Vitamin D intake was assessed based on the intake of vitamin D2 + D3 in the previous month. Then, LTPA (none, from 0 to <150 or ≥150) and DST (<4, 4 to 6, from 6 to 8 or >8) were chosen as categorical variables.

Experimental procedure

Recreational physical activity time, sedentary time and vitamin D determination

The Global Practice Assessment Questionnaire (GPAQ) was used to assess participants’ LTPA and DST. The GPAQ is a validated questionnaire developed by the World Health Organization (WHO) to monitor physical activity. This questionnaire was applied in more than 100 countries worldwide via the WHO step-by-step surveillance approach. This questionnaire was used to gather information on daily physical activity, LTPA and sedentary behavior.29 When answering the questionnaire, participants were asked to report their moderate- and high-intensity recreational activities in a week. Leisure-time physical activity is defined as the total time of conducting moderate-intensity recreational activity (min) plus twice the total time of conducting the vigorous-intensity recreational activity [min]. Based on the 2018 Physical Activity Guidelines for Americans, participants were classified as inactive (not participating in any physical activity), insufficiently active (more than 0 min but less than 150 min per week) and adequately active (more than 150 min active). Participants answered the question: “On a typical day, how much time do you usually spend sitting at school, at home, getting to and from places, or with friends, including time spent sitting at a desk, traveling in a car or bus, reading, playing cards, watching television, or using a computer?” to assess the participants’ sedentary time. Study participants were divided into 4 groups based on their DST (h/day) (0 to <4, from 4 to <6, from 6 to 8, and ≥8 h/day).30, 31 Serum 25(OH)D2 and 25(OH)D3 concentrations were determined using standard liquid chromatography-tandem mass spectrometry (LC-MS/MS), following CDC recommendations. Participants’ blood was drawn by qualified medical practitioners. Measurement of serum 25(OH)D levels was expressed as nmol/L.32

Statistical analyses

According to the vitamin D expression level defined by the relevant consensus, the enrolled patients were divided into vitamin D deficiency, vitamin D insufficiency and vitamin D sufficiency.33 Vitamin D, 25(OH)3 and 25(OH)2 expression levels, vitamin D intake, age, BMI, forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, LTPA, and DST were used as continuous variables with mean ± standard deviation (M ±SD). In this study, we employed a rigorous statistical approach to assess the relationship between vitamin D expression and 2 key lifestyle factors: LTPA and DST. To ensure the robustness of our analysis, we conducted several preliminary tests to examine the underlying assumptions of our chosen statistical methods.

We began by conducting tests of normality and homogeneity of variance on our data, as presented in Supplementary Table 1. The Kruskal-Wallis H test was utilized to assess variations in vitamin D expression based on 2 primary lifestyle factors: LTPA and DST.

Among the nonparametric tests, we used Spearman’s rank correlation coefficient to obtain a correlation between vitamin D and its other dependencies. Vitamin D intake number, age (from 40 to 60, >60), BMI (<25, from 25 to 30 and ≥30), ethnicity, family poverty–income index, education level, smoking history, complications, and LTPA (none, from 0 to <150 and ≥150) and DST (<4, 4 to 6, from 6 to 8, and >8) as categorical variables. They were expressed as absolute numbers and constituent ratios, and the differences between groups were compared using χ2 test. Logistic regression of the joint association of DST and with vitamin D was performed using the Wald χ2 test. Furthermore, we also performed the calculation of odds ratios (ORs) based on control and treatment regimens using MedCalc v. 20.106 (MedCalc Software Ltd., Ostend, Belgium).

Spearman’s correlation analysis was used to explore the correlation among vitamin D, FEV1, FVC, BMI, age, DST, and LTPA. Multivariate logistic regression analysis was used to study the relationship between vitamin D and LTPA, DSA, and the combination of the two. Results were expressed as OR and 95% confidence interval (95% CI). In Model 1, there was no adjustment of confounding factors; in Model 2, age, sex, and race were adjusted as confounding factors; in Model 3, age, sex, race, BMI, family poverty–income index, education level, and smoking history were adjusted as confounding factors; in Model 4, age, sex, race, BMI, household poverty–income index, education level, smoking history, vitamin D intake, comorbidities, and FEV1 were adjusted as confounding factors; in Model 5, age, sex, race, BMI, household poverty–income index, education level, smoking history, vitamin D intake, comorbidities, and FVC were adjusted for confounding factors. Data analysis was performed using IBM SPSS 26.0 (IBM Inc., Armonk, USA). A p-value <0.05 represented a statistical difference. GraphPad Prism 8 (GraphPad Software, San Diego, USA) was employed to generate comprehensive visualizations, including scatter plots and box plots (Figure 2, Figure 3, Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10).

Results

This study included 1,448 samples for analysis (Figure 1). Table 1 shows selected demographics and potential confounders according to vitamin D level. The average concentration of vitamin D in the samples was 68.27 ±26.78 nmol/L. Of the 1,448 participants, 360 (24.86%) had vitamin D deficiency, with an average concentration of (35.48 ±9.20) nmol/L, while 539 participants (37.22%) were insufficient in vitamin D, with an average concentration of (63.00 ±7.07) nmol/L. Participants with vitamin D deficiency were younger, more obese, smokers, had poorer lung function, and had lower education levels and household income. Additionally, these participants were mainly non-Hispanic White men, who were less likely to take vitamin D supplements, and the probability of combining tumors and rheumatic diseases was low. Only 4.1% of the patients in the vitamin D deficiency group conducted sufficient LTPA (≥150 min/week), while 17.3% of the participants did not carry out any LTPA, and their activity time was significantly shorter than that of vitamin D insufficient and vitamin D sufficient participants, with a statistical difference (p < 0.001). The Kruskal–Wallis H test was utilized to assess variations in vitamin D expression based on 2 primary lifestyle factors: LTPA and DST. Compared to the other 2 groups of participants, the vitamin D deficiency group had a longer sedentary time (p < 0.05), and 4.6% of the participants exceeded 8 h of sedentary time, with no statistical difference (t = 0.191, p = 0.848) found. The expression levels of vitamin D, 25(OH)D2 and 25(OH)D3 varied between different physical activity times (p < 0.05): the expression level of vitamin D was the highest in the participants with LTPA ≥150 min/week, and the lowest in those who did not conduct any physical activity (Table 2, Figure 2, Figure 3, Figure 4); between different sedentary times, only the expression level of 25(OH)D3 showed statistical difference (p < 0.05), and there was no statistical difference in the vitamin D and 25(OH)D2 expressions (p > 0.05) (Table 3, Figure 5, Figure 6, Figure 7). The combined analysis of physical activity time and sedentary time found that the expression levels of vitamin D 25(OH)D2 and 25(OH)D3 were different among the 4 groups (p < 0.05). The participants with LTPA ≥150 min/week and sedentary time >8 h showed the highest vitamin D expression level, while the participants with LTPA <150 min/week and sedentary time >8 h had the lowest vitamin D expression level (Table 4, Figure 8, Figure 9, Figure 10).

Table 5 showed the correlations among variables. Vitamin D had a weak correlation with FEV1, FVC, BMI, age, and LTPA (p < 0.01), but had no correlation with sedentary time; BMI and sedentary time were weakly positively correlated (r = 0.142; p < 0.01); and LTPA was weakly positively correlated with lung function parameters (FEV1, FVC; p < 0.01).

To further analyze the independent effects of physical activity and sedentary time, and their interaction on vitamin D in patients with COPD, vitamin D status (vitamin D deficiency, vitamin D insufficiency and vitamin D sufficiency in order) was used as the dependent variable, and an ordinal logistic regression was conducted to provide the estimation and direction of the influence of physical activity, sedentary time and their interaction on vitamin D sufficiency. Table 6 and Table 7 show that LTPA and sedentary time were related to vitamin D status. Compared with vitamin D deficiency, increased LTPA was a protective factor for vitamin D insufficiency and vitamin D sufficiency (Table 6), while increased sedentary time was a high-risk factor for vitamin D insufficiency and vitamin D sufficiency (Table 7). These associations remained after adjustment for relevant covariates (both p-values for trend <0.05).

Table 8 shows the results of a joint analysis of LTPA and sedentary time on vitamin D status. The combined effect of sedentary time and LTPA still impacted vitamin D status. Compared with the sedentary time of more than 8 h and active time of less than 150 min, when the active time was less than 150 min, sedentary time of less than 8 h was a protective factor for maintaining sufficient vitamin D levels; when the active time was longer than 150 min, no matter how long of sitting time (even more than 8 h) was a protective factor for maintaining normal vitamin D levels, and this relationship remained even after relevant covariates adjustment (both p-values for trend <0.05).

Parallelism test results were analyzed according to ordered logistic regression (Supplementary Table 2–4). We used vitamin D status as a dependent variable to conduct a multi-categorical logistic regression to analyze the effects of physical activity, sedentary time, and their interactions on vitamin D. Increased time spent on leisure physical activity after correction for relevant covariates was a protective factor for vitamin D sufficiency compared with vitamin D deficiency (Supplementary Table 5). Increased sitting time was a high factor for vitamin D adequacy (Supplementary Table 6). The joint analysis found that sitting for less than 8 h was a protective factor for maintaining adequate vitamin D levels when compared with sitting for more than 8 h and activity for less than 150 min (Supplementary Table 7). When the activity time was longer than 150 min, whether the sedentary time was more than 8 h was a protective factor to maintain the normal vitamin D levels.

Discussion

This study found that abnormal vitamin D levels were common in COPD patients, and that there was a significant association between physical activity and sedentary behavior and vitamin D levels in patients with COPD. The lack of sufficient physical activity and exhibiting long-term sedentary behavior are high-risk factors for abnormal expression of vitamin D in patients with COPD. Adequate physical activity and proper control of sedentary behavior can effectively improve vitamin D levels in patients with COPD.

Sedentary behavior and decreased physical activity due to exertional dyspnea are one of the main life characteristics of patients with COPD, and this lifestyle is associated with poor outcomes in patients with COPD34: physical activity level and health status of patients with COPD,35 the symptom burden,36, 37, 38 prolonged sedentary time, and decreased physical activity levels can all affect the mortality rate and the number of exacerbations39 in patients with COPD. A study with a mean follow-up of 2.7 years found that the number of daily steps in patients with COPD decreased periodically over time, and this change was significantly correlated with the degree of airflow limitation in patients with COPD. Regular physical activity can alleviate the decline in lung function in patients with COPD, reduce the deterioration of health status (symptom burden)38, 40, 41, 42 and limit the risk of hospital admission and mortality in patients with COPD.43, 44 Although physical activity is also beneficial for COPD extrapulmonary comorbidities, related research is limited.22, 23 Moreover, these studies did not analyze the effect of serum vitamin D levels in patients with COPD. Sedentary behavior or insufficient physical activity are the risk factors for vitamin D deficiency in the elderly patients.45, 46 An analysis based on the NHANES data showed that physical activity was associated with serum vitamin D expression levels and was not related to the exercise environment (indoor or outdoor environment).47 However, Scragg et al. studied the NHANES III database and found that the association between outdoor exercise and vitamin D was stronger than that of indoor environments.48 Ceolin et al. showed that moderate-to-severe physical activity was a protective factor for maintaining normal levels of vitamin D in the elderly,46 and Scragg et al. found out that regular outdoor activities and activity frequency are associated with higher vitamin D levels, and not with activity intensity.48 The above findings were based on the general population, and our findings showed that adequate activity time was related to high levels of vitamin D expression in patients with COPD, while prolonged sedentary behavior was related to lower vitamin D levels in patients with COPD. This observation confirmed the independent association of physical activity and sedentary time with serum vitamin D levels in patients with COPD.

Considering that high-intensity physical activity can alleviate the harmful effects of being sedentary, we conducted a joint analysis of the relationship between physical activity time and sedentary time and serum vitamin D levels in patients with COPD. A meta-analysis summarizing evidence from papers involving more than 1 million adults discovered that the risk of death was 59% higher in the least active group (8 h/day of sedentary activity, 2.5 MET h/week of physical activity (about 30 min/week of LTPA)) when compared to the most active group (4 h/day of sedentary activity, physical activity 35.5 MET h/week). The study showed that high levels of physical activity appear to lower the risk of death due to prolonged sitting.49 Another study on cancer populations discovered that sedentary behavior was related to an increased risk of death among inactive cancer populations through a combined analysis of sedentary time and active time. Overall mortality (HR: 5.38; 95% CI: 2.99–9.67) and cancer (HR: 4.71; 95% CI: 1.60–13.9) mortality were the highest in inactive cancer patients who sat for more than 8 h/day.30 Our joint analysis revealed that insufficient physical activity, coupled with a sedentary lifestyle of less than 8 h, emerged as a risk factor contributing to the challenge of maintaining optimal vitamin D levels in COPD patients.

Furthermore, to strengthen the statistical significance of the present study, we eveluated several recent studies on vitamin D intervention and analyzed the odds of COPD occurrence.50, 51, 52 Based on these papers, we developed a forest plot indicating a strong possibility that vitamin D deficiency and hence its intervention can help in limiting COPD prevalence (Figure 2).

The impaired ability of the skin to synthesize vitamin D due to the toxic effects of smoking and age. Decreased activity and lack of outdoor exercise contribute to reduced sun exposure. Additionally, intake of glucocorticoids increases the metabolic breakdown of vitamin D. Furthermore, the natural course of COPD involves mechanisms such as inflammatory response, decreased liver potential activation function, decreased gastrointestinal absorption functions, and vitamin D being blocked in adipose tissue, all of which can lead to metabolic disorders of vitamin D in patients with COPD.53, 54 Physical activity may ameliorate the aforementioned disturbances through various mechanisms. High levels of inflammation in COPD patients, often associated with insufficient physical activity,35 can be mitigated by regular exercise training. This can lead to reductions in immune cell counts and a transformation of the cytokine phenotype from pro-inflammatory to anti-inflammatory.55, 56 Furthermore, physical activity has the potential to counteract the damage caused by smoking by reducing oxidase activity, promoting antioxidation57 and mitigating inflammation.32 Additionally, it worth noting that physical activity can also stimulate the release of vitamin D from adipocytes through fat mobilization, further contributing to its beneficial effects.58

Limitations

This study has several limitations. First, we could not make causal inferences in this cross-sectional study, so the association between physical activity and serum vitamin D in patients with COPD needs further confirmation. Second, although our study used a validated physical activity questionnaire, measurement error was inevitable. In addition, non-leisure physical activities (such as work) may have confounded the results of the measurements. Third, we did not analyze whether these activities were carried out outdoors or indoors.

Conclusions

In patients with COPD, serum vitamin D levels are independently associated with physical activity and sedentary behavior, and increasing physical activity time and reducing sedentary time may play an important role in improving vitamin D levels in COPD patients and preventing vitamin D deficiency. Future studies should analyze the effects of activity environment (indoor or outdoor, exposure to sunlight, etc.), frequency and intensity on serum vitamin D concentrations in COPD patients. In addition, the optimal duration of activity and sedentary time needs to be further confirmed.

Supplementary data

The Supplementary materials are available at https://doi.org/10.5281/zenodo.10124644. The package includes the following files:

Supplementary Table 1. Test of normality and homogeneity of variance.

Supplementary Table 2. Test of parallel lines of ordered logistic regression models investigate the association between the joint association of DST and LTPA and serum 25 (OH)D concentrations in COPD patients.

Supplementary Table 3. Test of parallel lines of ordered logistic regression models investigate the association between DST and serum 25 (OH)D concentrations in COPD patients.

Supplementary Table 4. Test of parallel lines of ordered logistic regression models were used to investigate the association between the joint association of DST and LTPA and serum 25 (OH)D concentrations in COPD patients.

Supplementary Table 5. Multivariate logistic regression models were used to investigate the association between LTPA and serum 25 (OH)D concentrations in COPD patients.

Supplementary Table 6. Multivariate logistic regression models were used to investigate the association between DST and serum 25 (OH)D concentrations in COPD patients.

Supplementary Table 7. Multivariate logistic regression models were used to investigate the association between association of DST and LTPA and serum 25 (OH)D concentrations in COPD patients.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.

Consent for publication

Not applicable.

Tables


Table 1. Demographic and clinical characteristics of patients

Characteristic

All

(1,448)

Vitamin D deficiency

(360)

Vitamin D insufficiency

(539)

Vitamin D sufficiency

(549)

Statistical value

p-value

Vitamin D [nmol/L], mean ±SD

68.27 ±26.78

35.48 ±9.20

63.00 ±7.07

94.96 ±18.49

1271.28 (K–W)

0.000

25(OH)D3 [nmol/L], mean ±SD

63.65 ±26.30

33.28 ±9.37

59.15 ±9.53

87.98 ±21.47

1087.83 (K–W)

0.000

25(OH)D2 [nmol/L], mean ±SD

4.62 ±11.71

2.19 ±3.03

3.84 ±6.67

6.96 ±17.38

43.47 (K–W)

0.000

Number of patients with vitamin D intake (%)

343 (23.7)

21 (1.5)

115 (7.9)

207 (14.3)

124.81 (χ2)

0.000

Vitamin D intake [μg], mean ±SD

21.49 ±134.56

12.38 ±5.62

33.91 ±232.06

15.51 ±11.11

12.81 (K–W)

0.002

Age [years], mean ±SD

62.06 ±10.35

60.93 ±9.87

61.68 ±10.71

63.19 ±10.20

12.72 (K–W)

0.002

40–60, n (%)

598 (41.3)

164 (11.3)

233 (16.1)

201 (13.9)

8.49 (χ2)

0.014

>60, n (%)

850 (58.7)

196 (13.5)

306 (21.1)

348 (24.0)

Sex, n (%)

men

913 (63.1)

222 (15.3)

365 (25.2)

326 (22.5)

8.51 (χ2)

0.014

women

535 (36.9)

138 (9.5)

174 (12.0)

223 (15.4)

BMI [kg/m2], mean ±SD

27.85 ±5.97

28.40 ±7.04

28.26 ±5.99

27.08 ±5.06

10.74 (K–W)

0.005

<25, n (%)

502 (34.7)

129 (8.9)

163 (11.3)

210 (14.5)

20.72 (χ2)

<0.001

25–30, n (%)

522 (36.1)

105 (7.3)

211 (14.6)

206 (14.2)

≥30, n (%)

422 (29.2)

126 (8.7)

163 (11.3)

133 (9.2)

Race, n (%)

Mexican American

105 (7.3)

34 (2.3)

50 (3.5)

21 (1.5)

148.79 (χ2)

<0.001

Other Hispanic

23 (1.6)

41 (2.8)

36 (2.5)

100 (6.9)

Non-Hispanic White

887 (61.3)

148 (10.2)

326 (22.5)

413 (28.5)

Non-Hispanic Black

277 (19.1)

134 (9.3)

94 (6.5)

49 (3.4)

Other

79 (5.5)

21 (1.5)

28 (1.9)

30 (2.1)

Family poverty–income ratio*, n (%)

<1.3

433 (33.7)

139 (10.8)

152 (11.8)

143 (11.1)

28.33 (χ2)

<0.001

from 1.3 to <3.5

502 (39.1)

116 (9.0)

200 (15.6)

186 (14.5)

≥3.5

350 (27.2)

59 (4.6)

133 (10.4)

158 (12.3)

Educational attainment*, n (%)

High school or less

793 (54.8)

219 (15.1)

302 (20.9)

272 (18.8)

18.82 (χ2)

0.001

Some college

366 (25.3)

90 (6.2)

137 (9.5)

139 (9.6)

College graduate or higher

288 (19.9)

51 (3.5)

100 (6.9)

137 (9.5)

Smoking, n (%)

Never

401 (27.7)

82 (5.7)

157 (10.8)

162 (11.2)

35.59 (χ2)

<0.001

Former

548 (37.8)

109 (7.5)

207 (14.3)

232 (16.0)

Current

400 (34.5)

169 (11.7)

175 (12.1)

155 (10.7)

Comorbidities, n (%)

Asthma

276 (19.1)

79 (5.5)

104 (7.2)

93 (6.4)

3.56 (χ2)

0.169

Congestive heart failure*

69 (4.8)

19 (1.3)

22 (1.5)

28 (2.0)

0.92 (χ2)

0.631

Coronary heart disease*

105 (7.3)

25 (1.7)

47 (3.3)

33 (2.3)

3.04 (χ2)

0.218

Diabetes

229 (15.8)

72 (5.0)

80 (5.5)

77 (5.3)

7.32 (χ2)

0.120

Cancer

244 (16.9)

52 (3.6)

80 (5.5)

112 (7.7)

7.92 (χ2)

0.019

Arthritis

603 (41.6)

135 (9.3)

215 (14.8)

253 (17.5)

7.68 (χ2)

0.021

FEV1 and FVC, mean ±SD

FEV1(L)

2.35 ±0.79

2.17 ±0.74

2.40 ±0.81

2.43 ±0.77

22.32 (K–W)

0.000

FVC(L)

3.72 ±1.12

3.48 ±1.06

3.79 ±1.14

3.80 ±1.11

18.58 (K–W)

0.000

FEV1/FVC

0.63 ±0.07

0.62 ±0.08

0.63 ±0.07

0.64 ±0.07

10.18 (K–W)

0.006

LTPA [min/wk], mean ±SD

137.93 ±299.61

94.63 ±286.90

136.07 ±299.85

168.16 ±304.43

32.93 (K–W)

0.000

None (inactive), n (%)

859 (59.3)

251 (17.3)

325 (22.4)

283 (19.5)

34.78 (χ2)

0.039

From 0 to <150 (insufficiently active), n (%)

231 (16.0)

49 (3.4)

90 (6.2)

92 (6.4)

≥150 (active), n (%)

358 (24.7)

60 (4.1)

124 (8.6)

174 (12.0)

DST [h], mean ±SD

5.45 ±3.29

5.84 ±3.45

5.37 ±3.39

5.27 ±3.07

6.47 (K–W)

0.023

<4, n (%)

700 (48.3)

154 (10.6)

270 (18.6)

276 (19.1)

10.252 (χ2)

0.114

4–6, n (%)

317 (21.9)

82 (5.7)

106 (7.3)

129 (8.9)

6–8, n (%)

204 (14.1)

57 (3.9)

77 (5.3)

70 (4.8)

>8, n (%)

227 (15.7)

67 (4.6)

86 (5.9)

74 (5.1)

BMI – body mass index; K–W – Kruskal–Wallis H test; FEV1 – forced expiratory volume in 1 second; FVC – forced vital capacity; SD – standard deviation; LTPA – leisure-time physical activity; DST – daily sitting time; min/wk – minutes per week; *there was some missing data in these baseline characteristics.
Table 2. The expression of vitamin D according to LTPA

The expression of vitamin D

LTPA

Statistical value

p-value

(Kruskal–Wallis H test)

None

(inactive)

from 0 to <150

(insufficiently active)

≥150

(active)

Vitamin D [nmol/L]

65.11 ±27.02

69.23 ±24.99

74.93 ±26.07

39.51

<0.001

25(OH)D2 [nmol/L]

4.39 ±11.80

5.03 ±12.19

4.89 ±11.16

13.43

0.001

25(OH)D3 [nmol/L]

60.71 ±26.13

64.67 ±24.52

70.05 ±26.70

33.58

<0.001

SD – standard deviation; LTPA – leisure-time physical activity. Values are presented as mean ±SD.
Table 3. The expression of vitamin D according with the level of daily sitting time

The expression of vitamin D

Daily sitting time [h]

Statistical value

p-value

(Kruskal–Wallis H test)

<4

4–6

6–8

>8

Vitamin D [nmol/L]

68.80 ±25.92

69.78 ±26.20

67.51 ±29.19

65.23 ±27.83

6.18

0.103

25(OH)D2 [nmol/L]

4.15 ±9.23

4.37 ±9.92

5.82 ±16.67

5.33 ±15.00

0.07

0.995

25(OH)D3 [nmol/L]

64.66 ±25.89

65.39 ±26.53

61.69 ±28.58

59.89 ±24.76

8.58

0.036

SD – standard deviation. Values are presented as mean ±SD.
Table 4. The expression of vitamin D according with the joint associations of total sitting time and leisure-time physical activity (LTPA)

Activity time [h]

<150

≥150

Statistical value

p-value

(Kruskal–Wallis H test)

Sedentary time [h]

>8

≤8

>8

≤8

Vitamin D [nmol/L]

60.94 ±28.05

67.06 ±26.29

78.97 ±22.31

74.22 ±26.66

44.32

<0.001

25(OH)D2 [nmol/L]

5.24 ±15.63

4.39 ±11.04

5.61 ±12.90

4.76 ±10.84

8.21

0.042

25(OH)D3 [nmol/L]

55.6 ±23.70

62.66 ±26.08

73.34 ±23.42

69.4 ±27.24

39.94

<0.001

SD – standard deviation. Values are presented as mean ±SD.
Table 5. Relationship between vitamin D and related factors

Variables

Vitamin D

[nmol/L]

FEV1

[L]

FVC

[L]

BMI

[kg/m2]

Age

[years]

DST

[h]

LTPA [min/week]

Vitamin D [nmol/L]

1

0.095*

0.084*

–0.080*

0.096*

–0.036

0.160*

FEV1 [L]

1

0.943*

–0.077*

–0.336*

0.002

0.185*

FVC [L]

1

–0.095*

–0.328*

0.025

0.157*

BMI [kg/m2]

1

0.054#

0.142*

–0.035

Age [years]

1

0.018

–0.025

DST [h]

1

–0.008

LTPA [min/week]

1

Spearman correlation coefficient was used. *p < 0.01; #p < 0.05; BMI – body mass index; FEV1 – forced expiratory volume in 1 second; FVC – forced vital capacity; LTPA – leisure-time physical activity; DST – daily sitting time.
Table 6. Ordered logistic regression models investigated the association between LTPA and serum 25(OH)D concentrations in chronic obstructive pulmonary disease (COPD) patients

Models

LTPA [min/week]

Wald χ2

p-value for tend

none

(745, 59.1%)

from 0 to <150

(204, 16.2%)

≥150

(312, 24.7%)

Model 1

Ref.

1.42 (1.08, 1.85)

1.97 (1.56, 2.49)

33.92

0.000

Model 2

Ref.

1.32 (1.01, 1.74)

1.89 (1.49, 2.39)

27.71

0.000

Model 3

Ref.

1.20 (0.89, 1.62)

1.67 (1.28, 2.20)

13.69

0.000

Model 4

Ref.

1.17 (0.86, 1.59)

1.49 (1.13, 1.98)

7.84

0.005

Model 5

Ref.

1.18 (0.87, 1.61)

1.51 (1.14, 2.00)

8.27

0.004

Model 1 – LTPA; Model 2 – LTPA, age, sex, race; Model 3 – LTPA, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking; Model 4 – LTPA, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FEV1, vitamin D intake;
Model 5 – LTPA, age, sex, race,
BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FVC, vitamin D intake.
LTPA – leisure-time physical activity; FEV
1 – forced expiratory volume in 1 second; FVC – forced vital capacity; OR – odds ratio; 95% CI – 95% confidence interval. In the logistic regression model, LTPA was treated as the predictor. Values are presented as OR (95% CI).
Table 7. Ordered logistic regression models investigated the association between DST and serum 25(OH)D concentrations in chronic obstructive pulmonary disease (COPD) patients

Models

DST [h]

Wald χ2

p-value for tend

per 1 h/d increase

<4

4–6

6–8

>8

Model 1

Ref.

0.95 (0.75, 1.22)

0.77 (0.58, 1.03)

0.72 (0.54, 0.95)

6.98

0.008

0.97 (0.94, 0.99)

Model 2

Ref.

0.84 (0.65, 1.08)

0.69 (0.52, 0.93)

0.58 (0.44, 0.78)

15.84

0.000

0.94 (0.91, 0.97)

Model 3

Ref.

0.85 (0.65, 1.12)

0.70 (0.51, 0.96)

0.53 (0.38, 0.72)

16.89

0.000

0.93 (0.90, 0.96)

Model 4

Ref.

0.85 (0.64, 1.12)

0.68 (0.49, 0.95)

0.47 (0.34, 0.65)

21.11

0.000

0.92 (0.89, 0.95)

Model 5

Ref.

0.84 (0.63, 1.12)

0.67 (0.48, 0.94)

0.47 (0.34, 0.65)

21.42

0.000

0.92 (0.89, 0.95)

Model 1 – DST; Model 2 – DST, age, sex, race; Model 3 – DST, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking; Model 4 – DST, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FEV1, vitamin D intake;
Model 5 – DST, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FVC, vitamin D intake
.
DST – daily sitting time; OR – odds ratio; 95% CI – 95% confidence interval; in the logistic regression model, DST
was treated as the predictor.
Values are presented as OR (95% CI).
Table 8. Ordered logistic regression models investigated the joint association of daily sitting time (DST) and leisure-time physical activity (LTPA) with vitamin D levels among chronic obstructive pulmonary disease (COPD) patients

Activity time [h]

<150

≥150

Wald χ2

p-value for tend

Sedentary time [h]

>8

(173, 11.9%)

≤8

(917, 63.3%)

>8

(54, 3.7%)

≤8

(304, 21.0%)

Model 1

Ref.

1.57 (1.17, 2.13)

3.36 (1.87, 6.03)

2.57 (1.81, 3.65)

35.98

<0.001

Model 2

Ref.

1.82 (1.33, 2.49)

3.35 (1.85, 6.09)

2.86 (2.00, 4.10)

35.67

<0.001

Model 3

Ref.

2.04 (1.46,2.87)

3.28 (1.69, 6.34)

2.83 (1.91, 4.19)

25.27

<0.001

Model 4

Ref.

2.13 (1.50, 3.01)

2.74 (1.83, 4.12)

2.32 (1.18, 4.59)

16.89

<0.001

Model 5

Ref.

2.13 (1.50, 3.01)

2.76 (1.84, 4.14)

2.33 (1.18, 4.60)

17.21

<0.001

Model 1 – the joint of daily sitting time and leisure-time physical activity; Model 2 – the joint of daily sitting time and leisure-time physical activity, age, sex, race; Model 3 – the joint of daily sitting time and leisure-time physical activity, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking; Model 4 – the joint of daily sitting time and leisure-time physical activity, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FEV1, vitamin D intake; Model 5 – the joint of daily sitting time and leisure-time physical activity, age, sex, race, BMI, family poverty–income ratio, educational attainment, smoking, comorbidities, FVC, vitamin D intake.
eFEV1 – forced expiratory volume in 1 second; FVC – forced vital capacity; OR – odds ratio; 95% CI – 95% confidence interval; BMI - body mass index. Values are presented as OR (95% CI).

Figures


Fig. 1. Flow diagram of the overall procedure. A total of 1,448 samples were included for analysis
COPD – chronic obstructive pulmonary disease.
Fig. 2. The expression of vitamin D in different leisure-time physical activity (LTPA) levels
Fig. 3. The expression of 25(OH)D2 in different leisure-time physical activity (LTPA) levels
Fig. 4. The expression of 25(OH)D3 in different leisure-time physical activity (LTPA) levels
Fig. 5. The expression of vitamin D in different daily sitting time (DST) levels
Fig. 6. The expression of 25(OH)D2 in different daily sitting time (DST) levels
Fig. 7. The expression of 25(OH)D3 in different daily sitting time (DST) levels
Fig. 8. The expression of vitamin D in combined analysis of physical activity time and daily sitting time (DST)
Fig. 9. The expression of 25(OH)D2 in combined analysis of physical activity time and DST
Fig. 10. The expression of 25(OH)D3 in combined analysis of physical activity time and daily sitting time (DST)

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