2.1 Study Design

This study is a cross-sectional study that collected physical examination data of healthcare professionals at Shanxi Bethune Hospital from January to March 2022. The primary aim of this study is to compare the vitamin D deficiency status between doctors and nurses. All personal privacy information was removed before analysis.

2.2 Participants

All on-duty healthcare professionals without malignant diseases during the physical examination.

The inclusion criteria for hospital staff physical examination records were enrolled.

• Age ≥ 23 and ≤60

• LPs or nurses of Shanxi Bethune Hospital

The exclusion criteria for hospital staff physical examination records were enrolled.

• Third-party dispatched personnel

• ID number missing

• Duplicated records

• Staff with malignant neoplasms

• Retired employees

2.3 Ethical Approval and Consent to Participate

This study was approved by the Institutional Ethical Review Board of Shanxi Bethune Hospital (No. YXLL-2023-185, YXLL-SL-2022-221), according to the ethical guidelines of the Helsinki Declaration. All hospital staff signed Informed consent for clinical data use. As all data utilized in this study were anonymized, the requirement for informed consent was therefore waived.

2.4 Measurement Standards

Due to the stable nature of serum 25-hydroxyvitamin D (25-(OH)D), it is used as a marker for vitamin D status. Although there is controversy over using these cut-off values to define vitamin D deficiency, most agree that vitamin D levels <20 ng/mL (50 nmol/L) are considered deficient, 21 - 29 ng/mL (52 - 72 nmol/L) are considered insufficient, and >30 ng/mL (75 nmol/L) are considered sufficient 20. The IOM DRI committee in the United States suggested that people are at risk of deficiency at serum 25(OH)D concentrations <12 ng/mL (30 nmol/L).At the same time, studies have used the most conservative serum 25(OH)D threshold of <10/12 ng/mL (25/30 nmol/L) 8. This study used the enzyme-linked immunosorbent assay (ELISA) to measure [25(OH)D]. The range provided in the reagent instructions is <12.3 ng/mL (30.75 nmol/L) 19.

Besides basic information such as height, weight, gender, age, and blood pressure, we also collect other laboratory indicators from participants, including thyroid-stimulating hormone (TSH), Free triiodothyronine (FT3), Free thyroxine (FT4), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), UA, cholesterol (CHO), triglycerides (TG), and glucose (Glu). In addition, there are job-related factors such as involvement in surgical procedures and exposure to radiation.

3.1 Demographic Information

The demographic informations of all participants are listed in Table 1. A significant disparity in sex is observed, with 39.14% of LPs being male compared to 6.59% among nurses (P<0.001). LPs tend to be older, with a mean age of 36.89 years, while nurses have a mean age of 33.33 years (P<0.001). The mean BMI is higher for LPs (23.97 kg/m²) compared to nurses (22.64 kg/m²) (P<0.001). A larger proportion of nurses fall within the normal BMI range (66.54%) compared to LPs (52.80%), whereas more LPs are classified as overweight or obese (44.74% vs. 29.27%) (P<0.001). The incidence of hypertension is greater among LPs (32.57%) compared to nurses (22.23%) (P<0.001). Additionally, nurses are more frequently involved in surgical-related work (48.73% vs. 41.45%) (P<0.001) but have less radiation exposure (3.44% vs. 19.74%) (P<0.001) compared to LPs.

3.2 Laboratory Testing Results

hows the laboratory testing results for health professionals. There are no significant differences in FT3 and FT4 levels between the groups, with both having a mean FT3 of 3.70pg/mL and FT4 of 0.86 ng/dL. However, the median TSH level is 2.24 μIU/mL for LPs and 2.38 μIU/mL for nurses which shows significant difference. (P=0.0165). LDL-C levels are higher in LPs (3.05 mmol/L) compared to nurses (2.81 mmol/L) (P<0.001), while HDL-C levels are lower in LPs (1.36 mmol/L) compared to nurses (1.41 mmol/L) (P<0.001). The median UA level is higher in LPs (291.9 μmol/L) than in nurses (255.5 μmol/L) (P<0.001). CHO levels are higher in LPs (4.75 mmol/L) compared to nurses (4.49 mmol/L) (P<0.001). Glc levels are also higher in LPs (4.99 mmol/L) compared to nurses (4.80 mmol/L) (P<0.001). TG levels are higher in LPs, with a median of 1.03 mmol/L compared to 0.82 mmol/L in nurses (P=0.0001). The median vitamin D level is slightly higher in LPs (9.4 ng/mL) compared to nurses (8.7 ng/mL) (P=0.0001), but both groups exhibit a high prevalence of vitamin D deficiency, with 78.12% of LPs and 85.63% of nurses affected (P<0.001) (Figure 2).

3.3 Primary Endpoint

Table 3 shows the results of logistic regression analysis of vitamin D deficiency.

3.4 Univariable Analysis Results

The univariable analysis identifies several factors associated with vitamin D deficiency among health professionals. Age over 30 years is linked to a lower likelihood of vitamin D deficiency (OR=0.61, 95% CI 0.45-0.82, P=0.001). Job category is also a significant factor, with nurses more likely to have vitamin D deficiency compared to LPs (OR=1.67, 95% CI 1.30-2.13, P<0.001). BMI within the normal range serves as the reference group, with underweight individuals (BMI <18) showing an OR of 1.97 (P=0.119) and overweight individuals (BMI >24) showing an OR of 0.72 (P=0.010). UA levels below the normal range are associated with an increased risk of vitamin D deficiency (OR=1.53, P=0.026), whereas UA levels above the normal range show a decreased risk (OR=0.53, P=0.009). CHO levels below (OR=0.68, P=0.221) and above (OR=0.72, P=0.025) the normal range are not significant. The other factors examined, TSH levels, FT3 levels, FT4 levels, LDL-C levels, TG levels, Glc levels, hypertension, engagement in surgery-related work, and radiation exposure did not exhibit a significant association with the prevalence of vitamin D deficiency.

3.5 Multivariable Analysis Results

The multivariable analysis further refines the associations between various factors and vitamin D deficiency. Age over 30 years continues to be associated with a lower likelihood of vitamin D deficiency (OR=0.68, 95% CI 0.50-0.92, P=0.013). Job category remains a significant factor, with nurses still more likely to have vitamin D deficiency compared to LPs (OR=1.26, 95% CI 1.10-1.44, P=0.001). UA levels below the normal range continue to show an increased risk of vitamin D deficiency (OR=1.51, P=0.034), while UA levels above the normal range show a decreased risk (OR=0.57, P=0.048).

The rest of other factors examined, including TSH levels, FT3 levels, FT4 levels, LDL-C levels, CHO levels, TG levels, BMI, Hypertension, engagement in surgical relevant work, and radiation exposure are also not significantly associated with vitamin D deficiency.

3.6 Sensitivity Analysis with IPTW Data Set

Table 4 presents the IPTW data set for health professionals, comparing LPs and nurses across various parameters and all the variables are well-balanced with SMD from 0.001 to 0.083, p-values from 0.152 to 0.983.

Table 5 compares the prevalence of vitamin D deficiency between LPs and nurses using the IPTW data set. The results indicate that vitamin D deficiency is prevalent in both groups but higher among nurses. Specifically, 78.02% of LPs are affected by vitamin D deficiency, compared to 83.41% of nurses (P=0.032). This statistically significant difference suggests that, even after adjusting for various confounding factors using IPTW, nurses are more likely to experience vitamin D deficiency compared to LPs.

Acknowledgment

We extend our gratitude to Cuiqin Liu and Jingfang He from Bothwin Clinical Study Consultants for their valuable assistance and dedication to data analysis.

Sources of Support

• Yunnan Science and Technology Leading Talents Project, Young and Middle-aged Academic and Technical Leaders Reserve Talents Project (No. 202405AC350046 to X.L.)

• Technology Innovation Team of Kunming Medical University (No. CXTD202104 to X.L.)

• Yunnan Clinical Research Center for Neurological Diseases (No. ZX20190305 to X.L.)

• Shanxi Provincial Science and Technology Department Basic Research Program Project (No.202203021212093 to R.D.)

• Research Start-up Fund Project for Talent Introduction at Shanxi Bethune Hospital (No. 2021RC031 to R.D.)

Author Contributions

Y.W. contributed to the conceptualization and writing original draft. D.Z. handled data curation and writing. P.W. was involved in data curation and investigation. J.Z. focused on formal analysis and methodology. X.L. contributed to funding acquisition and methodology. R.D. was responsible for funding acquisition, resources, and validation. G.D. was involved in data curation and investigation. F.G. was responsible for the conceptualization, project administration, and supervision. All authors reviewed and edited this manuscript.