Vitamin D supplementation and selected metabolic parameters in patients with type 2 diabetes and obesity: a prospective observational study

Introduction: Vitamin D deficiency has been implicated in metabolic dysregulation, including insulin resistance and inflammation, commonly observed in patients with type 2 diabetes mellitus (T2DM) and obesity. Evidence on the metabolic impact of vitamin D supplementation in this population remains inconsistent.

Objective: To evaluate the effects of high-dose vitamin D3 supplementation on anthropometric and selected metabolic parameters in ambulatory obese patients with T2DM treated with metformin monotherapy.

Methods: This 12-week prospective cohort study included 200 patients with T2DM, allocated to a supplementation group (n = 100; vitamin D3 - 4,000 IU/day) or a control group (n = 100; no supplementation). Primary outcome was change in serum 25-hydroxyvitamin D [25(OH)D] concentration. Secondary outcomes included fasting serum glucose (FSG), glycated hemoglobin (HbA1c), blood pressure (BP), serum calcium, and body mass index (BMI). Predictors of failure to achieve target HbA1c ≤ 6.5% were identified using logistic regression.

Results: After 12 weeks, serum 25(OH)D significantly increased in the supplementation group compared with controls (Δ +23.7 vs +1.3 ng/mL; p < 0.001). FSG and HbA1c decreased significantly in the intervention group (Δ –0.4 mmol/L, p = 0.02; Δ –0.6%, p = 0.01, respectively), while no significant changes were observed in systolic or diastolic BP, serum calcium, or BMI. Logistic regression identified higher baseline FSG (OR 1.34, 95% CI 1.12–1.61), longer diabetes duration (OR 1.28, 95% CI 1.07–1.54), and higher BMI (OR 1.21, 95% CI 1.01–1.47) as independent predictors of suboptimal glycemic response.

Conclusions: High-dose vitamin D3 supplementation significantly improved vitamin D status and was associated with modest improvements in glycemic control in obese patients with T2DM, without affecting blood pressure, calcium, or body weight. These findings support vitamin D repletion as a potential adjunctive strategy in diabetes management, while not allowing causal inference, and warrant further confirmation in randomized controlled trials with longer follow-up.

1 Introduction

Since the 1990s, observational studies have consistently shown that serum 25-hydroxyvitamin D [25(OH)D] concentrations are inversely associated with type 2 diabetes mellitus (T2DM) and features of the metabolic syndrome (MS), although the causal relationship remains uncertain, as later highlighted in several meta-analyses (1–3). Important findings come from ‘The vitamin D and type 2 diabetes study (D2d)”, which was a randomized clinical trial (RCT) of overweight/obese participants in a prediabetes state, randomized to vitamin D_3–4000 IU daily vs. placebo and followed for 2.5 years for the primary outcome of T2DM. This study revealed that an intra-trial mean serum 25 (OH) D level ≥ 40 ng/mL was associated with significantly reduced risk of T2DM, but only among participants with body mass index (BMI) < 40 kg/m². The researchers suggested that targeting a serum 25 (OH) D level ≥ 40 ng/mL would be one of the T2DM prevention strategy in a prediabetic population with body mass excess (4).

Vitamin D deficiency exacerbates metabolic dysfunction through mechanisms involving insulin resistance (IR), inflammation, and dyslipidemia (5–7). Vitamin D is crucial for the regulation of insulin secretion in response to glucose and the modulation of hepatic glucose and triglyceride (TG) synthesis. It also contributes to reducing inflammation associated with IR, thereby lowering the risk of developing T2DM and cardiovascular disease (8–11). Moreover, vitamin D modulates intracellular calcium levels in pancreatic β-cells and hepatocytes, improving insulin sensitivity (12).

Deficiency of vitamin D exhibits pro-inflammatory activity and influences signaling pathways such as the receptor for advanced glycation end products (RAGE), promoting the development of both type 1 diabetes mellitus (T1DM) and T2DM (13). The discovery of 1,25(OH)₂D₃ and 1-α-hydroxylase expression in pancreatic β-cells further supports vitamin D’s role in glucose homeostasis (13). Vitamin D deficiency has also been linked to elevated inflammatory markers, including interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and high-sensitivity C-reactive protein (hs-CRP), which contribute to T2DM pathogenesis. Vitamin D supplementation (VDS) has been shown to downregulate RAGE expression (13).

Previous studies have highlighted the difficulty of correcting vitamin D deficiency in obese individuals, who often exhibit reduced serum 25(OH)D concentrations as a result of adipose tissue sequestration, volumetric dilution, and decreased bioavailability (14–16). Pharmacokinetic evidence suggests that individuals with obesity require higher doses of vitamin D to achieve sufficient serum concentrations (17). Findings from RCTs and meta-analyses regarding changes in fasting serum glucose (FSG), glycated hemoglobin (HbA1c), body weight, insulin resistance (IR), and lipid profiles following VDS remain inconsistent (2, 3, 18–22). Chen et al. observed that young adults with vitamin D deficiency had a significantly higher risk of developing atherogenic dyslipidemia, indicating a potential role of vitamin D in the treatment of dyslipidemia (21). Similarly, it was highlighted that patients treated with statins who had low serum vitamin D levels had a higher risk of muscle pain (22).

Regarding oncological outcomes, meta-analyses of prospective cohort studies examining non-skeletal effects have demonstrated a significantly reduced risk of colorectal cancer among individuals with higher 25(OH)D concentrations, although this association has not been observed for most other malignancies (23). In an umbrella review, Liu et al. reported an association between vitamin D supplementation and lower all-cause mortality, but not with reduced risk of T2DM, Alzheimer’s disease, arterial hypertension, or schizophrenia (24).

Lifestyle interventions—particularly dietary counseling and structured physical activity—remain the cornerstone of T2DM and obesity management. Both approaches independently improve anthropometric, glycemic, and lipid outcomes (25, 26). One RCT in obese menopausal women reported that vitamin D₃ supplementation enhanced the effects of supervised aquatic aerobic training on physical fitness indices compared with training alone, suggesting a potential synergistic effect on functional outcomes (27). However, whether VDS exerts additive or synergistic effects when combined with lifestyle measures remains uncertain.

The aim of this study was to evaluate the association between VDS and changes in anthropometric and selected metabolic parameters in ambulatory obese patients with T2DM.

2 Materials and methods

2.1 Study design and population

This 12-week prospective cohort study was conducted in Poland during the autumn–winter season (October 1, 2024 to March 31, 2025). Participants were recruited consecutively from a single outpatient metabolic clinic; all eligible patients attending routine follow-up visits during the recruitment period were screened and invited to participate, ensuring a non-selective recruitment process.

2.2 Attrition and follow-up

No participants were lost to follow-up. All 200 enrolled patients completed baseline and 12-week assessments and were included in the final analyses.

2.3 Seasonal control

Seasonal variability in endogenous vitamin D synthesis was minimized by conducting the entire study within a single autumn–winter period, when cutaneous vitamin D production is minimal at the study latitude.

2.4 Adherence assessment

Adherence to vitamin D supplementation was assessed using pill counts and self-reports. In addition, adherence was indirectly supported by the marked and consistent increase in serum 25(OH)D concentrations observed in the supplementation group.

2.5 Missing data

No missing data were observed for primary or secondary endpoints; therefore, no imputation procedures were required and all analyses were performed on complete cases.

2.6 Protocol and registration

The study protocol was predefined and approved by the institutional bioethics committee (see: 2.7 Ethical Approval). However, the study was not prospectively registered in a public registry, reflecting its observational design. This is acknowledged as a limitation.

2.7 Ethical approval

The decision to include a patient in the study was made by the attending physician. All recruited participants were fully informed about the study’s aims and conditions and provided written informed consent to participate. The study protocol was approved by the Bioethics Committee of the Poznan University of Medical Sciences (approval no. KB-664/23, September 13, 2023).

2.8 Inclusion criteria

Participants were eligible if they met the following criteria:

1. Age 18–64 years (young adulthood 18–39 years and middle adulthood 40–64 years)

2. Diagnosis of T2DM for at least 6 months according to the Polish Diabetes Association guidelines (28).

3. Baseline HbA1c between 6.5% and 7.5%.

4. Stable metformin monotherapy (1,500–2,000 mg/day) for at least 3 months before enrollment.

5. Serum calcium within the normal laboratory range.

2.9 Exclusion criteria

Patients were excluded for any of the following:

1. Current or recent (<6 months) use of vitamin D or calcium supplements.

2. Use of other antidiabetic agents (e.g., insulin, sulfonylureas, DPP-4 inhibitors, SGLT2 inhibitors, GLP-1 receptor agonists).

3. Advanced diabetic complications (e.g., nephropathy stage ≥3, proliferative retinopathy, or severe neuropathy).

4. History of hypercalcemia, nephrolithiasis, or parathyroid disorders.

5. Severe hepatic or renal impairment (eGFR <45 mL/min/1.73 m²).

6. Participation in another research study within the past 6 months.

7. Pregnancy or lactation.

8. Active malignancy or chemotherapy within 6 months.

9. Chronic liver disease (Child-Pugh class B or C) use of medications affecting vitamin D metabolism (anticonvulsants, glucocorticoids)

2.10 Intervention

Participants in the supplementation group received oral vitamin D₃ - 4,000 IU daily for 12 weeks. The control group received no supplementation. Both cohorts continued stable metformin monotherapy throughout the study to ensure treatment uniformity. Adherence was verified by pill counts and self-reports.

2.11 Clinical endpoints

Primary endpoint:

• Change in serum 25(OH)D levels after 12 weeks.

Secondary endpoints:

● Changes in FSG, HbA1c, systolic and diastolic blood pressure (SBP, DBP), serum calcium, and BMI.

● Identification of predictors of failure to achieve HbA1c ≤6.5% (≤48 mmol/mol) after 12 weeks.

2.12 Measurements

Fasting blood samples were collected at baseline and after 12 weeks.

Laboratory Methods: All laboratory analyses were performed at the hospital’s certified clinical laboratory using standardized protocols.

Biochemical Measurements (29–31):

● 25-hydroxyvitamin D: Electrochemiluminescence immunoassay (Roche Cobas, Basel, Switzerland)

● Glucose: Hexokinase method (Roche Cobas)

● HbA1c: High-performance liquid chromatography (Bio-Rad Variant II, Hercules, CA)

Quality Control: Internal quality control samples were analyzed with each batch. External quality assurance was maintained through participation in national proficiency testing programs.

BP was measured in the seated position with an automated sphygmomanometer (average of three readings). BMI was calculated from measured weight and height.

2.13 Statistical analysis

Continuous variables are expressed as mean ± standard deviation (SD). Baseline group comparisons were performed with independent Student’s t-tests or chi-square tests for categorical variables. Within-group changes were analyzed using paired t-tests, and between-group differences in mean change (Δ) were compared with independent t-tests.

Multiple logistic regression identified predictors of failure to achieve HbA1c ≤6.5% at 12 weeks. Covariates included age (per 10 years), gender, FSG (per 2 mmol/L), BMI (per 5 kg/m²), and duration of T2DM (per 6 months). Results are presented as odds ratios (OR) with 95% confidence intervals (CI).

A two-sided p-value <0.05 was considered statistically significant. Analyses were performed using SPSS version 27.0 (IBM Corp., Armonk, NY, USA).

3 Results

3.1 Baseline characteristics

The study cohort included 200 patients with T2DM (51% men, 49% women) with a mean age of 58.6 ± 7.35 years and a mean BMI of 30.1 ± 3.5 kg/m². In the entire study cohort, the mean duration of T2DM was 1.4 ± 0.6 years, the mean HbA1c level was 6.8 ± 0.9%, and the mean FSG level was 5.8 ± 0.2 mmol/l. At baseline, mean serum 25(OH)D concentrations in both groups (~21–22 ng/mL) corresponded to vitamin D deficiency/insufficiency according to established clinical thresholds. The baseline clinical characteristics of the study participants and controls are presented in Table 1. No significant differences were observed between groups at baseline with respect to age, sex distribution, diabetes duration, serum 25(OH)D, FSG, HbA1c, BP, serum calcium, or BMI (all p > 0.5). (Table 1).

Table 1

Table 1. Baseline clinical characteristics of study and control participants.

3.2 Changes in selected metabolic parameters after 12 weeks of vitamin D3 supplementation in patients with T2DM

After 12 weeks, the supplementation group achieved a mean serum 25(OH)D concentration of approximately 45 ng/mL, corresponding to vitamin D sufficiency, whereas the control group remained within the deficient/insufficient range. Significant improvements were also observed in FSG and HbA1c, with mean reductions of –0.4 mmol/L and –0.6%, respectively, in the supplementation group. Changes in SBP and DBP, serum calcium, and BMI were not statistically significant (Table 2; Figures 1, 2).

Table 2

Table 2. Changes in selected metabolic parameters after 12 weeks of vitamin D3 supplementation in patients with T2DM.

Figure 1

Figure 1. Baseline and follow-up clinical parameter levels in both groups.

Figure 2

Figure 2. Comparative changes (Δ) in key clinical parameters: study vs. control group.

Multiple logistic regression identified predictors of failure to achieve target HbA1c ≤ 6.5% (≤ 48 mmol/mol). Higher baseline FSG and longer T2DM duration were strongly associated with suboptimal glycemic control, with odds ratios (OR) of 1.34 (95% CI: 1.12–1.61; p = 0.001) and 1.28 (95% CI: 1.07–1.54; p = 0.006), respectively. Elevated BMI was also significantly associated with poor glycemic control (OR 1.21; 95% CI: 1.01–1.47; p = 0.04). In contrast, age and sex were not significant predictors (Table 3).

Table 3

Table 3. Multiple logistic regression analysis of predictors associated with failure to achieve target HbA1c ≤ 6.5% (≤ 48 mmol/mol).

4 Discussion

In this 12-week prospective ambulatory cohort of patients with T2DM, high-dose VDS was associated with a marked rise in serum 25(OH)D concentrations and modest but statistically significant improvements in glycemic control (FSG and HbA1c), without significant effects on SBP, DBP, serum calcium, or BMI. Logistic regression confirmed that higher baseline FSG, longer T2DM duration, and higher BMI independently predicted failure to reach the HbA1c target ≤ 6.5%, whereas age and sex did not.

4.1 Interpretation of glycemic effects

The substantial increase in serum 25(OH)D among supplemented participants confirms effective absorption and bioavailability of the administered high-dose regimen. The observed reductions in FSG and HbA1c indicate that VDS was associated with modest improvements in glycemic parameters in patients with T2DM managed on stable metformin therapy.

These findings are consistent with several meta-analyses reporting modest but significant improvements in glycemic indices following VDS in diabetic or prediabetic populations. For example, Musazadeh et al. (2023) observed mean reductions in FSG (–3.08 mg/dL; 95% CI –3.97 to –2.19) and HbA1c (–0.05%; 95% CI –0.10 to –0.01) across 14 studies (17,136 participants) (32). Similarly, Farahmand et al. (2023) demonstrated significant decreases in FSG, HbA1c, and fasting insulin in RCTs, although the magnitude of effect was modest and heterogeneity was noted (2).

Conversely, other trials have failed to demonstrate significant HbA1c reductions, particularly in cohorts with sufficient baseline vitamin D levels or when using lower doses or shorter durations of therapy (33). Results of meta-analysis conducted by Qi et al. (2022) showed that VDS had no impact on HbA1c level and serum lipids, but reduced IR and BP values (34).

Although modest in magnitude, the observed HbA1c reduction (–0.6%) exceeds expected short-term biological variability and occurred in a population with relatively well-controlled T2DM at baseline, suggesting potential clinical relevance when interpreted as an adjunctive effect.

4.2 Interpretation of blood pressure results

In the present study, both SBP and DBP declined modestly in the intervention group but the changes were not statistically significant. Evidence regarding vitamin D’s influence on BP remains inconsistent. Lee and Lee (2016) reported reductions in DBP among patients with T2DM receiving vitamin D, whereas Jafari et al. (2018) found a significant reduction in SBP but not DBP (35, 36). As it was mentioned above, meta-analysis by Qi et al. (2022) showed the improvement in hypertension control in patients with VDS (34). In contrast, analyses in the general population have shown minimal or no effect of VDS on BP, suggesting limited causal influence (37). An umbrella meta-analysis by Meng et al. (2023) reported that the overall effects of vitamin D supplementation on blood pressure were modest (38).

Mechanistically, vitamin D may modulate BP through regulation of the renin–angiotensin–aldosterone system (RAAS), improvement of endothelial function, and enhanced vascular smooth muscle tone. These mechanisms may underlie variable BP responses among susceptible individuals (38).

4.3 Interpretation of body mass index results

Numerous systematic reviews, meta-analyses, and an umbrella review have examined the relationship between vitamin D and obesity, combining data from RCTs and cohort studies (4, 26, 39). The findings vary depending on factors such as population characteristics, initial vitamin D status, dosage, and accompanying interventions. Overall, meta-analytic and umbrella evidence suggests modest reductions in BMI and weight circumference (WC), though the effects on body weight and fat mass remain inconsistent. Multimodal strategies involving exercise, protein supplementation, or caloric restriction achieve more substantial and consistent improvements in body composition and function (40).

In the present study there was no significant change in BMI. One of the key factor is a short study period. In the meta-analysis conducted by Musazadeh et al. (2022), the effects of vitamin D on body weight and fat mass were not considerable, but VDS significantly improved BMI, and WC (39). Similarly, Hu et al. in an umbrella meta-analysis reported small pooled reductions in BMI and WC, but no meaningful weight or fat−mass change overall (26).

In turn, Aquino et al. (2023) did not show a decrease of WC in patients with MS (41). Roth et al. (2022) reported that the effect of VDS on the preservation of free fat mass (FFM) during non-surgical and surgical weight loss remains controversial (40).

4.4 Predictors of glycemic non-response

Logistic regression analysis identified higher baseline FSG, longer disease duration, and higher BMI as significant predictors of failure to achieve target HbA1c levels. These findings are physiologically plausible and consistent with clinical experience, as patients with more pronounced baseline hyperglycemia, longer disease duration, or obesity typically exhibit reduced responsiveness to metabolic interventions. The lack of association with age and sex suggests that metabolic factors, rather than demographic characteristics, primarily determine glycemic response.

4.5 Strengths and limitations

This study offers several methodological strengths. The use of a standardized high-dose vitamin D regimen achieved robust improvement in serum 25(OH)D concentrations, enabling clear evaluation of metabolic effects. Homogeneous treatment with metformin monotherapy minimized pharmacologic confounding. The prospective, ambulatory design enhances external validity and clinical relevance, while multivariable modeling accounted for key covariates, strengthening internal validity. Seasonal variation in 25(OH)D concentrations could not have influenced the results, as the study was conducted during the autumn–winter 2024/2025 season.

Nonetheless, limitations must be acknowledged. The non-randomized design introduces potential residual confounding, including behavioral and unmeasured factors. The 12-week duration limits assessment of long-term outcomes. The sample size, although moderate, may have been underpowered to detect small changes in calcium or BMI. Finally, findings may not generalize to patients using complex or combination antidiabetic regimens.

The observational design precludes causal inference. Potential residual confounding, lack of placebo control, reliance on pragmatic adherence measures, and absence of prospective registration are acknowledged limitations. Observational designs often underestimate the true effect of vitamin D due to seasonal and temporal variability in serum levels. As emphasized by Pilz et al. (2022), large RCTs have generally failed to demonstrate consistent reductions in adverse outcomes, possibly owing to study design and dosing heterogeneity (42). Observational studies allowing variable supplementation and repeated 25(OH)D measurements may provide broader insight into dose–response relationships and health outcomes (43, 44).

Proposed biological mechanisms discussed herein are derived from prior experimental and clinical studies and were not directly investigated in the present study. They are included to provide biological plausibility and should be considered hypothesis-generating.

4.6 Implications and future directions

The present findings support the hypothesis that high-dose VDS may offer adjunctive benefits in glycemic control among obese T2DM patients with baseline deficiency. However, due to the observational nature of this study, causality cannot be inferred. Future RCTs with longer follow-up, uniform treatment regimens, and stratification by baseline vitamin D status and body composition are warranted. Mechanistic studies exploring effects on insulin sensitivity, β-cell function, inflammation, RAAS activity, and endothelial function would further elucidate the metabolic and cardiovascular implications of vitamin D in T2DM and obesity.

Recent research suggests that vitamin D supplementation may offer beneficial effects on oxidative stress as well as on reproductive, endocrine, and metabolic functions (45). In Hashimoto’s thyroiditis VDS shows promise in influencing immune activity, reducing symptom severity, and enhancing overall quality of life (46). Further investigation is needed to clarify the full range of potential therapeutic applications of VDS in diabetic neuropathy and statin-associated muscle symptoms (SAMS) (47, 48). So far, evidence suggest that vitamin D may support fertility and overall metabolic well-being by modulating hormone concentrations and key metabolic indicators (45). Despite these encouraging findings, additional studies are required to clarify the most effective dosage, treatment length, and timing for supplementation. It is essential for scientists, healthcare professionals, and policy leaders to work together to develop clear, evidence-based recommendations for the use of vitamin D in above mentioned indications (45–48).

4.7 Conclusions

High-dose VDS was associated with improved vitamin D status and modest improvements in glycemic control in obese patients with T2DM. These findings should be interpreted as associative rather than causal and support further investigation in randomized, placebo-controlled trials with extended follow-up and mechanistic endpoints.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The studies involving humans were approved by The Bioethics Committee of the Poznan University of Medical Sciences (approval no. KB-664/23, September 13, 2023). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

KH: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Validation, Writing – original draft. WB: Conceptualization, Methodology, Resources, Supervision, Writing – review & editing. BB: Methodology, Writing – review & editing. AA: Methodology, Writing – review & editing. ME-T: Visualization, Writing – review & editing. SR: Visualization, Writing – review & editing. ST: Visualization, Writing – review & editing. IR: Visualization, Writing – review & editing. AW: Visualization, Writing – review & editing. WI: Visualization, Writing – review & editing. SS: Visualization, Writing – review & editing. SI: Methodology, Writing – review & editing. II: Methodology, Writing – review & editing. VM: Project administration, Writing – review & editing. MR: Supervision, Writing – review & editing. AP: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – review & editing.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Conflict of interest

The authors declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

1. Boucher BJ. Inadequate vitamin D status: does it contribute to the disorders comprising syndrome ‘X’? Br J Nutr. (1998) 79:315–27. doi: 10.1079/bjn19980055

PubMed Abstract | Crossref Full Text | Google Scholar

2. Farahmand MA, Daneshzad E, Fung TT, Zahidi F, Muhammadi M, Bellissimo N, et al. What is the impact of vitamin D supplementation on glycemic control in people with type-2 diabetes: a systematic review and meta-analysis of randomized controlled trails. BMC Endocr Disord. (2023) 23:15. doi: 10.1186/s12902-022-01209-x

PubMed Abstract | Crossref Full Text | Google Scholar

3. Oliveira INN, Macedo-Silva A, Coutinho-Cruz L, Sanchez-Almeida J, Tavares MPS, and Majerowicz D. Effects of vitamin D supplementation on metabolic syndrome parameters in patients with obesity or diabetes in Brazil, Europe, and the United States: A systematic review and meta-analysis. J Steroid Biochem Mol Biol. (2024) 243:106582. doi: 10.1016/j.jsbmb.2024.106582

PubMed Abstract | Crossref Full Text | Google Scholar

4. Montgomery RC, Davenport CA, Johnson KC, Kashyap S, Leblanc ES, Nelson JP, et al. D2D RESEARCH GROUP. 30-OR: effects of vitamin D supplementation by race and weight status on serum vitamin D measures and diabetes risk in the D2d study. Diabetes. (2022) 71:30–OR. doi: 10.2337/db22-30-OR

Crossref Full Text | Google Scholar

5. Mirza I, Mohamed A, Deen H, Balaji S, Elsabbahi D, Munasser A, et al. Obesity-associated vitamin D deficiency correlates with adipose tissue DNA hypomethylation, inflammation, and vascular dysfunction. Int J Mol Sci. (2022) 23:14377. doi: 10.3390/ijms232214377

PubMed Abstract | Crossref Full Text | Google Scholar

6. Huang X, Yang Y, Jiang Y, Zhou Z, and Zhang J. Association between vitamin D deficiency and lipid profiles in overweight and obese adults: a systematic review and meta-analysis. BMC Public Health. (2023) 23:1653. doi: 10.1186/s12889-023-16447-4

PubMed Abstract | Crossref Full Text | Google Scholar

7. Giustina A, di Filippo L, Facciorusso A, Adler RA, Binkley N, Bollerslev J, et al. Vitamin D status and supplementation before and after Bariatric Surgery: Recommendations based on a systematic review and meta-analysis. Rev Endocr Metab Disord. (2023) 24:1011–29. doi: 10.1007/s11154-023-09837-x

PubMed Abstract | Crossref Full Text | Google Scholar

8. Norman AW, Frankel JB, Heldt AM, and Grodsky GM. Vitamin D deficiency inhibits pancreatic secretion of insulin. Science. (1980) 209:823–5. doi: 10.1126/science.6250216

PubMed Abstract | Crossref Full Text | Google Scholar

9. Hewison M. Vitamin D and immune function: autocrine, paracrine or endocrine? Scand J Clin Lab Invest Suppl. (2012) 243:92–102. doi: 10.3109/00365513.2012.682862

PubMed Abstract | Crossref Full Text | Google Scholar

10. Cheng Q, Boucher BJ, and Leung PS. Modulation of hypovitaminosis D-induced islet dysfunction and insulin resistance through direct suppression of the pancreatic islet renin-angiotensin system in mice. Diabetologia. (2013) 56:553–62. doi: 10.1007/s00125-012-2801-0

PubMed Abstract | Crossref Full Text | Google Scholar

11. Leung PS. The potential protective action of vitamin D in hepatic insulin resistance and pancreatic islet dysfunction in type 2 diabetes mellitus. Nutrients. (2016) 8:147. doi: 10.3390/nu8030147

PubMed Abstract | Crossref Full Text | Google Scholar

12. Szymczak-Pajor I, Drzewoski J, and Śliwińska A. The molecular mechanisms by which vitamin D prevents insulin resistance and associated disorders. Int J Mol Sci. (2020) 21:6644. doi: 10.3390/ijms21186644

PubMed Abstract | Crossref Full Text | Google Scholar

13. Akhter A, Alouffi S, Shahab U, Akasha R, Fazal-Ur-Rehman M, Ghoniem ME, et al. Vitamin D supplementation modulates glycated hemoglobin (HBA1c) in diabetes mellitus. Arch Biochem Biophys. (2024) 753:109911. doi: 10.1016/j.abb.2024.109911

PubMed Abstract | Crossref Full Text | Google Scholar

14. Dai D, Ling Y, Xu F, Li H, Wang R, Gu Y, et al. Impact of body composition on vitamin D requirements in healthy adults with vitamin D deficiency. Front Endocrinol (Lausanne). (2025) 16:1421663. doi: 10.3389/fendo.2025.1421663

PubMed Abstract | Crossref Full Text | Google Scholar

15. Tobias DK, Luttmann-Gibson H, Mora S, Danik J, Bubes V, Copeland T, et al. Association of body weight with response to vitamin D supplementation and metabolism. JAMA Netw Open. (2023) 6:e2250681. doi: 10.1001/jamanetworkopen.2022.50681

PubMed Abstract | Crossref Full Text | Google Scholar

16. Chattranukulchai Shantavasinkul P and Nimitphong H. Vitamin D and visceral obesity in humans: what should clinicians know? Nutrients. (2022) 14:3075. doi: 10.3390/nu14153075

PubMed Abstract | Crossref Full Text | Google Scholar

17. Molani-Gol R, Rafraf M, and Safari S. Effects of vitamin D supplementation on metabolic parameters, anthropometric measures, and diabetes risk in patients with prediabetes: an umbrella review of meta-analyses of randomized controlled trials. Nutr Metab (Lond). (2025) 22:99. doi: 10.1186/s12986-025-00994-1

PubMed Abstract | Crossref Full Text | Google Scholar

18. Barbarawi M, Zayed Y, Barbarawi O, Bala A, Alabdouh A, Gakhal I, et al. Effect of vitamin D supplementation on the incidence of diabetes mellitus. J Clin Endocrinol Metab. (2020) 105:dgaa335. doi: 10.1210/clinem/dgaa335

PubMed Abstract | Crossref Full Text | Google Scholar

19. Max F, Gažová A, Smaha J, Jankovský M, Tesař T, Jackuliak P, et al. High doses of vitamin D and specific metabolic parameters in type 2 diabetes patients: systematic review. Nutrients. (2024) 16:3903. doi: 10.3390/nu16223903

PubMed Abstract | Crossref Full Text | Google Scholar

20. Cojic M, Kocic R, Klisic A, and Kocic G. The effects of vitamin D supplementation on metabolic and oxidative stress markers in patients with type 2 diabetes: A 6-month follow up randomized controlled study. Front Endocrinol (Lausanne). (2021) 12:610893. doi: 10.3389/fendo.2021.610893

PubMed Abstract | Crossref Full Text | Google Scholar

21. Chen CW, Han YY, Hwang JS, Rizzo M, Yamashita S, Huey-Jen Hsu S, et al. Association between adequate serum 25(OH)D levels and atherogenic dyslipidemia in young adults. J Atheroscler Thromb. (2024) 31:524–39. doi: 10.5551/jat.64523

PubMed Abstract | Crossref Full Text | Google Scholar

22. Michalska-Kasiczak M, Sahebkar A, Mikhailidis DP, Rysz J, Muntner P, Toth PP, et al. Analysis of vitamin D levels in patients with and without statin-associated myalgia - a systematic review and meta-analysis of 7 studies with 2420 patients. Int J Cardiol. (2015) 178:111–6. doi: 10.1016/j.ijcard.2014.10.118

PubMed Abstract | Crossref Full Text | Google Scholar

23. Autier P, Boniol M, Pizot C, and Mullie P. Vitamin D status and ill health: a systematic review. Lancet Diabetes Endocrinol. (2014) 2:76–89. doi: 10.1016/S2213-8587(13)70165-7

PubMed Abstract | Crossref Full Text | Google Scholar

24. Liu D, Meng X, Tian Q, Cao W, Fan X, Wu L, et al. Vitamin D and multiple health outcomes: an umbrella review of observational studies, randomized controlled trials, and mendelian randomization studies. Adv Nutr. (2022) 13:1044–62. doi: 10.1093/advances/nmab142

PubMed Abstract | Crossref Full Text | Google Scholar

25. Kazemi A, Ryul Shim S, Jamali N, Hassanzadeh-Rostami Z, Soltani S, Sasani N, et al. Comparison of nutritional supplements for glycemic control in type 2 diabetes: A systematic review and network meta-analysis of randomized trials. Diabetes Res Clin Pract. (2022) 191:110037. doi: 10.1016/j.diabres.2022.110037

PubMed Abstract | Crossref Full Text | Google Scholar

26. Hu L, Velu P, Prabahar K, Hernández-Wolters B, Kord-Varkaneh H, and Xu Y. Effect of vitamin D supplementation on lipid profile in overweight or obese women: A meta-analysis and systematic review of randomized controlled trials. Nutr Rev. (2025) 83:1657–68. doi: 10.1093/nutrit/nuae226

PubMed Abstract | Crossref Full Text | Google Scholar

27. Zaravar F, Tamaddon G, Safari M, Zaravar L, and Jahromi MK. Vitamin D3 supplementation enhances the effect of aerobic water-based training on physical fitness indices in obese and overweight menopausal women: A randomized controlled trial. Womens Health (Lond). (2025) 21:17455057251361255. doi: 10.1177/17455057251361255

PubMed Abstract | Crossref Full Text | Google Scholar

28. Araszkiewicz A, Bandurska-Stankiewicz E, Borys S, Broncel M, Budzyński A, Cyganek K, et al. Zalecenia kliniczne dotyczące postępowania u osób z cukrzycą 2024. Stanowisko Polskiego Towarzystwa Diabetologicznego. Clinical recommendations for the management of people with diabetes 2024. Position of the Polish Diabetes Association. Curr Topics Diabetes. (2023) 4:1–158.

Google Scholar

29. Reda H, Soliman S, Girguis H, Nagy M, Mahmoud Y, and Yasser N. A comparison between three different automated total 25-hydroxyvitamin D immunoassay methods and ultra performance liquid chromatography. Asian Pac J Cancer Prev. (2020) 21:1039–44. doi: 10.31557/APJCP.2020.21.4.1039

PubMed Abstract | Crossref Full Text | Google Scholar

30. Kocak FE, Ozturk B, Isiklar OO, Genc O, Unlu A, and Altuntas I. A comparison between two different automated total 25-hydroxyvitamin D immunoassay methods using liquid chromatography-tandem mass spectrometry. Biochem Med (Zagreb). (2015) 25:430–8. doi: 10.11613/BM.2015.044

PubMed Abstract | Crossref Full Text | Google Scholar

31. Cai W, Zhou M, Xu L, Yang Q, and Fang Y. Correlation between serum 25(OH)D levels and diabetic foot ulcers in elderly patients with type 2 diabetes mellitus. Am J Transl Res. (2025) 17:6839–48. doi: 10.62347/LLUC7761

PubMed Abstract | Crossref Full Text | Google Scholar

32. Musazadeh V, Kavyani Z, Mirhosseini N, Dehghan P, and Vajdi M. Effect of vitamin D supplementation on type 2 diabetes biomarkers: an umbrella of interventional meta-analyses. Diabetol Metab Syndr. (2023) 15:76. doi: 10.1186/s13098-023-01010-3

PubMed Abstract | Crossref Full Text | Google Scholar

33. Randhawa FA, Mustafa S, Khan DM, and Hamid S. Effect of Vitamin D supplementation on reduction in levels of HbA1 in patients recently diagnosed with type 2 Diabetes Mellitus having asymptomatic Vitamin D deficiency. Pak J Med Sci. (2017) 33:881–5. doi: 10.12669/pjms.334.12288

PubMed Abstract | Crossref Full Text | Google Scholar

34. Qi KJ, Zhao ZT, Zhang W, and Yang F. The impacts of vitamin D supplementation in adults with metabolic syndrome: A systematic review and meta-analysis of randomized controlled trials. Front Pharmacol. (2022) 13:1033026. doi: 10.3389/fphar.2022.1033026

PubMed Abstract | Crossref Full Text | Google Scholar

35. Lee KJ and Lee YJ. Effects of vitamin D on blood pressure in patients with type 2 diabetes mellitus. Int J Clin Pharmacol Ther. (2016) 54:233–42. doi: 10.5414/CP202493

PubMed Abstract | Crossref Full Text | Google Scholar

36. Jafari T, Fallah AA, Rostampour N, and Mahmoodnia L. Vitamin D ameliorates systolic but not diastolic blood pressure in patients with type 2 diabetes: Results from a meta-analysis of randomized controlled trials. Int J Vitam Nutr Res. (2018) 88:90–9. doi: 10.1024/0300-9831/a000291

PubMed Abstract | Crossref Full Text | Google Scholar

37. Zhang D, Cheng C, Wang Y, Sun H, Yu S, Xue Y, et al. Effect of vitamin D on blood pressure and hypertension in the general population: an update meta-analysis of cohort studies and randomized controlled trials. Prev Chronic Dis. (2020) 17:E03. doi: 10.5888/pcd17.190307

PubMed Abstract | Crossref Full Text | Google Scholar

38. Meng R, Radkhah N, Ghalichi F, Hamedi-Kalajahi F, Musazadeh V, Saleh SAK, et al. The impact of vitamin D supplementation on improving blood pressure: evidence obtained from an umbrella meta-analysis. Clin Ther. (2023) 45:e208–16. doi: 10.1016/j.clinthera.2023.07.020

PubMed Abstract | Crossref Full Text | Google Scholar

39. Musazadeh V, Zarezadeh M, Ghalichi F, Kalajahi FH, and Ghoreishi Z. Vitamin D supplementation positively affects anthropometric indices: Evidence obtained from an umbrella meta-analysis. Front Nutr. (2022) 9:980749. doi: 10.3389/fnut.2022.980749

PubMed Abstract | Crossref Full Text | Google Scholar

40. Roth A, Sattelmayer M, Schorderet C, Gafner S, and Allet L. Effects of exercise training and dietary supplement on fat free mass and bone mass density during weight loss - a systematic review and meta-analysis. F1000Res. (2022) 11:8. doi: 10.12688/f1000research.75539.3

PubMed Abstract | Crossref Full Text | Google Scholar

41. Aquino S, Cunha A, Gomes Lima J, Sena-Evangelista K, Gouveia Oliveira A, Cobucci RN, et al. Effects of vitamin D supplementation on cardiometabolic parameters among patients with metabolic syndrome: A systematic review and GRADE evidence synthesis of randomized controlled trials. Heliyon. (2023) 9:e20845. doi: 10.1016/j.heliyon.2023.e20845

PubMed Abstract | Crossref Full Text | Google Scholar

42. Pilz S, Trummer C, Theiler-Schwetz V, Grübler MR, Verheyen ND, Odler B, et al. Critical appraisal of large vitamin D randomized controlled trials. Nutrients. (2022) 14:303. doi: 10.3390/nu14020303

PubMed Abstract | Crossref Full Text | Google Scholar

43. McDonnell SL, Baggerly CA, French CB, Baggerly LL, Garland CF, Gorham ED, et al. Breast cancer risk markedly lower with serum 25-hydroxyvitamin D concentrations ≥60 vs <20 ng/ml (150 vs 50 nmol/L): Pooled analysis of two randomized trials and a prospective cohort. PloS One. (2018) 13:e0199265. doi: 10.1371/journal.pone.0199265

PubMed Abstract | Crossref Full Text | Google Scholar

44. Mirhosseini N, Vatanparast H, and Kimball SM. The association between serum 25(OH)D status and blood pressure in participants of a community-based program taking vitamin D supplements. Nutrients. (2017) 9:1244. doi: 10.3390/nu9111244

PubMed Abstract | Crossref Full Text | Google Scholar

45. Alam F, Khan AH, Baig M, and Rehman R. Editorial: Recent advances in vitamin D supplementation for improved reproductive endocrine and metabolic parameters. Front Endocrinol (Lausanne). (2023) 14:1251388. doi: 10.3389/fendo.2023.1251388

PubMed Abstract | Crossref Full Text | Google Scholar

46. Sun W, Ding C, Wang Y, Li G, Su Z, and Wang X. Vitamin D deficiency in Hashimoto’s thyroiditis: mechanisms, immune modulation, and therapeutic implications. Front Endocrinol (Lausanne). (2025) 16:1576850. doi: 10.3389/fendo.2025.1576850

PubMed Abstract | Crossref Full Text | Google Scholar

47. Putz Z, Tordai D, Hajdú N, Vági OE, Kempler M, Békeffy M, et al. Vitamin D in the prevention and treatment of diabetic neuropathy. Clin Ther. (2022) 44:813–23. doi: 10.1016/j.clinthera.2022.03.012

PubMed Abstract | Crossref Full Text | Google Scholar

48. Nikolic D, Banach M, Chianetta R, Luzzu LM, Pantea Stoian A, Diaconu CC, et al. An overview of statin-induced myopathy and perspectives for the future. Expert Opin Drug Saf. (2020) 19:601–15. doi: 10.1080/14740338.2020.1747431

PubMed Abstract | Crossref Full Text | Google Scholar