https://orcid.org/0000-0003-1611-3029
Figures
Abstract
Dietary inflammation (DI) and suitable vitamin D intake was associated with frailty. However, the possible mechanism that how DI affected frailty was still unclear. The current study aimed to explore the mediating association of vitamin D levels in the link between DI and frailty. A cross-sectional study of 1172 participants from the National Health and Nutrition Examination Survey (NHANES) database in 2011−2014 was conducted. DI was assessed by the Dietary Inflammation Index (DII), serum vitamin D level were assessed by serum 25-hydroxyvitamin D3 (25-(OH)D3), and frailty was assessed by 49-frailty index. The mediation package in R 4.3.3 was used to examine the mediating association of serum 25-(OH)D3 levels on the relationship between DII and frailty. The prevalence of frailty was 32.3%. DII was negatively correlated with 25-(OH)D3 (r = −0.131, P < 0.001), and positively related with frailty (r = 0.131, P < 0.001). 25-(OH)D3 was negatively associated with frailty (r = −0.073, P = 0.013). And the results showed that 25-(OH)D3 was a possible mediating association between DI and frailty, which explained 10.5% of the total effect (0.0004/0.0038). Improvements in DI and increased vitamin D levels may help alleviate frailty. People should pay more attention to the diet pattern of older adults.
Citation: Wang Y, Yan N, Luo Y, Liu K, Wang J, Zhang J, et al. (2025) The serum vitamin D levels alleviate the influence of dietary inflammation on frailty: A cross-sectional analysis in the U.S. older adults. PLoS One 20(6): e0327251. https://doi.org/10.1371/journal.pone.0327251
Editor: Everson Nunes, McMaster University, CANADA
Received: November 18, 2024; Accepted: June 10, 2025; Published: June 30, 2025
Copyright: © 2025 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: This work was supported by Scientific Research Funding Project of Ningxia Medical University (grant number XT2022014).
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: NHANES, National Health and Nutrition Examination Survey; US, United States; DII, Dietary Inflammation Index; FI, Frailty Index; 25-(OH)D3, 25-hydroxyvitamin D3; IL-1β, Interleukin-1 β; IL-4, Interleukin-4; IL-6, Interleukin-6; IL-10, Interleukin-10; TNF-α, Tumor Necrosis Factor-α; CRP, C-reactive protein; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; PIR, Poverty Income Ratio; HDL, High-Density Lipoprotein; OR, Odds Ratio; IQR, Interquartile Range.
Background
With the development of an aging society, frailty is gradually becoming a public health problem threatening human health. Frailty is a state characterized by reduced physiological reserve and loss of resistance to stressors caused by accumulated age-related deficits [1]. There is an increasing agreement that indicators of frailty encompass age-related declines in lean body mass, strength, endurance, balance, walking ability, and low activity levels, and that frailty is defined in clinical by the presence of multiple contributing factors [2]. Frailty may also trigger and exacerbate other health issues [3], such as the elevated rates of mortality [4], hospitalization [5], and disability [6]. In the long term, frailty can be effectively treated or prevented.
Some researchers have suggested that better dietary quality or healthier eating patterns may reduce the risk of frailty in recent years [7]. Among them, dietary factors have attracted much attention as one of the controllable factors; it can affect frailty by regulating inflammatory factors and oxidative stress. Therefore, inflammation plays a vital role in the pathogenesis of debilitating diseases. To more fully and accurately quantify the inflammatory power of diet, Shivappa et al. created a literature-based, population-based Dietary Inflammation Index (DII) in 2014 [8]. The DII was calculated using an individual’s record of food consumption and assessment of relevant nutrients. It is believed that a high DII score represents a pro-inflammatory diet, which is closely related to serum inflammatory markers [9,10]; however, a low score indicates anti-inflammatory properties [9,10]. A recent study on nutritional status and DII in older adults found that DII levels were higher in frail and malnourished individuals, and further to reduced their life quality [11]. The positive correlation between the DII and the risk of frailty in patients with osteoarthritis has also been confirmed [12]. Hence, understanding dietary inflammation’s role may provide valuable insights for frailty prevention and treatment.
Vitamin D is a fat-soluble molecule referring to the different isoforms (D2 and D3). 25-hydroxyvitamin D3 (25 (OH) D3) is the main circulating form of vitamin D and widely used to assess vitamin D status [13]. A prospective cohort study found an association between low vitamin D levels and frailty and mortality among older adults [14]. In recent years, several studies have found that vitamin D has anti-inflammatory, antioxidant, and other biological functions [15–17], which make vitamin D a great potential for preventing and treating frailty in older population. Recent studies have identified a significant correlation between vitamin D and DII; specifically, vitamin D deficiency was associated with elevated DII levels [18]. This effect may be mediated through vitamin D’s ability to regulate immune responses by modulating the balance between pro- and anti-inflammatory cytokines [19,20].
However, there still existed literature gaps of the potential mechanism between DII and frailty. Hence, in this study, we hypothesize that 1) DII is positively associated with frailty and negatively associated with vitamin D; 2) vitamin D is negatively correlated with frailty; 3) vitamin D may have a mediating association on the relationship between DII and frailty among U.S. older adults (as shown in Fig 1).
Methods
Study design and participants
The samples in this study were from the NHANES database (NHANES Questionnaires, Datasets, and Related Documentation). NHANES was conducted by the Center for Disease Control and Prevention (CDC), aimed to assess the health status of the U.S. non-institutionalized civilian population. The present analysis combined two NHANES cycles (NHANES 2011–2012 and 2013–2014). Owing to the complex, multistage, and probabilistic nature of the sampling design, the selected samples are representative of the non-institutionalized US civilian population. This combined sample included 1172 older adults aged 60 years or older. Among them, we excluded people with severe cardiovascular and cerebrovascular diseases, liver and kidney diseases, and people who could not provide biological samples [21,22], the details are shown in Fig 2. The NHANES protocols were approved by the National Center for Health Statistics (NCHS) Research Ethics Review Board (ERB). All participants provided written informed consent in accordance with federal regulations and institutional requirements. An individual investigator utilizing the publicly available NHANES data do not need to file the institution internal review board (IRB).
Frailty
Frailty was assessed using frailty index (FI). The FI is a robust and concise instrument for assessing frailty in older adults, it performs well in distinguishing frailty states [2], and exhibits conceptual soundness and excellent content validity. A value ranging from 0 to 1 was assigned based on the severity of each deficit, allowing for the integration of continuous and categorical variables. Participants were divided into 4 subgroups: FI ≤ 0.1 (fit), 0.1 < FI ≤ 0.2 (vulnerable), 0.2 < FI ≤ 0.3 (mildly frail), and FI > 0.3 (moderately/severely frail) [14,23]. The frailty index comprised 49 deficits spanning multiple systems [24], including Cognition (Experience confusion/memory problems), Dependence(Managing money, Stooping, crouching, kneeling, and Lifting or carrying; etc., 15 items), Depressive Symptoms (Have little interest in doing things, Trouble sleeping or sleeping too much and Feeling tired or having little energy; etc., 7 items), Comorbidities (Arthritis, Thyroid problems and Chronic bronchitis; etc., 13 items), Hospital Utilization and Access to Care (Self-rated health, Health now compared with 1 year ago and Overnight hospital patient in past year; etc., 6 items), Laboratory Values (Glycohemoglobin, Red blood cell count and Hemoglobin; etc., 6 items) (S1 Table in S1 File). In this study, fit and vulnerable (i.e., FI ≤ 0.2) were combined into the no-frailty group, while mildly frail and moderately/severely frail (i.e., FI > 0.2) were combined into the frailty group.
Dietary inflammatory
Dietary inflammatory (DI) was evaluated by DII. All NHANES participants were eligible to undergo two 24-hour dietary recall interviews. The first recall was conducted in person at a mobile examination center, while the second was carried out via telephone 3 to 10 days later. Dietary data were derived from the average of these two recalls.
The DII, developed by Shivappa through an extensive literature review, was utilized to assess the potential inflammatory levels associated with dietary components [8]. The DII quantifies the inflammatory potential of a diet by integrating its relationships with six key inflammatory biomarkers: IL-1β, IL-4, IL-6, IL-10, TNF-α, and CRP. The index estimates the inflammatory effects of the consumption of 45 nutrients, expressed as a z-score relative to a standardized global mean. The z-scores were calculated by subtracting the mean intake from a regionally representative database and dividing the result by the standard deviation of the respective nutrient. These z-scores were then transformed into proportions (ranging from 0 to 1), doubled, and centered by subtracting 1. The DII score for each participant was derived by summing all food parameter-specific DII values. In this study, 26 nutrients were used to compute the DII, including alcohol, vitamins B12 and B6, β-carotene, caffeine, carbohydrates, cholesterol, total fat, fiber, folic acid, iron, magnesium, zinc, selenium, MUFA, niacin, omega-3 and omega-6 fatty acids, protein, PUFA, riboflavin, saturated fat, thiamine, and vitamins A, C, and E. Importantly, the DII remained valid even when fewer than 30 nutrients were included in the calculation [8]. Participants were subsequently categorized into two dietary groups based on their DII scores: an anti-inflammatory diet (DII < 0) and a pro-inflammatory diet (DII ≥ 0) [25].
Serum vitamin D levels
Participants’ blood samples are collected by a certified phlebotomist at a Mobile Examination Center (MEC) under standardized protocols. The serum concentrations of 25-hydroxyvitamin D3 [25(OH)D3] (nmol/L) were quantified using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The CDC LC-MS/MS method has better analytical specificity and sensitivity, and the analytical targets for imprecision(≤10%) and bias (≤5%) are fixed (25-Hydroxyvitamin D in Serum (cdc.gov)).
Assessment of covariates
In this study, we selected several covariates associated with DI, frailty based on previously published research [25–27]. Covariates include numerical variables such as age (actual value), sitting time(min/d), diastolic blood pressure (DBP, mmHg), total cholesterol (mmol/L), high-density lipoprotein (HDL, mmol/L), vitamin B12 (pmol/L) and Energy ((kcal). Binary variables were sex (Female, Male), smoking (Yes or No), alcohol consumption (Yes or No), and physical activity (Yes or No); the multi categorical variables were ethnicity (Mexican American, Other Hispanic, Non-Hispanic White, Non-Hispanic Black, Other race), education(Less than 9th grade, 9–11th grade, High School graduate/GED or equivalent, Associate or associate degree, College graduate or higher), marriage(Married, Unmarried, Divorce, Other), and poverty income ratio (PIR) (<1.3, 1.3–3.49, ≥ 3.5).
Statistical analysis
This study conducted statistical analyses using R version 4.3.3, with a P-value of less than 0.05 (two-tailed) considered statistically significant. Continuous but non-normal variables are represented as medians and quartiles (median [IQR]), and categorical variables are shown as frequency (%). Differences between continuous variables were assessed using Analysis of Variance (ANOVA), while the Chi-square test was employed for categorical variables. Logistic regression was used to analyze the relationship between participants’ DI and frailty. Three sets of models were used: an unadjusted model (model 1), model 2 adjusting for sex, age, education, PIR and BMI, and model 3 adjusting for physical activity, DBP, total cholesterol, HDL and Energy. The results of logistic regression analysis were reported as odds ratio (OR) and 95%CI. Taking DI as independent variable, serum 25(OH)D3 levels as mediating variable, and frailty as dependent variable, the mediating association of serum 25(OH)D3 levels between DI and frailty was examined. The mediation package in R 4.3.3 was used to examine the mediating association of serum 25(OH)D3 levels between DI and frailty. Numerous studies have utilized publicly available data from the NHANES to investigate risk factors for various diseases. In these studies, some researchers have employed weighted analysis methods, while others have used unweighted approaches. Although NHANES employs complex sampling techniques to enhance the representativeness and generalizability of the survey results, discrepancies in conclusions may arise between weighted and unweighted analyses. In the present study, we conducted a sensitivity analysis using weighted logistic regression to reaffirm our findings. The weighting variable wtdrd2 were selected, and the combined weight was calculated as 1/2*wtdrd2. All sensitivity analyses were conducted using these weighted approaches.
Results
Demographic characteristics of participants
A total of 1172 participants were involved in the final study, of which 793 were non-frailty and 379 were frailty; males accounted for 46.59% of the sample, while females accounted for 53.41%. As shown in Table 1. Among all participants, the number of Pro-inflammatory diet (DII ≥ 0) accounted for 76.28% of the total sample, and 309 people in the sample with high DII were frailty. Significant differences were observed between the frailty and non-frailty groups across demographic characteristics (age, sex, ethnicity, marriage, PIR), clinical parameters (physical activity, sedentary time, total cholesterol, DBP, HDL, height, weight, BMI, hypertension, diabetes), and nutritional profiles (energy, protein, carbohydrates, and DII) (all P < 0.05).
Correlation between DI, Serum vitamin D and frailty
Through the normality test, DI was normally distributed, with Mean ±SD (1.46 ± 1.92). 25-(OH)D3 and frailty index showed skewed distribution, and median[IQR] were 73.61 [53.41,91.47] and 0.16 [0.12, respectively. 0.23]. DI was negatively correlated with 25-(OH)D3 (r = −0.14, P < 0.001), and positively correlated with frailty (r = 0.14, P < 0.001). 25-(OH)D3 was negatively correlated with frailty (r = −0.07, P = 0.013), and the results were shown in Table 2.
Relationship between DI, Serum vitamin D and frailty
Table 3 shows the results of the logistic regression of DII and frailty by three models. After adjusting for potential confounders (in Model 3), the results showed a significant association between DII and frailty, when DII was a continuous variable (OR=1.08, 95%CI [1.01 ~ 1.16], P = 0.044). When DII was categorized into anti-inflammatory and pro-inflammatory diets, with the anti-inflammatory diet serving as the reference group, no significant association was observed between the pro-inflammatory dietary pattern and frailty (OR = 1.13, 95% CI [0.80 ~ 1.62], P = 0.471). When DII was modeled as quantiles, it was found that after adjusting for confounding factors (in Model 3), compared to quartile Q1, the odds ratios (OR) for Q2, Q3, and Q4 were all greater than 1, but showed no statistical significance (P > 0.05). These results suggest that, after adjusting for confounding factors, there may be a positive association between DII and frailty. There was no statistical significance in the interaction between DI and 25-(OH)D3 (P > 0.05), Therefore, we suggest that 25-(OH)D3 may play a mediating role.
Relationship between DII and frailty stratified by age and sex
Table 4 displays the correlation between DII and frailty in various subgroups sex. We observed that after adjusting for demographic and lifestyle factors (In Model 3), DII were positively associated with frailty in males, and the difference was statistically significant (Males: OR=1.19, 95% CI [1.06–1.33], P = 0.003). DII was also positively correlated with frailty in female but the difference was not statistically significant (Female: OR=1.03, 95%CI [0.93–1.14], P = 0.570). Table 4 shows the relationship between DII and frailty in subgroups of different ages. We observed that in the 60–70 age group, after adjusting for potential confounders (In Model 3), there was a significant association between DI and frailty (OR=1.12, 95%CI [1.01 ~ 1.24], P = 0.035). In the 70–80 age group, we observed a statistically significant positive correlation between dietary inflammatory index and frailty in older adults in unadjusted model 1(OR=1.10, 95%CI [1.01 ~ 1.21], P = 0.047). In the final model (In Model 3), after controlling for confounders, DII was also positively correlated with frailty in older adults, but the difference was not statistically significant (OR=1.08, 95%CI [0.98 ~ 1.20], P = 0.129).
Mediator role of Serum vitamin D in DI and frailty
As shown in Table 5, after controlling for covariates, serum 25-(OH)D3 has a significant mediation association on the relationship between DII and frailty. The results showed that both the direct effect (P < 0.001) and the indirect effect (P < 0.001) were significant. The mediation association explained 10.5% (0.0004/0.0038) of the total variance. Fig 3 visualizes the results of the mediating association of 25-(OH)D3.
Sensitivity analysis
Similarly, the sensitivity analysis using weighted logistic regression indicated that when DII was treated as a continuous variable, a one-unit increase in DII was associated with a 9% increase in the risk of frailty in Model 3 (OR = 1.09, 95% CI: 1.01–1.18, P = 0.019). When DII was dichotomized (pro-inflammatory vs. anti-inflammatory), individuals with a pro-inflammatory diet had an 18% higher risk of frailty compared to those with an anti-inflammatory diet in Model 3 (OR = 1.18, 95% CI: 0.89–1.57, P = 0.216), although this association was no longer statistically significant. When DII was categorized into quartiles, individuals in the highest quartile (Q4) had a 62% higher risk of frailty compared to those in the lowest quartile (Q1) in Model 3 (OR = 1.62, 95% CI: 1.16–2.26, P = 0.006) (Table 6). The weighted mediation association accounted for 6.8% of the total variance (0.0129/0.1886) (Table 7). Subgroup analysis using the weighted approach are detailed in the supplementary material (S2 Table in S1 File).
Discussion
Based on nationwide representative sample data, the aim of this study was to investigate the relationship between DI, serum vitamin D, and frailty in old age. The results showed DII is positively associated with frailty and negatively associated with vitamin D in old adults. In the relationship between DI and frailty, serum vitamin D levels played a mediator role, accounting for 10.5% of the total. In addition, men showed higher frailty compared to women, and in the age group of 60–70, the higher the DII, the more likely they are to be frailty. To our knowledge, this is the first study to examine the mediating association of serum vitamin D levels between DI and frailty.
This study reported a significant positive correlation between DI and frailty, consistent with previous findings that DI elevates frailty risk [28]. In a survey of people with depression, there existed association between a pro-inflammatory diet and the onset of frailty [29], and pro-inflammatory diets were associated with an increased risk of frailty. The underlying molecular mechanism may involve pro-inflammatory cytokines exerting a direct influence on frailty by promoting protein degradation or an indirect effect via key metabolic pathways [30]. Our study found a negative association between serum 25-(OH)D3 levels and frailty. This finding was consistent with previous research, which also confirmed a significant association between serum vitamin D levels and frailty [31]. Moreover, studies have documented that low levels of 25(OH)D are linked to impaired balance [32], an increased risk of falls [33], a higher incidence of fractures [34], and persistent pain [35]. These factors can contribute to a sedentary lifestyle and immobility, ultimately leading to increased frailty [36,37]. Deficiency of vitamin D as a prohormone [38] may lead to a series of physiological dysfunction by reducing serum calcium concentration [39], which in the long run can impair the body’s ability to cope with environmental stress and disrupt homeostasis. Supporting this premise, a study conducted on murine models reported that high-dose vitamin D supplementation mitigated frailty and improved balance [40]. Therefore, maintaining appropriate vitamin D levels is essential for maintaining musculoskeletal health and physiological homeostasis.
In this study, serum vitamin D levels were found to mediate between DI and frailty. The most crucial reason for this may be that vitamin D not only affects the homeostasis of mineral metabolism but also possesses anti-inflammatory and antioxidant properties [41,42]. It plays a role in anti-angiogenesis by regulating various aspects of the cell cycle, including cell division, proliferation, and apoptosis [43]. Specifically, Vitamin D directly regulates the inflammatory microenvironment by inhibiting the expression of pro-inflammatory cytokines (e.g., TNF-α, IL-6) and upregulating anti-inflammatory factors (e.g., IL-10) [44,45]. We found that individuals with lower serum vitamin D levels had a significantly higher risk of frailty in the face of higher DII, it is suggested that diet-induced chronic inflammation may exacerbate the debilitating process through vitamin D deficiency. This is consistent with previous studies that the vitamin D receptor (VDR) is widely expressed in immune cells and its deficiency impairs negative feedback regulation of inflammatory signaling [46], leads to muscle atrophy, loss of bone density and impaired nerve function, eventually manifesting as a debilitating syndrome [47,48]. A possible mechanism for this is that chronic low-grade inflammation leads to degeneration of the bone-muscle system through activation of osteoclasts and inhibition of muscle protein synthesis [49,50], while vitamin D disrupts this vicious cycle through its dual actions of regulating calcium-phosphorus metabolism and exerting anti-inflammatory effects [51].
The study acknowledges the presence of several strengths and limitations. Broadening the knowledge regarding the underlying mechanisms in the relationship between DII and frailty of older adults, particularly the mediating role of serum vitamin D in the relationship between DII and frailty was explored. However, several limitations of the study must also be clarified. Firstly, given the type of study in which cross-sectional studies are conducted, causation cannot be determined. In the future, further prospective studies are needed to determine the exact relationship between DII and frailty. Secondly, the diet inflammation index was measured through 24-hour recall interviews. Therefore, the diet at the time of the interview may not reflect long-term habitual eating patterns. However, previous work has demonstrated the effectiveness and practicality of this approach to assess the link between diet and health outcomes [52–54]. In addition, the diet of older adults was found to be relatively stable for at least five to seven years [55], suggesting that 24-hour recall may be an accurate reflection of eating over a longer period of time. Finally, NHANES is a representative survey of the US, and its conclusions may not be generalized to other countries, and should be applied with caution.
Conclusions
The results of this study indicate that reducing DI and increasing serum vitamin D levels may help alleviate frailty in older people. This finding provides important implications for public health policy; that is, when formulating measures to prevent and intervene in aging faltering, diet quality should be considered comprehensively, and the health level of the older people should be improved by improving their diet habits. In the future, further prospective studies are needed to determine the exact relationship between DII and frailty.
Supporting information
S1 File.
S1 Table Variables in the 49-Item Frailty Index and Their Respective Scorings. S2 Table The relationship between DII and frailty was observed by subgroup analysis after weighting. S1 Data.
https://doi.org/10.1371/journal.pone.0327251.s001
(ZIP)
References
- 1. Kojima G, Iliffe S, Walters K. Frailty index as a predictor of mortality: a systematic review and meta-analysis. Age Ageing. 2018;47(2):193–200. pmid:29040347
- 2. Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56(3):M146–56. pmid:11253156
- 3. Zhang H, Liu X, Wang X, Jiang Y. Association of two novel systemic inflammatory biomarkers and frailty based on NHANES 2007-2018. Front Public Health. 2024;12:1377408. pmid:38655524
- 4. Hanlon P, Nicholl BI, Jani BD, Lee D, McQueenie R, Mair FS. Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493 737 UK Biobank participants. Lancet Public Health. 2018;3(7):e323–32. pmid:29908859
- 5. Kojima G. Frailty as a predictor of hospitalisation among community-dwelling older people: a systematic review and meta-analysis. J Epidemiol Community Health. 2016;70(7):722–9. pmid:26933121
- 6. Kojima G. Frailty as a predictor of disabilities among community-dwelling older people: a systematic review and meta-analysis. Disabil Rehabil. 2017;39(19):1897–908. pmid:27558741
- 7. Ni Lochlainn M, Cox NJ, Wilson T, Hayhoe RPG, Ramsay SE, Granic A, et al. Nutrition and frailty: opportunities for prevention and treatment. Nutrients. 2021;13(7):2349. pmid:34371858
- 8. Shivappa N, Steck SE, Hurley TG, Hussey JR, Hébert JR. Designing and developing a literature-derived, population-based dietary inflammatory index. Public Health Nutr. 2014;17(8):1689–96. pmid:23941862
- 9. Shivappa N, Stubbs B, Hébert JR, Cesari M, Schofield P, Soysal P, et al. The relationship between the dietary inflammatory index and incident frailty: a longitudinal cohort study. J Am Med Dir Assoc. 2018;19(1):77–82. pmid:28943182
- 10. Phillips CM, Chen L-W, Heude B, Bernard JY, Harvey NC, Duijts L, et al. Dietary inflammatory index and non-communicable disease risk: a narrative review. Nutrients. 2019;11(8):1873. pmid:31408965
- 11. Çalapkorur S, Bakır B, Toklu H, Akın S. The effect of the nutritional status and dietary inflammatory index on frailty and activities of daily living in geriatric outpatients. Ir J Med Sci. 2024;193(3):1671–80. pmid:38127190
- 12. Zhao F, Pan F, Li J. Relationship between dietary inflammation index and frailty in patients with osteoarthritis. Ann Hum Biol. 2024;51(1):2369274. pmid:38979932
- 13. Zhang J, Zhang A. Association between serum 25-hydroxyvitamin D3 level and cognitive impairment in older chronic kidney disease patients. Sci Rep. 2024;14(1):12403. pmid:38811765
- 14. Jayanama K, Theou O, Blodgett JM, Cahill L, Rockwood K. Frailty, nutrition-related parameters, and mortality across the adult age spectrum. BMC Med. 2018;16(1):188. pmid:30360759
- 15. Artaza-Artabe I, Sáez-López P, Sánchez-Hernández N, Fernández-Gutierrez N, Malafarina V. The relationship between nutrition and frailty: Effects of protein intake, nutritional supplementation, vitamin D and exercise on muscle metabolism in the elderly. A systematic review. Maturitas. 2016;93:89–99. pmid:27125943
- 16. Wimalawansa SJ. Vitamin D deficiency: effects on oxidative stress, epigenetics, gene regulation, and aging. Biology (Basel). 2019;8(2):30. pmid:31083546
- 17. Gu J-C, Wu Y-G, Huang W-G, Fan X-J, Chen X-H, Zhou B, et al. Effect of vitamin D on oxidative stress and serum inflammatory factors in the patients with type 2 diabetes. J Clin Lab Anal. 2022;36(5):e24430. pmid:35403296
- 18. Sharifan P, Darroudi S, Rafiee M, Toussi MSE, Sedgh Doust FN, Taghizadeh N, et al. Association of dietary and blood inflammatory indicators with depression, anxiety, and stress in adults with vitamin D deficiency. Int J Geriatr Psychiatry. 2023;38(8):e5972. pmid:37539817
- 19. Krishnan AV, Feldman D. Mechanisms of the anti-cancer and anti-inflammatory actions of vitamin D. Annu Rev Pharmacol Toxicol. 2011;51:311–36. pmid:20936945
- 20. Wu S, Sun J. Vitamin D, vitamin D receptor, and macroautophagy in inflammation and infection. Discov Med. 2011;11(59):325–35. pmid:21524386
- 21. Shrauner W, Lord EM, Nguyen X-MT, Song RJ, Galloway A, Gagnon DR, et al. Frailty and cardiovascular mortality in more than 3 million US Veterans. Eur Heart J. 2022;43(8):818–26. pmid:34907422
- 22. Schleicher EM, Kremer WM, Kalampoka V, Gairing SJ, Kaps L, Schattenberg JM, et al. Frailty as tested by the clinical frailty scale is a risk factor for hepatorenal syndrome in patients with liver cirrhosis. Clin Transl Gastroenterol. 2022;13(7):e00512. pmid:35905416
- 23. Theou O, Blodgett JM, Godin J, Rockwood K. Association between sedentary time and mortality across levels of frailty. CMAJ. 2017;189(33):E1056–64. pmid:28827436
- 24. Hakeem FF, Bernabé E, Sabbah W. Association between oral health and frailty among american older adults. J Am Med Dir Assoc. 2021;22(3):559–563.e2. pmid:32859517
- 25. Sun M, Wang L, Wang X, Tong L, Fang J, Wang Y, et al. Interaction between sleep quality and dietary inflammation on frailty: NHANES 2005-2008. Food Funct. 2023;14(2):1003–10. pmid:36546877
- 26. Ma R, Zhou X, Zhang G, Wu H, Lu Y, Liu F, et al. Association between composite dietary antioxidant index and coronary heart disease among US adults: a cross-sectional analysis. BMC Public Health. 2023;23(1):2426. pmid:38053099
- 27. Mao Y, Weng J, Xie Q, Wu L, Xuan Y, Zhang J, et al. Association between dietary inflammatory index and Stroke in the US population: evidence from NHANES 1999-2018. BMC Public Health. 2024;24(1):50. pmid:38166986
- 28. Moradi S, Hadi A, Mohammadi H, Asbaghi O, Zobeiri M, Marx W, et al. Dietary inflammatory index and the risk of frailty among older adults: a systematic review and meta-analysis. Res Aging. 2021;43(7–8):323–31. pmid:32815464
- 29. Millar CL, Dufour AB, Hebert JR, Shivappa N, Okereke OI, Kiel DP, et al. Association of proinflammatory diet with frailty onset among adults with and without depressive symptoms: results from the framingham offspring study. J Gerontol A Biol Sci Med Sci. 2023;78(2):250–7. pmid:35830506
- 30. Güngör Başaran AY, Akal Yıldız E. Nutrition status, muscle mass, and frailty in older people: a cross-sectional study conducted in cyprus. J Am Nutr Assoc. 2022;41(3):318–24. pmid:33729904
- 31. Cai Y, Wanigatunga AA, Mitchell CM, Urbanek JK, Miller ER 3rd, Juraschek SP, et al. The effects of vitamin D supplementation on frailty in older adults at risk for falls. BMC Geriatr. 2022;22(1):312. pmid:35399053
- 32. Bluher AE, Kearney T, Vazifedan T, Baldassari CM. Vitamin D deficiency and pediatric obstructive sleep apnea severity. JAMA Otolaryngol Head Neck Surg. 2025;151(1):72–7. pmid:39480411
- 33.
Sizar O, Khare S, Goyal A, Givler A. Vitamin D Deficiency. Treasure Island (FL): StatPearls Publishing.
- 34. LeBoff MS, Chou SH, Ratliff KA, Cook NR, Khurana B, Kim E, et al. Supplemental vitamin D and incident fractures in midlife and older adults. N Engl J Med. 2022;387(4):299–309. pmid:35939577
- 35. Habib AM, Nagi K, Thillaiappan NB, Sukumaran V, Akhtar S. Vitamin D and its potential interplay with pain signaling pathways. Front Immunol. 2020;11:820. pmid:32547536
- 36. Zhou Y, Zhu J, Huang Y, Ma Y, Liu Y, Wu K, et al. Physical activity, sedentary behavior, and the risk of frailty and falling: a mendelian randomization study. Scand J Med Sci Sports. 2024;34(2):e14582. pmid:38349064
- 37. Li T, Pan Y, He Q, Du L, Chen K, Ren X, et al. Associations between sedentary behaviour, physical activity and frailty in older Chinese women: a cross-sectional study. J Clin Nurs. 2023;32(5–6):825–33. pmid:35570376
- 38. Courbebaisse M, Cavalier E. Vitamin D in 2020: an old pro-hormone with potential effects beyond mineral metabolism. Nutrients. 2020;12(11):3378. pmid:33153017
- 39.
Chauhan K, Shahrokhi M, Huecker MR. Vitamin D. Treasure Island (FL): StatPearls Publishing; 2025.
- 40. Seldeen KL, Troen BR. Pinpointing a role for vitamin D in frailty: a time for animal models? Adv Geriatr Med Res. 2021;3(2):e210007. pmid:33738461
- 41. Della Nera G, Sabatino L, Gaggini M, Gorini F, Vassalle C. Vitamin D determinants, status, and antioxidant/anti-inflammatory-related effects in cardiovascular risk and disease: not the last word in the controversy. Antioxidants (Basel). 2023;12(4):948. pmid:37107323
- 42. Kouba BR, Camargo A, Gil-Mohapel J, Rodrigues ALS. Molecular basis underlying the therapeutic potential of vitamin D for the treatment of depression and anxiety. Int J Mol Sci. 2022;23(13):7077. pmid:35806075
- 43. Hou Y, Li J, Deng C. Vitamin D/vitamin D receptor, autophagy, and infection. Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2022;47(6):780–5. pmid:35837778
- 44. Johnson CR, Thacher TD. Vitamin D: immune function, inflammation, infections and auto-immunity. Paediatr Int Child Health. 2023;43(4):29–39. pmid:36857810
- 45. Barrea L, Verde L, Grant WB, Frias-Toral E, Sarno G, Vetrani C, et al. Vitamin D: a role also in long COVID-19? Nutrients. 2022;14(8):1625. pmid:35458189
- 46. Minton K. Vitamin D shuts down T cell-mediated inflammation. Nat Rev Immunol. 2022;22(1):1. pmid:34799725
- 47. Yoshida S, Shiraishi R, Nakayama Y, Taira Y. Can nutrition contribute to a reduction in sarcopenia, frailty, and comorbidities in a super-aged society? Nutrients. 2023;15(13):2991. pmid:37447315
- 48. Bollen SE, Bass JJ, Fujita S, Wilkinson D, Hewison M, Atherton PJ. The Vitamin D/Vitamin D receptor (VDR) axis in muscle atrophy and sarcopenia. Cell Signal. 2022;96:110355. pmid:35595176
- 49. Płudowski P, Kos-Kudła B, Walczak M, Fal A, Zozulińska-Ziółkiewicz D, Sieroszewski P, et al. Guidelines for preventing and treating vitamin D deficiency: a 2023 update in Poland. Nutrients. 2023;15(3):695. pmid:36771403
- 50. Chevalley T, Brandi ML, Cashman KD, Cavalier E, Harvey NC, Maggi S, et al. Role of vitamin D supplementation in the management of musculoskeletal diseases: update from an European Society of Clinical and Economical Aspects of Osteoporosis, Osteoarthritis and Musculoskeletal Diseases (ESCEO) working group. Aging Clin Exp Res. 2022;34(11):2603–23. pmid:36287325
- 51. Charoenngam N, Holick MF. Immunologic effects of vitamin D on human health and disease. Nutrients. 2020;12(7):2097. pmid:32679784
- 52. Shivappa N, Steck SE, Hurley TG, Hussey JR, Ma Y, Ockene IS, et al. A population-based dietary inflammatory index predicts levels of C-reactive protein in the Seasonal Variation of Blood Cholesterol Study (SEASONS). Public Health Nutr. 2014;17(8):1825–33. pmid:24107546
- 53. Hébert JR, Hurley TG, Steck SE, Miller DR, Tabung FK, Peterson KE, et al. Considering the value of dietary assessment data in informing nutrition-related health policy. Adv Nutr. 2014;5(4):447–55. pmid:25022993
- 54. Shivappa N, Steck SE, Hurley TG, Hussey JR, Ma Y, Ockene IS, et al. A population-based dietary inflammatory index predicts levels of C-reactive protein in the Seasonal Variation of Blood Cholesterol Study (SEASONS). Public Health Nutr. 2014;17(8):1825–33. pmid:24107546
- 55. Jankovic N, Steppel MT, Kampman E, de Groot LC, Boshuizen HC, Soedamah-Muthu SS, et al. Stability of dietary patterns assessed with reduced rank regression; the Zutphen Elderly Study. Nutr J. 2014;13:30. pmid:24690194