Association between triglyceride-glucose index and vitamin D levels in Saudi postmenopausal women: a cross-sectional study

Abstract

Objectives: To investigate the relationship between the Triglyceride-Glucose Index (TGI), a surrogate marker of insulin resistance (IR), and serum vitamin D levels in postmenopausal Saudi women, a population at high risk of both metabolic dysfunction and vitamin D deficiency. Methods: This cross-sectional study included 1,020 postmenopausal Saudi women who were categorized into two groups based on TGI values (< 8.7 and ≥ 8.7). Anthropometric, biochemical, and clinical parameters were assessed. Statistical analyses, including multivariate regression, were performed to evaluate the association between TGI and vitamin D levels, adjusting for confounding variables such as body mass index (BMI). Results: Women with TGI ≥ 8.7 had significantly higher BMI, systolic and diastolic blood pressure, fasting glucose, and triglyceride levels, along with lower high-density lipoprotein cholesterol (HDL) cholesterol and serum vitamin D concentrations compared to those with TGI < 8.7. A significant inverse association between TGI and vitamin D levels was found, which remained robust after adjusting for BMI and other confounders. Multivariate regression revealed systolic blood pressure and HDL cholesterol as positive and negative predictors of TGI, respectively, while vitamin D levels showed an independent inverse association. Contributing factors to vitamin D deficiency included limited sun exposure, poor dietary intake, and cultural practices. Conclusions: The study identifies a significant inverse association between TGI and vitamin D levels, underscoring the metabolic interrelationship between insulin resistance and vitamin D deficiency in postmenopausal Saudi women. Public health strategies targeting both conditions may mitigate metabolic and cardiovascular risks in this vulnerable population. Further longitudinal and interventional research is warranted to confirm causality and evaluate the benefits of vitamin D supplementation.

Introduction

Vitamin D is a fat-soluble vitamin essential for maintaining bone mineral homeostasis, regulating calcium absorption, and supporting the immune system [1]. Beyond its classical skeletal functions, vitamin D also plays a role in modulating the immune response, reducing inflammation, and regulating glucose metabolism [2,3]. With many studies associating vitamin D insufficiency to chronic diseases like cardiovascular disease, insulin resistance, and type 2 diabetic mellitus (T2DM), its function in metabolic control has lately been a study focus area [4,5]. Through its actions on pancreatic β-cells, vitamin D controls insulin release; it also increases insulin sensitivity in peripheral tissues by lowering systemic inflammation and raising glucose transporter expression [6,7].

Although vitamin D is biologically important, its insufficiency has grown to be a worldwide public health issue affecting around a billion people [8]. Many environmental, genetic, and behavioral factors lead to its general lack. Major risk factors have been shown to include limited sun exposure, usage of sunscreen, darker skin tone, obesity, and poor nutrition [9,10]. Furthermore impacting vitamin D metabolism are chronic conditions like malabsorption syndromes, liver diseases, and renal ailments [11]. Though definitive data is still lacking, the COVID-19 epidemic has also drawn attention to vitamin D because of its suggested ability to lower respiratory infections and increase immunological responses [12].

Postmenopausal women are particularly vulnerable to vitamin D deficiency due to hormonal changes that compromise bone integrity and metabolic stability [13]. After menopause, declining oestrogen levels help to explain greater bone resorption, lower bone density, and higher risk of osteoporosis and fractures [14,15]. Simultaneously, it contributes to central obesity, impaired insulin sensitivity, and heightened inflammatory cytokines, all of which exacerbate vitamin D deficiency and metabolic dysfunction [16,17]. Vitamin D deficiency and hormonal changes taken together increase the risk postmenopausal women have for acquiring metabolic syndrome, osteoporosis, and cardiovascular problems [18,19].

In Saudi Arabia, despite year-round sunshine, vitamin D deficiency is highly prevalent, especially among women. Cultural practices such as wearing body-covering garments, combined with limited outdoor activity due to high temperatures, significantly reduce dermal synthesis of vitamin D [10,20]. Furthermore, aggravating the shortfall is restricted outside activities resulting from high temperatures, which prevent sun exposure [20]. Another important consideration is dietary habits in Saudi Arabia as the local cuisine usually lacks items high in vitamin D, like eggs, fortified dairy products, and fatty fish.

Studies show that over 70% of Saudi women have low levels of vitamin D; severe shortage has been documented in several parts of the nation [21]. This shortfall raises their risk of metabolic syndrome, cardiovascular disease, and osteoporosis [21]. Studies reflecting a larger public health concern have shown that vitamin D deficiency in Saudi women corresponds with higher frequency of obesity, insulin resistance, and type 2 diabetes mellitus [22]. Geographic latitude and air pollution are among environmental elements that also affect the strength of UVB photons required for vitamin D synthesis [23]. Seasonal variations aggravate the problem even more as winter months produce significantly less vitamin D synthesis from less sunlight [14]. Though public health initiatives encouraging vitamin D supplementation have been started, adherence and efficacy remain erratic [24]. Developing focused treatments meant to lower the prevalence of vitamin D insufficiency in Saudi Arabia depends on an awareness of these complex factors.

A main component of metabolic syndrome, insulin resistance (IR) is a well-known risk factor for many chronic illnesses including type 2 diabetes mellitus (T2DM), cardiovascular disorders, non-alcoholic fatty liver disease (NAFLD), and polycystic ovarian syndrome (PCOS) [25-27]. It is characterized by the reduced capacity of insulin to induce glucose absorption in peripheral tissues including muscle and adipose tissue, hence producing hyperglycemia and compensatory hyperinsulinemia [28]. Fueling the development of many metabolic diseases, persistent insulin resistance causes beta-cell malfunction, higher hepatic glucose production, and chronic inflammation [29,30].

Calculated from fasting triglycerides and glucose levels, the Triglyceride-Glucose Index (TGI) has become a dependable low-cost surrogate diagnostic for IR. Because of its simplicity and availability in regular clinical environments, the TGI is more practical and generally applicable than the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and the hyperinsulinemic-euglycemic clamp test [31]. A major predictor of metabolic syndrome, many studies have shown that a higher TGI is highly correlated with negative metabolic profiles including obesity, dyslipidemia, and hypertension [32-34]. Its predictive power has been confirmed in a variety of demographics, including teenagers, diabetics, even prediabetic patients [35,36].

The disruption of lipid and glucose metabolism grounds the link between the TGI and IR. Hepatic insulin resistance in those who are insulin-resistant causes poor lipoprotein metabolism and higher hepatic glucose generation, therefore influencing fasting glucose and triglyceride levels [37,38]. In the liver, insulin resistance throws off the balance between hepatic glycogenesis and gluconeogenesis, hence raising circulating glucose levels [39]. Concurrent with insulin resistance in adipose tissue, lipolysis and free fatty acid release cause very low-density lipoprotein (VLDL) overproduction by the liver and hypertriglyceridemia [40]. This twin disturbance emphasizes the value of the TGI in forecasting other metabolic abnormalities like T2DM, cardiovascular risk, and even microvascular consequences such as diabetic nephropathy [41].

Recent research has suggested a potential inverse relationship between TGI and vitamin D levels, as both are linked to the pathophysiology of insulin resistance. Elevated TGI values may reflect metabolic disturbances that concurrently impair vitamin D metabolism, including chronic inflammation and hepatic dysfunction [42,43].

Another important process connecting IR to vitamin D deficiency is obesity-associated inflammation. By lowering vitamin D receptor (VDR) activation and hence restricting hepatic hydroxylation of vitamin D, inflammatory cytokines compromise vitamin D metabolism [19]. Moreover, adipose tissue serves as a vitamin D reservoir, therefore lowering its bioavailability in those with more fat mass [27]. Insulin resistance may further reduce hepatic hydroxylation of vitamin D, hence reducing circulating 25-hydroxyvitamin D (25(OH)D), the most accurate measure of vitamin D status [29].

Additionally, TGI becomes very important as a predictor of cardiovascular illnesses. Greater TGI readings have been linked, according studies, to greater risk of cardiovascular death, myocardial infarction, and other cardiovascular events [35]. Predicting cardiometabolic risk, the score beats conventional indicators like fasting glucose or triglycerides [44]. Its predictive power covers macrovascular problems, vascular stiffness, and cardiovascular death in both low- and high-risk groups [19].

Despite the shared pathophysiological background, the direct association between TGI index and vitamin D levels - particularly in postmenopausal women - remains underexplored. Investigating this link may offer a simple, indirect means of identifying individuals at high risk for vitamin D deficiency through metabolic profiling.

Despite these observations, few studies - especially in postmenopausal women - have looked at the TGI connection with vitamin D insufficiency. Because of declining estrogen, this group is prone to metabolic dysregulation which aggravates central obesity, insulin resistance, and bone loss [5]. These elements lead to an environment fit for IR and vitamin D insufficiency; however, studies on Saudi postmenopausal women are still rare.

Given these multifactorial influences, investigating the TGI as a predictor of vitamin D status alongside demographic and lifestyle factors such as age, BMI, menopausal duration, physical activity, and sun exposure could offer valuable insights into clinical management and public health strategies.

The present study aims to investigate the association between TGI and vitamin D levels among Saudi postmenopausal women. The study explores how demographic, anthropometric, and lifestyle factors - such as age, BMI, menopausal duration, physical activity, and sun exposure - affect this association. Understanding these relationships could guide targeted interventions to improve metabolic and bone health in this high-risk population.

Methodology

Study design and participants

This cross-sectional study was conducted at the Osteoporosis Registry of the Chair for Biomarkers of Chronic Diseases (CBCD), King Saud University, Riyadh, Saudi Arabia. A total of 1,020 postmenopausal Saudi women were recruited from outpatient clinics. Postmenopausal status was defined as the absence of menstrual periods for at least 12 consecutive months. Participants were divided into two groups based on their calculated Triglyceride-Glucose Index (TGI): group 1: TGI < 8.7 (n = 286) and group 2: TGI ≥ 8.7 (n = 734). Cutoff value of 8.7 was chosen based on previous studies identifying this threshold as an optimal indicator of insulin resistance in middle-aged and elderly populations, particularly for cardiometabolic risk assessment (Salazar et al., 2017 and Tang et al., 2023) [33,45]. This value allows for meaningful classification of participants based on their metabolic profile.

The inclusion criteria were: Saudi nationality, female, age ≥ 45 years, postmenopausal status confirmed by ≥ 12 consecutive months of amenorrhea, not currently taking vitamin D supplements, calcium, hormonal therapy, lipid-lowering agents, insulin-sensitizing medications, or corticosteroids within the last six months, and willingness to provide informed consent. The exclusion criteria included: known diagnosis of chronic liver disease, renal insufficiency, malignancy, autoimmune disorders, malabsorption syndromes, thyroid dysfunction, or other endocrine/metabolic disorders (e.g., Cushing’s syndrome, acromegaly) that could influence glucose and lipid metabolism or affect vitamin D status; current use of medications that interfere with glucose or lipid metabolism; and incomplete clinical or laboratory data.

The study protocol was reviewed and approved by the Institutional Review Board (IRB) of King Saud University. All participants provided written informed consent prior to enrollment. The study adhered to the ethical principles outlined in the Declaration of Helsinki for medical research involving human subjects.

Anthropometric measurements

Comprehensive anthropometric evaluations were performed by trained healthcare professionals. Each measurement was taken twice to ensure accuracy, and the average was recorded.

(1) Body Mass Index (BMI): Height was measured using a standard stadiometer, and body weight was recorded using a calibrated digital scale, with participants wearing light clothing and no shoes. BMI was calculated using the following formula: BMI = Weight (kg)/Height² (m).

(2) Waist-to-Hip Ratio (WHR): Waist circumference was measured at the narrowest part of the torso, while hip circumference was measured at the widest point using a flexible measuring tape. WHR was calculated by dividing waist circumference by hip circumference.

(3) Blood Pressure (BP): Systolic and diastolic BP were measured using a digital sphygmomanometer after participants had rested for at least five minutes in a seated position. Three measurements were taken at two-minute intervals, and the average was recorded.

Biochemical analysis

After an overnight fast of at least eight hours, venous blood samples were drawn from each participant in the morning to minimize diurnal variation. Blood samples were processed immediately for biochemical analyses, including:

(1) Fasting Glucose: Measured using the glucose oxidase method on the Konelab 20 analyzer, with a computed total CV ≤ 5%. (2) Lipid Profile: Including triglycerides, total cholesterol, and HDL-cholesterol, assessed using enzymatic colorimetric assays on the Konelab 20 analyzer, with a total CV ≤ 4% for all lipid parameters. (3) Vitamin D (25[OH]D): Measured using a chemiluminescence immunoassay (CLIA) on the Roche Cobas e411 analyzer, with intra-assay CV = 4.5% and inter-assay CV = 5.2%. (4) Parathyroid Hormone (PTH): Measured using the CLIA method on the Roche Cobas e411 analyzer, with intra-assay CV = 3.8% and inter-assay CV = 4.6%. (5) Calcium and Corrected Calcium: Measured using a colorimetric assay on the Konelab 20 analyzer, with a total CV ≤ 4%. Corrected calcium values were calculated to account for variations in serum albumin levels.

Triglyceride-Glucose Index (TGI) calculation

The TGI was calculated for each participant using the following established equation:

TGI = ln[(Fasting Triglycerides (mg/dL) × Fasting Glucose (mg/dL)/2].

This formula has been validated in previous metabolic research and serves as a reliable surrogate marker for insulin resistance.

Data analysis

All collected data were coded and analyzed using SPSS Version 21 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were presented as means ± standard deviation (SD) for normal continuous variables and median (Quartile 1-Quartile 3) was used for non-normal variables. Categorical variables were presented as frequencies (percentages). Independent t-tests and Mann-Whiney-U test were used for normal and non-normal variables respectively, to determine difference in anthropometric, biochemical, and clinical characteristics between two TGI groups (TGI < 8.7 vs. TGI ≥ 8.7). Analysis of covariance was used with BMI as covariate to determine adjusted differences. Multivariate logistic regression analysis was used to determine both unadjusted and adjusted odds ratios (ORs) and corresponding 95% confidence intervals (CIs). Significance level: A p-value of less than 0.05 was considered statistically significant in all analyses. Multivariate linear regression analysis was used with TGI as dependent variable and BMI, systolic BP, diastolic BP, HDL-C and vitamin D as independent variables to determine the relationship between TGI and select variables. A p-value of less than 0.05 was considered statistically significant in all analyses.

Results

Participant classification and study overview

This study investigated the association between the Triglyceride-Glucose Index (TGI) and serum vitamin D levels among postmenopausal Saudi women. A total of 1,020 participants were classified into two groups based on their TGI values: TGI < 8.7 and TGI ≥ 8.7. Comprehensive analyses were conducted, including anthropometric measurements, biochemical profiles, and TGI calculations, to explore potential correlations and differences between the groups. The findings provide insight into the metabolic health status of postmenopausal women and highlight key factors influencing insulin resistance and vitamin D deficiency.

Comparison of anthropometric, clinical, and biochemical characteristics by TGI groups

Table 1 presents the anthropometric, biochemical, and clinical characteristics of postmenopausal Saudi women stratified by Triglyceride-Glucose Index (TGI < 8.7 vs. TGI ≥ 8.7). Several parameters exhibited statistically significant differences between the two groups, reflecting distinct metabolic and cardiovascular profiles. Participants with TGI ≥ 8.7 demonstrated significantly higher BMI (33.6 ± 6.1 vs. 32.2 ± 6.0, P = 0.001), indicating greater obesity prevalence. Both systolic BP (128.9 ± 18.2 mmHg vs. 121.7 ± 16.5 mmHg, P < 0.001) and diastolic BP (78.0 ± 10.5 mmHg vs. 74.2 ± 10.1 mmHg, P < 0.001) were markedly elevated in the TGI ≥ 8.7 group, highlighting increased cardiovascular risk. Metabolic parameters showed even more pronounced differences. Fasting glucose levels were significantly higher in the TGI ≥ 8.7 group (9.4 ± 4.5 mmol/L vs. 5.3 ± 0.9 mmol/L, P < 0.001), indicating potential insulin resistance. Similarly, triglycerides were markedly elevated in this group (2.1 ± 1.0 mmol/L vs. 1.0 ± 0.3 mmol/L, P < 0.001), consistent with a dyslipidemic profile. HDL cholesterol was significantly lower (1.2 ± 0.4 mmol/L vs. 1.3 ± 0.4 mmol/L, P < 0.001), reflecting reduced cardioprotective lipid levels. Notably, serum vitamin D levels were significantly lower in the TGI ≥ 8.7 group (70.0 ± 35.2 nmol/L vs. 78.2 ± 36.2 nmol/L, P = 0.001), suggesting a possible inverse relationship between TGI and vitamin D status. This association persisted after BMI adjustment (P = 0.012), reinforcing the link between higher insulin resistance and lower vitamin D levels.

Table 1.

Descriptive statistics according to triglycerides glucose index

Parameters	TGI < 8.7	TGI ≥ 8.7	P-value	P-value*
N	286	734
Age (years)	55.8 ± 8.0	55.8 ± 7.9	0.981	0.552
BMI	32.2 ± 6.0	33.6 ± 6.1	0.001	--
WHR	0.9 ± 0.5	1.0 ± 0.4	0.196	0.249
Systolic BP	121.7 ± 16.5	128.9 ± 18.2	< 0.001	< 0.001
Diastolic BP	74.2 ± 10.1	78.0 ± 10.5	< 0.001	< 0.001
Glucose (mmol/l)	5.3 ± 0.9	9.4 ± 4.5	< 0.001	< 0.001
Triglycerides (mmol/l)	1.0 ± 0.3	2.1 ± 1.0	< 0.001	< 0.001
Total Cholesterol (mmol/l)	5.0 ± 1.0	5.1 ± 1.2	0.042	0.063
HDL Cholesterol (mmol/l)	1.3 ± 0.4	1.2 ± 0.4	< 0.001	< 0.001
Vitamin D (nmol/l)	78.2 ± 36.2	70.0 ± 35.2	0.001	0.012
Calcium (mmol/l)	2.3 ± 0.3	2.3 ± 0.3	0.531	0.886
Corrected Calcium	2.4 ± 0.3	2.3 ± 0.3	0.124	0.203
PTH	8.6 (4.3-20.3)	9.0 (5.4-17.5)	0.665	0.970

Note: Data presented as mean ± SD; P-value < 0.05 considered significant;

^*indicates p-values adjusted for BMI.

BMI, body mass index; WHR, waist-to-hip ratio; BP, blood pressure; HDL, high-density lipoprotein; PTH, parathyroid hormone; Corrected calcium, albumin-adjusted serum calcium.

In contrast, several parameters showed no statistically significant differences between the groups. Age was identical across groups (55.8 ± 8.0 vs. 55.8 ± 7.9, P = 0.981), indicating comparable age distributions. Although the waist-to-hip ratio (WHR) was slightly higher in the TGI ≥ 8.7 group (1.0 ± 0.4 vs. 0.9 ± 0.5), this difference was not statistically significant (P = 0.196). Additionally, total cholesterol levels were similar (5.1 ± 1.2 mmol/L vs. 5.0 ± 1.0 mmol/L, P = 0.042), and the adjusted p-value of 0.063 indicated no significant difference after BMI correction. Calcium (P = 0.531), corrected calcium (P = 0.124), and parathyroid hormone (PTH) (P = 0.665) levels also showed no meaningful differences, suggesting that TGI was not directly associated with calcium metabolism or PTH regulation in this population.

Distribution of vitamin D status by TGI groups

Table 2 presents the distribution of vitamin D status among postmenopausal Saudi women, stratified by Triglyceride-Glucose Index (TGI < 8.7 vs. TGI ≥ 8.7), with corresponding odds ratios (ORs) and p-values for unadjusted and BMI-adjusted models. Participants with desirable vitamin D levels (≥ 75 nmol/L) were more frequently observed in the TGI < 8.7 group (51.7%) compared to the TGI ≥ 8.7 group (42.9%), indicating a potential inverse relationship between TGI and vitamin D status, although this difference was not statistically tested. The proportion of women with sufficient vitamin D levels (50-74.9 nmol/L) was nearly identical between the two groups (23.1% vs. 23.0%, P = 0.290), yielding an unadjusted OR = 1.20 (95% CI: 0.85-1.70) and an adjusted OR = 1.17 (95% CI: 0.81-1.67, P = 0.403), indicating no significant association even after adjusting for BMI.

Table 2.

Descriptive statistics according to Triglycerides Glucose Index (TGI)

Parameters	TGI < 8.7	TGI ≥ 8.7	Unadjusted		Adjusted
			OR	P-value	OR	P-value
Desirable	148 (51.7)	315 (42.9%)
Sufficient	66 (23.1)	169 (23.0)	1.20 (0.85-1.70)	0.290	1.17 (0.81-1.67)	0.403
Deficient	72 (25.2)	250 (34.1)	1.63 (1.18-2.26)	0.003	1.52 (1.08-2.14)	0.016

Note: Data presented as mean ± SD.

In contrast, women with vitamin D deficiency (< 50 nmol/L) were significantly more prevalent in the TGI ≥ 8.7 group (34.1%) compared to the TGI < 8.7 group (25.2%). This association was statistically significant, with an unadjusted OR = 1.63 (95% CI: 1.18-2.26, P = 0.003). After adjusting for BMI, the association remained significant, with an adjusted OR = 1.52 (95% CI: 1.08-2.14, P = 0.016), indicating that women in the higher TGI group were approximately 1.5 times more likely to have vitamin D deficiency compared to their lower TGI counterparts.

Multivariate predictors of triglyceride-glucose index

Table 3 summarizes the results of a multivariate regression analysis with Triglyceride-Glucose Index (TGI) as the dependent variable and BMI, systolic BP, diastolic BP, HDL-C, and vitamin D levels as independent variables. Among these, systolic BP emerged as the strongest positive predictor (B = 0.008 ± 0.002, β = 0.19, P < 0.001), indicating that higher systolic BP is significantly associated with an elevated TGI. Similarly, diastolic BP was positively associated with TGI (B = 0.006 ± 0.003, β = 0.08, P = 0.035), though its effect size was smaller. Conversely, HDL-C showed a significant inverse relationship with TGI (B = -0.336 ± 0.064, β = -0.17, P < 0.001), reinforcing its protective role in lipid metabolism.

Table 3.

Multivariate regression analysis with TGI as dependent variable

Parameters	B ± SE	Standardized Beta	P-value
BMI	0.004 ± 0.004	0.03	0.351
Systolic BP	0.008 ± 0.002	0.19	< 0.001
Diastolic BP	0.006 ± 0.003	0.08	0.035
HDL-C	-0.336 ± 0.064	-0.17	< 0.001
Vitamin D	-0.235 ± 0.095	-0.08	0.014

Note: Data presented as B ± SE; P-value obtained from multivariate regression analysis including BMI, systolic BP, diastolic BP, HDL-C and vitamin D as independent variables and TGI as dependent variable; P < 0.05 considered significant.

Additionally, vitamin D levels were inversely associated with TGI (B = -0.235 ± 0.095, β = -0.08, P = 0.014), suggesting that lower vitamin D concentrations correlate with increased TGI, even after adjusting for other metabolic factors. However, BMI was not a significant predictor (B = 0.004 ± 0.004, β = 0.03, P = 0.351), indicating that its influence on TGI might be mediated through other parameters included in the model. These findings highlight the roles of blood pressure, HDL-C, and vitamin D levels as important determinants of TGI in postmenopausal women.

Correlation between TGI and serum vitamin D levels

Figure 1 illustrates the correlation between Triglyceride-Glucose Index (TGI) and serum 25-hydroxyvitamin D [25(OH)D] concentration in postmenopausal Saudi women. The scatter plot depicts a negative linear relationship, indicating that higher TGI values are associated with lower 25(OH)D concentrations. The regression line suggests a downward trend, supporting the potential inverse association between insulin resistance (as indicated by TGI) and vitamin D status.

Figure 1.

Correlation between Triglyceride Glucose Index and 25-hydroxyvitamin D (25(OH)D) concentration.

The strength and significance of the correlation are consistent with findings from the multivariate regression analysis, where 25(OH)D levels were independently associated with TGI after adjusting for relevant confounders. This relationship underscores the metabolic interplay between vitamin D status and insulin resistance markers in this population.

Discussion

This study highlights a significant inverse relationship between the Triglyceride-Glucose Index (TGI), a validated surrogate marker of insulin resistance, and serum vitamin D levels in postmenopausal Saudi women. Women with higher TGI values (≥ 8.7) demonstrated lower vitamin D concentrations, a relationship that persisted even after adjusting for BMI and other confounders. These findings reveal the multifaceted interplay between vitamin D deficiency, insulin resistance, and associated metabolic dysfunctions, particularly in a population with unique cultural and environmental factors.

TGI reflects the combined effects of hyperglycemia and hypertriglyceridemia, two hallmark features of insulin resistance and metabolic syndrome. Elevated TGI was associated with adverse metabolic profiles, including increased fasting glucose, triglycerides, blood pressure, and BMI, along with decreased HDL cholesterol. These findings are consistent with prior studies identifying TGI as a robust marker for predicting type 2 diabetes, cardiovascular disease, and other metabolic disorders [2,7,16]. Similar results were observed by Guerrero-Romero et al., 2010 [46], who showed a strong correlation between TGI index and insulin resistance in Latin American populations. Chronic hyperglycemia in insulin resistance promotes pancreatic β-cell dysfunction, while hypertriglyceridemia disrupts insulin signaling in muscle and adipose tissue, further compounding metabolic dysregulation [16,47].

The observed association between TGI and hypertension in this study underscores the contribution of insulin resistance to vascular dysfunction. Hyperinsulinemia enhances sodium reabsorption in the kidneys and activates the renin-angiotensin-aldosterone system (RAAS), which elevates blood pressure. Furthermore, insulin resistance impairs endothelial function, leading to reduced nitric oxide bioavailability, increased vascular stiffness, and impaired vasodilation [10,38]. These mechanisms establish TGI not only as a marker of metabolic syndrome but also as an indicator of cardiovascular risk.

The inverse association between TGI and vitamin D levels aligns with growing evidence that vitamin D deficiency exacerbates insulin resistance. Vitamin D modulates glucose homeostasis through its actions on pancreatic β-cells, peripheral tissues, and inflammatory pathways. In pancreatic β-cells, vitamin D receptors (VDRs) regulate calcium flux, an essential process for insulin secretion. Deficiency disrupts this mechanism, impairing insulin release and promoting hyperglycemia [48,49]. In peripheral tissues, vitamin D enhances the expression of insulin receptors and glucose transporter-4 (GLUT-4), facilitating glucose uptake and reducing circulating glucose levels [14,50]. Our findings are supported by Mahat et al. (2024), who reported an inverse association between TGI index and serum vitamin D levels in Indian Tribal Community [43], and Li et al. (2025), who demonstrated similar findings in a large US adult cohort [51]. In contrast, Al-Daghri et al. (2015) found no significant association in Saudi adolescents, possibly due to age-related metabolic and hormonal differences [50]. These comparisons further highlight the relevance of our findings in adult, postmenopausal populations.

Vitamin D also exhibits potent anti-inflammatory effects by downregulating pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6), which are elevated in insulin resistance. These cytokines interfere with insulin signaling, further contributing to metabolic dysfunction. The deficiency of vitamin D amplifies systemic inflammation, creating a vicious cycle that perpetuates insulin resistance [34,35].

Vitamin D deficiency is highly prevalent in Saudi Arabia, despite abundant sunlight, due to cultural practices that limit sun exposure. Traditional clothing that covers most of the skin and limited outdoor activities reduce endogenous vitamin D synthesis. Additionally, dietary patterns deficient in vitamin D-rich foods, such as fatty fish and fortified products, exacerbate this issue [1,52]. The high prevalence of vitamin D deficiency in the Saudi population is consistent with other studies, particularly in postmenopausal women who experience estrogen decline. This hormonal change further impairs calcium and vitamin D metabolism, increasing the risk of metabolic syndrome and osteoporosis [1,12,53].

The inverse relationship between TGI and HDL cholesterol observed in this study highlights HDL’s protective role against metabolic dysfunction. HDL facilitates reverse cholesterol transport, thereby reducing atherogenic lipid accumulation in peripheral tissues. Additionally, HDL exerts anti-inflammatory and antioxidant effects, mitigating the oxidative stress and inflammation associated with insulin resistance [13,23]. Reduced HDL levels, as seen in participants with elevated TGI, fail to counteract these pathological processes, thereby exacerbating insulin resistance and cardiovascular risk.

These findings emphasize the need for integrated strategies to address both vitamin D deficiency and metabolic syndrome in postmenopausal women. Routine vitamin D screening in individuals with elevated TGI could help identify those at heightened risk for insulin resistance and related complications. Public health interventions, such as promoting safe sun exposure, dietary modifications to include vitamin D-rich foods, and supplementation, are crucial in this population [10]. Strategies to improve HDL cholesterol levels, such as weight management, increased physical activity, and pharmacological interventions, should also be prioritized to mitigate metabolic and cardiovascular risks [1,52].

This study benefits from a large sample size and a comprehensive analysis of anthropometric, biochemical, and clinical parameters, enhancing the reliability of its findings. Adjusting for BMI as a confounder strengthens the study’s rigor by isolating the independent relationship between TGI and vitamin D levels. However, the cross-sectional design limits the ability to establish causality. Additionally, the lack of data on dietary vitamin D intake, physical activity, and genetic polymorphisms affecting vitamin D metabolism may introduce residual confounding factors. Longitudinal and interventional studies are needed to establish causal pathways and evaluate the efficacy of targeted therapies [53,54].

Conclusion

This study highlights a significant inverse association between TGI and vitamin D levels, alongside its associations with key metabolic markers such as HDL cholesterol and blood pressure, in postmenopausal Saudi women. The findings underscore the importance of addressing vitamin D deficiency and managing cardiovascular and metabolic risks in this vulnerable population. By integrating nutritional, pharmacological, and lifestyle interventions, healthcare providers can improve metabolic and bone health outcomes, ultimately reducing the burden of chronic diseases in postmenopausal women. Future research should explore the genetic, environmental, and lifestyle determinants of these associations to inform precision medicine approaches tailored to high-risk populations.

Disclosure of conflict of interest

None.

Abbreviations

TGI

Triglyceride-Glucose Index

BMI

Body Mass Index

VDR

Vitamin D Receptor

GLUT-4

Glucose Transporter-4

TNF-α

Tumor Necrosis Factor-alpha

IL-6

Interleukin-6

RAAS

Renin-Angiotensin-Aldosterone System

HDL

High-Density Lipoprotein

CRP

C-Reactive Protein

25(OH)D

25-hydroxyvitamin D

1

25(OH)₂D, 1,25-dihydroxyvitamin D

DBP

Vitamin D-Binding Protein