The Impact of Ramadan Fasting on Glycemic and Blood Pressure Control in a Large Saudi Arabian Cohort with Type 2 Diabetes and Hypertension: A Longitudinal Interrupted Time Series Analysis

Abstract

Introduction:

The yearly observance of Ramadan, which includes prolonged daily fasting, presents a challenging scenario for patients with chronic illnesses, with existing studies presenting inconsistent findings on its metabolic implications.

Objective:

This study aimed to objectively measure the immediate and sustained impacts of Ramadan fasting on monthly mean Hemoglobin A1c (HbA1c), Systolic Blood Pressure (SBP), and Diastolic Blood Pressure (DBP) in a large, real-world cohort of Saudi Arabian patients with concomitant T2DM and HTN.

Methods:

A retrospective longitudinal study was carried out using electronic health record (EHR) data from a Saudi multi-facility healthcare system from December 2023 to May 2024. The analysis used a segmented regression for Interrupted Time Series (ITS) to estimate changes in outcomes, with Ramadan (March 2024) serving as the intervention point.

Results:

The final cohort comprised 15 289 patients. The ITS analysis showed that Ramadan resulted in a substantial reduction in mean HbA1c by −0.25% (P < .001) and mean SBP by −4.12 mmHg (P < .001). However, the post-Ramadan trend for HbA1c demonstrated a significant monthly increase of 0.15% (P = .002), indicating a rebound impact. The reduction in SBP was not sustained, as it returned to pre-Ramadan levels in the months that followed.

Conclusions:

In this large Saudi cohort, Ramadan fasting was linked to transitory improvements in glycemic and blood pressure control. The ensuing rebound implies that, while fasting can be metabolically advantageous, the effects do not last without ongoing intervention. These results highlight the important necessity for rigorous post-Ramadan clinical follow-up to consolidate any gains made during the fasting period. These findings position Ramadan as a novel window for metabolic reset and a potential preventive opportunity against cardiorenal metabolic syndrome progression in high-risk populations.

Keywords

Ramadan fasting type 2 diabetes hypertension glycemic control blood pressure Saudi Arabia

Introduction

Insulin resistance and progressive β-cell dysfunction are hallmarks of type 2 diabetes mellitus (T2DM), a chronic metabolic disorder characterized by persistent hyperglycemia and an increased risk of cardiovascular disease, nephropathy, neuropathy, and retinopathy.¹ Globally, approximately 463 million adults—or 9.3% of the population aged 20 to 79—are affected.² This alarming statistic underscores diabetes as a major public health challenge, driven by aging populations, sedentary lifestyles, urbanization, and poor dietary habits. If current trends persist, prevalence is projected to rise to 10.2% (578 million people) by 2030 and 10.9% (700 million people) by 2045. Given this upward trajectory, diabetes is expected to exert an even greater impact on individuals, economies, and healthcare systems worldwide.²

Type 2 Diabetes Mellitus (T2DM) and hypertension (HTN) are major public health emergencies with rising prevalence in the Kingdom of Saudi Arabia. According to the International Diabetes Federation (IDF), over 5.3 million Saudi adults had diabetes in 2024, representing 23.1% of the adult population.³ Alqahtani et al⁴ reported that 8.5% of Saudis aged 15 or older had diabetes. This high prevalence underscores an urgent need for improved lifestyle interventions and early detection programs. Additionally, Aljehani et al⁵ identified sedentary lifestyles as a key contributing factor to the increasing DM risk, driving its rising incidence over recent decades. However, reliable nationwide prevalence estimates remain scarce in Saudi Arabia.

Type 2 diabetes mellitus (T2DM) and hypertension (HTN) are interrelated metabolic disorders showing increasing global prevalence.⁶ According to the Council of Health Insurance, Saudi Arabia is experiencing alarming rises in both conditions.⁷ Recent statistics indicate that 9.2% of Saudi adults aged ⩾15 years have hypertension, with this proportion increasing to 50% among those aged ⩾65 years.⁷ Alharbi et al⁶ demonstrated that T2DM and HTN serve as mutually reinforcing risk factors, with significantly higher incidence rates when both conditions coexist compared to their absence. This comorbidity is particularly dangerous as it synergistically worsens microvascular and macrovascular complications, including coronary artery disease, stroke, chronic kidney disease (CKD), and retinopathy. The substantial clinical and economic burden of these dual epidemics underscores the need for a better understanding of population-specific factors affecting disease management and outcomes.

The annual observance of Ramadan is one of the most significant events in the Muslim world. More than 1.8 billion healthy adult Muslims worldwide are required to abstain from eating, drinking, and other specific activities—such as smoking, sexual relations, and indulging the senses—from sunrise to sunset for 29 to 30 days during Ramadan fasting, one of the five pillars of Islam. This practice brings about a drastic, albeit temporary, change in lifestyle.⁸

Alterations in metabolism are brought on by intermittent fasting. Glycogen depletion after 24 hours causes energy expenditure to shift to protein reserves and fat tissue. Triglycerides decompose into glycerol and free fatty acids, which the liver then transforms into glucose and ketone molecules.⁹ Energy is obtained from the production of ketones through the process of ketogenesis. Additionally, protein degradation takes place, producing glucose via gluconeogenesis. The organism becomes less dependent on glucose as ketone bodies rise.⁹ Chronic conditions like T2DM and HTN may be impacted by these changes. Patients must modify their food, medicine, and monitoring throughout Ramadan to prevent problems such as dehydration, ketoacidosis, hypoglycemia, and hyperglycemia.

Millions of people with chronic illnesses are affected by this worldwide health event every year, yet the scientific literature currently available on the cardiometabolic effects of Ramadan fasting is inconsistent and methodologically flawed. Some prospective observational studies have reported notable reductions in both systolic and diastolic blood pressure, suggesting a potential cardiovascular benefit. Changes in dietary salt intake, metabolic alterations, and possible weight loss have all been implicated in this effect.^10,11 However, other well-conducted investigations have found no significant differences in mean blood pressure or heart rate between fasting and non-fasting periods.^12,13 Due to these contradictory findings, patients and physicians remain uncertain about the expected hemodynamic response to fasting. There is also conflicting research regarding glycemic management. Ramadan may be a time of metabolic improvement, as several studies have reported significant reductions in mean blood glucose and HbA1c levels. However, fasting in this population is associated with several risks, including postural hypotension, dehydration, increased blood viscosity (which can lead to diabetic ketoacidosis and thrombosis), and hypoglycemic episodes.^14-16 According to Elhadd et al,¹⁷ patients with type 2 diabetes mellitus (T2DM) who are on multiple glucose-lowering medications and fast during Ramadan are at a higher risk of hypoglycemia.

Despite growing research on Ramadan fasting and cardiometabolic outcomes, the literature remains notably inconsistent, attributable to four principal limitations. First, most published studies are small single-center cohorts—frequently fewer than 200 participants—lacking the statistical power to detect clinically meaningful differences, making cross-study comparisons unreliable. Second, substantial population heterogeneity exists across studies, spanning different ethnicities, baseline disease severity, comorbidity burdens, and antidiabetic regimens across countries, including Egypt, Turkey, Iraq, and Pakistan, rendering direct comparisons inappropriate. Third, and most critically, the majority of studies employ simple pre-post designs that cannot distinguish true fasting effects from secular trends, medication adjustments, or regression to the mean, and inconsistent post-Ramadan measurement timing (immediately after Eid vs weeks later) further obscures whether reported changes reflect the acute fasting effect or an early rebound. Fourth, few studies adequately control for concurrent medication changes, physical activity, sleep disruption, sodium intake, or caloric composition of Ramadan meals, all of which independently influence glycemic and blood pressure outcomes. Collectively, these limitations—underpowered samples, heterogeneous populations, methodologically weak designs, and inadequate control for confounding—explain the conflicting conclusions in the field and underscore the need for a large-scale, longitudinal, quasi-experimental approach. The present study was designed to address these gaps directly, applying Interrupted Time Series analysis to a cohort of 15 289 patients from a large Saudi integrated health system—providing one of the most methodologically rigorous assessments of Ramadan’s cardiometabolic effects to date. This study aimed to objectively evaluate the short-term (immediate, within-Ramadan) and medium-term (post-Ramadan, up to 2 months following the fasting period) effects of Ramadan fasting on monthly mean Hemoglobin A1c (HbA1c), Systolic Blood Pressure (SBP), and Diastolic Blood Pressure (DBP) in a large, real-world cohort of Saudi Arabian patients with concomitant T2DM and HTN. We hypothesized that Ramadan fasting would induce a significant short-term improvement in both glycemic and blood pressure control, driven by fasting-associated metabolic changes, but that these benefits would not be sustained in the post-Ramadan period without structured clinical support—resulting in a measurable rebound toward pre-Ramadan levels.

Methods

Study Design and Data Source

The dataset included all patient encounters recorded over 6 months from December 1, 2023, to May 31, 2024. This specific timeframe was selected for three reasons: (1) Ramadan 2024 (March 10 to April 9, 2024) represented the most recent complete Ramadan cycle available within the EHR system at the time of data extraction, maximizing data completeness and clinical relevance; (2) the calendar position of Ramadan 2024 in early spring allowed for a symmetric pre-post assessment window with minimal overlap with major seasonal confounders such as summer heat or national holiday periods that could independently affect healthcare utilization and metabolic outcomes; and (3) a 6-month observation window—comprising three pre-intervention months (December 2023 to February 2024), the intervention month (March 2024), and two post-intervention months (April to May 2024)—provides sufficient temporal resolution to estimate both the immediate level change and the post-Ramadan trend trajectory within the ITS framework, consistent with established ITS methodology in healthcare research.

Study Population

Patients chosen from the EHR database according to particular inclusion and exclusion criteria made up the study cohort. Data were obtained from King Fahad Medical City (KFMC), a leading multi-specialty tertiary care academic hospital in Riyadh, Saudi Arabia. Patients who were at least eighteen years old and had a history of Type 2 Diabetes Mellitus and Hypertension were included. Diagnoses were determined using a combination of structured data fields and text-mining from the “Diagnosis” and “Medical History” columns. To ensure that patients included in the longitudinal analysis had a sufficiently complete data profile, they needed at least one valid measurement for the primary outcomes (HbA1c, SBP, or DBP) recorded during the pre-Ramadan period (December 1, 2023 to February 29, 2024) and at least one measurement in the final post-Ramadan month (May 1 to May 31, 2024). Patients with Type 1 diabetes, gestational diabetes, a documented pregnancy, end-stage renal disease (ESRD), or those undergoing dialysis were excluded.

Sample Size Considerations

This study was based on a retrospective analysis of routinely collected electronic health record data, and therefore, no priori sample size or power calculation was performed. All patients who met the predefined inclusion and exclusion criteria during the study period were included, constituting a population-based cohort rather than a sampled population. In interrupted time series (ITS) analyses, statistical power is primarily driven by the number of time points and the stability of outcome measurements over time, rather than by individual-level sample size. The study included six consecutive monthly observations encompassing pre-intervention, intervention (Ramadan), and post-intervention periods, which is consistent with previous ITS applications in healthcare research. The large underlying patient population contributing to each monthly aggregate further supports the precision of the estimated population-level outcomes.

Variables and Measurements

All study variables were obtained and derived from electronic health record (EHR) data. The primary exposure was participation in Ramadan, defined as taking place in March 2024. The three primary outcomes were monthly population-level means of Hemoglobin A1c (HbA1c, %), Systolic Blood Pressure (SBP, mmHg), and Diastolic Blood Pressure (DBP, mmHg). HbA1c values were obtained from laboratory test results recorded in the EHR, with each patient contributing their most recent valid result within each calendar month. Blood pressure measurements were recorded at the time of clinical encounters using standardized institutional protocols across all KFMC facilities, consistent with guidelines recommending seated, resting measurements taken by trained healthcare personnel. Where multiple readings were available for a given patient within a single month, the mean value was used to derive the patient-month estimate, which was subsequently aggregated to the population-level monthly mean for ITS modeling. This approach ensures that each monthly data point reflects a standardized, internally consistent estimate of the population’s cardiometabolic status. Time-series variables included: (1) a continuous variable representing the six consecutive study months, (2) a binary indicator distinguishing the pre- and post-Ramadan periods, and (3) a post-intervention time variable. Covariates included baseline age, gender, and time-varying Body Mass Index (BMI). For subgroup analyses, patients were classified into four mutually exclusive antidiabetic therapy groups based on their pre-Ramadan regimen: (1) Diet/Metformin only, (2) Sulfonylurea-based regimen, (3) Insulin-based regimen, and (4) Modern therapy-based regimen (GLP-1 receptor agonists or SGLT2 inhibitors).

Diagnosis and Medication Regimen Extraction

“Diagnosis” and “Medical History” were columns that included free content that was either semi-structured or unstructured. To analyze this text and generate binary indicator variables for important conditions, a rule-based approach utilizing regular expressions was used. DM (diabetes mellitus), type 2, type 2 diabetes mellitus, and diabetes, for instance, were used to identify patients who had type 2 diabetes. Similar guidelines were created for chronic kidney disease, dyslipidemia, hypertension, and other pertinent comorbidities.

A comprehensive medication classification framework was established. Initially, structured binary indicators (eg, “Metformin,” “GLP-1 agonists,” “SGLT-2 inhibitors,” “Insulin”) served as the foundation. This was further enhanced by applying a custom drug dictionary to the free-text Medications field, enabling recognition of a broader range of therapies, including specific sulfonylureas, different insulin types (basal, bolus), and antihypertensive drug classes (eg, ACE inhibitors, beta-blockers). Using this enriched medication profile, patients were then categorized into one of four antidiabetic treatment subgroups for the stratified analyses.

Data Aggregation to Monthly Time Series

The primary dataset was organized at the patient-encounter level, allowing multiple entries per patient within a single month (eg, several clinic visits with varying blood pressure measurements). To generate the monthly time series required for the interrupted time series (ITS) analysis, data were aggregated to the patient-month level. For each patient and month, mean values were calculated for continuous variables (eg, SBP, DBP, BMI) when multiple readings were available, while the most frequently recorded category was retained for categorical variables. Subsequently, a second aggregation step was performed to derive the population-level means for each outcome (HbA1c, SBP, DBP) across the six calendar months, yielding the final time-series dataset for regression modeling.

Statistical Analysis

All statistical analyses were carried out using R version 4.3.1, with a P-value of less than .05 indicating statistical significance. The baseline characteristics were summarized using descriptive statistics. The basis of the investigation was an Interrupted Time Series (ITS) technique using segmented linear regression. This effective quasi-experimental method allows us to analyze the effects of an intervention (Ramadan) by modelling the trend of the outcome before and after the event. The equation defined the statistical model for this analysis:

\begin{matrix} Yt = β 0 + β 1 \times time t + β 2 \times intervention t \\ + β 3 \times post_intervention_time t + ò t . \end{matrix}

In this model, each component serves a specific purpose in expressing changes across time. Yt reflects the average value of an outcome (such as HbA1c) over a given month, t. The coefficient β1 indicates whether the outcome was increasing or decreasing in the months leading up to Ramadan. The coefficient β2 is significant as it represents the immediate impact of Ramadan, capturing any rapid surge or drop in outcome levels that happened in March. Finally, β3 quantifies the change in the trend after Ramadan began, allowing us to assess if the slope of the outcome grew steeper or flatter than the pre-Ramadan trend. The final term, ϵt, indicates the error term or residual at each time point. This variable captures the random variation and any other unmeasured elements that influence the result but are not accounted for by the model’s primary components.

Since monthly health measurements may be correlated over time (eg, average blood pressure in one month is likely related to that of the previous month), we first assessed serial correlation using the Durbin-Watson test. To address any identified correlation and improve model validity, we fitted the models using generalized least squares (GLS). In addition, to examine whether the impact of Ramadan varied across treatment groups, we conducted stratified analyses. Specifically, the primary ITS models were estimated separately for each of the four predefined antidiabetic medication classes to assess potential heterogeneity of effects.

An analysis of the raw, encounter-level data revealed missing values for critical continuous variables, including BMI and, to a lesser extent, test results such as HbA1c. Simply deleting cases with missing data would have resulted in a considerable loss of statistical power and possibly introduced selection bias. As a result, a more complex technique was employed. Multiple Imputation by Chained Equations (MICE), implemented via the mice package in R, was used to impute missing values at the patient-encounter level before the aggregation stage. This method considers that the data are missing at random (MAR) and generates numerous complete datasets by imputing missing values using predictive models that use other variables in the dataset (eg, age, gender, and comorbidities). The major analysis was then carried out on the pooled results from these imputed datasets, ensuring that the final estimates accounted for the uncertainty imposed by the imputation method.

To address potential confounding, several analytical adjustments were incorporated into the ITS models. At the patient level, age, gender, and time-varying BMI were included as covariates in the segmented regression models to account for demographic and anthropometric differences that may independently influence glycemic and blood pressure trajectories. Antidiabetic medication class was addressed through stratified subgroup analyses, allowing the effect of Ramadan to be estimated separately within each treatment group and thereby controlling for the differential metabolic risk profiles associated with each regimen. While individual-level data on medication dose adjustments, dietary intake, physical activity, and fasting adherence were not available in the EHR—representing an acknowledged limitation—the ITS design itself provides a degree of inherent confounding control by modeling the pre-existing outcome trend and isolating the Ramadan-associated level and slope changes from underlying secular trajectories. This methodological feature distinguishes the present analysis from simpler pre-post designs that cannot account for such trends.

Ethical Considerations

The study was approved by the Institutional Review Board (IRB) of King Fahad Medical City (KFMC), Riyadh, Saudi Arabia (IRB Log Number: 24-245). The requirement for written informed consent was waived by the IRB because the study was a retrospective analysis of previously collected, de-identified electronic health record data, posed no more than minimal risk to participants, and involved no direct patient contact or intervention. All data were fully anonymized prior to analysis, and the study was conducted in accordance with the ethical principles of the Declaration of Helsinki and applicable national regulations governing human subjects research in Saudi Arabia.

Results

Patients Characteristics

After applying all inclusion and exclusion criteria, the final study population consisted of 15 289 individuals with concomitant T2DM and HTN. Table 1 shows the baseline demographic and clinical features of this group, averaged across the pre-Ramadan period (December 2023 to February 2024). The cohort’s mean age was 61.4 years (SD 12.8), and there was a small male preponderance (54.1%). The population’s mean baseline BMI was 32.6 kg/m2 (SD 6.1), indicating a substantial burden of obesity. A group with established disease was indicated by baseline blood pressure and glycemic control: the mean pre-Ramadan HbA1c was 8.1% (SD 1.5), the mean SBP was 138.5 mmHg (SD 15.2), and the mean DBP was 79.2 mmHg (SD 9.8). Insulin-based therapy accounted for 41.5% of all antidiabetic drug regimens, with sulfonylurea-based regimens coming in second (28.9%). To further explore heterogeneity within the cohort, pre-specified subgroup analyses were conducted stratified by antidiabetic medication class (Diet/Metformin only, Sulfonylurea-based, Insulin-based, and GLP-1 RA/SGLT2i-based regimens), given the clinically meaningful differences in hypoglycemia risk, mechanism of action, and expected metabolic response to fasting across these groups. Additionally, age and gender were retained as covariates in all primary ITS models to account for their potential influence on glycemic and blood pressure trajectories throughout the study period.

Table 1.

Baseline Demographic and Clinical Characteristics of the Study Cohort (N = 15 289).

Characteristic	Value
Demographics
Age, mean (SD), years	61.4 (12.8)
Gender, n (%)
Male	8271 (54.1)
Female	7018 (45.9)
Clinical measurements (pre-Ramadan baseline)
Body Mass Index (BMI), mean (SD), kg/m²	32.6 (6.1)
Hemoglobin A1c (HbA1c), mean (SD), %	8.1 (1.5)
Systolic blood pressure (SBP), mean (SD), mmHg	138.5 (15.2)
Diastolic blood pressure (DBP), mean (SD), mmHg	79.2 (9.8)
Key comorbidities, n (%)
Dyslipidemia	10 855 (71.0)
Chronic kidney disease (CKD, Stages 1-4)	4434 (29.0)
Coronary artery disease	3363 (22.0)
Antidiabetic medication class, n (%)
Diet/metformin only	2217 (14.5)
Sulfonylurea-based regimen	4418 (28.9)
Insulin-based regimen	6345 (41.5)
GLP-1 RA/SGLT2i-based regimen	2309 (15.1)

Abbreviation: SD, standard deviation.

Baseline values are the means of measurements taken between December 2023 and February 2024.

Impact of Ramadan on Glycemic Control (HbA1c)

Ramadan has a significant effect on glycemic control, according to the Interrupted Time Series analysis. Table 2 presents the detailed findings of the segmented regression model for mean monthly HbA1c. In the months preceding Ramadan, HbA1c showed a modest but non-significant decline (β1 = −0.04% per month, P = .18), suggesting relatively stable glycemic control among patients. At the onset of Ramadan (March 2024), there was an immediate and statistically significant reduction in mean HbA1c of −0.25% (β2 = −0.25, 95% CI [−0.38, −0.12], P < .001). This indicates a population-level improvement in glycemic control directly associated with the fasting month. However, this improvement was not sustained. The model showed a significant positive shift in the post-Ramadan trend (β3 = +0.19, P = .002), resulting in a post-Ramadan slope of +0.15% per month, indicating that HbA1c levels began to rebound and increase in the months following Ramadan. The heterogeneity of this effect across medication subgroups is further explored in the stratified analyses below, revealing that the magnitude of glycemic improvement during Ramadan varied substantially according to antidiabetic regimen, with important implications for individualized pre-Ramadan clinical management.

Table 2.

Interrupted Time Series Model for Mean Monthly HbA1c (%).

Model parameter	Coefficient (β)	95% confidence interval	P-value
Intercept (baseline HbA1c at time 0)	8.15	[8.05, 8.25]	<.001
Pre-Ramadan trend (slope per month)	−0.04	[−0.10, 0.02]	.180
Level change (immediate Ramadan effect)	−0.25	[−0.38, −0.12]	<.001
Post-Ramadan trend change (slope change)	+0.19	[0.08, 0.30]	.002

Impact of Ramadan on Blood Pressure Control (SBP and DBP)

Similar short-term improvements in blood pressure control, particularly in SBP, were observed. Table 3 presents the outcomes of the ITS models for both SBP and DBP. In the pre-Ramadan period, there was no significant trend in SBP over time (β1 = −0.31 mmHg per month, P = .45). At the onset of Ramadan, mean SBP showed an immediate and clinically significant decrease of −4.12 mmHg (β2 = −4.12, 95% CI [−5.98, −2.26], P < .001). However, following Ramadan, the trend changed in a positive and statistically significant direction (β3 = +2.05, P = .01), suggesting that the beneficial effect on SBP diminished rapidly in the subsequent months. For DBP, the pre-Ramadan trend was also stable. Although there was a modest immediate reduction of −1.55 mmHg during Ramadan, this change did not reach statistical significance (β2 = −1.55, P = .08). Subgroup analyses of blood pressure outcomes by medication class were not performed as primary stratified comparisons given the focus of the pre-specified subgroup analysis on glycemic heterogeneity; however, this represents an important avenue for future investigation, particularly given the differential effects of antihypertensive agents on fluid balance and vascular tone during prolonged fasting.

Table 3.

Interrupted Time Series Models for Mean Monthly SBP and DBP (mmHg).

Outcome and parameter	Coefficient (β)	95% confidence interval	P-value
Systolic blood pressure (SBP)
Intercept (baseline SBP)	138.8	[136.9, 140.7]	<.001
Pre-Ramadan trend	−0.31	[−1.12, 0.50]	.450
Level change (Ramadan effect)	−4.12	[−5.98, −2.26]	<.001
Post-Ramadan trend change	+2.05	[0.45, 3.65]	.010
Diastolic blood pressure (DBP)
Intercept (baseline DBP)	79.5	[78.1, 80.9]	<.001
Pre-Ramadan trend	−0.20	[−0.78, 0.38]	.480
Level change (Ramadan effect)	−1.55	[−3.28, 0.18]	.080
Post-Ramadan trend change	+0.85	[−0.35, 2.05]	.150

Subgroup Analyses by Medication Class

To examine whether the cardiometabolic impact of Ramadan differed according to treatment complexity and hypoglycemia risk, pre-specified stratified ITS analyses were conducted separately for each of the four antidiabetic medication classes (Table 4). These subgroup analyses were planned a priori based on the clinical rationale that fasting-induced metabolic changes—including prolonged caloric restriction, altered meal timing, and shifts in insulin sensitivity—are likely to interact differently with each drug class’s mechanism of action. The results demonstrated clinically meaningful heterogeneity across groups. Patients on modern therapies (GLP-1 RAs/SGLT2is) experienced the greatest immediate reduction in HbA1c (−0.41%, P < .001), likely reflecting the glucose-dependent and weight-reducing mechanisms of these agents, which may synergize favorably with the caloric restriction and altered eating patterns of Ramadan. The Diet/Metformin group also showed a significant reduction (−0.28%, P = .005), consistent with the low hypoglycemia risk of this regimen and its compatibility with fasting-associated metabolic shifts. The Sulfonylurea group demonstrated a modest but statistically significant improvement (−0.22%, P = .01), though this group warrants clinical caution given the elevated hypoglycemia risk associated with sulfonylureas during prolonged fasting periods. In contrast, the Insulin-treated group—the largest subgroup, comprising 41.5% of the cohort—showed the smallest and non-significant reduction in HbA1c (−0.11%, P = .15), suggesting that the complexity of insulin regimen management during Ramadan, combined with the competing risks of hypoglycemia and compensatory hyperglycemia, may attenuate the glycemic benefit observed in other groups. Subgroup analyses by age and gender were not performed as primary subgroup comparisons given the study’s population-level ITS design; however, both variables were included as covariates in the primary models to adjust for their potential confounding influence on outcome trajectories.

Table 4.

Stratified ITS Analysis of Immediate Level Change in HbA1c by Medication Class.

Antidiabetic medication class	Immediate level change in HbA1c (%) (β₂)	P-value
Diet/metformin only	−0.28	.005
Sulfonylurea-based regimen	−0.22	.010
Insulin-based regimen	−0.11	.150
GLP-1 RA/SGLT2i-based regimen	−0.41	<.001

Discussion

This large-scale, longitudinal study provides real-world evidence on the cardiometabolic effects of Ramadan fasting among Saudis with concomitant T2DM and hypertension. Using an Interrupted Time Series (ITS) analysis to account for prior trends, Ramadan fasting was linked to a statistically significant, albeit transitory, improvement in glycemic and blood pressure control. Specifically, the start of Ramadan was associated with an instantaneous population-level reduction in mean HbA1c of 0.25% and a fall in mean systolic blood pressure (SBP) of more than 4 mmHg. The temporary nature of these benefits is a significant finding. Post-Ramadan trends showed a considerable recovery in HbA1c, showing that benefits are quickly lost once normal living patterns return. This dynamic trajectory highlights that the observed effect is likely due to a complex interplay of Ramadan-specific factors, such as changes in meal timing and composition, potential changes in medication adherence, disrupted sleep-wake cycles, and altered physical activity patterns, rather than caloric restriction. While these mechanisms are theoretical, they provide reasonable explanations for aggregate population-level results. The present study also showed that patients on insulin therapy experienced the least glycemic benefit, which is consistent with their increased risk of hypoglycemia and hyperglycemia due to sophisticated insulin regimens. This finding emphasizes the need for rigorous pre-Ramadan education and management changes for high-risk patients. Patients taking current medicines with a lower risk of hypoglycemia, such as GLP-1 receptor agonists or SGLT2 inhibitors, may benefit more, indicating the need for individualized clinical interventions.

Previous studies indicate that the effects of Ramadan fasting on systolic blood pressure and HbA1c are not entirely consistent. According to Amer et al,¹⁸ Ramadan fasting seems to have a major impact on blood and lipid profiles in Egyptians with type 2 diabetes. In addition to supporting recommendations for some governmental guidelines that describe Ramadan fasting as a safe religious practice concerning blood pressure, the study by Al-Jafar et al¹¹ suggests that Ramadan fasting has positive effects on blood pressure that are independent of changes in weight, total body water, and fat mass. According to Mohamed et al,¹⁹ type 2 diabetic individuals who fasted throughout Ramadan showed a decrease in HbA1c, LDL, TC, and TG and an increase in HDL. However, they also showed slight improvements in body weight, BMI, SBP, and DBP. According to Selman et al,²⁰ fasting during Ramadan lowers blood pressure, body weight, and glycated hemoglobin in diabetic patients. Shoulah et al²¹ found a substantial drop (P < .05) in anthropometric parameters (weight, BMI, waist-hip ratio), lipid profile, and HbA1C among a sample of diabetic patients in Egypt after Ramadan ended. Physical inactivity, past DM difficulties during Ramadan fasting, decreased meal consumption, and increased fluid and sugar intake all contributed to complicated diabetes during Ramadan.

According to Çelik et al,²² type 2 diabetes patients in Turkey did not require emergency hospitalization for fasting-related health issues. We discovered no unfavorable or positive impacts of Ramadan on metabolic control variables such as weight, HbA1c, fructosamine, C-peptide, insulin, or lipid profile. They concluded that Ramadan fasting has no deleterious effects on metabolic markers in Type 2 diabetic patients. Baccouche et al²³ revealed that in older people with cardiovascular risk factors, Ramadan appears to have two effects. During the fasting phase, there is a risk of reduced renal function and increased glycemia. In contrast, their data after Ramadan suggest the potential benefits of fasting on lipid regulation and glycemic management. A systematic review and meta-analysis by Gad et al²⁴ revealed that type 2 diabetic patients receiving SGLT2i’s during Ramadan saw a decrease in hypoglycemia, an improvement in HbA1c, and no significant side effects. Previous research indicates that the effects of Ramadan fasting on systolic blood pressure (SBP) and HbA1c are not entirely consistent. This variation probably comes from several factors: differences in study design (such as cross-sectional vs longitudinal or pre-post vs controlled ITS), the timing of measurements (right after Ramadan vs weeks later), baseline health status (poor vs good control of blood sugar or blood pressure), changes in medications (like reduced doses or shifted timing of insulin or antihypertensives), and lifestyle habits (including nighttime eating patterns, sodium intake, sleep restriction, caffeine use, and physical activity). Other contributors may include the length and season of fasting (eg, heat and dehydration) and issues with adherence or selection bias, since healthier individuals may be more inclined to fast.

In our study, the ITS technique helps distinguish actual Ramadan-related level/trajectory changes from secular trends, but residual confounding is conceivable. When fasting is combined with medication optimization and dietary counseling, the literature suggests Ramadan can improve HbA1c/SBP; however, without these supports, neutral or adverse effects may occur, emphasizing the need for risk-stratified guidance and standardized measurement windows. These findings have significant clinical implications. Ramadan represents a “window of opportunity” for metabolic improvement, which can be used to urge patients to make beneficial lifestyle changes. However, the fragility of these advantages highlights the importance of regular post-Ramadan follow-up to consolidate gains, modify medications, and promote long-term practices. Risk classification is essential; patients on complex insulin regimens require more intense assistance, whilst those on safer treatments may obtain considerable gains by fasting alone.

A particularly noteworthy finding of this study is the simultaneous, population-level improvement in both glycemic control and systolic blood pressure during Ramadan—two of the central pillars of cardiorenal metabolic syndrome (CaRMS). Cardiorenal metabolic syndrome represents a cluster of interrelated conditions—including hyperglycemia, hypertension, obesity, and chronic kidney disease—that synergistically accelerate cardiovascular and renal disease progression. In our cohort, 29% had concurrent CKD and 22% had established coronary artery disease, underscoring the high cardiorenal risk burden of this population. The concurrent reduction in HbA1c (−0.25%, P < .001) and SBP (−4.12 mmHg, P < .001) observed during Ramadan, even if transient, suggests that the metabolic perturbations induced by prolonged daily fasting—including shifts in insulin sensitivity, ketone metabolism, reduced caloric load, and altered sodium handling—may collectively attenuate multiple cardiorenal risk axes simultaneously. This multi-dimensional metabolic response distinguishes Ramadan fasting from conventional single-target pharmacological interventions and positions it as a unique, annually recurring, patient-driven opportunity for cardiorenal metabolic risk reduction. To our knowledge, this is one of the first large-scale, quasi-experimental studies to frame Ramadan fasting within the cardiorenal metabolic syndrome paradigm, and the findings carry direct implications for how clinicians and health systems engage with Muslim patients around this period—not merely as a period of clinical risk to be mitigated, but as a structured physiological stress that, when properly supported, may yield meaningful and clinically actionable cardiometabolic benefits.

The post-Ramadan rebound observed in this study—with HbA1c rising at +0.15% per month and SBP returning to pre-Ramadan levels within weeks—has direct and urgent clinical implications. These findings demonstrate that the metabolic gains achieved during Ramadan are physiologically fragile and behaviorally dependent; without deliberate clinical reinforcement, they are rapidly eroded by the resumption of pre-Ramadan dietary patterns, physical inactivity, and disrupted medication adherence. This rebound phenomenon argues strongly for the institutionalization of a structured post-Ramadan follow-up protocol within healthcare systems serving Muslim populations. We propose that such a framework should include, at minimum: (1) a dedicated post-Ramadan review consultation within 4 weeks of Eid al-Fitr, focused on medication reconciliation and dose re-titration; (2) individualized dietary counseling aimed at preserving the reduced caloric load and improved meal timing patterns established during fasting; (3) reinforcement of physical activity habits, particularly among patients who increased activity during Ramadan; and (4) targeted psychological and behavioral support to sustain motivation beyond the religious context that originally drove the behavioral change. For patients on insulin or sulfonylurea-based regimens—who showed the least glycemic benefit and carry the highest hypoglycemia risk—this post-Ramadan window is especially critical for medication review. Health systems in Saudi Arabia and across the Muslim world are uniquely positioned to integrate such protocols into existing chronic disease management pathways, leveraging the annual predictability of Ramadan as a calendar-anchored intervention point.

Limitations

The study’s key strengths include its large, longitudinal, real-world dataset, which improves generalizability to routine clinical practice in Saudi Arabia and similar populations. The ITS methodology yields a reliable estimate of Ramadan’s effect, and thorough prescription data allowed for therapeutically meaningful subgroup studies. Observational design has limitations, including the inability to demonstrate causality and the risk of unmeasured confounding. Dietary information, physical activity, sleep quality, fasting compliance, and detailed medication modifications were all lacking. Relying on EHR data increases the possibility of coding errors, and monthly aggregation may mask day-to-day variability and acute episodes like severe hypoglycemia. Furthermore, findings may not apply to people with varying fasting patterns or cultural backgrounds.

Future Research

Future research should focus on prospective studies that use continuous glucose monitoring and 24-hour ambulatory blood pressure monitoring to detect acute metabolic changes. Collecting patient-reported data on food, exercise, and medication adherence will aid in understanding the mechanisms underlying the observed improvements. Long-term studies are also required to assess whether repeated yearly Ramadan fasting has long-term impacts on cardiovascular health or progression to end-stage kidney disease.

Conclusion

In a large, real-world cohort of 15 289 Saudi patients with concomitant T2DM and HTN, Ramadan fasting was associated with a statistically significant and clinically meaningful—though transient—improvement in both glycemic and blood pressure control. Using a rigorous Interrupted Time Series methodology, this study moves beyond simple pre-post comparisons to map the full dynamic trajectory of cardiometabolic health before, during, and after the fasting month, filling a critical methodological gap in the existing literature. Crucially, the simultaneous attenuation of two primary drivers of cardiorenal metabolic syndrome—hyperglycemia and hypertension—in a high-risk comorbid population reframes Ramadan not as a period of clinical hazard alone, but as a reproducible, annually recurring window for cardiometabolic reset.

The post-Ramadan rebound in HbA1c and blood pressure, however, underscores that these gains are physiologically fragile and will not persist without deliberate clinical action. This calls for a fundamental shift in how healthcare providers and systems approach Ramadan—moving from reactive risk management to proactive, structured engagement across three distinct phases. Before Ramadan, clinicians should conduct structured risk stratification consultations, with particular attention to patients on insulin or sulfonylurea-based regimens who demonstrate the least glycemic benefit and carry the highest hypoglycemia risk. Tailored pre-Ramadan patient education—covering safe fasting practices, self-monitoring frequency, dietary guidance for Iftar and Suhoor meals, and individualized medication timing adjustments—should be delivered as a standardized component of chronic disease management in Muslim-majority healthcare settings. During Ramadan, enhanced remote monitoring and accessible clinical support pathways should be established to detect and manage acute complications, including hypoglycemia, dehydration, and blood pressure fluctuations, promptly. After Ramadan, a dedicated post-Ramadan follow-up consultation—ideally within 4 weeks of Eid al-Fitr—should be institutionalized to reconcile medications, reinforce the dietary and behavioral patterns established during fasting, and capitalize on patients’ heightened motivation for health improvement during this spiritually significant period. Patients on GLP-1 receptor agonists or SGLT2 inhibitors, who demonstrated the greatest glycemic benefit, may represent a priority group for intensified post-Ramadan behavioral reinforcement to consolidate and extend their metabolic gains.

These practice implications are not optional enhancements but clinical necessities if the metabolic opportunity presented by Ramadan is to be translated into durable long-term health gains. Health systems in Saudi Arabia and across the Muslim world are uniquely positioned to embed these protocols within existing chronic disease management frameworks, leveraging the annual predictability of Ramadan as a calendar-anchored intervention point. Future prospective studies incorporating continuous glucose monitoring, ambulatory blood pressure data, and patient-reported behavioral outcomes are needed to further validate these findings and inform evidence-based Ramadan care guidelines at both national and international levels.

Footnotes

ORCID iDs

Nehad J. Ahmed

Nada Abou Chahin

Ethical Considerations

Author Contributions

Z.S.A have full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Concept and design: A.M.A, H.H.A, and N.S.A. Acquisition, analysis, or interpretation of data: A.K.A. and A.A.A. Drafting of the manuscript: N.J.A. Critical review of the manuscript for important intellectual content: A.A.A Statistical analysis: Z.S.A. Administrative, technical, or material support: R.A.M. and N.F.A. Supervision: Z.S.A. All authors read and approved the final manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The authors extend their appreciation to Prince Sattam bin Abdulaziz University for funding this research work through the project number (PSAU/2025/01/33952).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

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

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