Abstract
Background
Ramadan fasting involves prolonged daytime abstinence from food and fluid intake and may influence cardiovascular and physiological regulation. Although prior studies have examined metabolic and cardiovascular effects, evidence on ambulatory blood pressure patterns and geriatric outcomes in the “oldest old” remains limited.
Objective
To evaluate the effects of Ramadan fasting on ambulatory blood pressure, hydration status, mobility, and fall risk in community-dwelling adults aged ≥ 80 years.
Methods
In this prospective within-subject repeated-measures study, 69 adults aged ≥ 80 years were evaluated during both fasting and non-fasting periods. Twenty-four-hour ambulatory blood pressure monitoring (ABPM) was performed using a validated automated device. Hydration status was assessed using serum and urine osmolality and the Dehydration Screening Tool. Functional and geriatric outcomes were evaluated using the Katz Activities of Daily Living scale, Timed Up and Go test, Five-Times Sit-to-Stand test, and the Itaki Fall Risk Scale. Paired comparisons were conducted between periods, and linear mixed-effects regression models were used to assess hourly blood pressure patterns.
Results
Mean 24-hour systolic and diastolic blood pressure demonstrated small but statistically significant increases during fasting compared with the non-fasting period (132.5 ± 16.1 vs. 129.8 ± 14.8 mmHg, p = 0.049; and 70.2 ± 9.6 vs. 68.0 ± 8.7 mmHg, p = 0.008, respectively). Hydration parameters and functional mobility did not differ significantly between periods. However, fall risk scores were significantly higher during fasting (mean difference 0.44 points; Cohen’s dz = 0.52; p < 0.001). Mixed-effects analyses demonstrated significant circadian variation in blood pressure, with the greatest divergence between fasting and non-fasting conditions observed in the afternoon (approximately 15:00).
Conclusion
In adults aged ≥ 80 years, Ramadan fasting was associated with small effect-size increases in ambulatory blood pressure and a moderate effect-size increase in fall risk, without significant changes in hydration status, or mobility. These findings suggest that fasting may be tolerated in selected very elderly individuals; however, individualized clinical assessment, blood pressure monitoring, and fall risk evaluation should be considered in primary care settings.
Keywords: Ramadan fasting, Ambulatory blood pressure monitoring, Elderly, Circadian blood pressure, Dehydration, Fall risk
Introduction
Population ageing is one of the most important demographic transitions of the 21st century. The number of individuals aged 80 years and older is increasing rapidly worldwide, leading to a growing population of very elderly individuals with complex health needs [1, 2]. Individuals aged ≥ 80 years, often referred to as the “oldest old,” represent a clinically distinct subgroup characterized by increased physiological vulnerability, reduced homeostatic reserve, and heightened susceptibility to environmental stressors [3–5]. In addition, multimorbidity and polypharmacy are highly prevalent in this population and may further increase susceptibility to environmental or lifestyle stressors [6, 7]. For this reason, the present study specifically focused on this age group to better capture the potential impact of prolonged fasting under conditions of advanced biological ageing.
Ramadan fasting is observed annually by millions of Muslims worldwide and involves abstaining from food and fluid intake from dawn until sunset. During this period, substantial changes occur in dietary habits, sleep patterns, and circadian rhythms, which may influence metabolic and cardiovascular physiology [8–10]. Previous studies have evaluated the cardiometabolic effects of Ramadan fasting and have reported modest changes in body weight, lipid profile, and metabolic parameters. However, the effects of fasting on blood pressure remain inconsistent across different populations and study designs [9–12].
Ambulatory blood pressure monitoring (ABPM) provides a more comprehensive assessment of blood pressure patterns than office measurements and is particularly useful for evaluating circadian blood pressure variability. Previous studies investigating ambulatory blood pressure responses to Ramadan fasting have reported heterogeneous findings [11, 13]. Nevertheless, evidence regarding ambulatory blood pressure responses to Ramadan fasting remains limited, and data in very elderly individuals are particularly scarce.
Older adults may be especially susceptible to the potential physiological effects of prolonged fasting. Age-related impairments in thirst perception and reduced renal concentrating capacity may increase the risk of dehydration during fasting periods [14, 15]. In addition, alterations in autonomic cardiovascular regulation and circadian blood pressure patterns may influence hemodynamic stability in elderly individuals [3, 4]. These physiological changes may have important clinical implications, as both hemodynamic instability and dehydration are well-established contributors to adverse geriatric outcomes [14–16].
Beyond cardiovascular parameters, fasting may also influence functional outcomes such as mobility, and fall risk. Falls represent one of the leading causes of injury, disability, and loss of independence among older adults worldwide [17–19]. Identifying factors that may influence fall risk in very elderly individuals is therefore an important component of geriatric clinical care.
Despite these potential concerns, few studies have specifically evaluated the combined effects of Ramadan fasting on ambulatory blood pressure patterns, hydration status, mobility, and fall risk in adults aged 80 years and older. Therefore, the aim of this study was to evaluate the effects of Ramadan fasting on blood pressure, hydration status, mobility, and fall risk in community-dwelling adults aged 80 years and older. We hypothesized that, compared with the non-fasting period, fasting would be associated with higher ambulatory blood pressure, impaired hydration status, reduced mobility, and increased fall risk.
Methods
Study design and participants
This prospective within-subject repeated-measures study was conducted among community-dwelling adults aged ≥ 80 years in a primary care setting. Participants were recruited from individuals registered at a three-unit Family Health Center, as well as from patients presenting for routine clinical evaluation; none were institutionalized. Eligible participants were those able to complete assessments during both fasting and non-fasting periods and who provided informed consent.
Exclusion criteria included inability to complete both assessment periods, acute illness, severe cognitive impairment preventing participation, and conditions that could significantly affect hydration status or blood pressure regulation.
Ramadan assessments were conducted during different periods of Ramadan according to participant availability and routine clinic scheduling. Daily fasting duration was approximately 13–14 hours, with complete abstinence from both food and fluid intake between dawn and sunset. Participants continued their usual Ramadan practices and were not instructed to modify their fasting behavior. Fasting adherence was based on participant self-report, and no objective verification methods (e.g., dietary records or continuous monitoring) were applied.
All assessments were conducted in the same primary care setting under both fasting and non-fasting conditions. Ambulatory blood pressure monitoring devices were applied in the clinic between 15:00 and 16:00 and removed approximately 24 hours later during the follow-up visit.
Non-fasting measurements were obtained at least 8 weeks after Ramadan to allow sufficient time for the resolution of fasting-related physiological changes, including alterations in hydration status, circadian rhythm, and dietary patterns, thereby minimizing potential carry-over effects.
The participant selection process is summarized in Fig. 1. Of the 100 individuals assessed for eligibility, 31 were excluded (27 who did not fast and 4 who declined participation). A total of 69 participants completed both fasting and non-fasting assessments and were included in the final paired analysis.
Fig. 1.
Flow diagram of participant selection and study procedures. Flow diagram showing participant selection, exclusions, and inclusion in the final paired analysis
No formal sample size calculation was performed, and the sample size was determined based on feasibility within the study period.
Data collection
Sociodemographic characteristics, medical history, and medication use were recorded through structured interviews and review of medical records. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared. Information on medication use was recorded; however, the timing of medication administration during Ramadan was not standardized.
Ambulatory blood pressure monitoring
Ambulatory blood pressure monitoring was performed using a validated oscillometric device (ABPM50, Contec Medical Systems, Qinhuangdao, China). The monitor was applied to the non-dominant arm and programmed to record blood pressure at 15-minute intervals during daytime and 30-minute intervals during nighttime.
Each participant underwent two separate 24-hour monitoring sessions: one during the fasting period and one during the non-fasting period. Participants were instructed to maintain their usual daily activities while avoiding excessive physical exertion during monitoring.
Daytime and nighttime periods were defined as 07:00–23:00 and 23:00–07:00, respectively. Recordings were considered valid if at least 70% of scheduled measurements were successfully obtained, with a minimum of 20 daytime and 7 nighttime readings. Participants kept a brief diary to record sleep and wake times.
Data were transferred to dedicated computer-based analysis software. Mean 24-hour, daytime, and nighttime systolic and diastolic blood pressure values were calculated for each participant.
Hydration assessment
Hydration status was assessed using serum osmolality, urine osmolality, and the Dehydration Screening Tool (DST). The DST is a validated screening instrument designed to identify dehydration risk in older adults through questions addressing fluid intake, thirst perception, urinary symptoms, functional status, and clinical signs associated with inadequate hydration. Higher DST scores indicate a greater risk of dehydration. The Turkish version has demonstrated adequate validity and reliability in older adults [20].
During the Ramadan assessment, blood and urine samples were collected during daytime fasting hours while participants were actively observing the fast. During the non-fasting assessment, samples were collected under usual non-fasting conditions without dietary restriction. All samples were processed immediately after collection. Serum and urine osmolality were measured using a freezing point depression osmometer (Osmo1, Advanced Instruments, USA) in accordance with the manufacturer’s instructions, with routine calibration and quality control procedures applied.
Functional assessment
Functional status and geriatric outcomes were evaluated using standardized instruments. Functional independence was assessed using the Katz Activities of Daily Living (ADL) scale, which evaluates six basic activities, with higher scores indicating greater independence. The Turkish version has demonstrated validity and reliability [21].
Mobility and balance were assessed using the Timed Up and Go (TUG) test, a validated measure in older adults. The Turkish version of the test has demonstrated good reliability and validity [22]. Longer completion times indicate poorer mobility and balance performance.
Lower extremity strength and functional mobility were evaluated using the Five-Times Sit-to-Stand Test (FTSTS), a validated measure in older adults, with longer completion times indicating reduced lower extremity strength and functional performance [23].
Fall risk was assessed using the Itaki Fall Risk Scale, which evaluates multiple risk factors including mobility, cognition, comorbidities, medication use, and environmental factors, with higher scores indicating greater fall risk [24].
Statistical analysis
Statistical analyses were performed using Python 3.13. Data processing and statistical analyses were conducted using the pandas, numpy, scipy, statsmodels, and matplotlib libraries. Descriptive statistics were used to summarize demographic and clinical characteristics and were presented as mean ± standard deviation (SD) for continuous variables and as number (percentage) for categorical variables.
Comparisons of ambulatory blood pressure parameters, hydration indicators, and geriatric functional outcomes between fasting and non-fasting periods were performed using paired t-tests. Effect sizes were calculated using Cohen’s dz. Cohen’s dz value was calculated by dividing the mean difference between post-measurement and pre-measurement values by the standard deviation of these differences (dz = mean difference / SD difference). Effect sizes were interpreted according to conventional thresholds, with dz values of 0.2, 0.5, and 0.8 representing small, moderate, and large effects, respectively.
To evaluate the temporal variation in blood pressure throughout the day, linear mixed-effects regression models were applied. In these models, time (hour) was included as a continuous fixed effect, while participants were included as random effects with random intercepts to account for within-individual repeated measurements. Separate models were fitted for systolic and diastolic blood pressure, including condition (fasting vs. non-fasting), time (hour), and the condition × time interaction. A two-sided p value < 0.05 was considered statistically significant for all analyses.
Circadian blood pressure curves were generated to visualize hourly changes in systolic and diastolic blood pressure, with mean values plotted across time and confidence intervals displayed as shaded areas.
Results
Participant characteristics
A total of 69 community-dwelling adults aged ≥ 80 years were included in the analysis. The mean age was 83.7 ± 4.2 years, and 49.3% of participants were male. Hypertension was the most common comorbidity (82.6%), followed by diabetes mellitus (17.4%) and coronary artery disease (13.0%). Additional baseline characteristics are summarized in Table 1.
Table 1.
Baseline characteristics of the study participants (n = 69)
| Variable | Value |
|---|---|
| Age, years | 83.7 ± 4.2 |
| Body mass index, kg/m² | 28.8 ± 5.7 |
| Male sex, n (%) | 34 (49.3) |
| Hypertension, n (%) | 57 (82.6) |
| Diabetes mellitus, n (%) | 12 (17.4) |
| Coronary artery disease, n (%) | 9 (13.0) |
| Atrial fibrillation, n (%) | 8 (11.6) |
| Dyslipidemia, n (%) | 8 (11.6) |
| Chronic obstructive pulmonary disease, n (%) | 9 (13.0) |
| Current smoking, n (%) | 10 (14.5) |
| Diuretic use, n (%) | 29 (42.0) |
| ACE inhibitor use, n (%) | 18 (26.1) |
| Calcium channel blocker use, n (%) | 27 (39.1) |
| Beta-blocker use, n (%) | 21 (30.4) |
Values are presented as mean ± standard deviation (SD) or number (%)
ACE Angiotensin-converting enzyme
Comparison of ambulatory blood pressure and clinical outcomes
Comparisons between fasting and non-fasting periods revealed significant differences in several ambulatory blood pressure parameters. Twenty-four–hour systolic blood pressure was higher during fasting (132.5 ± 16.1 mmHg) than during the non-fasting period (129.8 ± 14.8 mmHg; p = 0.049, Cohen’s dz = 0.25). Similarly, 24-hour diastolic blood pressure was higher during fasting (70.2 ± 9.6 mmHg vs. 68.0 ± 8.7 mmHg; p = 0.008, dz = 0.34).
Daytime and nighttime diastolic blood pressure were also significantly higher during fasting (p = 0.029, dz = 0.28 and p = 0.015, dz = 0.31, respectively), whereas no significant differences were observed for daytime or nighttime systolic blood pressure (p = 0.053 and p = 0.206).
Hydration parameters, including serum osmolality, urine osmolality, and dehydration screening scores, did not differ significantly between fasting and non-fasting periods. Similarly, no significant differences were observed in geriatric functional measures, including Katz activities of daily living score, Timed Up and Go test, and Sit-to-Stand test (all p > 0.05).
However, fall risk scores were slightly higher during fasting (12.68 ± 5.75 vs. 12.14 ± 5.91; p < 0.001, dz = 0.52) (Table 2).
Table 2.
Comparison of ambulatory blood pressure, hydration status, and geriatric functional outcomes between fasting and non-fasting periods
| Parameter | Non-fasting | Fasting | P value | Cohen’s dz | Mean difference (95% CI) |
|---|---|---|---|---|---|
| 24-h systolic BP (mmHg) | 129.8 ± 14.8 | 132.5 ± 16.1 | 0.049 | 0.25 | 2.92 (0.17, 5.67) |
| 24-h diastolic BP (mmHg) | 68.0 ± 8.7 | 70.2 ± 9.6 | 0.008 | 0.34 | 2.07 (0.44, 3.69) |
| Daytime systolic BP (mmHg) | 130.7 ± 14.2 | 133.4 ± 15.9 | 0.053 | 0.24 | 3.02 (0.18, 5.85) |
| Daytime diastolic BP (mmHg) | 69.2 ± 8.6 | 71.2 ± 10.1 | 0.029 | 0.28 | 1.90 (0.10, 3.70) |
| Nighttime systolic BP (mmHg) | 126.2 ± 20.3 | 128.6 ± 19.7 | 0.206 | 0.16 | 2.26 (− 1.42, 5.94) |
| Nighttime diastolic BP (mmHg) | 62.7 ± 10.8 | 65.7 ± 10.5 | 0.015 | 0.31 | 2.69 (0.34, 5.04) |
| Serum osmolality (mOsm/kg) | 305.5 ± 7.9 | 305.4 ± 7.1 | 0.714 | 0.04 | −0.82 (− 2.57, 0.93) |
| Urine osmolality (mOsm/kg) | 572.8 ± 185.3 | 599.3 ± 153.5 | 0.196 | 0.16 | 34.84 (− 16.02, 85.70) |
| Dehydration Screening Tool score | 7.05 ± 1.80 | 7.21 ± 2.33 | 0.435 | 0.16 | 0.16 (− 0.09, 0.41) |
| Katz ADL score | 5.48 ± 0.81 | 5.38 ± 0.79 | 0.070 | 0.22 | −0.08 (− 0.20, 0.04) |
| Timed Up and Go Test (s) | 13.21 ± 7.12 | 13.65 ± 7.16 | 0.155 | 0.17 | 0.53 (− 0.29, 1.35) |
| Sit-to-Stand Test (s) | 12.92 ± 5.35 | 13.64 ± 6.74 | 0.305 | 0.13 | 0.75 (− 0.61, 2.11) |
| Fall Risk Score | 12.14 ± 5.91 | 12.68 ± 5.75 | < 0.001 | 0.52 | 0.44 (0.22, 0.65) |
Boldface indicates statistical significance (p < 0.05)
Values are presented as mean ± SD. Comparisons between fasting and non-fasting periods were performed using paired t-tests. Effect sizes were calculated using Cohen’s dz. Mean differences are presented as fasting minus non-fasting values. Higher scores indicate greater independence for Katz ADL, and greater fall risk for the Fall Risk Score
BP Blood pressure, SD Standard deviation, CI Confidence interval
Mixed-effects regression analysis
A total of 3004 ambulatory blood pressure measurements from 69 participants were included in the analysis, with a mean of 43.5 measurements per participant (range: 8–48 measurements per participant). Time was modeled as a continuous variable representing hourly measurements across the 24-hour monitoring period (00:00–23:00), with 00:00 used as the reference time point.
Accordingly, the estimated time coefficient represents the average linear change in blood pressure per hour across the entire 24-hour period, rather than a change attributable to any specific clock-time point. As illustrated in Figs. 2 and 3, blood pressure values exhibit dispersion across all time points, with a modest overall upward trend over time.
Fig. 2.
Hourly distribution and temporal trend of ambulatory systolic blood pressure during fasting and non-fasting periods. Points represent individual ambulatory blood pressure measurements. Solid lines represent fitted linear trends derived from the mixed-effects model for fasting and non-fasting conditions. Time is expressed in hours across the 24-hour monitoring period
Fig. 3.
Hourly distribution and temporal trend of ambulatory diastolic blood pressure during fasting and non-fasting periods. Points represent individual ambulatory blood pressure measurements. Solid lines represent fitted linear trends derived from the mixed-effects model for fasting and non-fasting conditions. Time is expressed in hours across the 24-hour monitoring period
Although visual inspection of Figs. 2 and 3 suggests potential non-linear circadian variation, the linear specification was retained to estimate the overall temporal trend.
Within the fasting reference condition, systolic blood pressure increased by 0.36 mmHg per hour (β = 0.360, 95% CI 0.237–0.483; p < 0.001), while diastolic blood pressure increased by 0.40 mmHg per hour (β = 0.404, 95% CI 0.305–0.502; p < 0.001). Fasting status was not significantly associated with systolic blood pressure (β = −1.295, 95% CI − 3.651 to 1.061; p = 0.281) or diastolic blood pressure (β = −1.738, 95% CI − 3.620 to 0.145; p = 0.070). The interaction between fasting status and time was not significant for systolic (β = −0.097, 95% CI − 0.272 to 0.079; p = 0.281) or diastolic blood pressure (β = −0.012, 95% CI − 0.152 to 0.129; p = 0.870), indicating similar temporal trajectories between fasting and non-fasting periods (Table 3).
Table 3.
Mixed-effects linear regression model evaluating the effects of time and fasting status on blood pressure
| Variable | β | 95% CI | P value |
|---|---|---|---|
| SBP (Systolic Blood Pressure) | |||
| Fasting status (non-fasting) | -1.295 | -3.651, 1.061 | 0.281 |
| Time (hour) | 0.360 | 0.237, 0.483 | < 0.001 |
| Fasting status × Time | -0.097 | -0.272, 0.079 | 0.281 |
| DBP (Diastolic Blood Pressure) | |||
| Fasting status (non-fasting) | -1.738 | -3.620, 0.145 | 0.070 |
| Time (hour) | 0.404 | 0.305, 0.502 | < 0.001 |
| Fasting status × Time | -0.012 | -0.152, 0.129 | 0.870 |
Boldface indicates statistical significance (p < 0.05)
Results were obtained using linear mixed-effects regression models including fasting status, time (hour), and their interaction (fasting status × time) as fixed effects. A random intercept was specified for each participant to account for repeated measurements within individuals. β coefficients represent estimated changes in blood pressure associated with each predictor
CI Confidence intervals indicate 95% confidence intervals, SBP Systolic blood pressure, DBP Diastolic blood pressure
Hourly blood pressure patterns
The circadian variation of systolic and diastolic blood pressure during fasting and non-fasting periods is illustrated in Fig. 4. Hourly mixed-effects regression analysis identified significant increases in blood pressure beginning at 04:00 compared with the reference time (00:00). At 04:00, systolic blood pressure increased by 7.74 mmHg (β = 7.736, 95% CI 2.083–13.389; p = 0.007), and diastolic blood pressure increased by 8.26 mmHg (β = 8.255, 95% CI 3.820–12.690; p < 0.001).
Fig. 4.
Circadian variation of systolic and diastolic blood pressure during fasting and non-fasting periods. Hourly mean systolic and diastolic blood pressure values measured by ambulatory blood pressure monitoring are presented for fasting and non-fasting periods. Solid lines represent mean values, and shaded areas represent bootstrap-derived 95% confidence intervals. Systolic blood pressure is shown in red tones and diastolic blood pressure in blue tones. The gray shaded region indicates daytime hours (06:00–19:00). This figure illustrates the circadian pattern of blood pressure across the 24-hour monitoring period
Blood pressure elevations became more pronounced during daytime hours, particularly around midday and early afternoon. The largest increase in systolic blood pressure occurred at 15:00 (β = 19.908, 95% CI 13.872–25.943; p < 0.001), accompanied by a similar increase in diastolic blood pressure (β = 18.224, 95% CI 13.489–22.958; p < 0.001).
Significant elevations persisted during the afternoon and early evening hours (Table 4). The diurnal pattern of hourly differences between fasting and non-fasting periods is shown in Fig. 5, with the largest divergence occurring around 15:00.
Table 4.
Hourly mixed-effects linear regression model results for blood pressure
| Time (hour) | SBP β | 95% CI | p | DBP β | 95% CI | P value |
|---|---|---|---|---|---|---|
| 1 | -2.205 | -7.858, 3.448 | 0.445 | -1.082 | -5.517, 3.353 | 0.633 |
| 2 | 0.979 | -4.652, 6.611 | 0.733 | 1.375 | -3.043, 5.792 | 0.542 |
| 3 | 2.293 | -3.383, 7.969 | 0.428 | 1.370 | -3.083, 5.822 | 0.547 |
| 4 | 7.736 | 2.083, 13.389 | 0.007 | 8.255 | 3.820, 12.690 | < 0.001 |
| 5 | 7.991 | 2.267, 13.714 | 0.006 | 6.285 | 1.796, 10.775 | 0.006 |
| 6 | 1.579 | -4.097, 7.255 | 0.586 | 1.275 | -3.177, 5.728 | 0.575 |
| 7 | -3.838 | -9.492, 1.815 | 0.183 | -2.350 | -6.785, 2.085 | 0.299 |
| 8 | -4.293 | -9.946, 1.361 | 0.137 | -3.168 | -7.603, 1.267 | 0.161 |
| 9 | 2.005 | -3.694, 7.704 | 0.491 | 2.056 | -2.415, 6.527 | 0.367 |
| 10 | 4.389 | -1.265, 10.043 | 0.128 | 5.029 | 0.594, 9.464 | 0.026 |
| 11 | 6.769 | 1.021, 12.516 | 0.021 | 7.677 | 3.169, 12.186 | 0.001 |
| 12 | 8.938 | 3.262, 14.615 | 0.002 | 9.563 | 5.110, 14.016 | < 0.001 |
| 13 | 11.111 | 5.388, 16.834 | < 0.001 | 14.577 | 10.088, 19.067 | < 0.001 |
| 14 | 15.672 | 9.702, 21.643 | < 0.001 | 16.554 | 11.870, 21.238 | < 0.001 |
| 15 | 19.908 | 13.872, 25.943 | < 0.001 | 18.224 | 13.489, 22.958 | < 0.001 |
| 16 | 16.839 | 11.041, 22.638 | < 0.001 | 14.502 | 9.953, 19.051 | < 0.001 |
| 17 | 6.815 | 1.092, 12.538 | 0.020 | 10.039 | 5.550, 14.529 | < 0.001 |
| 18 | 8.874 | 3.151, 14.597 | 0.002 | 9.820 | 5.330, 14.309 | < 0.001 |
| 19 | 17.110 | 11.363, 22.858 | < 0.001 | 16.174 | 11.665, 20.682 | < 0.001 |
| 20 | 4.947 | -0.776, 10.670 | 0.090 | 9.359 | 4.870, 13.849 | < 0.001 |
| 21 | 2.590 | -3.042, 8.221 | 0.367 | 4.857 | 0.439, 9.275 | 0.031 |
| 22 | 1.998 | -3.725, 7.721 | 0.494 | 2.189 | -2.301, 6.679 | 0.339 |
| 23 | 2.008 | -3.624, 7.639 | 0.485 | 1.215 | -3.203, 5.633 | 0.590 |
Boldface indicates statistical significance (p < 0.05)
Results were obtained using linear mixed-effects regression models including fasting status, time (hour), and their interaction (fasting status × time) as fixed effects, with a random intercept specified for each participant to account for repeated measurements within individuals. Analyses were performed using combined fasting and non-fasting measurements. The hourly coefficients represent estimated differences relative to the reference time point (00:00) within the reference condition (fasting)
CI Confidence interval, SBP Systolic blood pressure, DBP Diastolic blood pressure
Fig. 5.
Hourly difference in blood pressure between fasting and non-fasting periods (Δ blood pressure). The figure shows the hourly mean difference in systolic and diastolic blood pressure calculated as fasting minus non-fasting values. Circles represent systolic blood pressure differences and squares represent diastolic blood pressure differences. Red and blue shaded areas represent bootstrap-derived 95% confidence intervals around the mean differences. Positive values indicate higher blood pressure during fasting, whereas negative values indicate higher values during the non-fasting period. Statistical inference was based on bootstrap-derived 95% confidence intervals. The yellow shaded region highlights the daytime interval between 06:00 and 19:00 hours. The horizontal dashed line represents zero difference. Confidence intervals not crossing zero indicate statistically significant differences at the corresponding time points
Discussion
The present study evaluated the effects of Ramadan fasting on ambulatory blood pressure patterns, hydration status, mobility, and fall risk in adults aged 80 years and older. The principal finding was that fasting was associated with statistically significant increases in ambulatory blood pressure and higher fall risk scores. However, the observed effect sizes for blood pressure parameters were small (Cohen’s dz ranging from 0.24 to 0.34), whereas the increase in fall risk score demonstrated a moderate effect size (dz = 0.52). Hydration status and functional mobility remained largely unchanged. Importantly, this study contributes to the limited body of evidence regarding the physiological effects of Ramadan fasting in the ‘oldest old,’ a population that has been underrepresented in previous research [1, 2].
One of the most notable findings of this study was the increase in ambulatory blood pressure during the fasting period. Both 24-hour systolic and diastolic blood pressure values were slightly but significantly higher during Ramadan compared with the non-fasting period. Although paired comparisons demonstrated small increases in mean ambulatory blood pressure, mixed-effects models accounting for hourly variation did not reveal a statistically significant overall effect of fasting, suggesting that circadian variability may partly explain the observed differences. Previous studies have reported heterogeneous findings, particularly among younger or middle-aged populations [8–12], whereas evidence in very elderly individuals remains limited. Age-related physiological alterations—including increased arterial stiffness, impaired baroreflex sensitivity, and altered autonomic regulation—may predispose older adults to greater hemodynamic variability during prolonged fasting [3–5]. In this context, the higher ambulatory blood pressure values observed in the present study may reflect reduced cardiovascular adaptive capacity. Although the observed increases were statistically significant, their absolute magnitude and effect sizes were limited and should be interpreted cautiously in terms of clinical relevance, particularly given the substantial inter-individual variability.
Several physiological mechanisms may explain the observed increase in ambulatory blood pressure during fasting in very elderly individuals. Aging is associated with increased arterial stiffness, reduced baroreflex sensitivity, and impaired autonomic regulation, all of which contribute to diminished cardiovascular adaptability [3–5]. In the context of prolonged daytime fasting, these age-related changes may interact with additional stressors such as relative dehydration, circadian disruption, and neurohormonal alterations [8, 11]. Reduced plasma volume and increased sympathetic activity during prolonged fasting hours may lead to transient elevations in vascular tone and blood pressure. Furthermore, disruption of the normal diurnal pattern of food intake and sleep may influence circadian blood pressure regulation, potentially amplifying daytime variability [9, 12]. In very elderly individuals, who already exhibit attenuated physiological reserve, these combined effects may result in a more pronounced hemodynamic response compared with younger populations. These mechanisms are likely to be particularly relevant in the “oldest old,” in whom reduced physiological reserve may limit compensatory responses to fasting-related stressors.
Interestingly, hourly analysis demonstrated that divergence between fasting and non-fasting blood pressure values became more pronounced during the afternoon, peaking around 15:00. This pattern likely reflects the cumulative physiological effects of prolonged fasting. As fasting duration progresses, relative dehydration, autonomic fluctuations, fatigue, and altered medication timing may interact to influence cardiovascular regulation. In very elderly individuals—who often exhibit diminished physiological reserve—such circadian hemodynamic fluctuations may be more pronounced [3, 4].
Despite prolonged daytime fasting, no significant differences were observed in hydration parameters. Although dehydration is often considered a risk during Ramadan, particularly in older adults [14, 15], previous research suggests that many individuals compensate through increased fluid intake during non-fasting hours [8]. The present findings support this adaptive hypothesis, suggesting that dehydration may not be inevitable among community-dwelling older adults capable of completing the fasting period.
Another notable observation was a statistically significant increase in fall risk scores during fasting; however, the absolute difference between periods was small (mean difference 0.44 points on a 19-point scale). Falls are a major cause of morbidity and loss of independence in older adults [17–19]. Even modest increases in fall risk may therefore have clinically meaningful implications.
An additional explanation for this finding may relate to blood pressure variability. Although mean ambulatory blood pressure was modestly higher during fasting, hourly analyses demonstrated substantial circadian fluctuations. Increased short-term blood pressure variability has been associated with impaired cerebral perfusion and hemodynamic instability in older adults, which may contribute to dizziness and fall risk [25]. Transient declines in blood pressure on a background of greater hemodynamic variability may contribute to instability and fall risk, even when mean values are elevated. The absence of formal variability indices represents a limitation and warrants further investigation.
From a clinical perspective, these findings highlight the importance of individualized assessment when advising very elderly individuals about Ramadan fasting. Although fasting appeared generally tolerated, the observed increases in ambulatory blood pressure and fall risk suggest that careful monitoring is warranted. Clinicians should consider cardiovascular stability, medication timing, and fall risk when counseling patients. These findings should be interpreted within the context of an observational design and modest effect sizes, which may limit their clinical generalizability and warrant cautious interpretation.
Clinical implications
From a primary care perspective, these findings have several practical implications. Family physicians are often the first point of contact for older adults seeking advice regarding Ramadan fasting, yet guidance remains limited. Even in relatively well-functioning individuals aged ≥ 80 years, fasting may be associated with modest increases in ambulatory blood pressure and measurable increases in fall risk. Clinicians should therefore consider individualized pre-fasting assessment, including cardiovascular status, comorbidities, and functional capacity. Particular attention should be given to antihypertensive medication timing, which may require adjustment to avoid excessive daytime fluctuations. In addition, proactive fall risk assessment and counseling on hydration, safe mobility, and warning symptoms such as dizziness or presyncope are recommended. Periodic monitoring during Ramadan—either through home measurements or ambulatory monitoring in selected cases—may be beneficial.
Several limitations should be acknowledged. The sample size was modest and derived from a single community-based population, which may limit generalizability. Participants who were able to fast at advanced ages may represent a healthier subgroup, introducing potential selection bias. Although hydration was assessed using osmolality measures, additional biomarkers and orthostatic assessments were not included. Medication timing was not standardized and may have influenced results. Fasting adherence was not objectively verified, introducing potential misclassification bias. Although each participant served as their own control, the absence of a parallel non-fasting control group may limit the ability to account for temporal or seasonal effects. Finally, the observational design precludes causal inference.
In conclusion, Ramadan fasting in adults aged ≥ 80 years was associated with small effect-size increases in ambulatory blood pressure (dz = 0.24–0.34) and a moderate effect-size increase in fall risk score (dz = 0.52), while hydration status and functional mobility remained largely unchanged. These findings suggest that fasting may be tolerated in some very elderly individuals, but careful clinical evaluation and individualized guidance are essential when advising very elderly individuals about fasting.
Acknowledgements
Not applicable.
Abbreviations
- ABPM
Ambulatory Blood Pressure Monitoring
- ACE
Angiotensin-Converting Enzyme
- ADL
Activities of Daily Living
- BMI
Body Mass Index
- BP
Blood Pressure
- CI
Confidence Interval
- DBP
Diastolic Blood Pressure
- DST
Dehydration Screening Tool
- FTSTS
Five-Times Sit-to-Stand Test
- SBP
Systolic Blood Pressure
- SD
Standard Deviation
- TUG
Timed Up and Go Test
Authors’ contributions
Conceptualization: R.B., H.D. Methodology: R.B., H.D. Data curation: R.B., T.Ö.B., E.Y. Formal analysis: R.B., H.D. Investigation: R.B., T.Ö.B., E.Y. Supervision: H.D. Writing – original draft: R.B., H.D. Writing – review & editing: H.D. All authors have read and approved the final version of the manuscript.
Funding
The authors received no financial support for the research, authorship, and/or publication of this article.
Data availability
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
The study protocol was approved by the local ethics committee of Bursa Yüksek İhtisas Training and Research Hospital. All procedures performed in studies involving human participants were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. Written informed consent was obtained from all participants.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.