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ORIGINAL ARTICLE
Year : 2013  |  Volume : 3  |  Issue : 4  |  Page : 375-382

Effect of Coptic Orthodox Christian church fasting on healthy and diabetic subjects


1 Department of Biochemistry, Faculty of Science, Ain Shams University, Cairo, Egypt
2 Department of Clinical and Chemical Pathology, El-Mataria Teaching Hospital, Cairo, Egypt

Date of Submission05-Jun-2013
Date of Acceptance19-Jul-2013
Date of Web Publication15-Oct-2013

Correspondence Address:
Nadia Y. S. Morcos
20 Qubba Street, Heliopolis 11413, Cairo
Egypt
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2231-0738.119853

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   Abstract 

Background and Aim: Coptic Orthodox Christian (COC) diet is unique in that it regularly interchanges between an omnivorous to a vegetarian type of diet, through four fasting periods over the course of the ecclesiastical year. Several studies have described its dietary regulations, however, its possible involvement in health is lacking. The aim of the present study is to detect the metabolic changes during COC fasting. Subjects and Methods: Seventy two devout Orthodox Christian fasters, 25 of whom were diabetics and 40 matched controls, of whom 10 were diabetics, voluntarily participated in this study. A total of 240 blood samples were taken after at least 2 weeks before and during the different fasting periods. The fasting schedule was identified as either vegan (no sea food) or vegetarian (with sea food). Serum glucose (Glu), lipid profile, renal markers and hepatic enzymes, were measured and their within-subject biological variation was calculated. Results: The within-subject biological change due to fasting differed among subjects of the same group, gender and diet. Still, generally healthy subjects showed a decrease in Glu, triglycerides (TG) and TG/ high-density lipoprotein while the diabetics had a decline in blood urea nitrogen (BUN), BUN/creatinine ratio and uric acid. Conclusion: The effect of fasting differs among subjects and we cannot generalize its effect on all people. The strong individuality observed supports the preferential use of within-subjects biological variations and the reference change values rather than population-based reference intervals.

Keywords: Diets, intra-individual variation, serum lipids, uric acid


How to cite this article:
Morcos NY, Seoudi DM, Kamel I, Youssef MM. Effect of Coptic Orthodox Christian church fasting on healthy and diabetic subjects. Int J Nutr Pharmacol Neurol Dis 2013;3:375-82

How to cite this URL:
Morcos NY, Seoudi DM, Kamel I, Youssef MM. Effect of Coptic Orthodox Christian church fasting on healthy and diabetic subjects. Int J Nutr Pharmacol Neurol Dis [serial online] 2013 [cited 2018 Oct 17];3:375-82. Available from: http://www.ijnpnd.com/text.asp?2013/3/4/375/119853


   Introduction Top


Accelerated changes are taking place in the food habits of the present day Egyptians. Examples are drawn from foods that continue to be consumed by those considered guardians of the Egyptian tradition (Coptic Christians and isolated farming communities) and from interpretation of archaeological evidence. [1] Recent decades have witnessed the progressive erosion of the traditional Egyptian diet and the introduction of new foods and eating habits. Sociocultural and economic changes are accelerating this erosion. [2] The foods consumed during the fasts that are observed for about two-thirds of the year are derived with cereals, legumes, vegetables, green leafy vegetables and fruits. Given their pre-Christian origin, these foods are eaten by all Egyptians, though to a lesser extent by those urban dwellers who have adopted imported food habits. [1]

Fasting is defined as a partial or total abstention from all foods or a select abstention from prohibited foods. As a potential non-pharmacological intervention for improving health and increasing longevity, fasting has been the subject of numerous scientific investigations. [3]

The Coptic Orthodox Christian (COC) dietary regulations are an important component of the Mediterranean diet of Egypt, which is close to the Greek Orthodox Christian (GOC) diets, but low in some of its constituents, mainly olive oil and nuts, on the other hand, it is rich in whole-grain brown bread ( Egyptian pita bread), beans (Fava beans) and sesame (as "tahini" and "helva" made from a paste of sesame seeds). The four major fasting periods are: Christmas (40 days, with sea food), lent (48 days, without sea food), apostles' fast (varies from 15 to 49 days without sea food) and assumption (15 days, with sea food). The dietary pattern is unique in that it regularly interchanges between an omnivorous to a vegetarian (with sea food) or vegan (without sea food) type of diet over the course of the ecclesiastical year [3] and its potential implication on Egyptian's health has not been yet investigated.

Most studies on GOC have reported a decreased caloric intake during the fasting periods, [4],[5] which may result in lowered body mass. Percentage wise, carbohydrate intake appears to increase while both protein and fat intake decrease. Both saturated fat and trans-fatty acid consumption appear to decrease during fasting periods while both monounsaturated and polyunsaturated fat consumption do not change. [6],[7] The Mediterranean diet is ranked as the most likely dietary model to provide protection against coronary heart disease, where no diet-related adverse effects were reported. [8]

Clinicians are often faced with the problem and may accost the laboratory with "is this change in result a "real" change in a patient or is it simply a reflection of "noise" in the assay?" Within the last few years, the field-personalized medicine entered the stage answering this question. It offers the opportunity to improve our ability to diagnose and predict disease, provide earlier intervention and identify new treatment regimens. [9],[10] Biological variation of quantities examined in laboratory medicine can be described as of three types, namely; variation over the span of life, predictable cyclical variation that can be daily, monthly or seasonal in nature and random variation. [11],[12],[13] There is a subtle variation affecting all analytes, which consists of random fluctuation around the setting point of each individual, known as the within-subject or intra-individual biological variation (CV i ). Each person's setting point may be different from another's and the overall variation resulting from this difference is known as between-subject or interindividual biological variation. Using the CV i data is the best way to detect changes in a patient's health status through a comparison between serial analytical results rather than comparison with population based reference values. This is because of the marked individuality of the majority of analytes. [12] Hence, values obtained in consecutive analyses of samples from a patient may fall within the reference range, but show a considerable difference. When the difference exceeds a certain value, known as the reference change value (RCV), a change in the patient's condition is indicated. [11],[12],[13] A comprehensive database constituted from biological variation data of nearly 320 analytes, in health and disease, which is updated every 2 years serves as a useful reference for many clinical laboratories and is available at Westgard. [14]


   Subjects and Methods Top


Seventy-two devout Egyptian Orthodox Christian fasters (44 men; 28 women) were enrolled in this study. The mean age of subjects was 47.9 ± 1.2 years. Forty-seven fasters were healthy (25 men; 22 women), twenty-five had a diagnosis of well-controlled type II diabetes and used oral hypoglycemic agents (19 men; 6 women). Forty matching non-fasters, Muslims and Christians voluntarily participated in this study (28 men; 12 women) and served as controls. Their mean age was 46 ± 2.1 years, 30 of them were healthy (18 men; 7 women) and 10 were diabetic (8 men; 2 women).

No restrictions were placed on subjects regarding body mass for enrollment. Collectively, subjects were relatively healthy, active men and women. Prior to participation, each subject was informed of the benefits associated with the study. It is important to note that subjects purchased and prepared their own food. The outcome variables described below were measured in a total of 240 blood samples collected from the non-fasting periods (at least 2 weeks) (pre-fasting) and during fasting for 2-12 weeks (fasting). The type of fast (with or without seafood) was recorded. All blood collections were carried out in the morning hours in a 12 h fasted state. [Table 1] represents the baseline characteristics of the study population.
Table 1: Characteristics of subjects

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Parameters studied included: Glucose (Glu), total-, high density- and low density-cholesterol (T. Chol; high-density lipoprotein (HDL); Low-density lipoprotein (LDL)), triglycerides (TG), blood urea nitrogen (BUN), creatinine (Crea), uric acid (UA) and liver enzymes aspartate aminotransferase (AST) and alanine aminotransferase (ALT). Analyses were carried by commercial kits.

Statistical analysis

Statistical analysis was performed using the Statistical Package of Social Science version 17. Data was presented as mean ± standard error of the mean. The study design and complex aim call for different ways of statistical analysis that allow to compare not only effects of fasting, but also to compare effects with respect to the baseline of each subject individually.

The corresponding parameters in the groups (healthy and diabetics from fasters and controls) were compared by means of a one-way analysis of variance (ANOVA) test followed by least significant difference multiple range-test to find intergroup significance. Results were then compared with their own baseline values (paired tests). Because non-normal distribution was found for most of the analytes, results were assessed by Wilcoxon ranked-pairs test. The level of statistical significance was set at P < 0.05.

The RCV, defined as the critical differences that must be exceeded between two sequential results for a significant (or true) change to occur [15] were calculated according to Ricos et al.[13] and Westgard [14] (for healthy subjects) and Hölzel [16] (for diabetics).


   Results Top


Different results were attained according to the intention of the statistical analyses. Comparisons between all fasting and non-fasting samples (healthy and diabetics) and control subjects were performed by ANOVA [Table 2]. In the non-fasting state, the diabetic group showed higher Glu and a lower HDL values compared with the healthy group. UA level was higher in diabetics than both healthy and control groups. No other significant differences were observed.
Table 2: Descriptive data before and after fast for healthy and diabetic subjects compared to control

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Comparing results in the fasting state with those of the pre-fasting period were assessed by Wilcoxon ranked-pairs test. Fewer samples were analyzed, due to the decrease in the number of participants who followed-up before and during the same fasting period [Table 3]. Results differed between healthy and diabetic subjects. Fasting in healthy participants caused a significant decrease in blood Glu, TG, TG/HDL (P < 0.01) and T. Chol/HDL (P < 0.05). In diabetics, fasting caused a decrease in BUN, BUN/Crea and UA (P < 0.05).
Table 3: Descriptive data of healthy and diabetic subjects before and after fast (paired samples)

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Using the within-subject or CV i data calculated from the RCVs (RCV, % of the median) is the best way to detect changes in a patient's health status. Results revealed considerable differences that exceeded the RCV, better or worse, in both group genders and diets. [Figure 1] and [Table 4] illustrate the changes in each group, where the RCV % value is displayed next to each analyte. In general, LDL improved (decreased by 8.3% of the median) in 50% of participants of both groups and genders and was better in those on a vegetarian diet (75%). Glu (RCV = 5.7% for healthy and 30% for diabetics), cholesterol (RCV = 6% and 7.3% for healthy and diabetics) and TG (RCV = 21%) levels were improved in 71.4%, 62.5% and 64.7% healthy individuals respectively, corresponding to 22.2%, 27.3% and 30% of the diabetics respectively. A worse change (increase) in T. Chol was observed in 54.5% diabetics and in 25% healthy subjects. Gender-wise, 62.5%, 66.7% and 55.6% of the healthy males showed improved Glu, cholesterol and TG levels, compared with 83.3%, 57.3% and 75% in healthy females respectively. Meanwhile, 42.9% of the females had a worse change in their T. Chol, compared with only 11.1% of males. In healthy fasters, the improvement in these markers was enhanced with the vegetarian diet compared with the vegan one, where 75%, 80% and 80% on a vegetarian diet versus 70% 54.5% and 58.3% on vegan fast showed a critical decrease in their Glu, T. Chol and TG levels respectively. An increase in LDL level was observed only in fasters on the vegan diet (75%).
Figure 1: Within-individual changes (better or worse) after fasting in healthy and diabetic subjects calculated from the RCV% values for each analyte in both groups. Bars represent the % of subjects in each category. The RCV value is given next to each analyte according to Ricos et al. (2009)[13] and Westgard (2012)[14] (for healthy subjects), and Hölzel (1987)[16] (for diabetics)

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Table 4: Effect of gender, diet and fasting days on the within-individual changes (better or worse), after fasting in healthy subjects, presented as % subjects, calculated from RCV % values for each analyte according to Ricos et al.[13] and Westgard[14]

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The CV i in renal and liver markers differed within groups, genders and diets. Crea level was worse in 66.7% diabetics (RCV = 7.4%). AST and ALT increased critically in 42.9% and 62.5% diabetics respectively versus 21.4% only from the healthy fasters. UA favorably decreased in 50% healthy (RCV = 8.6%) and 83.3% diabetic (RCV = 10.7%) fasters and in 58.3% of vegans versus 25% from the healthy fasters on vegetarian diets.


   Discussion Top


Findings from the present investigation, indicate that modifying dietary intake in accordance with COC fast (1) lowers blood Glu, TG, T. Chol/HDL and TG/HDL in healthy subjects, (2) lowers BUN, BUN/Crea and UA in diabetics, (3) the estimated within-subject biological change due to fasting differed among subjects of the same group, gender and diet and we cannot generalize the effect of fasting on all people and (4) as it is currently unknown what caused these variable outcomes, longer-term studies are needed to explore this line of inquiry. To the best our knowledge, this is the first scientific investigation on both; the possible involvement of COC fast on health and on using a within-individual approach to study the effect of Christian fasting on health.

Dietary intervention studies traditionally evaluate group responses and aim to identify the overall effect in the population studied. In contrast, our study analyzed the variance in the fasting challenge responses, using a within-individual approach, rather than a group approach. This approach may be useful for detecting subclinical metabolic dysfunctions and it could contribute to improved personalized nutrition management.

The present results, for total groups, differ coarsely from those reported with the Daniel Fast (DF) [17],[18] and the GOC fast. [4],[19],[20]

Clinical and epidemiological evidences have shown that during the DF and GOC fast both T. Chol and LDL cholesterol (LDL-C) levels decrease during fasting periods. [4],[17],[18],[19],[20] Conflicting results exist regarding HDL-cholesterol (HDL-C) levels, some reported a decrease, [4],[18] while others found no change. [19],[20] Similarly, the LDL/HDL ratio was reported to decrease in DF [18] while others reported no change in GOC. [4] Both DF and GOC fasts found no change in TG level. [4],[18] These studies also conveyed that fasting may or may not decrease blood Glu levels. [4],[18],[19],[20]

It is known that in human intervention studies the within-individual variability in body fluid metabolic profiles can easily dominate over the average response to the nutritional intervention; however, there is very limited knowledge on how the extensive human genetic variability influences these nutritional effects. [21],[22]

In the present study, the overall changes in T. Chol, HDL-C and LDL-C were non-significant, though, on the individual level, we found that cholesterol improved in 62.5% healthy individuals and in 27.3% of the diabetics. Furthermore, a worse change (increase) in T. Chol was observed in 54.5% diabetics and in 25% from the healthy subjects. Although LDL showed a slight non-significant increase in both healthy and diabetic groups, but on the individual level, we found that LDL was clinically improved in 50% of participants of both groups and genders and was better in 75% of those on a vegetarian diet. HDL, on the other hand was worse in 55.6% of the diabetics and 18.8% of the healthy subjects, parallel to improvement in 33% and 25% respectively.

TG and blood Glu levels were significantly lowered in the healthy group. Actually, 67% of the healthy subjects showed critical improvement in their TG, parallel to 30% of the diabetics, we noted that the improvement in diabetics was related to the fasting period. Statistical analysis revealed that 80% of the healthy fasters had Glu reduced in a clinically meaningful manner (−5.7% of the median), corresponding to only 22.2% from the diabetics (RCV = −30%).

Many dietitians consider the diet of plant origin consumed by vegans to be "lighter" and "more healthful" for the kidneys than the diet of both plant and animal origin consumed by omnivores. [23],[24],[25] This is because of the lower dietary protein intake (particularly meat), which decreases BUN and BUN: Crea ratio. [17],[23] The present findings agree with these conclusions only for the diabetic fasters. Although BUN was lowered to a clinically meaningful level in 54.5% of the healthy group, it was statistically insignificant. UA was significantly lowered in the diabetics at the inter- and intra-individual level, where 80% had a critical decrease. Since the serum UA is associated to cardiovascular disease, metabolic syndrome and chronic kidney disease, [26],[27] its significant decrease in diabetic fasters necessitates further investigations.

The conflicting results between the different studies, including the present one, could be attributed to differences in the amount and ratio between carbohydrates, fats and unsaturated fats in the fasting diets. [28] Differences could also be attributed to the type and constituents of the diets, mainly their plant sterols and stanols (PS) levels. [29] Egyptians in general, due to traditional and economic reasons, consume much less quantities from olive oil and nuts, which are the main constituents of the GOC fast and the Mediterranean diets. Both constituents are known to reduce the incidence of major cardiovascular events through their lowering effect on T. Chol, LDL and the LDL/HDL ratio. [8],[30],[31] Alternatively, Egyptian food is rich in brown whole-grain pita (baladi) bread, beans (fava beans) and sesame seeds (as "tahini" and "helva" (halva) that are made from a paste of sesame seeds). Long-term cohort studies have indicated that whole-grain consumption reduces the risk of developing renal disease in type 2. [32] Faba beans (vicia faba) were reported to act as a carbohydrate absorption blockers, [33] have lipid-lowering effects [34] and might be of value in treating conditions such as hypertension, heart failure, renal failure and liver cirrhosis. [35] Sesame, on the other hand, is known to reduce T. Chol, LDL-C and TG levels and ameliorate renal dysfunction in healthy and diabetic subjects. [36],[37],[38],[39] The nutritive values and synergism of these dietary constituents could explain some of the health benefits observed in the Egyptian Christian fasters.


   Conclusion Top


Effect of fasting differs among subjects and we cannot generalize its effect on all people. Generally, COC fasting diets are healthful and are associated with lower risk of cardiovascular diseases. More research remains to be performed on biochemical variables during fasting periods due to both the lack of previous research and the inconclusive findings. Furthermore, future studies should examine each of the four principal fasting periods both separately and aggregately, because each fasting period has unique food proscriptions and durations.

 
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    Figures

  [Figure 1]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4]


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