The metabolic syndrome (MetS) is specified by clustering of cardiometabolic events, such as hyperglycaemia/insulin resistance, abdominal obesity and dyslipidaemia(Reference Alberti, Eckel and Grundy1,Reference Huang2) . Globally, the prevalence of the MetS is indicated between 14 and 32 % in men and women, and this trend will be increasing with expanded life expectancy(Reference Obeidat, Ahmad and Haddad3). Estimations indicated that one-third of Iranians over the age of 20 years suffered from the MetS between 2000 and 2016(Reference Kalan Farmanfarma, Kaykhaei and Adineh4), which is much greater than the incidence in other countries like Japan (5·3 %)(Reference Urashima, Wada and Fukumoto5) and the USA (22·9 %)(Reference Beltrán-Sánchez, Harhay and Harhay6). Also, individuals with the MetS are at twice the risk of developing cardiovascular events during the coming 5–10 years than those without. Moreover, the MetS confers a five times increase in the incidence of type 2 diabetes(Reference Alberti, Eckel and Grundy1,Reference Virani, Alonso and Benjamin7) . Furthermore, a growing body of evidence indicated fasting and eating patterns (involving nightly fasting duration, meal timing and frequency) affect cardiometabolic health(Reference Patterson and Sears8,Reference St-Onge, Ard and Baskin9) .
Human metabolism is highly regulated by internal body clocks (circadian rhythms), which are nearly 24 h long(Reference Panda10). Hence, proper functioning of internal body clocks is important for keeping metabolic health(Reference Zimmet, Alberti and Stern11). Consuming meals irregularly, defined as consuming food in different amounts during the day and at different times from one day to another, could affect the circadian rhythms, which is unfavourably linked with cardiometabolic disease risk, such as the MetS or type 2 diabetes(Reference Pot, Almoosawi and Stephen12).
In addition, numerous studies demonstrated that meal timing(Reference Baron, Reid and Kern13–Reference Bandin, Scheer and Luque15) and nightly fasting duration (24 h minus mealtime interval between the first and last meal for each day)(Reference Makarem, Sears and St-Onge16) significantly affect weight gain and obesity. Also, higher meal frequency is positively linked with improving body composition, including increased fat-free mass, as well as decreased fat mass and body fat percentage, which is suggested to be related to cardiometabolic health(Reference Jon Schoenfeld, Albert Aragon and Krieger17). Marinac et al. in a study of 2212 women in the USA indicated that a longer nightly fasting duration was related to lower HbA1c and cardiometabolic factors(Reference Marinac, Natarajan and Sears18). However, a study in 1054 non-shift workers in Japan showed that there was no consistent connection between nightly fasting duration and the MetS(Reference Ueda, Inoue and Hu19). A study in 116 US women, aged 20–64 years, showed that earlier meal timing and more frequent eating could lead to lower cardiometabolic events. Additionally, adverse effects were seen in individuals with longer nightly fasting duration(Reference Makarem, Sears and St-Onge16). Another study in 14 279 Korean adults showed an inverse association between eating frequency and the MetS components in men subjects only(Reference Ha and Song20). Due to cultural differences related to time-related eating patterns and a great incidence of the MetS in Iran and a limited number of inconclusive studies, we sought to explore the relationship between nightly fasting duration, meal timing and frequency with the MetS in Iranian adults.
Methods
Design and study population
Subjects for this cross-sectional study were adults selected from health houses in Tehran, Iran. Eight hundred fifty adults aged 20–59 years were selected by the two-stage cluster sampling method, from five districts of the Tehran province, including North, South, West and East, and the urban core. The subjects were randomly chosen from five districts (forty health houses), and then the number of subjects in each centre was obtained in the following manner: total sample size (850)/the number of health houses (40). Eligible criteria was 20–59 years, willing to participate, with no specific health issues, living in Tehran and be a member of health houses. Those who had cancer, chronic kidney and liver disease, rheumatoid arthritis, Parkinson’s and any other chronic health issues, and pregnant or lactating people and those with under- or over-reporting food intake (< 191·20 KJ/d or > 1003·82 KJ/d) were excluded(Reference Esmaillzadeh and Azadbakht21,Reference Fung, Hu and Pereira22) . Finally, 850 participants (266 men and 584 women) were added to the analysis.
The study protocol was confirmed by the Medical Ethics Committee of the Tehran University of Medical Sciences, Tehran, Iran (Ethic number: IR.TUMS.MEDICINE.REC.1399.797). The written informed agreement was acquired by all individuals who involved in this study.
Demographic data
Participant’s age, sex (men/women), education (illiterate, under diploma, diploma and educated) and occupation (employed, housekeeper, retired and unemployed) status, marital status (single/married/divorced), smoking status (non-smoker/smoker), having CVD (yes/no), menopause (yes/no) and diabetes (yes/no) were completed using a standard questionnaire.
Physical activity
Physical activity was evaluated by applying the International Physical Activity Questionnaire(Reference Moghaddam, Aghdam and Jafarabadi23). Individuals were categorised into three groups, comprising very low (< 600 metabolic equivalent-min/week), low (600–3000 metabolic equivalent-m/week) and moderate and high (> 3000 metabolic equivalent-min/week), assessed on the basis of metabolic equivalents(Reference Wareham, Jakes and Rennie24).
Anthropometric measures and blood pressure
Before the assessment, all the anthropometric instruments were calibrated. Weight was assessed with an accuracy of 0·1 kg and minimal clothing without shoes, applying a digital scale (Seca 808). Height was assessed with a precision of 0·1 cm, in the stand-up state, unshod, applying a stadiometer (Seca 206). BMI was assessed as weight (kg)/height2 (m2). Waist circumference (WC) was assessed in the middle of lower rib and iliac crest, with light clothing, applying a tape meter (Seca 201)(Reference Kouchi25). All the anthropometric measures were carried out two times and the average of them was reported.
Blood pressure (BP) was measured twice, applying a digital sphygmomanometer (BC 08, Beurer), in a sitting position after 10–15 min of rest. The average of its measurement was recorded.
Laboratory investigation
All subjects were given 10 ml of fasting blood between 07.00 and 10.00 hours. Accordingly, acid-washed test tubes (with no anticoagulants) were used for collecting blood samples. Then, after clot formation by storing the blood samples for 30 min at room temperature, samples of blood were centrifuged for about 20 min. For future testing, we stored serums at −80°C. The enzymatic (glucose oxidase) colorimetric approach applying a commercial kit (Pars Azmun) was adopted for measuring fasting blood glucose (FBG). In addition, cholesterol oxidase phenol aminoantipyrine and glycerol-3 phosphate oxidase phenol aminoantipyrine enzymatic approaches were applied to assess serum total cholesterol and HDL-cholesterol, and TAG, respectively.
Dietary assessment
Dietary data were collected by a trained dietitian using three non-consecutive days (two weekdays and one weekend day) 24-h dietary recalls. The initial 24-h recall is collected via interviews, and another two recalls are documented by using the telephone during this study. Food and food groups were also extracted from these questionnaires(Reference Subar, Kipnis and Troiano26). Then, an individual’s nutrients intake was analysed by Nutritionist IV software.
Meal timing
Frequency of eating was evaluated as the eating occasions number reported each day, explained as food or beverage consumption of 1 kcal or more (to remove water drinking and yet recognise all other time-related eating patterns) at a single point in time(Reference Srour, Plancoulaine and Andreeva27). First and last meal eating times (time and energy proportion) reported each day, explained as consuming 25 kcal or more(Reference Marinac, Nelson and Breen28,Reference Marinac, Sears and Natarajan29) . Nightly fasting duration was calculated as 24 h minus mealtime interval between the first and last meal for each day(Reference Marinac, Natarajan and Sears18,Reference Marinac, Nelson and Breen28) , the average nightly fasting duration across 3 d was computed and the first eating occasion defined as eating occurred from 05.00 hour, since no eating was recorded from 12.00 to 05.00 hours. The first meal was described as the first eating occasion after waking and the last meal was described as the last eating occasion prior to sleep(Reference Gill and Panda30). Late night eating was regarded as eating after 21.00 hour. We classified individuals into non-late night eaters if they ate less than 25 % of total energy intake > 21.00 hour and late night eaters if they ate at least 25 % of their total energy intake > 21.00 hour, according to the night eating syndrome definition(Reference Allison, Lundgren and O'Reardon31). Early morning eating was regarded as eating from 05.00 to 09.00 hours. By applying the estimated value of the top quartile for a percentage of energy intake in the morning (25 %), we classified individuals as non-early morning eaters if they ate less than 25 % of their total energy intake from 05.00 to 09.00 hours and early morning eaters if they ate at least 25 % of their total energy content intake from 05.00 to 09.00 hours(Reference Ha and Song20).
Definition of the metabolic syndrome
On the basis of National Cholesterol Education Program Adult Treatment Panel III criteria(Reference Grundy, Cleeman and Daniels32), without considering WC(Reference Heshmat, Khashayar and Meybodi33), the MetS was diagnosed in individuals who had at least three of the following medical conditions: (1) WC ( ≥ 99·5 cm in men and ≥ 94·25 cm in women); (2) decreased HDL-cholesterol (< 40 mg/dl in men and < 50 mg/dl in women); (3) increased BP (systolic blood pressure ≥ 130 mmHg or diastolic blood pressure ≥ 85 mmHg); (4) high levels of TAG (≥ 150 mg/dl) and (5) increased FBG (≥ 100 mg/dl)(Reference Alberti, Eckel and Grundy1).
Statistical analysis
Data on daily time-related eating patterns are provided as the averages from three dietary recalls for each participant. Generally, for all applicable variables, the averages are referred to as ‘habitual’. Moreover, each of the time-related eating patterns (time and energy proportion of first and last meal, meal frequency and nightly fasting duration) was treated in a separate model. Therefore, for each meal time variable, we considered the following confounders: age, energy intake, marital status, smoking, education, occupation, BMI (not including abdominal obesity) and physical activity. Moreover, in the model of energy intake throughout each time interval, the habitual early/late first meal (with the 09.00 hour cut-off and only for the habitual first meal), habitual early/late last meal (with the 21.00 hour cut-off and only for the habitual last meal) and habitual eating occasions were additionally confounder adjusted.
General characteristics of subjects in accordance with sex were evaluated by independent sample t test and χ 2 test for continuous and categorical variables, respectively. Binary logistic regression was conducted to obtain OR and 95 % CI for the MetS and its elements in accordance with habitual mealtime eating, frequency and nightly fasting duration. We determined confounders from the previous study(Reference Ha and Song20), without considering nightly fasting duration because last and first meal energy intake might be affected by the time of the last and first meal. Therefore, instead of adjusting for nightly fasting duration, we adjusted for early/late first meal (with the 09.00 hour cut-off) for the first meal analyses and for early/late last meal (with the 21.00 hour cut-off) for the last meal analyses to obtain more accurate results. Moreover, these confounders identified a correlation with the MetS and its components(Reference Al-Daghri, Alkharfy and Al-Attas34–Reference Zhang, Xue and Yao40).
We performed binary logistic regression in adjusted models for age, energy intake, marital status, smoking, education, occupation, BMI (not including abdominal obesity) and physical activity. Besides, in the model of energy intake throughout each time interval, the habitual early/late first meal (with the 09.00 hour cut-off and only for the habitual first meal), habitual early/late last meal (with the 21.00 hour cut-off and only for the habitual last meal) and habitual eating occasions were additionally adjusted. Habitual meal frequency was classified into two groups based on a median split (< 4 v. ≥ 4 times/d). Habitual nightly fasting duration was also classified into two groups based on the median split (< 11·25 v. ≥ 11·25 h). In this analysis, habitual eating occasions < 4 times/d, habitual nightly fasting duration < 11·25 h, habitual first meal and last meal energy < 25 % of total energy, habitual early first meal eating from 05.00 to 09.00 hours and habitual early last meal eating from 17.00 to 21.00 hours were considered as the reference groups. A P-value < 0·05 was considered statistical significance. We applied SPSS version 26 (IBM) for all analyses.
Results
The general characteristics of the study population, containing habitual meal timing, frequency and nightly fasting duration, are indicated in Table 1. The average and standard deviation age was 44·2 (sd 9·87) years in men and 44·5 (s d 11·0) years in women. The women were more likely to be employed (51·4% v. 48·6%) and be married (65·6% v. 34·4%) and were less likely to be a smoker (25·0% v. 75·0%) and have high WC (90·5 (sd 12·3) v. 95·3 (sd 12·0) cm) than men. Moreover, the women were more likely to have CVD (85·1% v. 14·9%) and the MetS (76·1% v. 23·9%) than men. Women consumed a higher total energy intake than men (P < 0·001). Moreover, the average habitual eating occasions per day were 4·13 (sd 0·81) and were greater in women than in men (P = 0·001). The mean habitual energy intake of first and last meals was 19·3 (sd 10·0) % and 23·3 (sd 11·5) %, respectively, and was greater in women than in men (all P < 0·001). The average habitual nightly fasting duration was 11·2 (sd 0·57) h and was greater in men compared with women, although this result was not significant. Of 850 participants, 310 individuals met our criteria for diagnosing the MetS (36·5%).
General characteristics of the study population (Mean values and standard deviations; numbers and percentages)
DBP, diastolic blood pressure; FBG, fasting blood glucose; MetS, metabolic syndrome; SBP, systolic blood pressure WC, waist circumference.
* Calculated by χ 2 and independent sample t test for qualitative and quantitative variables, respectively, and P-value < 0·05 indicates significant level.
The results of binary logistic regression indicating the OR and 95% CI for the MetS based on habitual nightly fasting duration, meal timing and frequency are indicated in Table 2. We found that longer habitual fasting duration was associated with lower prevalence of both the MetS (adjusted OR = 0·74, 95 % CI 0·55, 0·99, P = 0·04) and ‘increased TAG’ (adjusted OR = 0·73, 95 % CI 0·55, 0·98, P = 0·03). However, no consistent relations between the habitual eating occasions and habitual meal timing and the MetS and its elements were found after adjusting for age, energy intake, marital status, smoking, education, occupation, BMI (not including abdominal obesity) and physical activity (all P > 0·05). Re-analysing data by sex demonstrated that the longer habitual nightly fasting duration was associated with lower prevalence of both the MetS (adjusted OR = 0·50, 95 % CI 0·28, 0·88, P = 0·02) and ‘increased BP’ only in men (adjusted OR = 0·43, 95 % CI 0·22, 0·87, P = 0·02) (online Supplementary Table S1).
The metabolic syndrome based on habitual* nightly fasting duration, meal timing and frequency (Odds ratios and 95 % confidence intervals) †
FBG, fasting blood glucose; MetS, metabolic syndrome.
* This means that the exposure was averaged over all recalls.
† Calculated by logistic regression.
‡ Adjusted for age, energy intake, marital status, smoking, education, occupation, BMI (except for abdominal obesity) and physical activity.
§ P-value < 0·05 indicates significant level.
The results of binary logistic regression indicating the OR and 95 % CIs for the MetS based on habitual energy intake in the first and last meal are shown in Table 3. No consistent relations between habitual first and last meal energy intake and the MetS and its components were found after controlling for age, energy intake, marital status, smoking, education, occupation, BMI (except for abdominal obesity), early/late habitual first meal (with the 09.00 hour cut-off and only for the habitual first meal), early/late habitual last meal (with the 21.00 hour cut-off and only for the habitual last meal), habitual eating occasions and physical activity (all P > 0·05). However, the odds of ‘increased FBG’ were lower in subjects who consumed ≥ 25% of habitual energy intake in the last meal (adjusted OR = 0·60, 95 % CI 0·42, 0·85, P = 0·005). Re-analysing data by sex did not modify our findings. However, women who consumed ≥ 25% of habitual energy intake in the last meal had lower odds of ‘increased FBG’ (adjusted OR = 0·56, 95 % CI 0·36, 0·86, P = 0·009) (online Supplementary Table S2).
The metabolic syndrome based on habitual* energy intake in the first and last meal (Odds ratios and 95 % confidence intervals) †
FBG, fasting blood glucose; MetS, metabolic syndrome.
* This means that the exposure was averaged over all recalls.
† Calculated by logistic regression.
‡ Adjusted for age, energy intake, marital status, smoking, education, occupation, BMI (except for abdominal obesity), eating occasions and physical activity.
§ Adjusted for b + habitual early/late first meal (with the 09.00 hour cut-off).
|| Adjusted for b + habitual early/late last meal (with the 21.00 hour cut-off).
¶ P-value < 0·05 indicates significant level.
Discussion
In this cross-sectional study of 850 Iranian adults, longer habitual nightly fasting duration was related to lower prevalence of both the MetS and ‘elevated TAG’, but this association was not significant for other mealtime eating, that is, habitual meal timing and frequency were not related to the MetS and its components (including abdominal obesity, decreased HDL-cholesterol and increased BP, TAG and FBG). Furthermore, men with a longer habitual nightly fasting duration (≥ 11·25 h) indicated a lower chance of both the MetS and having high BP. Moreover, no significant association was seen between habitual first and last meal energy and the MetS. However, individuals who consumed ≥ 25 % of habitual energy intake in the last meal had a lower prevalence of ‘increased FBG’. This effect was seen in the stratified analyses to be driven by women.
Our findings were in line with previous studies in rodent models(Reference Patterson and Sears8) and US adults(Reference LeCheminant, Christenson and Bailey41,Reference Sutton, Beyl and Early42) , in which they indicated that more prolonged nightly fasting duration had preventive impacts towards cardiometabolic events. The findings from observational studies in Asian adults have shown results conflicting with those carried out in the USA, where Asian adults are quite under-represented(Reference Ueda, Inoue and Hu19,Reference Ha and Song20) . Ueda et al., in a survey of 1054 Japanese non-shift employees, indicated no consistent connection between nightly fasting duration and the MetS(Reference Ueda, Inoue and Hu19). However, a more prolonged nightly fasting duration (16 h compared with 10–12 h) might have adverse effects on cardiometabolic events in the Korean NHANES (average age: 41 years)(Reference Ha and Song20).
This discrepancy with previous studies might be due to different study populations, in which overnight fasting-related metabolic events may differ across racial and ethnic groups. Another reason for this discrepancy among studies might be due to differences in nightly fasting duration classification and definition. For example, our study defined nightly fasting duration based on the duration between the first and last meal, whereas another study defined nightly fasting duration based on the duration between breakfast and dinner(Reference Ueda, Inoue and Hu19). Moreover, we classified habitual nightly fasting duration into two groups based on the median split (< 11·25 v. ≥ 11·25 h), whereas other studies classified nightly fasting duration into four groups (≤ 9, 10, 11 or ≥ 12 h)(Reference Ueda, Inoue and Hu19) and five groups (< 8, 8–10, 10–12, 12–16 or ≥ 16 h)(Reference Ha and Song20).
In this study, habitual longer nightly fasting duration was related to lower prevalence of both the MetS and ‘increased BP’ in men. We could not totally explain why these significant relations were seen in men but not in women. However, men had lower habitual energy intake in the last meal than women, which might be related to other lifestyle behaviours, including low employment rate and marriage. These differences, together with endocrine factors, might impact cardiometabolic events(Reference Kautzky-Willer, Harreiter and Pacini43). In line with our findings, Sutton et al. indicated that 5 weeks early time-restricted feeding (6 h feeding period compared with 12 h feeding period) could significantly lower systolic blood pressure and diastolic blood pressure in men(Reference Sutton, Beyl and Early42), which might be explained by reducing insulin level and promoting natriuresis through altering salt intake to early time as Na excretion is up-regulated by internal body clock(Reference Johnston, Speed and Jin44).
We also indicated no significant relationships between habitual eating occasions and the MetS and its components. This was contrary to previous studies, which demonstrated that higher eating occasions were linked with a lower incidence of metabolic abnormalities among Korean men(Reference Ha and Song20). The findings of cross-sectional studies demonstrated that more eating occasions were related to a lower chance of having ‘increased BP’, obesity and abdominal obesity in US and European adults(Reference Ma, Bertone and Stanek45,Reference Holmbäck, Ericson and Gullberg46) . However, Murakami and Livingstone reported apposite findings in which a greater eating frequency was related to greater BMI and WC(Reference Murakami and Livingstone47). These discrepancies among findings might be due to methodological differences. For instance, our study and several studies assessed dietary intakes by the 24-h dietary recall(Reference Ha and Song20,Reference Ma, Bertone and Stanek45) , while some other studies assessed by 168-item dietary questionnaire(Reference Holmbäck, Ericson and Gullberg46) or 7-d dietary record(Reference Murakami and Livingstone47). In addition, the subjects in these studies were from different geographical areas.
We also did not find any consistent relationship between habitual timing and amount of eating and the MetS. In comparison, our study findings were opposed to other studies, which demonstrated that meal timing was related to obesity, diabetes, cardiometabolic and cardiovascular events(Reference St-Onge, Ard and Baskin9,Reference Ha and Song20,Reference Garaulet and Gómez-Abellán48) . A review study that analysed data from ten observational studies indicated that late-evening eating was related to higher BMI(Reference Fong, Caterson and Madigan49) by disturbing the circadian rhythms(Reference Patterson and Sears8). On the other hand, earlier first meal eating can be a protective factor against cardiometabolic events(Reference Makarem, Sears and St-Onge16). In addition, the results of two observational studies indicated a positive relation between evening or dinner energy intake and the MetS and obesity risks(Reference Summerbell, Moody and Shanks50–Reference Wang, Patterson and Ang52). Reid et al. indicated that higher energy intake in the breakfast was linked to higher weight loss than high energy intake during dinner(Reference Reid, Baron and Zee53).
In this study, we also showed that greater habitual energy intake (≥ 25 % of total energy intake) in the last meal was linked with a lower probability of ‘increased FBG’, and this relationship was independent of the time of the habitual last meal eating (early/late last meal). However, a study by Jakubowicz et al. indicated a greater glucose concentration after higher energy intake in the dinner (700 kcal) than higher energy intake in the breakfast (700 kcal) after 12 weeks of isoenergetic weight loss intervention (1400 kcal) among obese women with the MetS(Reference Jakubowicz, Barnea and Wainstein14). Other studies indicated that glucose tolerance and insulin sensitivity decline during the day with insulin sensitivity reaching the lowest level in the evening(Reference Lee, Ader and Bray54–Reference Van Cauter, Shapiro and Tillil56). These relations might explain why evening or night eating is related to weight gain or obesity(Reference Kant, Schatzkin and Ballard-Barbash57). Nevertheless, it is plausible that we underestimated the relation between habitual timing and amount of eating and cardiometabolic risks due to our dietary data collection that was based on three non-consecutive days, as the last meal of the previous day influences the first meal of the following day. Moreover, most of our participants were healthy adults, while other studies were conducted in high-risk populations (such as adults with the MetS and/or obesity)(Reference Jakubowicz, Barnea and Wainstein14,Reference Lee, Ader and Bray54) .
The strengths of our study include that our study sample size was sufficient, so it was possible to analyse data for both men and women separately. Adjusting for confounders was further strength of our study. Moreover, dietary data collection was based on three non-consecutive days. Hence, we could better capture within-person variation for all of the time-related eating patterns except for nightly fasting duration, as the last meal of the previous day influences the first meal of the following day. Also, several limitations should be outlined. The cross-section design of this study wards off any indication of causality among habitual meal timing and frequency and overnight fasting and the MetS. We used 24-h dietary recall for collecting individual’s dietary data, so recall bias is plausible. Finally, our participants did not have habitual nightly fasting duration ≥ 16 h that did not allow analysis data for a longer duration. Previous studies indicated the beneficial effects of longer nightly fasting duration (16 v. 10–12 h) on cardiometabolic events in the Korean NHANCE adults (average age: 41 years)(Reference Makarem, Sears and St-Onge16).
Conclusion
In summary, having longer nightly fasting duration may be useful for decreasing the risk of both the MetS and ‘elevated TAG’. However, no significant association was seen between habitual meal timing and frequency and the MetS. Also, habitual first and last meal energy had no significant connection with the MetS. However, individuals who consumed ≥ 25 % of habitual energy intake in the last meal had a lower prevalence of ‘increased FBG’. Considering the limitations of our study, further studies using dietary data on consecutive days with a longer duration are needed to explore the relationship between habitual meal timing and frequency and nightly fasting duration with the MetS.
Acknowledgements
We thank all participants of the study for their cooperation.
S. S. B. and K. D. contributed to the conceptual framework of the study. A. L., N. J. and M. M. collected the data. S. Z. M. performed the statistical analysis. S. Z. M. wrote the first draft of the manuscript. K. D. and S. S. B. critically revised the first draft. All of the authors are responsible for the final manuscript.
There are no competing interests to declare.
Supplementary material
For supplementary material referred to in this article, please visit https://doi.org/10.1017/S0007114521005079
