i Faculty of Health Sciences
A Systematic Review on the Effects of Alternate Day Fasting on Subjective Feelings of Appetite and Body Weight for Overweight and Obese Adults
Bahar Kucuk
Master’s Thesis in Public Health, HEL-3950 July 2021
Supervisor: Professor Rigmor C Berg, Norwegian Institute of Public Health
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ACKNOWLEDGEMENTS
It was a genuine pleasure to be an MPH student at UiT, The Arctic University of Norway, in Tromsø, this magical place.
I would like to express my sincere thanks and gratitude to my supervisor, Professor Rigmor C Berg, for her expert guidance, acceptance, patience, and kindness. I am grateful for her constructive criticisms during each step of my thesis process and I really appreciate her
generosity with her time. Her commitment, motivation, enthusiasm, and wisdom have been key components for completion of this thesis and have made this an inspiring experience for me.
I would also like to express my deep appreciation to the MPH program coordinators for bringing me together with highly talented academics. I would like to thank Dr. Eirik Reierth and Research Librarian Lien Nguyen for all the useful tips that they provided. I wish to extend my special thanks to my student advisor, Janne E. Strømmesen for her encouragement, time, and kindness.
I am very much grateful to my wonderful family especially my grandma and my little aunt Ceyhan.
I am also thankful to my great friends, but especially, Muho, my dear friend, for his unconditional and limitless love and support. I feel so lucky to have you in my life.
Last but not least, for my lovely dad and mom;
No word is enough to express my love and gratefulness towards you. Thank you for always being there for me, your constant kindness and encouragement. Thank you for the vision you gave and the path you paved. Without you, none of this would be possible. Your inspiration is going to be with me in every moment of my life.
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Key messages
ADF might lead to small changes in subjective feelings of appetite
ADF regimen might be an alternative to current dietary approaches for weight
management for overweight and obese adults
The heterogeneity and high risk of bias in the current evidence limit the capability to draw robust conclusions
Randomized, large-scale, longer duration studies with a control group are needed
ABSTRACT
Background: Feelings of appetite are known to have an important effect on adherence to dietary approaches. Therefore, it is related to the success
of dietary interventions for weight management for especially overweight and obese patients. Alternate day fasting (ADF), one of the most used
intermittent fasting regimens, is promoted as an alternative approach for treating obesity.
Objective: This systematic review aimed to assess the effects of ADF on subjective feelings of
appetite and body weight for overweight and obese adults.
Methods: I conducted this systematic review following the Cochrane Handbook for Systematic Reviews of Interventions. I performed an
electronic search in EMBASE, Medline, PsycInfo, and CINAHL. I identified additional records through Google scholar and reference lists of relevant studies. Because of the low number of included studies and high level of heterogeneity across the included studies, conducting meta- analyses was not possible. Hence, I used a narrative approach to synthesize the results. I evaluated the certainty of the body of evidence using the GRADE approach.
Results: With three randomized controlled trials and five uncontrolled before and after studies, a total of eight studies were included in the syntheses. I identified high clinical and methodological heterogeneity and I assessed high risk of bias in seven of the included eight studies. Feelings of appetite were assessed in the included studies by hunger, fullness, satisfaction, and desire to eat.
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Overall, with ADF less than six months, the eight included studies showed small a decrease or no change in hunger, small increases or no change in fullness and satisfaction, and a small decrease in desire to eat after the intervention compared to baseline. Additionally, the studies demonstrated small to moderate losses in body weight with ADF less than six months, compared to baseline.
The certainty of the evidence ranged from low to very low for the outcomes.
Conclusions: Although it is hard to draw robust conclusions because of the low quality of evidence, ADF of less than six months shows promise as an alternative approach for weight management for overweight and obese adults by its effects on subjective feelings of appetite and body weight. This systematic review highlights the need for further rigorous, large-scale, and long-term studies.
Keywords: alternate-day fasting, appetite, hunger, fullness, body weight, weight loss
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS iii
ABSTRACT v
TABLE OF CONTENTS vii
LIST OF TABLES x
LIST OF FIGURES xi
LIST OF ABBREVIATIONS xii
1. CHAPTER 1: INTRODUCTION 1
1.1. Description of the Condition 1
1.1.1. Overweight and obesity: definitions, prevalence, and consequences 1 1.2. Description of the intervention and how it might work 4 1.2.1. Intermittent fasting: definition, mechanism, and alternate day fasting 4
1.2.2. Psychobiological nature of appetite 9
1.3. Why is it important to do this review 13
1.3.1. Rationale for the study: relation between appetite regulation and weight
management with ADF approach 13
1.4. Objective 15
2. CHAPTER 2: METHODOLOGY 16
2.1. Criteria for considering studies for this review 16
2.1.1. Types of studies 16
2.1.2. Types of participants 16
2.1.3. Types of interventions 16
2.1.4. Types of comparisons 17
2.1.5. Types of outcome measures 17
2.1.5.1. Primary outcomes 17
2.1.5.2. Secondary outcomes 17
2.1.6. Other criteria 17
2.2. Search methods for identification of studies 18
2.3. Data collection and analysis 18
2.3.1. Selection of studies 18
2.3.2. Data extraction and management 19
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2.3.3. Assessment of methodological quality of included studies 19
2.4. Data synthesis 20
2.5. Assessment of the certainty of the evidence 21
3. CHAPTER 3: RESULTS 23
3.1. Stage 1: development of the theory of how the intervention works, why and for
whom 23
3.2. Stage 2: development of a preliminary synthesis of findings of included studies 23
3.2.1. Results of the literature search 23
3.2.2. Description of included studies 24
3.2.2.1. Design and Location 27
3.2.2.2. Population 27
3.2.2.3. Intervention 27
3.2.2.4. Comparison 29
3.2.2.5. Outcomes 29
3.2.2.5.1. Primary outcome 29
3.2.2.5.2. Secondary outcome 30
3.2.3. Risk of bias assessment of included studies 30
3.2.3.1. Selection bias 32
3.2.3.2. Performance bias 32
3.2.3.3. Detection bias 33
3.2.3.4. Attrition bias 33
3.2.3.5. Reporting bias 34
3.2.3.6. Other bias 35
3.2.3.7. Overall bias 35
3.3. Stage 3: Exploration of relationships within and between studies 35 3.3.1. Effects of the intervention on the primary outcome 36
3.3.1.1. Hunger 39
3.3.1.2. Fullness 40
3.3.1.3. Satisfaction 42
3.3.1.4. Desire to eat 43
3.3.2. Effects of the intervention on the secondary outcome 43
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3.3.3. Sensitivity analysis, sub-group analysis, and publication bias 45 3.4. Stage 4: assessment of the robustness of the synthesis 45
3.4.1. Certainty of the evidence 45
4. CHAPTER 4: DISCUSSION 46
4.1. Summary of main results 46
4.2. Ethics 48
4.3. Overall completeness and applicability of evidence 48 4.4. Agreements and disagreements with other reviews 48
4.5. Strengths and limitations 49
4.6. Implications for practice/policy 51
4.7. Implications for further research 51
4.8. Conclusion 52
REFERENCES 53
APPENDICES 61
Appendix 1. PRISMA 2020 checklist 62
Appendix 2. The study protocol 65
Appendix 3. Full search strategy 69
Appendix 4. Data extraction forms with RoB assessments 73 Appendix 5. Raw Data from the included studies obtained by ―GetData Graph
Digitizer‖ 124
Appendix 6. Excluded studieswith reasons 129
Appendix 7. GRADE assessments 135
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LIST OF TABLES
Table 1. Classification of BMI for adults 2
Table 2. Popular dietary strategies with different forms and structures 4 Table 3. Commonly used intermittent fasting protocols 8
Table 4. Alternate day fasting 8
Table 5. GRADE certainty ratings 21
Table 6. Applying the GRADE approach when a meta-analysis is not available and the evidence for an effect is summarized narratively 22
Table 7. Brief overview of the included studies 25
Table 8. Various components of ADF/ADMF protocols in included studies 28 Table 9. Drop-outs from the intervention arms of included studies 34 Table 10. Changes in hunger from baseline to follow-up in included RCTs 39 Table 11. Changes in fullness from baseline to follow-up in included RCTs 41 Table 12. Changes in satisfaction from baseline to follow-up in included RCTs 42 Table 13. Body weight values for baseline and follow-up 43 Table 14. Body weight changes between baseline and follow-up 44
Table 15. Summary of findings 45
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LIST OF FIGURES
Figure 1. Share of adults that are overweight or obese in 2016 1
Figure 2. The mechanism of intermittent fasting 6
Figure 3. Mechanism of reaching satiety with consumption of standard food 11
Figure 4. The satiety cascade 12
Figure 5. The theoretical model 23
Figure 6. The flow diagram 24
Figure 7. RoB graph: judgements about each RoB item presented as percentages
across all included studies 31
Figure 8. RoB summary: judgements for each RoB item for each included study 32
Figure 9. Forest plots 37
Figure 10. AUC charts for hunger, fullness and desire to eat 38
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LIST OF ABBREVIATIONS
1. ADF Alternate Day Fasting 31. MIN Minutes
2. ADMF Alternate Day Modified Fasting 32. MM Millimeter
3. ADP Adenosine Diphosphate 33. mTOR
Mechanistic Target of Rapamycin
4. AgRP Agouti-Related Protein 34. N Total Number
5. AMP Adenosine Monophosphate 35. NA Not Applicable
6. AMPK AMP-Activated Protein Kinase 36. NAD
Nicotinamide Adenine Dinucleotide
7. ATP Adenosine Triphosphate 37. NPY Neuropeptide Y
8. AUC Area Under Curve 38. OVID
Offshore Vessel Inspection Database
9. BMI Body Mass Index 39. P
Probability value (quantifying statistical significance)
10. CCK Cholecystokinin 40. PICO
Population, Intervention, Comparison, Outcome
11. CER Continuous Energy Restriction 41. PP Per-Protocol
12. CHO Carbohydrate 42. PRISMA
Preferred Reporting Items for Systematic Reviews and Meta- Analyses
13. CINAHL
Cumulative Index to Nursing and
Allied Health Literature 43. PROSPERO
International Prospective Register of Systematic Reviews
14. CR Caloric Restriction 44. PSYCINFO
Psychological Information Database
15. DASH
Dietary Approaches to Stop
Hypertension 45. PYY Peptide YY
16. DER Daily Energy Restriction 46. RB Rigmor C Berg
17. EMBASE Excerpta Medica Database 47. RCT Randomized Controlled Trial
18. EODF Every Other Day Fast 48. RevMan Review Manager
19. EPOC
Effective Practice and Organization
of Care Group 49. RoB Risk of Bias
20. GLP-1 Glucagon-Like Peptide-1 50. RoBANS
Risk of Bias Assessment Tool for Non-Randomized Studies
21. GRADE
Grading of Recommendations Assessment, Development, and
Evaluation 51. SD Standard Deviation
22. IER Intermittent Energy Restriction 52. SEM Standard Error of Mean
23. IF Intermittent Fasting 53. SPICO
Study Design, Population, Intervention, Comparison, Outcome
24. ITT Intention to Treat 54. SoF Summary of Findings
25. KCAL Kilocalorie 55. TRF Time Restricted Feeding
26. KG Kilogram 56. UCBA Uncontrolled before and after
27. LCD Low Calorie Diet 57. VAS Visual Analogue Scales
28. LDL Low Density Lipoprotein 58. VLCD Very Low Calorie Diet
29. MEDLINE
Medical Literature Analysis and
Retrieval System 59. WHO World Health Organization
30. MeSH Medical Subject Headings 60. WK Weeks
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CHAPTER 1: INTRODUCTION 1.1. Description of the Condition
1.1.1. Overweight and obesity: definitions, prevalence, and consequences
Obesity, a well-known risk factor for many metabolic disorders, is a worldwide epidemic (1). The prevalence of this condition has increased rapidly during the past 50 years and nearly tripled since 1975 worldwide (2, 3). According to World Health Organization (WHO), 39% of adults aged 18 years and over were overweight and 13% were obese in 2016 (3). The share of adults who are overweight or obese for this year can be seen in figure 1.
Overweight and obesity are defined as abnormal or excessive fat accumulation that may impair health (3). Body mass index (BMI) is a simple index of weight-for-height that is commonly used to classify overweight and obesity in adults (3). It is defined as a person's weight in kilograms divided by the square of his height in meters (kg/m2) (3). For adults, WHO defines overweight as a BMI greater than or equal to 25; and obesity as a BMI greater than or equal to 30 (3). The detailed BMI classification can be seen in table 1.
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Maintaining a raised BMI in the long-term results in metabolic changes that are associated with an increased lifetime risk for developing various conditions that are significant risk factors for mortality worldwide according to the ―2019 Global Burden of Diseases Study‖ (6). Globally, 8%
of deaths in 2017 were the result of obesity which has increased from 4.5% in 27 years (4).
Overweight, obesity, and the associated chronic diseases have a negative impact on both the economy and the health of societies (7). Obesity is associated with a high risk of morbidity, mortality as well as reduced life expectancy (8). Overweight and obesity are major risk factors for a number of chronic diseases, including cardiovascular diseases, diabetes, musculoskeletal disorders, respiratory disorders, cancer, and psychosocial problems (1-3, 8, 9). The risk of these diseases grows more serious as the BMI climbs (9).
Although other factors are involved, the fundamental cause of obesity is an imbalance of calories consumed and calories expended (3). The largest environmental driver of this cause is the
increasing ‗obesogenic environment‘ which consists of poor diet with availability and
accessibility of many unhealthy food options and sedentary lifestyles (1, 6). Luckily, overweight and obesity are largely preventable and reversible (3, 9). The increasing prevalence highlights the need for improved evidence-based prevention and treatment strategies (8). Many government initiatives and awareness campaigns have been initiated worldwide to help to overcome obesity (8). A wide variety of obesity treatments are available, including diet, exercise, behavioral modification, pharmacological treatment, and surgery (2, 8, 10-13).
Table 1. Classification of BMI for Adults (5)
Weight Status Body Mass Index (BMI) ,kg/m2
Underweight <18.50
Normal range 18.50-24.99
Overweight ≥25.00
Pre-obese 25.00-29.99
Obese ≥30.00
Obese class I 30.00-34.99
Obese class ll 35.00-39.99
Obese class Ill ≥40.00
BMI values are age-independent and the same for both sexes.
The table is adapted from WHO 2000 report. “Obesity : preventing and managing the global epidemic : report of a WHO consultation”
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Among several strategies, lifestyle interventions have been documented to lead safely to
improvements in metabolic abnormalities such as increased body weight, dyslipidemia, elevated blood pressure, impaired glucose control, and pro-inflammatory activity that are linked to the development of obesity, diabetes, metabolic syndrome, and cardiovascular diseases (8). In one meta-analysis, it is suggested that lifestyle changes are one of the most effective methods
especially in reducing weight and the risks for cardiovascular diseases (8). Lifestyle programs are multi-factorial interventions that are designed for each patient or group of patients according to their risk factor status and the needs of the individuals (8). These include promoting healthy lifestyle habits, dietary counseling, physical exercise training, and behavioral change targets (8).
In a 2021 systematic mapping review, commissioned by the Norwegian Directorate of Health, it is found that nearly half of the studies of lifestyle interventions for overweight and obesity treatment comprised both changing of diet, increasing physical activity, and psychological counseling (14). It was highlighted that caloric restriction (CR) is the most common element in the interventions (14).
Restriction of the daily food intake results in weight loss and is associated with improvement in the overall wellbeing of patients and their biomarkers such as triglycerides, total cholesterol, low- density lipoprotein cholesterol, blood pressure, glucose, insulin, and C-reactive protein levels (1).
A reduction in energy intake producing modest losses of between 5-10% of initial body weight maintained for over a year has been associated with improved metabolic outcomes such as insulin sensitivity and decreased risk of mortality from all obesity-related comorbidities as well as
reduced risk of developing diabetes and some forms of cancer (6). Optimal diets for weight management have been a topic of debate not only among researchers, nutrition experts, and healthcare professionals but also among the general public (2). However, there is still research needed on the effectiveness of most of the dietary interventions (1).
Although dietary interventions with CR were the primary driver of weight loss, according to a meta-analysis of several diet programs, weight management depends upon complex factors such as the amount of food eaten, type of food eaten, and timing of meals (2, 15, 16). Thus, a variety of dietary approaches can produce weight loss in overweight and obese adults. Some of the most popular ones are given in table 2.
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1.2. Description of the intervention and how it might work
1.2.1. Intermittent fasting: definition, mechanism, and alternate day fasting
Intermittent fasting (IF) is a relatively novel weight loss regimen that has been steadily growing in popularity in media, public, experts, and scientific literature over the past decade as an alternative strategy to continuous energy restriction (CER) for individuals with overweight and obesity (2, 17-20). The roots of it derive from traditional fasting, a universal ritual used for health or spiritual benefit as described in early texts by Socrates, Plato, and religious groups (21).
Fasting exists in various religious practices, including Buddhism, Christianity, Hinduism, and Islam (22, 23). Therapeutic intermittent fasts for the treatment of obesity were investigated since
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at least 1915, with a renewed interest in the medical community in the 1960s after a report (24, 25). Intermittent fasts, or "short-term starvation periods", were ranging from 1 to 14 days in these early studies (24, 25). Its popularity has increased after a BBC Horizon documentary, ―Eat, Fast, and Live Longer‖, aired in the United Kingdom, August 2012 (26, 27). It introduced the 5:2 diet, one of the popular fasting approaches today (26, 27). IF is an umbrella term for various meal timing schedules that cycle between voluntary fasting and non-fasting over a predefined period (22, 28, 29).
Although IF is commonly used interchangeably with intermittent energy restriction (IER), as a definition, IER consists of intermittent periods of partial intake whereas IF consists of no intake on restricted days (30). As it may have similar effects to CER, IER is promoted to change body composition through loss of fat mass and weight and to improve markers of health such as blood pressure and cholesterol levels (21, 29). Although there are also some studies with conflicting results and studies with the long-term sustainability of these effects are needed, a 2019 review concluded that IF may help with obesity, insulin resistance, dyslipidemia, hypertension, and inflammation (28, 29).
In addition to the effect on weight loss, many studies have shown that IER has additional benefits from its effects on metabolic switching such as reversing insulin resistance, strengthening the immune system and improving systemic inflammatory diseases, enhancing physical and cognitive functions, protecting against neurodegeneration, and even expanding the life span (2, 19). While there is no standard definition of the metabolic switch and its components, it has been agreed that there are several signaling pathways affected by IER as shown in figure 2 (31).
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The first pathway, with a rise in adenosine monophosphate (AMP) and adenosine diphosphate (ADP) and a fall in cellular adenosine triphosphate (ATP), results in activation of AMP-activated protein kinase (AMPK) that inhibits various anabolic reactions and stimulates catabolic reactions, stimulates autophagy, which rejuvenates cells by eliminating damaged proteins and organelles, and improves mitochondrial function (31). The second pathway, with a decrease in circulating amino acids and glucose, inhibits the mechanistic target of rapamycin (mTOR) that leads to decreased protein synthesis, increase in mitochondrial biogenesis and autophagy, and increased life span in experimental animals (31). The third pathway, which has been proposed as a critical component of prolonged fasting, with the marked reduction of carbohydrate (CHO), results in depletion of hepatic glycogen that leads to activation of fatty acid mobilization from adipose
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tissues and stimulation of hepatic β-oxidation with increased production of ketones (β- hydroxybutyrate) in both humans and animals (31). In addition, nicotinamide adenine dinucleotide (NAD+) deacetylase activity of sirtuins is activated, leading to autophagy and
decreased oxidative stress (31). The combination of these pathways leads to improved healthspan and longevity in various animal species (31). The literature shows that the CER approach
promotes weight loss, decreases blood glucose, insulin, blood pressure, triglycerides, and cholesterol levels (31). Although it is largely related to the observation that individuals
implementing IER protocols also frequently lose weight; benefits from the use of IER protocols overlap with those derived fromCER approaches (31). However, CER alone does not have the benefits of the metabolic switch that is uniquely produced from the use of IER protocols, as shown in figure 2 (31).
With these mechanisms, IER has deep effects on many organs and tissues, including the brain, cardiovascular system, adipose tissue, liver, and skeletal muscle with improvements in metabolic homeostasis, tissue repair, mitochondrial biogenesis, and overall resilience that leads to the extension of health and life span (31).
IER can include fasting for several hours to days, can be continuous or interrupted, and the calorie intake during the non-fasting periods may also be different than the usual intake (31).
Commonly used IER protocols are; alternate day fasting (ADF), time-restricted feeding (TRF), 5:2 fasting, and Ramadan fasting. Detailed definitions of different IER approaches can be seen in table 3.
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Alternate day fasting (ADF), also called every other day fasting (EODF), is one of the most used IER approaches in the scientific literature (32). It involves a 24-hour ―fast day‖ alternated with a 24-hour ―feed day‖ where people usually eat ad libitum as shown in table 4 (33, 34).
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It has two subtypes: Complete ADF, where no calories are consumed on fast days and modified alternate-day fasting (ADMF) which allows the consumption of very-low-calorie diets (VLCD) which means up to 25% of daily calorie needs on fasting days instead of complete fasting (35, 36). However, in the literature, these are commonly used as interchangeable terms. Several studies have demonstrated that ADF administration for 4 to 12 weeks may effectively reduce body weight and visceral fat mass (17). ADF appears to achieve a higher weight loss than other forms of IF (17). In addition to these beneficial effects of ADF on body composition; favourable outcomes on blood lipids such as decreases in low-density lipoprotein (LDL) cholesterol and triglycerides have been reported (17). The use of ADF protocols has been mainly aimed at counteracting obesity and maximizing the effects on healthy living by reducing the incidence of many diseases such as cardiovascular disease, metabolic syndrome, hypertension, and diabetes (31).
1.2.2. Psychobiological nature of appetite
The human appetite system is deeply linked to body composition and therefore to obesity (41).
The role of appetite in obesity has a long research history rooted back to 1968 when a series of experiments demonstrated that adults with obesity compared to normal weight eat more highly palatable foods but showed no difference in intake of standard foods (6). Appetite forms a bridge between the internal and external environments and therefore has both biological and behavioural or psychological aspects (41). By definition, appetite is the system that informs patterns of eating behaviour (6, 41). There are two forms of signals involved in appetite regulation (6, 42). The first form, episodic signals, are mainly inhibitory and usually generated by episodes of eating (42).
The second form, tonic signals, arise from adipose tissue stores and indicate the level of fat storage (6).
Episodic signals inform the brain about the amount of food ingested and its nutritional content via input through the senses to contribute to the termination of an eating episode and subsequently influence the strength and duration of the suppression of eating after a meal (6, 42). Following ingestion, specialized chemo- and mechano-receptors that are located within the gastrointestinal tract pass information to the hypothalamus in the form of gut hormones released in the stomach and intestines such as cholecystokinin (CCK), peptide YY (PYY), and glucagon-like peptide-1 (GLP-1) (6, 43). In the post-absorptive phase, after the nutrients have been digested and crossed
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the intestinal wall into circulation, they metabolize in peripheral tissues or organs which constitute satiety signals (6). In addition, the products of digestion and their respective metabolites reach the brain where they can bind to specific sites of action which influence neurotransmitter synthesis that informs the brain about the metabolic state resulting from food consumption (6). These signals underlie fluctuations in subjective feelings of appetite which mediate the termination of an eating episode as well as the strength and duration of inhibition overeating following a meal (6).
Generally, while hunger is suppressed by episodic signaling, it arises through tonic signaling and the overall strength of the drive to eat is the balance between these physiological processes (43).
Leptin and insulin are important tonic signals of long-term energy stores (6). They bind to receptors in the hypothalamus to inform energy balance by altering food intake (6). During periods of food deprivation, tonic signaling declines as reduced leptin and insulin signals reach the hypothalamus (6). This lowers sensitivity to episodic satiety signals causing an imbalanced homeostatic regulation resulting in a need for energy intake to generate a sufficient satiation signal to inhibit an eating episode (6). Ghrelin illustrates the characteristics of both an episodic and tonic signal in appetite control (42, 43). Endogenous ghrelin levels appear responsive to nutritional status and ghrelin acts as a compensatory hormone (42). Although there is individual variability in hormone secretion, this means that in obese people ghrelin levels would be reduced in an apparent attempt to restore a normal body weight status and with weight loss, ghrelin levels would rise to promote the feeling of hunger (42). This is likely to be one of the signals that make the loss of body weight so difficult to maintain, therefore appetite regulation is highly important when it comes to weight loss strategies (42).
If eating behavior were only regulated by these homeostatic systems, food consumption would simply be a response to a purely physiological need, and the great majority of people would easier manage to keep normal body weight (44). However, the regulation of appetite in humans is much more complex as the homeostatic control of food intake is strongly influenced by
hedonistic impulses, the reward system, and eating experiences (44). The hypothalamus controls both the homeostatic and non-homeostatic regulation of appetite (44). Pre-prandial motivation is where diminished satiety signals are detected in the gut by hypothalamic areas which respond by increasing the drive to consume (6). The activation in hypothalamic areas results in cephalic
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phase responses (6). These are anticipatory responses generated in many parts of the
gastrointestinal tract when exposed to the sensory properties of food like sight and smell which aim to optimize the metabolism of ingested nutrients (6, 42). The senses provide input via peripheral receptors to the primary sensory cortices which are integrated with information about motivational subjective state and memory to influence behaviour (6). Food hedonics is comprised of important motivational components which represent the sensory and cognitive processes involved in the experiences of ‗liking‘ and ‗wanting‘ (6).
Historically, hedonic processes have been viewed as a function of the nutritional need-state. In a state of depletion, the hedonic response to energy-providing foods is enhanced and when replete, the hedonic effect of these foods is reduced (42). However, such hedonic reward pathways can override the homeostatic system and increase the desire to consume, despite physiologic satiation and replete energy stores (45). It is important to make the distinction between biological drive and implicit wanting as separate, but interacting entities (43). Consumption of standard food generates information on its energy content and taste in the brain stem (42). This information is transmitted to the hypothalamus leading to an up-regulation of various satiety peptides, causing consumption to cease which can be shown in figure 3 (6, 42).
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However, with ingestion of palatable food, information is transmitted to the reward circuit, leading to the greater release of reward mediators like dopamine, endocannabinoids, and opiates (6, 42). In turn, this causes increases in hunger peptides such as neuropeptide Y (NPY) and orexins and decreases the signalling in satiety peptides such as insulin, leptin, and CCK (6, 42).
Therefore when food is highly palatable, the drive to eat is maintained, with continued eating now mediated by reward mechanism rather than biological need (6, 42).
To better understand the integration of these behavioral and sensory elements with physiological factors for appetite regulation, a conceptual scheme called the Satiety Cascade was proposed over 30 years ago by Blundell et al which the adapted form can be seen from figure 4 (43, 44).
Sensory elements induce appetite before food intake as a preparatory act (44). Hunger, defined as the physiological sensation generated in response to a biological need for energetic nutrients, drives food intake (44). After eating has been initiated, there is satiation or fullness, which is the process that triggers a series of signals which lead to meal termination (43, 44). Lastly, satiety is the process that leads to the post-meal suppression of hunger, hence, inhibition of further eating (43). In sum, hunger is conceptualized as part of a broader system of appetite control (43). The rise and fall of hunger during the day drive patterns of food intake (43). Satiation occurs during the act of eating, and satiety determines the time-lapse between meals (44). All these hedonic
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processes interact with homeostatic processes in the overall control of appetite and food intake (43).
Appetite regulation is highly significant as it helps to shape eating behaviours that may lead to overconsumption which include behaviours related to satiety, like weakened satiety response;
reward, like strong hedonic attraction to palatable food; and behavioural control, like disinhibited eating (6). Overweight and obese individuals face critical behavioural issues that lead to overconsumption and contribute to maintaining a positive energy balance (6). Therefore, understanding these concepts is crucial for fighting obesity with lifestyle interventions for better weight management.
1.3. Why is it important to do this review
1.3.1. Rationale for the study: relation between appetite regulation and weight management with alternate day fasting approach
As weight gain is a result of energy surplus, to achieve a weight loss, energy expenditure must exceed intake through a reduction in energy intake and/or an increase in physical activity (6).
However, considering the fact that the energy balance is a dynamic regulatory system that integrates current body composition, energy expenditure, and metabolism with appetitive processes and energy intake, the solution to achieve weight loss becomes more complex (6).
Although many diet options are available and effective for weight loss, most attempts are unsuccessful in both the short and long term. Many people are unable to achieve and maintain modest losses, and the majority of those who do, regain this within 3 to 5 years (6, 46).
Numerous studies have compared dietary patterns of differing compositions for weight loss.
However, an emerging body of evidence suggests that adherence to the dietary prescription, regardless of diet composition, is the strongest predictor of weight loss (46, 47). Reduced motivation and compliance to dietary intervention are major challenges for obesity treatment (48).
A multitude of factors is likely to influence adherence to dietary prescriptions for weight loss.
Changes in appetite, cravings, and diet satisfaction or acceptability that often occur during weight loss likely contribute to poor dietary compliance (46). Although few studies have examined
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adaptations in psychobehavioral determinants of appetite and eating behavior instead of the physiological factors during diet-induced weight loss, it is known that lower hunger ratings were predictive of greater weight loss during lifestyle-only and lifestyle plus pharmacological
interventions, and increased feelings of hunger following weight loss likely contribute to weight regain (20, 46). Therefore, one of the biggest underlying reasons for low compliance is not being able to properly manage appetite as increased sensations of hunger and reward responsivity to food cues make appetite regulation and dietary adherence challenging for especially overweight and obese patients. Yet, it should be noted that these vary between individuals. Adherence to dietary interventions could be improved by dietary strategies which help control or suppress appetitive drives to eat that occur during the intervention (6).
One such strategy thought to suppress this drive while simultaneously avoiding compensatory increases in hunger that usually occur during energy restriction is VLCDs (6, 49). These diets use severe energy restriction which is ≤800 kcal/day that creates a metabolic response to a low CHO intake resulting in increased circulation of ketones bodies produced by the liver (6). In the meta- analyses of Gibson et al. conducted in 2014, it is found that individuals showed significantly lower levels of hunger and higher levels of fullness following adherence to a VLCD diet compared to baseline (49). However, although CER or daily energy restriction (DER) where energy intake is restricted every day is the most frequently used weight loss strategy, individuals who struggle to cope with strong sensations of hunger may not be able to maintain sufficient levels of severe restriction to experience the beneficial changes in sensations of satiety that helps to increase dietary adherence (6).
Several studies have shown marked increases in hunger after 5-10% weight loss with a CER regimen (20). As an example, Sumithran and colleagues showed that hunger was elevated after 10% weight loss with a VLCD (∼500 kcal/day for ten weeks) and remained elevated one year later (50). An increase in desire to eat was also shown with more modest diet-induced weight loss in women with overweight (∼4.6% weight loss with a 700 kcal/day restriction) (51). Thus, not only could diet-induced weight loss lead to a stronger motivation to eat, but it may also be accompanied by weaker satiety (20).
Also, the more restrictive the regimen the greater the demand for discipline in the face of an intense physiological desire to eat (52). And as the intake must be limited daily, it is difficult to
15
follow these strategies for most overweight and obese individuals (52). Another problem is that CER may become monotonous and may cause the body to adapt to the CR and therefore prevent further weight loss (21, 26, 52, 53). IER is an alternative approach to weight loss thought to be easier to follow due to favourable changes in appetite as a result of shorter spells of intense energy restriction followed by periods of ad libitum intake (6). Anecdotal reports suggest IER makes individuals more aware of food habits and reassures them that they can manage the high levels of hunger on restriction days (6).
Especially the type ADF/ADMF was created as an alternative to CER to improve compliance (54). As it only requires a restriction of food intake every other day, it may prevent body
adaptations to the diet that hinders further weight loss (21, 54). It may decrease the monotony and as the individual will know that food is not going to be restricted the next day, it might increase the motivation (21, 54). Hence, ADMF can greatly promote adherence to these protocols.
Besides, because of the periodic nature of fasting, it may mitigate the constant hunger that practitioners of CER endure (55). However, the effect of ADF on appetite regulation is not well- defined in the scientific literature which warrants further investigation. Interventions that reduce hunger, food cravings, and feelings of deprivation and increase or maintain diet satisfaction during weight loss could promote greater diet adherence and improve beneficial outcomes (46).
Investigating these factors may be a promising approach to enhance the effectiveness of behavioral obesity treatment programs. A better understanding of the effects of ADF on
subjective measures of appetite might be important to evaluate the feasibility of this treatment for longer periods, especially in free-living settings.
1.4. Objective
The purpose of this thesis is to systematically review the available evidence and summarize the effects of ADF/ADMF on subjective feelings of appetite, that is, feelings of hunger, fullness, satisfaction, and desire to eat for overweight and obese adults aged between 18-65. Hence, the primary outcome of interest in this systematic review is feelings of appetite and for the secondary outcome, body weight or the weight change is examined. It is hypothesized in this study that ADF/ADMF leads to a reduction in subjective feelings of hunger, desire to eat, and body weight while increasing subjective feelings of fullness and satisfaction among overweight and obese individuals.
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CHAPTER 2: METHODOLOGY
I conducted this systematic review in accordance with the Cochrane Handbook for Systematic Reviews of Interventions, Version 6, 2019 and PRISMA Checklist 2020 (56, 57). The filled checklist can be found in appendix 1. The study protocol was registered in PROSPERO in May 2021, with reference number CRD42021247708, enclosed in appendix 2. Neither ethical permission nor budget were required for conducting the review.
2.1. Criteria for considering studies for this review
The inclusion and exclusion criteria for this systematic review are described below in SPICO format (study design, population, intervention, comparison, outcome).
2.1.1. Types of studies
This systematic review considered randomized controlled trials (RCTs). As stated in the protocol, in the event a low number of RCTs were identified, also non-RCTs and controlled and
uncontrolled before and after (UCBA) studies would be considered.
2.1.2. Types of participants
This systematic review considered studies with male and/or female adult participants, aged between 18 and 65, of any nationality, who were overweight or obese with a BMI greater than or equal to 25 or 30 kg/m2, respectively. Adults with unstable body weight (meaning more than 4 kg weight loss or weight gain three months prior to the beginning of the study), patients with chronic infections, cancer or history of eating disorders, individuals who had bariatric surgery, pregnant women, and those planning a pregnancy or breastfeeding were excluded. In the event of mixed populations, this review only considered studies when at least 75% of the population fit the inclusion criteria.
2.1.3. Types of interventions
Alternate day fasting. The alternate day fasting intervention consists of a cyclical feeding pattern with a ―fast day‖ where an individual consumes between 0-25% of their daily energy needs for a period of 24 hours, alternated with a ―feast day‖ where a person has no CR or is permitted to eat ad libitum in the following 24 hours. In the event of no or limited information about the
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percentage of the diet, studies with energy intake of more than 600 kcal on fast days were excluded. As there is no golden standard for the duration of this intervention, I only considered interventions with a duration of minimum eight weeks because this is the most common duration used in the literature for this intervention. In the event of studies having multiple intervention arms, only ADF arms in the studies were included.
2.1.4. Types of comparisons
CER, DER, or ad libitum diet was eligible as the comparator in this review. For non-RCT design, no comparison was also eligible.
2.1.5. Types of outcome measures 2.1.5.1. Primary outcomes
The primary outcome of interest in this systematic review was feelings of appetite that are hunger/fullness/satisfaction/desire to eat. Appetite had to be assessed by quantitative scales such as numeric rating scales or visual analogue scales (VAS). Especially VAS are widely used scales for measuring the experience of appetite (58). Numeric rating scales often range from 0 or 1 (to a small degree) to 10 (to a very high degree). VAS usually consist of 100 or 150-mm lines and participants are asked to place a vertical mark across the line corresponding best to their feelings, with the scale ranging from 0 (not at all) to 100/150 (extremely). Quantification of the scales is performed by measuring the distance between the left end of the line and the vertical mark either by hand or by a validated electronic system.
2.1.5.2. Secondary outcomes
The secondary outcome of this review was body weight /weight change. It had to be described quantitatively, such as kilograms, pounds, BMI, or weight change from baseline to follow-up.
While these can only provide a crude estimate of obesity for an individual as it is not a measure of adiposity, these are the most useful and practical measures that have strong correlations with fat mass in adults (6).
2.1.6. Other criteria
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In order to decrease the risk of having problems with access to full texts of studies, I only included journal articles and only studies in English language that were published between 2000 and 2020. Setting/country was not an exclusion criterion.
2.2. Search methods for identification of studies
I prepared the search strategy by myself and searched four electronic databases that were considered to be the most relevant for the topic:
MEDLINE In‐Process & Other Non‐Indexed Citations Ovid (1946 to February 20, 2021)
Embase Classic+Embase (1947 to February 20, 2021)
APA PsycINFO (1806 to February 20, 2021)
EBSCOhost CINAHL.
The search strategy aimed to find published articles only. I identified important keywords in PICO format. I used controlled vocabulary that is MeSH (for Medline), Emtree (for Embase), PsycInfo Thesaurus, and CINAHL Headings. To broaden the scope of the search and increase the specificity and sensitivity of the results, I used both explode and focus options at the same time for the controlled vocabulary. This means that the search included the selected subject headings as well as more specific headings underlying, and only retrieved references that have any of these headings as their main topic. Title, abstract, and keyword fields and phrases were utilized. I used boolean operators (―AND‖, ―OR‖ and ―NOT‖), proximity operators (―ADJn‖, ―Nn‖ and ―Wn‖), and truncation and wild cards (―*‖, ―?‖ and ―#‖). I filtered the studies by human studies, study language, publication year, and type of publication. I also manually checked Google scholar and the reference lists of relevant systematic reviews, literature reviews, and other relevant
publications to identify relevant studies that were not covered by the database searches. The last search, both in electronic databases and manual was done on February 20, 2021. The full search strategy can be found in appendix 3.
2.3. Data collection and analysis 2.3.1. Selection of studies
I imported all records from the searches to EndNote X9, a software package used to manage bibliographies and references. Duplicates were removed. I screened the remaining titles and
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abstracts from the literature searches by the use of Rayyan QCRI, a free web and mobile tool designed to facilitate the screening process for researchers working on systematic reviews (59).
All relevant records were promoted to full-text examination against the inclusion and exclusion criteria. The full texts of all relevant studies were obtained, screened and reasons for exclusion were recorded. When I was not certain about the relevance of a study, it was resolved by discussion with my thesis supervisor (RB).
2.3.2. Data extraction and management
I extracted the data from studies that met the inclusion criteria by a data extraction form that I adapted from EPOC (Effective Practice and Organization of Care Group) resources (60). The form can be found in appendix 4. The extracted data included: title, authors, and other details of publication; study design, setting, and aim; population characteristics like age and gender;
intervention characteristics like detailed content and duration of treatment; methods of outcome measurement like the scales used, unit of measurement and time points of measurement; and results related to the outcomes. In most of the studies the data were only presented in figures and authors of some studies were contacted to request data, but no reply was received. Hence, as stated in the Cochrane handbook, data from figures can be extracted manually, for example by using a ruler or by using software (56). Because the manual approach would be time-consuming and might be inaccurate, I decided to use a software. Numerous simple and convenient tools are available. I chose ―GetData Graph Digitizer‖ as it is user-friendly and is one of the most practical and commonly used softwares for systematic reviews. The software works by taking an image of a figure and then digitizing the data points of the figure using the axes and scales set by the users (56). I utilized the version 2.26 to export the numbers from the graphs and I calculated additional data such as means, standard deviations (SDs), and standard error of the mean(SEM) from individual-level data points. I double-checked exported data by creating the same graphs using Microsoft Excel version 2010. These data and graphs were enclosed in appendix 5.
2.3.3. Assessment of methodological quality of included studies
Each selected randomized controlled study was assessed for risk of bias (RoB) according to the Cochrane 'Risk of bias' tool for randomized controlled trials (RoB2) (56). This tool assesses five domains: bias arising from the randomization process; bias due to deviations from intended
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interventions; bias in the measurement of the outcome; bias due to missing outcome data; bias in the selection of the reported result; and other sources of bias can be added if needed. At the point of preparing the protocol, the tool for the non-RCT studies was not decided. As different non- RCT study designs fit with the inclusion criteria of the review, to be able to select the most appropriate and comprehensive tool for the included studies with non-RCT designs, I postponed the selection of this tool until the end of the data extraction process. For the selected UCBA studies, I utilized RoBANS (Risk of Bias Assessment Tool for Non-Randomized Studies) to assess the risk of bias. RoBANS is a valid tool designed to assess the risk of bias of non- randomized studies and contains six domains: the selection of participants, confounding variables, measurement of intervention, blinding of outcome assessment, incomplete outcome data, selective outcome reporting and other sources of bias can again be added if needed (61).
The risk of bias for each of the domains for each study is reported as ‗Low Risk‘, ‗Unclear Risk‘, or ‗High Risk‘. Domains with no cause for concern were assigned low risk, when a judgement could not be made, the risk was assigned as unclear, and domains with cause for concern were assigned as high risk of bias. Since RoBANS is harmonized with Cochrane‘s RoB tool and GRADE and can be incorporated into RevMan, it appears to be useful to people undertaking systematic reviews (61). When I had doubts about the risk of bias, it was resolved by a discussion with my thesis supervisor (RB). I included a visual summary of appraisals in the review. This type of summarization was used to get an appreciation for what the general strengths and
weaknesses are for studies included in the review. Detailed assessments can be found in appendix 4.
2.4. Data synthesis
In this systematic review, I planned to statistically pool the results only if the data from individual studies were sufficiently similar. However, there were potential biases arising from the study designs and I identified both conceptual and methodological heterogeneity among the studies arising from the differences in SPICO. Therefore, I decided that it was not appropriate to undertake a meta-analysis for this review. I adopted a systematic, narrative approach to
synthesize the results. The narrative synthesis was undertaken following the four principles that were stated in the protocol:
1. Developing a theory of how the intervention works, why and for whom
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2. Developing a preliminary synthesis of findings of included studies 3. Exploring relationships within and between studies
4. Assessing the robustness of the synthesis (62).
I created a diagram to explain the theoretical model. To search for heterogeneity and patterns across the studies, I tabulated the characteristics of each study and various components of
interventions and I used graphs and figures for risk of bias assessments. To explore relationships, as both the outcomes were continuous, I calculated mean differences and created forest plots for both outcomes by using RevMan Software version 5.4 and presented them without pooled results.
Because less than ten studies were included in the synthesis, I decided not to use a funnel plot as I stated in the protocol.
2.5. Assessment of the certainty of the evidence
I assessed the confidence in the evidence of the included studies for both the primary and secondary outcomes by using the GRADE approach (63). The study design is the starting point for the assessment (64). RCTs start as high certainty while observational studies start as low certainty (64). The GRADE approach has five criteria for a possible downgrading of the confidence in the evidence: study limitations, imprecision, inconsistency between studies, indirectness of evidence, and reporting bias. It has three criteria that can raise the certainty of the evidence: large magnitude of effect, dose-response relationship, and opposing bias and
confounders (64). The decision to upgrade certainty of the evidence is only made for
observational studies and only when serious limitations in any of the five criteria reducing the certainty of the evidence are absent (64). The certainty of the evidence is described as high, moderate, low, or very low as shown in table 5 (64).
Table 5. GRADE Certainty Ratings (64) Certainty Symbol Definition
High ⊕⊕⊕⊕ The authors are very confident that the true effect lies close to that of the estimate of the effect
Moderate ⊕⊕⊕◯ The authors are moderately confident in the effect estimate: The true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different
Low ⊕⊕◯◯ The author’s confidence in the effect estimate is limited: The true effect may be substantially different from the estimate of the effect
Very low ⊕◯◯◯ The authors have very little confidence in the effect estimate: The true effect is likely to be substantially different from the estimate of effect
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The GRADE domains can be applied without a single pooled estimate as shown in table 6 (65).
The approach leverages the meaning of the constructs that represent GRADE domains to produce judgements on how these constructs affect our certainty (65).
Justifications for decisions to downgrade the ratings were shown and evidence was reported in the ―summary of findings (SoF)‖ tables.
Table 6. Applying the GRADE Approach When a Meta-analysis is Not Available and the Evidence for an Effect is Summarized Narratively (65)
GRADE domain How to apply
Methodological limitations of the studies Make a judgement on the risk of bias across studies for the outcome.
Indirectness Make a judgement on how dissimilar the research evidence is to the clinical question at hand in terms of PICO.
Imprecision Consider the optimal information size or the total number of participants for continuous outcomes across all studies. A threshold of 400 or less is concerning for imprecision. Results
may also be imprecise when the confidence intervals of all the studies or the largest studies include no effect and
clinically meaningful benefits or harms.
Inconsistency Evaluate the consistency of the direction and primarily the difference in the magnitude of effects across studies since statistical measures of heterogeneity are not available.
Widely differing estimates of the effects indicate inconsistency.
Likelihood of publication bias Suspect when the body of evidence consists of only small positive studies. Publication bias is more likely if the search of
the systematic review is not comprehensive.
Factors that can raise certainty in evidence:
Large effect
Dose-response gradient
Plausible confounders or other biases increase the certainty in the effect
If one of three domains that can increase certainty in a body of evidence, typically from non-randomized studies, is noted, consider rating up the grade of certainty, particularly if it is
noted in the majority of studies.
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CHAPTER 3: RESULTS
3.1. Stage 1: development of the theory of how the intervention works, why and for whom Theory building is usually a neglected aspect of systematic reviews (66). In terms of the narrative synthesis, this can contribute to the interpretation of the review‘s findings and be valuable in assessing how widely applicable these findings might be (66). Hence, I found it useful to develop a model of what Carol Weiss refers to as
an intervention‘s ―theory of change‖ to inform this systematic review (66). The
―theory of change‖ describes the chain of causal assumptions that link
intervention, outcomes, and ultimate goals (66). The theory was created based on the scientific literature and used as a preliminary framework for synthesizing results. The theory for the effectiveness of ADF/ADMF on improving weight management depends upon the prevailing theory of why weight management is poor. The theoretical model can be seen in figure 5.
3.2. Stage 2: development of a preliminary synthesis of findings of included studies 3.2.1. Results of the literature search
After the removal of duplications, I identified a total of 5074 articles with the search in electronic databases and additional records from Google Scholar and reference lists. Among these, 5000 were discarded in the screening process of titles and abstracts because they clearly did not meet the inclusion criteria. I assessed the full texts of the remaining 74 records for eligibility in more detail. Of these records, I excluded 66. The excluded records with reasons can be found in appendix 6. The most common reason for exclusion was not being able to find data for the
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primary outcome of this review. Consequently, eight studies were included. The flow diagram for study selection can be seen in figure 6.
3.2.2. Description of included studies
To organize findings to describe patterns and identify factors that might have influenced the results reported in included studies, I tabulated the main characteristics of included studies which are shown in table 7. All the detailed extracted information for the included studies can be found in appendix 4.
Figure 6. The Flow Diagram
Identification
Included Eligibility Screening
25 Table 7. Brief Overview of the Included Studies
Study ID1
Design Population2 Intervention Comparison Outcomes for the purpose of this
review and measurement methods
Beaulieu et al.
20193 (20)
RCT
Women with overweight and obesity
N= 46 (CER group n=22 IER group n=24 ) Age range: 18-55 years BMI range: 25-34.9 kg/m2
IER period consists of consumption of 25% of baseline energy needs on fast days (24 hours) alternating with ad libitum feed days (24 hours)
Duration of intervention:
12 weeks
CER with consumption of 75% of baseline energy
needs every day
Duration of intervention:
12 weeks
Primary:
- Hunger - Fullness - Desire to eat
Method of measurement: VAS (0 to 100mm)
Secondary:
- Body weight
Method of measurement: Salter scale model 9206 and BodPod (Life measurement, Inc.)
Cai et al.
20194 (17)
RCT
Adults with non-alcoholic fatty liver disease N= 169 (for control and
ADF arms) (Control group n=79
ADF group n= 95) Age range: 18-65y BMI range: >24 kg/m2
ADF period consists of consumption of 25% of baseline energy needs on fast days (24 hours) alternating with ad libitum feed days (24 hours)
Duration of intervention:
12 weeks
CER with consumption of 80% of baseline energy
needs every day
Duration of intervention:
12 weeks
Primary:
- Hunger - Fullness - Satisfaction
Method of measurement: VAS (0 to 100mm)
Secondary:
- Body weight
Method of measurement: Calibrated digital scale
Bhutani et al.
20134 (67)
RCT
Obese adults N=41 (for control and ADF
arms) (Control group n=16
ADF group n=25) Age range: 25-65 y BMI range: 30-39.9 kg/m2
12-week trial with a 4-week ADF controlled feeding period and an 8-week ADF self-selected feeding period. ADF consists of consumption of 25% of baseline energy needs on fast days (24 hours) alternating with ad libitum feed days (24
hours)
Duration of intervention:
12 weeks
Control group participants were asked to maintain their regular food habits.
Duration of intervention:
12 weeks
Primary:
- Hunger - Fullness - Satisfaction
Method of measurement: VAS(0 to 100mm)
Secondary:
- Body weight change
Method of measurement: Balance beam scale (HealthOMeter; Sunbeam Products, Boca
Raton, FL, USA)
Kalam et al. 2020
(68)
Uncontrolled before and after
study
Obese adults N= 52 Age range: 18-65 y BMI range: 30 -50 kg/m2
6 months trial with an ADF low carbohydrate diet with first 3 months consisting of consumption of 600 kcal on fast days (24 hours) alternating with 1000 kcal + ad libitum feed days
(24 hours) and last 3 months consisting of consumption of 600 kcal on fast days (24 hours)
alternating with 600 kcal + ad libitum feed days (24 hours)
Duration of intervention: 6 months
NA
Primary:
- Hunger - Fullness
Method of measurement: VAS (0 to 100mm)
Secondary:
- Body weight
Method of measurement: Digital scale (Omron HBF-500)
