Chronotype, Chrononutrition and Glucose Tolerance Among Prediabetic Individuals: Chrono-DM TM
Conditions: PreDiabetes, Diabetes Mellitus, Type 2
Sponsor: Universiti Tunku Abdul Rahman

 
 
                             
 
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Study Protocol with Statistical Analysis Plan and Informed Consent Form 
 
Title 
Details 
Date 
6 May 2024 
NCT Number 
NCT05163964 
Study title 
Chronotype, Chrononutrition and Glucose Tolerance Among 
Prediabetic Individuals: Chrono-DMTM 
Name and 
Institution of 
Principal 
Investigator 
Dr Koo Hui Chin 
Department of Bioscience 
Faculty of Applied Sciences (FOAS) 
Tunku Abdul Rahman University Management and Technology 
(TARUMT)  
koohc@tarc.edu.my 
 
Name and 
Institution of Co-
Researchers 
Dr Satvinder Kaur D/O Nachatar Singh 
Assistant Professor  
Department of Food Science and Nutrition 
UCSI University, Malaysia 
satvinderkaur@ucsiuniversity.edu.my 
 
Dr Loy See Ling 
Assistant Professor 
Department of Reproductive Medicine 
Duke-NUS Medical School, Singapore 
loyseeling@duke-nus.edu.sg 
 
Dr Tan Hui Yin 
Deputy Dean 
Faculty of Applied Sciences 
Tunku Abdul Rahman University Management and Technology 
(TARUMT)  
hytan@tarc.edu.my 
 
Dr Sarjit Singh A/L Dr Harjit Singh 
Physician 
Department of Emergency and Trauma 
Hospital Serdang, Malaysia 
sarjitsingh83@hotmail.com 
 
Prof. Dr. Ruzita Abd Talib 
Professor, Deputy Dean of Graduate School, Lecturer 
Faculty of Health Sciences  
Universiti Kebangsaan Malaysia 
rzt@ukm.edu.my 
 
Sub investigators 
at the site and Co-
Researchers 
 
 
Dr Rosmiza Binti Abdullah  
Family Specialist 
Community Clinic Batu Berendam, 
rosmiza1@hotmail.com 
 

 
 
                             
 
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Dr Hanisah Binti Mahmud 
Medical Officer 
Community Clinic Batu Berendam 
hanisahbtemahmud@gmail.com 
 
Siah Woan Yie 
Clinical/ Community Dietitian 
Community Clinic Kuala Sungai Baru 
Ministry of Health 
siahwoanyie@gmail.com 
 
Principal 
investigators at 
the site and Name 
of PhD Student 
Chong Guey Yong 
Department of Bioscience 
Faculty of Applied Sciences (FOAS) 
Tunku Abdul Rahman University Management and Technology 
(TARUMT)  
chonggy-wr21@student.tarc.edu.my 
Study Population 
Prediabetic individuals in Community Clinic Melaka 
Study Design 
Study Type: Prospective Longitudinal Study 
Sampling Method: Convenient sampling method 
General Objective 
To determine the associations of chronotype and chrononutrition 
with glucose tolerance among prediabetic individuals in Malaysia. 
Specific 
Objectives 
1) To investigate the effect of chrononutrition on glycemia 
measures among prediabetic individuals.  
2) To investigate the associations of lifestyle factors with 
glycemia measures among prediabetic individuals.  
3) To investigate the associations of anthropometric 
measurements with glycemia measures among prediabetic 
individuals. 
Study outcomes 
The main outcomes of this study are 
1) The change of baseline glycated hemoglobin (HbA1c) among 
prediabetes adults at 6 months. 
2) The change of baseline fasting plasma glucose (FPG) among 
prediabetes adults at 6 months. 
3) The change of baseline 2-hour post-load plasma glucose 
among prediabetes adults at 6 months. 
4) The change of baseline continuous glucose monitoring (CGM) 
profile among prediabetes adults at 6 months. 
 
Secondary outcome of this study are 
1) The change of eating misalignment among prediabetes adults 
at 6 months. 
2) The change of chronotype among prediabetes adults at 6 
months. 
Sample Size 
120 prediabetic individuals 
Study Duration 
1 March 2022 until 31 December 2023 
Name and 
Address of 
Sponsor 
Fundamental Research Grant Scheme (FRGS), Ministry of 
Higher Education/ UMalaya (FRGS/1/2021/SKK06/TARUC/02/1) 

 
 
                             
 
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Ethics Approval 
Tunku Abdul Rahman University Management and Technology 
Ethics Committee (TAR UC/EC/2021/02-3) 
Medical Research and Ethics Committee (RSCH ID-21-00114-
IVI) 
 
 
Executive Summary:  
 
Early meal timing affects the circadian rhythmicity and influenced the postprandial 
blood glucose level in response to meal in diabetes patients. In the other words, 
diabetes patients with earlier meal timing had a stable glycemic control compared with 
those with late meal timing. This is a new concept to switch the meal timing earlier 
than later in diabetes self-monitoring management. However, there is insufficient 
evidence from Southeast Asia to determine the optimal-meal-timing and its association 
with glycemic measures in prediabetes individuals. Hence, this study carried out to 
determine the associations of chronotype and chrononutrition with glucose tolerance 
among prediabetic individuals in Malaysia. 
 
1. INTRODUCTION AND JUSTIFICATION OF THE STUDY 
 
Diabetes Mellitus is the chronic non-communication diseases which elevated blood 
glucose level and human body unable to utilize it effectively, hence cause rise of 
complications to microvascular and macrovascular damage (IPH, NIH and MOH, 
2019). There are about 463 million of patients aged 20 until 79 years old diagnosed 
diabetes in worldwide (IDF, 2019). It showed an increasing trend adults living with 
diabetes from 108 million in year 1980 until 422 million in year 2014 (IDF, 2019). 
International Diabetes Federation, (2019) estimated diabetes will affected in 578 
million of adults globally in year 2030 and it reach up to 700 million of worldwide adults 
in year 2045. 373.90 million western pacific people had impair blood glucose 
commonly among adults aged 20 years old until 79 years old and it is the highest in 
global(IDF, 2019). 8% of western pacific adults had impaired glucose tolerance and 
55.8% of them are undiagnosed diabetes (IDF, 2019).  
 
Malaysia is one of the countries in Western Pacific region and have Peninsular 
Malaysia and East Malaysia which separated by South China Sea (Hussein et al., 
2015). In the latest Malaysia National Health and Morbidity Survey, the total diabetes 
incidence among adults ages 18 years old and above in Malaysia is about 3.9 million 
(18.3%), which indicated that 1 in 5 Malaysian adults have diabetes (IPH, NIH and 
MOH, 2019). The highest prevalence of diabetes found in state Negeri Sembilan 
(33.2%), followed by Perlis (32.6%) and Pahang (25.7%) (IPH, NIH and MOH, 2019). 
The rise of diabetes, hypertension and cholesterol increase the risk to develop 
cardiovascular disease and it leading to death (IPH, NIH and MOH, 2019). There are 
1.7 million Malaysian adults stay with these three major risk factors of cardiovascular 
disease (IPH, NIH and MOH, 2019). Besides, 1 in 4 adults in Malaysia are physically 
not active and 95% of adults did not consume recommended both fruits and 
vegetables (IPH, NIH and MOH, 2019). Sugar are the preferable substitute in self-
prepared drinks (coffee, tea, chocolate and malt beverages), and 4.2% adults in 

 
 
                             
 
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Malaysia drink carbonated drinks and non-carbonated drinks daily. Instant drink 
products contained sugar also another choice of adults Malaysian daily (IPH, NIH and 
MOH, 2019). The development of diabetes related module by Ministry of Health and 
Malaysia Diabetes Educators Society emphasize 7 section diabetes management  
(MDES, 2020), included assessment, healthy eating, physical activity, medication, 
self-monitoring , disease complications and behavior. Despite the numerous strategies 
have been implemented by Malaysian government, however, it has failed to 
substantially reduce the prevalent of T2DM from prediabetes in Malaysia. Perhaps, 
there is a missing ingredient in diabetes guidelines today.  
 
Management of excessive caloric intake and promote on exercise are both core 
lifestyle modification for T2DM which have been recommended in several diabetes 
management guidelines (MDES, 2020; MOH et al., 2020; WHO, 2020). However, 
other factors such as dysregulation of circadian rhythms may also contribute to 
disease development (Onaolapo and Onaolapo, 2018). The growth of chronobiology 
and evidence on disturbed circadian rhythm contributed to dysfunction of carbohydrate 
and macronutrients metabolism and it related to hormone melatonin (Onaolapo and 
Onaolapo, 2018). From a chronobiological point, glucose metabolism in humans follow 
a circadian rhythm through diurnal variation of glucose tolerance that typically peaks 
during day-light hours, when food consumption usually happens and reduces when it 
comes to night-dark hours when fasting usually occurs (Henry, Kaur and Quek, 2020). 
Unusual meal timings can cause glucose intolerance by affecting the phase 
relationship between the central circadian pacemaker and peripheral oscillators in 
cells of the liver and pancreas in rodents (Bandin et al. 2015). Similarly in humans, 
timed meal intake is also driven by the suprachiasmatic nucleus, play a role in 
synchronization of circadian rhythms in peripheral tissues, thereby affecting glucose 
metabolism (Henry, Kaur and Quek, 2020). The effects of diet on circadian rhythmicity 
clearly involves a relationship between factors such as meal timings and nutrients 
(chrononutrition), that can contribute to circadian perturbance and influence the 
manifestation of metabolic disorders such as type 2 diabetes; by extension, circadian 
timing may also be important in prevention of T2DM development from prediabetes. A 
new concept is born: perhaps it is not what you eat but when you choose to eat it.  
 
In Malaysia, there are no specific guideline for prediabetes individual and they are 
managed according to the latest Clinical Practice Guideline in Malaysia (MOH et al., 
2020). For prevention prediabetes to further develop to diabetes, lifestyle intervention 
such as weight loss (5-10% of initial body weight), regular physical activity (150 
min/week), with dietary strategies including reduced calories and behavior 
modification are recommended in Clinical Practice Guideline in Malaysia (MOH et al., 
2020). A high fibre diet (20-30g/day with 5 to 7 servings/day) consisting of vegetables, 
fruits, legumes and whole grains is encouraged too (MDES, 2020). All the prediabetic 
individuals will be referred to dietitian and nurse educators for 6 months routine 
treatment, prior to T2DM diagnosis, determined by second-round of oral glucose 
tolerance test (OGTT) in 6-month period (MOH et al., 2020). To the puzzlement of 
many diabetes researchers and clinicians, some of the prediabetes cases showed 
tremendous improvement in their blood sugar result, yet some of the prediabetes 

 
 
                             
 
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individuals developed full-blown of T2DM with their blood sugar result higher than the 
normal range; despite all of them followed the same routine treatment from healthcare 
clinics. Perhaps, besides the usual routine treatment from Clinical Practice Guideline 
(MOH et al., 2020) (weight management, physical activity advices and dietary 
modification); prediabetic individuals who able to improve their blood sugar result in 6-
month period has particular meal-timing, compared to those has uncontrolled blood 
sugar result in 6-month period.  
 
Although clinical practice guideline applied in the routine treatment does not include 
meal-timing advices, but the importance of circadian rhythms in regulating mammalian 
physiological responses has been recognized (Mezitis and Bhatnagar, 2018). Mezitis 
and Bhatnagar, (2018) from United States of America (US) has emphasized the 
importance of circadian timing in people with diabetes because insulin sensitivity has 
been shown to exhibit circadian rhythmicity. Glycemic responses to meals are 
exaggerated in prediabetes and diabetes patients, more so when the meal is timed to 
be consumed out of sync with the metabolic pacemaker. Accordingly, Mezitis and 
Bhatnagar, (2018) have recognized optimal hormonal and hepatic function beginning 
in the early morning (4:00 a.m.) and fading in the early evening (4:00 p.m.). However, 
the times proposed by Mezitis and Bhatnagar, (2018) suitable for diabetes patients in 
US, and might not be able to apply in Malaysia diabetes management. This is because 
circadian timing system is affected by factors consisting of cosmic events related to 
the universe and earth, environmental factors (light, night and day duration, seasons) 
and lifestyles. To the best of our understanding, neither have there been any studies 
that have exploring the new concept of circadian timing in Malaysia prediabetes 
individuals, nor in Southeast Asia. The outcome of the present study will be able to 
recognize the optimal-meal-timing (chrono-nutrition) and activity/ sleeping (chrono-
type) among Malaysian prediabetic individuals, in order to prevent prediabetes 
individuals from developing T2DM. Figure 1 shows the theoretical framework of the 
present study, adapted from Henry, Kaur and Quek, (2020). The theoretical framework 
shows that a schematic representation outlining the factors affecting the circadian 
clock system. Meal timing and dietary components (chrono-nutrition) play an important 
role in regulating circadian clocks, to enhance metabolic health and reduce the risk of 
type 2 diabetes. These recommendations could be considered as strategies to 
improve glycemic control, rather than focusing on the nutritional value of a meal alone, 
to optimize dietary patterns of diabetics. It is necessary to further elucidate this 
fascinating area of research to understand the circadian system and its implications 
on nutrition that may ultimately reduce the burden of type 2 diabetes. 
 

 
 
                             
 
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Figure 1 Theoretical framework showed factors affecting circadian rhythm.  
 
The investigator propose that the individual is nested within their environment which 
includes the influences of social demands e.g. social timing resulting from demands 
such as school or work schedules, social activities, family obligations and routines, 
parenting practices, community involvement, time zone, etc., the modern lighting and 
climate controlled environment, as well as the effect of the earth’s natural environment. 
Within the individual, there is an interdependence of the circadian clocks, behavior, 
and health. The major contribution of this model is that the circannual clock interacts 
with the circadian clocks to promote optimal glucose tolerance of individual’s 
circannual influences may have health consequences. The investigator propose 
interactions within the individual and across levels of this model. For example, social 
demands influence an individual’s behavior which affects alignment of the clocks either 
by direct entrainment of the peripheral clocks (i.e., meal timing and consistency) or by 
affecting exposure to the light-dark cycle via sleep timing and consistency, physical 
activity, and exposure to artificial light at night. It is also proposed that circadian 
disruption caused by the environmental factors may contribute to disruption of 
circannual rhythms of growth, resulting in accelerated blood sugar and contributing to 
the development of type 2 diabetes mellitus. 
 

 
 
                             
 
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Figure 2 Conceptual framework  
 
Identifying novel, potentially modifiable, life-style factors associated with increased 
blood sugar level, can lead to innovative strategies for improving health status and 
preventing T2DM in prediabetes individuals. The proposed study presents a novel 
approach as a paradigm shift in Malaysia diabetes management. The investigator 
anticipate that this study will not only reveal the optimal-meal timing (chrono-nutrition) 
for prediabetic individuals, it will also disclose the associations of chrono-nutrition with 
glycemic measures and anthropometric measurements in prediabetic individuals. The 
findings may act as guidance to government bodies to develop policies at national 
level. For non-governmental agencies, the outcome may be applied to plan public 
campaigns to improve blood sugar outcome in prediabetic and diabetic individuals. 
Besides, optimal-meal timing and factors associated with chrono-nutrition would be 
identified and management of these factors can be delivered to diabetic individuals. 
For example, improvement of the dietary pattern and timing coupled with physical 
activity to ensure good blood sugar control. Understanding the optimal-meal-timing for 
blood sugar control could tailor education and intervention in diabetes management. 
This research has potential to be converted into a larger cohort study and intervention 
whereby prediabetic individuals could be follow-up for longer duration to study health 
outcomes and blood sugar control to manage the diabetes 
 
 
 
 
 
 
 
 
 

 
 
                             
 
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2. LITERATURE REVIEWS 
 
1.0 Diabetes mellitus  
 
The pathophysiology of type 2 diabetes mellitus (T2DM) is complex and involves 
insulin resistance, pancreatic β-cell dysfunction and visceral adiposity. T2DM is now 
a disease of major concern both globally and regionally; and is a leading cause of 
death in most countries (WHO 2017). In 2017, the International Diabetes Federation 
(IDF) estimated that 382 million people had diabetes worldwide, and by 2035, this was 
predicted to rise to 592 million. Almost all developing countries in the Western Pacific 
region and also in Southeast Asia have shown escalating diabetes rates. Eighty 
percent live in low- and middle income countries, and of the total, more than 60% live 
in Asia, with almost one-third in China (IDF 2017). An estimated 82 million adults aged 
20-79 years were living with diabetes in the Southeast Asia region in 2017, 
representing a regional prevalence of 8.5% . About 45.8% of these diabetes case were 
undiagnosed (IDF 2017). In Malaysia, prevalence of diabetes has drastically increased 
from 6.3% (IPH 1986) to 18.3% (IPH 2019). Major increase in the prevalence of 
diabetes have occurred in developing countries due to rapid and ongoing 
socioeconomic transition and will likely lead to further rises (Nanditha et al. 2016).  
 
1.1 Prediabetes  
 
Prediabetes is defined as a condition in which people have higher than normal blood 
glucose levels but not high enough for a diagnosis of diabetes. Prediabetes prevalence 
is higher than that of diabetes in China and many of the Western Pacific region 
countries, this is true of many countries in Asia (IDF 2017). South Asian population 
also have a high prevalence of prediabetes and a more rapid progression to diabetes 
(IDF 2017). In Malaysia, National Health and Morbidity Survey (IPH 2019) found the 
prevalence of prediabetes was 8.9%. These prevalence were likely to be 
underestimates because diagnosis relied only on a single fasting blood sugar, history 
of physician diagnosis and information on medication (Nanditha et al. 2016). Globally, 
an estimated 318 million people had prediabetes in 2015, with a projected alarming 
increase to 482 million in 2040 (IDF 2015). Prediabetes is high-risk condition for 
diabetes and cardiovascular disease (Nanditha et al. 2016). Without appropriate 
interventions, 5.8%-18.3% of people with prediabetes develop diabetes yearly 
(Anothaisintawee et al. 2017). How to prevent the development of diabetes from 
prediabetes?  
 
2.0 Preventing diabetes development from prediabetes  
 
Identifying additional modifiable risk factors may lead to a research to develop novel 
lifestyle interventions to reduce incident diabetes from prediabetes. While there are 
many factors that influence the development of type 2 diabetes (T2DM), it is evident 
that the most influential are the behaviors commonly associated with urbanization and 
a modern lifestyle (Early & Stanley 2018). Randomized controlled trials from different 
parts of the world including United States, China, India and elsewhere have 

 
 
                             
 
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established the proof of principle that lifestyle modification with physical activity and/ 
or healthy diet can delay or prevent the onset of type 2 diabetes (Anothaisintawee et 
al. 2017; Early & Stanley 2018). Dietary recommendations of World Health 
Organization (WHO) for the prevention of T2DM include limiting saturated fatty acid 
intake to less than 10% of total energy intake (and for high risk groups, less than 7%); 
and achieving adequate intake of dietary fiber (minimum daily intake of 20 grams) 
through consumption of wholegrain cereals, legumes, fruits and vegetables (WHO 
2017). WHO strongly recommends reducing the intake of free sugars to less than 10% 
of total energy intake (WHO 2017), IDF fully supports these recommendations and in 
response published the IDF framework for Action of on Sugar (IDF 2017) Modern 
lifestyle are characterized by physical inactivity and long sedentary periods. 
Community-based interventions can reach individuals and families through campaigns, 
education, social marketing and encourage physical activity both inside and outside 
workplace (Early & Stanley 2018). IDF recommends physical activity at least between 
three to five days a week for a minimum of 30-45 minutes (IDF 2017). WHO has also 
developed recommendations on physical activity among different age groups, similar 
to IDF (WHO 2017), to prevent T2DM. Taking a life course perspective is essential for 
preventing type 2 diabetes and its complications. Early in life, when eating and 
physical activity habits are established and when the long-term regulation of energy 
balance may be programmed, there is an especially critical window to obtained a 
normal weight and mitigate the risk of T2DM (Zarrinpar et al. 2016). Despite 
recommendations from WHO and IDF have been adopted in Clinical Practice 
Guideline of T2DM in Malaysia (MOH 2015); to the befuddlement of many diabetes 
researchers and clinicians, it has failed to substantially reduce the prevalent of T2DM 
from prediabetes in Malaysia. Perhaps, there is a missing ingredient in diabetes 
guidelines today. Numerous studies suggested that the main risk factors for T2DM are 
excessive caloric intake and a lack of exercise; however, other factors such as 
disturbed sleep/wake rhythms may also contribute to disease development (Onaolapo 
& Onaolapo 2018). In recent years, several lines of evidence have increasingly 
demonstrated the role of the biological circadian clock and multiple clock genes in 
contributing to T2DM pathogenesis. There is a growing body of knowledge associating 
alterations in circadian rhythms and circadian genes with the development of T2DM 
(Onaolapo & Onaolapo 2018). While the implication of this advance in knowledge for 
the prevention and therapeutic management of diabetes mellitus is evolving, there are 
strong indications that circadian misalignment is relevant for the regulation of blood 
sugar level in chronic shift workers (Morris et al. 2017) and insulin resistance 
(Hashinaga et al. 2013) in rodents’ model; by extension, may also be important in 
prevention of T2DM development from prediabetes. Human and animal studies from 
Western countries suggested that desynchronize between components of the 
circadian timing symptom and the behavioral rhythms of feeding/ fasting and activity/ 
sleep, or the external rhythm of light/ darkness may contribute to the pathophysiology 
of obesity and T2DM (Onaolapo & Onaolapo 2018). However, such relevant advices/ 
information are not included in pathophysiology of obesity and T2DM (Onaolapo & 
Onaolapo 2018). However, such relevant advices/ information are not included in any 
diabetes guidelines, particularly in Malaysia. Therefore, the need to drastically reduce 

 
 
                             
 
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the global prevalence of T2DM necessitates a widening of the search for etiological 
factors.  
 
3.0 Circadian timing system  
 
To everything there is a rhythms. In most organisms, each day is organized into two 
phases: (1) activity and feeding and, (2) rest and fasting. The circadian system, 
controlled by the master circadian clock located in the suprachiasmatic nuclei (SCN) 
of the hypothalamus, plays a major role in regulating daily rhythms of sleep/ wake and 
various metabolic outputs, such as peripheral tissue metabolism, feeding behavior and 
hormone secretions, generate a rhythm of approximately 24-h (hence ‘circadian’) 
(Johnson et al. 2017). As a discipline, the study of these rhythms has grown in leaps 
in bounds during the past quarter century. The pursuit of understanding in 
chronobiology has taken us from the flowering plant and the fruit fly to the mammalian 
nervous system and back. Within this endeavor, study of the intersection between the 
circadian timing system and metabolism has experienced an almost herculean pace 
of advancement (Perelis et al. 2016). Although interest in the topic of clock function 
and metabolism has percolated across the years, curiosity seems to have boomed in 
the early 21st century thanks to the cloning of the mammalian clock genes, the 
availability of various rodent genetic models, and the advances made by a number of 
excellent clinical sleep research labs (King et al. 1997). In 2005, a group of researchers 
published a brief but highly impactful paper, wherein they revealed that mice with a 
dominant negative mutation of the Clock locus became obese on a standard diet 
(Turek et al. 2005). Turek et al. (2005) suggested a new paradigm, one in which 
disrupting or altering the clock at the biochemical level could itself produce metabolic 
dysfunction. In the years that followed, it was determined that obesity in the Clock 
mutant mouse was likely due, in part, to a disturbance in the balance of food intake 
across the 24-hour day (Arble et al. 2010). That is, food intake out of phase with the 
bodies internal clock (eg, late night snacking) leads to considerable weight gain in 
otherwise healthy animals (Astiz et al. 2019). A new concept was born: perhaps it is 
not what you eat as much as when you choose to eat it. Although the importance of 
circadian rhythms in regulating mammalian physiological responses has been 
recognized for a long time, its impact on nutrition and metabolism is relatively new and 
is an area of evolving interest (Mezitis & Bhatnagar 2018).  
 
3.1 Chrono-nutrition and blood glucose homeostasis  
 
It has been recognized for nearly five decades that, in rodents’ model, there was a 
diurnal rhythm in glucose tolerance. Oral glucose, intravenous glucose infusions, and 
identical meals all results in a significantly higher elevation of plasma glucose (i.e., 
lower glucose tolerance) in the evening than in the morning. Because they are 
nocturnal (i.e., active at night), they have lower glucose tolerance during the daytime 
(resting phase) than nighttime (active phase) (la Fleur 2001). There are multiple 
factors that could contribute to the reduced glucose tolerance, including decreased 
insulin sensitivity, excessive hepatic glucose production (HGP), and decreased 
betacell function. Study has shown that in healthy humans, both insulin sensitivity and 

 
 
                             
 
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beta-cell responsivity to glucose are lower at dinner than at breakfast (Astiz et al. 2019). 
The role of HGP in the diurnal regulation of glucose homeostasis in normoglycemic 
humans is still not clear. While some studies showed a sleep-associated fall in HGP 
(Shigiyama et al. 2018) and an increased HGP at dawn (Wu et al. 2017), other studies 
found no diurnal rhythm in 24-hr fasting HGP (Jamshed et al. 2019) or a lower pre-
meal HGP at breakfast comparing to lunch and dinner (Ferrer-Cascales et al. 2018). 
Different meal schedule on the test day in these studies may contribute to the different 
observation. However, convincing evidence has demonstrated a clear diurnal rhythm 
of HGP in patients with T2DM that contributes to the dawn phenomenon 
(hyperglycemia in the morning) often observed in the diabetic patients (Wu et al. 2017). 
The elevated morning HGP before breakfast could be due to a prolonged overnight 
fast and the resultant surge of counter regulatory hormones (e.g., cortisol, growth 
hormones and norepinephrine) and/or due to a circadian modulation of HGP as 
suggested by rodent studies (la Fleur 2001). It is well recognized that food intake, 
appetite, digestion and metabolism each exhibit circadian patterns (Almoosawi et al. 
2016). Nutrients ingested during the active period provide substrates such as glucose, 
lipids and amino acids, which fuel the metabolic pathways in our cells, whereas during 
the resting period energy and substrates stored in our body are mobilized to sustain 
metabolic homeostasis (Bhadra et al. 2017). Food intake itself serves as a regulator 
of the circadian clock, particularly the peripheral circadian clock in tissues such as the 
liver and the intestine (Astiz et al. 2019). Conversely, the central circadian clock, 
entrained by the darklight cycle, is known to extend its effect on food absorption. More 
specifically, small peptides cleaved in the intestine from dietary carbohydrate have 
been shown to be transported in a circadian driven process (Almoosawi et al. 2016). 
Blood glucose homeostasis can be seen as a paradigm of the circadian control of 
energy metabolism. Indeed, whereas during the activity/feeding period blood glucose 
is mainly of dietary origin, during the resting/starvation period glucose is progressively 
recruited from endogenous glucose production in the liver to maintain blood glucose 
levels within a relatively narrow range. In this process liver glycogen content 
undergoes large daily fluctuations to sustain blood glucose levels, as glycogen 
synthesis and degradation are specifically recruited during the activity/feeding and 
resting/starvation periods, respectively (Karthikeyan et al. 2018). In modern societies, 
individuals often consume food at different time points during the day, away from home 
and therefore at what may be considered, from an evolutionary perspective, 
physiologically inappropriate times of the day (Almoosawi et al. 2016). This irregularity 
in eating patterns is often enforced by external pressures to conform to social 
schedules. Increasingly, individuals often engage in activities that are misaligned with 
their circadian clock system and the natural rhythm of the light-dark cycle. The 
resulting misalignment between the sleep-awake, fasting-feeding cycles and the light-
dark cycle subsequently disrupts the natural oscillations of physiologic processes such 
as lipid metabolism and blood pressure, eventually manifesting itself as heightened 
risk of developing T2DM (St-Onge et al. 2017). Therefore, besides time-of-the-day 
dietary intake; prediabetes individuals may also look at the time-ofthe-day activities 
e.g. sleep or awake to prevent T2DM development.  
 
 

 
 
                             
 
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3.1.1 Meal intakes timing of ingestion: morning versus dinner  
 
Evidence suggests that meal ingestion in the morning and late evening (time of day) 
influence glucose metabolism in humans. Earlier studies, using mixed meals or 
glucose infusion, have reported circadian responses of reduced glucose tolerance and 
insulin sensitivity in healthy participants for the evening rather than in the morning 
(Almoosawi et al. 2016). An acute study which examined the effects of a late evening 
meal on diurnal variation of blood glucose in healthy individuals, assessed by 
continuous glucose monitoring (CGMS™). There was an increase in blood glucose 
after the late evening meal which shifted towards later at night, with peaking of blood 
glucose observed during sleep (Astiz et al. 2019). Late evening meals may cause 
postprandial hyperglycaemia with this decrease in glucose tolerance from morning 
towards the night. A cohort study was the first to show the relationship between late-
night dinner consumption and glycaemic control in type 2 diabetics, whereby having a 
late dinner meal after 8 pm was independently associated with an increase in HbA1c 
(Sakai et al. 2018). In some acute trials, both healthy individuals (Kajiyama et al. 2018) 
and type 2 diabetics (Imai et al. 2017) showed significantly higher blood glucose and 
insulin values after night-time meals. These studies deduce that the disruption of the 
circadian rhythm led to the exacerbation of the physiological nocturnal decrease of 
glucose tolerance. Peter et al. showed that type 2 diabetic subjects who ate three 
identical meals had glucose excursions that were higher in the morning than in the 
evening (Sakai et al. 2018). There was increased glucose tolerance in response to the 
first and third meals of the day, irrespective of glycaemic control. There was also a 
change in circadian variation in insulin sensitivity in type 2 diabetics (Sakai et al. 2018). 
Type 2 diabetics exhibit a different daily circadian pattern from healthy individuals, with 
increased insulin sensitivity towards the night, and higher glucose excursions in the 
morning than in the evening. Methods to improve glycaemic control at dinner has been 
reported by some authors. Dinner that was divided into two smaller meals reduced 
post-meal glycaemic excursions, due to the “second-meal effect” phenomenon, by 
enhancing β-cell responsiveness (Karthikeyan et al. 2018) at the second dinner meal 
induced by the first meal (Imai et al. 2017). It was also suggested that if meal size and 
carbohydrate quantities were smaller, postprandial glucose can be ameliorated in both 
healthy and type 2 diabetics. In summary, time of day is indicative of having an 
influence on the postprandial glucose response to a meal. There is a defined circadian 
pattern for postprandial glycaemia for similar meals consumed either in the evening or 
morning. Glucose metabolism is not only affected by what and how much you eat 
alone, but also when the meal is consumed. However, more data from well-designed 
epidemiological studies is necessary to prove causality. Mezitis & Bhatnagar (2018) 
emphasize the importance of chrononutrition in people with diabetes because even 
insulin sensitivity has been shown to exhibit circadian rhythmicity. Glycemic responses 
to meals are exaggerated in these individuals, more so when the meal is timed to be 
consumed out of sync with the metabolic pacemaker (Almoosawi et al. 2016). 
Accordingly, Mezitis & Bhatnagar (2018) recognize optimal hormonal and hepatic 
function beginning in the early morning (4:00 a.m.) and fading in the early evening 
(4:00 p.m.). Review of glucose records—increasingly more abundant in the era of 
continuous glucose monitoring (CGM), which permits review of several months of 

 
 
                             
 
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detailed glucose profiling and follow-up care—confirms that evening lifestyle defines 
morning glycaemia, thus setting the stage for the day’s profile. Late-night feeding and 
night-shift work introduce a “jet-lag” experience, which, when sustained, virtually 
guarantees metabolic dysregulation.  
 
3.2 Chrono-type and blood glucose homeostasis  
 
Individual differences in the time at which people refer to do particular behaviors, most 
notably sleep, are referred to as chrono-type (Anothaisintawee et al. 2017). It is a 
behavioral manifestation of an individual’s internal circadian clock system, which can 
be assessed with the use of multiple methodologies that classify individuals as having, 
e.g., a morning or an evening type (Gottlieb et al. 2015). Chrono-type is also used to 
describe personality traits associated with the preferred times-of-the-day for activities 
such as sleep or awake (Anothaisintawee et al. 2017). Generally, in the absence of 
environmental stimuli such as light, endogenous circadian clocks oscillate in a manner 
approximating a 24-hour cycle (Astiz et al. 2019). An individual’s chrono-type is likely 
created by an interaction between the endogenous circadian pacemaker and its 
responses to light (Astiz et al. 2019) and can be modulated by factors such as age 
(Fischer et al. 2017) and life circumstance (e.g., needing to get to work early over 
years may shift preference towards earlier hours). In our modern society, night-shift 
work, which requires workers to eat and be active during their circadian night and sleep 
during their circadian day, represents and extreme form of circadian misalignment. A 
recent meta-analysis of 10 cohort studies (262294 participants) revealed that shift 
work was associated with a 40% increase in the risk of developing T2DM 
(Anothaisintawee et al. 2015). Recently, epidemiological and experimental studies 
have demonstrated that sleep quality and quantity are important determinants of 
whole-body metabolism. It has been suggested that impaired sleep might causally 
contribute to the T2DM (Sakamoto et al. 2018). Despite the clear association between 
short sleep and metabolic impairments, the underlying endocrine and molecular 
mechanisms remain only partially elucidated. Among the suggested mechanisms, the 
causal role of the hypothalamus-pituitary-adrenal (HPA) axis and sympathetic 
activation are supported by the largest body of literature. Circulating cortisol, assessed 
either by 24 h profiles or by single measurements of evening cortisol levels, were 
elevated together with markers of sympathetic activation and circulating 
catecholamine after total or partial sleep deprivation as well as in short sleepers 
(Reynolds et al. 2012). In contrast, some studies reported impairments in glucose 
homeostasis in sleep restricted individuals along with unchanged cortisol and 
catecholamine levels (Buxtone et al. 2012). The complexity of associated endocrine 
mechanisms can be further demonstrated by observations of elevated levels of pro-
inflammatory cytokines, lower circulating testosterone, decreased thyroid stimulating 
hormone levels and changes in adipokines secreted from adipose tissue in sleep 
deprivation (Froy & Garaulet 2018). Evening types (or late chrono-types) typically have 
later bedtime than those who are morning types (or early chrono-types). Those with 
later chrono-type usually experience a mild form of circadian misalignment due to a 
greater degree of misalignment between social rhythms and the circadian clock, a 
phenomenon called “social jetlag” (Fischer et al. 2017). In an individual presenting with 

 
 
                             
 
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an extreme evening chrono-type, the circadian phase of biological rhythms could be 
shifted by as much as much as 2-3 hours compared with that of an extreme morning 
chrono-type (Kantermann et al. 2015). This shift can result in a desynchronization 
between the period of biological night, as regulated by the intrinsic circadian clock 
system, and the environmental night governed by the light-dark cycle (Kantermann et 
al. 2015). Patients with T2DM, later chrono-types and evening preferences have been 
found to be associated with poorer glycemic control (Brady et al. 2019). A recent study 
revealed that evening type was associated with an increased risk of having type 2 
diabetes in prediabetes individuals (Anothaisintawee et al. 2017). These data may 
demonstrate the contribution of circadian regulation on reversing prediabetes from 
developing T2DM in the future.  
 
4.0 In summary  
 
As shown above, evidence that provides new insight into clock function and the 
pathophysiology of type 2 diabetes is accumulating rapidly. Disruption of circadian 
rhythms, such as that due to shift work, affects not only body weight and adiposity, but 
glucose metabolism itself. Since the magnitude of these effects in the present increase 
seen in the development of type 2 diabetes is obscure, more precise mechanisms and 
the relative importance of these factors in the development of type 2 diabetes should 
be investigated. To achieve this goal, it will be necessary to establish methodologies 
to measure parameters of circadian systems in feeding and glucose and lipid 
metabolism. In addition, it is also necessary to analyse the contribution of circadian 
gene variations in the development of type 2 diabetes. Clinical studies related to the 
development of type 2 diabetes are also needed to evaluate the health-compromising 
behaviours that affect circadian disruption with definitions that include chrono-type or 
circadian typology. According to the currently available data, medical nutrition therapy 
for Malaysian diabetes should include meal timing as one of the strategy, to manage 
glycaemic control. Study should be conducted to determine the optimal-meal-timing to 
manage blood sugar level. Although it is very difficult to control meal timing for every 
individual patient with prediabetes or type 2 diabetes, a socioeconomical approach 
such as recommendations regarding the work environment may also be important. 
Although there is now insufficient evidence to evaluate the impact of these chrono-
physiological disruptions on the progression or pathophysiology of diabetes precisely, 
future focused research on these issues can answer these questions. 
 
Identifying novel, potentially modifiable, meal-timing, chrononutrition, life-style factors 
associated with glycemic measures; can lead to innovative strategies for improving 
health status and preventing T2DM in prediabetic individuals. The proposed study 
presents a novel approach as a paradigm shift in Malaysia diabetes management. The 
investigator anticipate that this study will not only reveal the optimal meal-feeding for 
Malaysia prediabetic individuals to improve their blood glucose level, it will also provide 
greater insight of the associations of chrononutrition, lifestyle factors and 
anthropometric measurements with glycemic measures. The findings will also set the 
directions to adopt optimal-meal-timing approach in Clinical Practice Guideline for 
diabetes. The investigator anticipate that our proposed study which incorporate the 

 
 
                             
 
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circadian timing, as a novel approach, may provide the fundamental information that 
could be adopted by the government and policy makers. The outcome can be included 
in the future clinical practice guideline or to develop innovative and effective lifestyle 
interventions to improve the T2DM prevalent in Malaysia. 
 
 
3. RESEARCH METHODOLOGY 
 
Hypothesis:  
 
The morning chronotype and early meal-timing are associated with low glycemic 
outcome among prediabetic individuals. 
 
Research Questions:  
 
Is the morning chronotype and early meal-timing are associated with better glucose 
tolerance among prediabetic individuals? 
 
General objective:  
 
To determine the associations of chronotype and chrononutrition with glucose 
tolerance among prediabetic individuals in Malaysia. 
 
Specific objectives:  
 
1. To examine the associations among chronotype, chrononutrition and glucose 
outcomes.  
2. To investigate the association between lifestyle factors (physical activity level, light 
exposure, diet timing, sleep pattern) and chrononutrition.  
3. To investigate the association between anthropometry measurements and glycemic 
outcomes. 
 
Description of Methodology: 
 
Participants will be recruited using the convenience sampling method. The proposed 
study will be conducted in community clinics in Malacca, Malaysia. Malacca is the 
capital of the coastal stage, located in southwestern Malaysia, with an estimated total 
population of 0.93 million in the year 2019 (Department of Survey and Mapping 
Malaysia, 2021). In 2019, National Health and Morbidity Survey reported that 17% of 
Malaccan adults had hyperglycemia and 13.7% of them had known diabetes. Malacca 
is 1 out of the top five states showing the highest prevalence of diabetes in Malaysia 
(IPH, NIH and MOH, 2019). Permission to carry out data collection has been granted 
by the Medical Research and Ethics Committee (MREC) (RSCH ID-21-00114-IVI). 
The study protocol has been reviewed and approved by the Tunku Abdul Rahman 
University College (TARUC) research ethics committee (TAR UC/EC/2021/02-3). 
 
During the process of recruitment, a trained research assistant (one of the co-
researcher), clinical dietitian (one of the co-researcher) or family medicine specialist 

 
 
                             
 
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(one of the co-researcher) will inform potential prediabetic individuals research 
protocol verbally and written information will be provided. Newly diagnosed prediabetic 
individuals who are agreeable to participate will provide written informed consent. 
Baseline and follow up appointments will be determined based on the community clinic 
appointment schedules. Those who decline to participate will continue to receive their 
routine treatment as usual, and care provided to each prediabetic individual will not be 
affected by the  decision to either participate or not participate in the study. 
 
Those who meet the inclusion criteria will be invited to participate in this study. Eligible 
participants shall meet all the following inclusion criteria. 
 
1) Newly diagnosed prediabetic individuals who have been first seen by clinical 
dietician registered under the Ministry of Health Malaysia.  
2) Malaysian ≥ 18 years old. 
3) Those who plan to continue prediabetes care at a community clinic in Melaka. 
4) Those who can read, write and understand the Malay Language. 
 
Participants who meet the following criteria will be excluded from continuing the study.  
 
1) Night shift workers at least 3 times per week.  
2) Known sleep disorder.  
3) Pregnant Women. 
4) Those on oral glucose-lowering medications, diabetes supplements, anticonvulsant 
medications or oral steroids currently or in the last month. 
5) Those with prior explored to any information regarding time-of-eating/time-of-
activity restriction.  
6) Those with chronic kidney disease. They are excluded as current research lack of 
evidence to support the accuracy of using 24-hour continuous glucose monitoring 
system (CGMS) (Freestyle Libre Pro, Abbott, Germany). 
 
Prediabetes and diabetes will be defined according to the latest Clinical 
Practice Guideline in Malaysia (WHO & IDF, 2006; ADA, 2020; MOH et al., 2020). 
Diagnosis must be confirmed by measurement of venous plasma glucose (FBG and 
OGTT) or HbA1c level. Table 1 shows the diagnostic value for diabetes on plasma 
glucose. Table 2 shows the diagnostic values for prediabetes and diabetes based on 
OGTT. Table 3 shows the diagnostic values for prediabetes and diabetes based on 
HbA1c. All the tables are adapted from the Clinical Practice Guideline in Malaysia 
(WHO & IDF, 2006; ADA, 2020; MOH et al., 2020). 
 
Table 1 The diagnostic value for diabetes on plasma glucose 
 
 
Fasting 
Random 
Venous Plasma Glucose  
≥ 7.0mmol/L 
≥ 11.1 mmol/L 
In symptomatic individual, one abnormal glucose value is diagnostic. 
In asymptomatic individual, 2 abnormal glucose value are required.  
 
 
 
 

 
 
                             
 
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Table 2 The diagnostic values for prediabetes and diabetes based on OGTT 
 
OGTT Plasma Glucose Values (mmol/L) 
Category 
0 hour 
2- hour 
Normal 
<6.1 
<7.8 
IFG 
6.1-6.9 
 
IGT 
- 
7.8-11.0 
DM 
≥ 7.0 
≥ 11.1 
IFG= impaired fasting glucose; IGT=impaired glucose tolerance; DM=diabetes 
mellitus 
 
Table 3 The diagnostic values for prediabetes and diabetes based on HbA1c 
 
 
Normal 
Pre-diabetes 
Diabetes 
A1c  
<5.6% 
(38mmol/mol)  
5.6-6.2% (38-44 
mmol/mol 
≥6.3% 
(45mmol/mol) 
A repeated A1c should be done 4 weeks after the first positive test for asymptomatic 
patients. 
In symptomatic individual, a single positive test is sufficient.  
 
Location of Research:  
 
Location of Research 
Expected 
number 
of 
subjects per site 
Community Clinic Batu Berendam 
56 
Community Clinic Bukit Rambai 
55 
Community Clinic Sungai Udang 
55 
 
 
Recruitment pamphlets that contain general information of the study will be placed in 
all the healthcare clinics in Malacca. During the process of recruitment, a trained 
research assistant, clinical dietitian (one of the co-researchers) or family medicine 
specialist (one of the co-researchers) will inform potential prediabetic individuals of the 
study both verbally and will be provided written information (Appendix A). Newly 
diagnosed prediabetic individuals who are agreeable to participate will be provide 
written informed consent (Appendix A). Study visits (recruitment and follow-up visits) 
of this study will be determined based on the healthcare clinic appointment schedules. 
Those who decline to participate continue to receive their routine treatment as usual, 
and care provided to each prediabetic individual is not affected nor affected by each 
individual’s decision to either participate or not participate in the study. An overview of 
the study procedure is illustrated in Figure 3. All the newly diagnosed prediabetic 
individuals who fulfill the inclusion criteria will be invited to participate in the present 
study. They will be recruited when they visit the diet clinic for for the first time for their 
initial appointment scheduling. This would be considered the baseline visit. OGTT, 
HbA1c and FBS results will be traced from medical records.  
 
Data regarding sociodemographic information and anthropometric measurements will 
be collected in the baseline visit. Enrolled participants will be interviewed by a trained 

 
 
                             
 
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research assistant using the following questionnaire including (1) Munich Chronotype 
Questionnaires (MCTQ) (Appendix D), (2) Pittsburgh Sleep Quality Index 
Questionnaire (PSQI) (Appendix H), (3) Harvard Light Exposure Questionnaire (HLEQ) 
(Appendix G), (4) International Physical Activity Questionnaire (IPAQ) (Appendix C) 
and (5) Chrononutrition Profile Questionnaire (CPQ) (Appendix I). Anthropometry 
measurements including body fat, height, body fat percentage, visceral fat, waist 
circumference and hip circumference will be measured. Participants are requested to 
fill up 3-days dietary record (3DDR) (2 weekdays and one weekend day) and the data 
will be collected in the next visit. Baseline reading of fasting plasma glucose (FPG, 
OGTT, liver function, and HbA1c) will be retrieved from medical records in the 
community clinic. Routine treatment will be provided as usual. To minimize the loss of 
follow-up, phone conversations will be made to ensure the 3-days dietary data is 
completed.   
 
At the second visit (three months from the baseline), all participants are 
required to wear a CGMS sensor at the back of their upper arms to measure the 24 
hours glucose fluctuation over 14 consecutive days. 3DDR will be given to participants 
to record their consecutive 3 days dietary record and will be returned after 14 days. 
After 14 days, participants will return the CGMS sensor at the community clinic. Or 
alternative way of CGMS sensor collection by an assistant at the participant's home. 
All questionnaires will be interviewed by a trained research assistant again. 
Anthropometry measurements including body fat, height, body fat percentage, visceral 
fat, waist circumference and hip circumference will be measured repeatedly. 
 
At the third visit (six months from the first visit), for FBG, OGTT and HbA1c test, 
all the readings will be retrieved by the research assistant from the medical record to 
document the glycemic outcome. The participants will be interviewed by the trained 
research assistant during all clinic visits using similar questionnaires. All 
anthropometry measurements (body fat, height, body fat percentage, visceral fat, 
waist circumference and hip circumference) will be conducted again. 3DDR will be 
given to record their 3 days dietary intake again and the record progress will be 
followed up through phone. The original 3DDR will be collected at the routine 
appointment.   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
                             
 
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Sample size Calculation: 
 
The sample size is estimated using G*Power software version 3.1.9.4 (Erdfelder, Faul 
and Buchner, 1996). To determination of association between chrononutrition and 
glycemic control, the β-coefficient of 0.13 adopted from Sakai et al., (2018), the power 
was set to 0.9 with 2 sided significance level and alpha error given 0.05, a total of 83 
prediabetic adults expected in this study. To compensate for the non-responding and 
non-compliance during follow-up, a dropout rate of 50% will be considered, the total 
sample size required is 166 subjects in the study for 6 months.  
Test Family: T Test 
Statistical Test: Linear Multiple Regression Fixed Model, single regression coefficient 
Tail(s): 2 
Effect Size (β-coefficient): 0.13 (Sakai et al., 2018) 
α Error prob: 0.05 
Power(1- β err prob): 0.90  
Total Sample Size: 83 prediabetes individuals 
 
50% dropout rate taken as consideration in study for 6 months follow up, total 166 
prediabetes individuals shall be recruit in this study.  
Dropout Rate: 
= 
83
1−0.5    = 166  prediabetic individuals 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
                             
 
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Figure 3: Flow diagram of the study design 
 
 
Ethical approval obtained from Medical Research and Ethics Committee and Tunku Abdul Rahman University College  
 
 
 
 
Permission to carry out data collection has been granted by Health Department Malacca.  
 
 
 
 
Recruitment processes start 
 
 
 
Baseline 
 
Family medicine specialists will screen potential participants (FBG, OGTT, Liver Function Test, and HbA1c test) & refer to a 
dietitian. Medical Nutrition Therapy will be provided to participants if diagnosed with impaired fasting glucose and impaired 
glucose tolerance. The family medicine specialist, dietitian, and trained research assistant explain to patients regarding the study, 
followed by consent completeness. All the data obtained from participants: 
 
Socio-demographic characteristics, chronotype, chrononutrition, sleep quality and disturbances, physical activity, sedentary 
lifestyle, light exposure, 3-days dietary record, anthropometry, and biochemistry measurements. 
 
The tools included: 
Socio-demographic Questionnaire, Munich Chronotype Questionnaires (MCTQ), Pittsburgh Sleep Quality Index Questionnaire 
(PSQI), Harvard Light Exposure (HLEQ) Questionnaire, International Physical Activity Questionnaire (IPAQ), 3 days dietary 
record, Chrononutrition Profile Questionnaire (CPQ), Omron Karada Scan (HBF-375). 
 
 
 
 
Second visit 
 
Participants will be briefed and required to wear a continuous glucose monitoring system for 14 days continuously and 3-days 
dietary data will be recorded. Other data collected to determine the confounding factors include: 
 
Chronotype, chrononutrition, sleep quality and disturbances, physical activity, sedentary lifestyle, light exposure, anthropometry, 
and biochemistry measurements. 
 
The tools included: 
Freestyle Libre Pro Flash Glucose Monitoring System (Abbott), Munich Chronotype Questionnaires (MCTQ), Pittsburgh Sleep 
Quality Index Questionnaire (PSQI), Harvard Light Exposure (HLEQ) Questionnaire, International Physical Activity Questionnaire 
(IPAQ), 3 days dietary record, Chrononutrition Profile Questionnaire (CPQ), Omron Karada Scan (HBF-375), portable stadiometer 
(SECA 213). 
 
 
 
 
Third visit 
 
An appointment will be given based on the scheduled community clinic, participants will be screened for FBG, OGTT, and HbA1c. 
The other data continue to distribute for the participants: 
 
Chronotype, chrononutrition, sleep quality and disturbances, physical activity, light exposure, food dairy, anthropometry, and 
biochemistry measurements. 
 
The tools included: 
Munich Chronotype Questionnaires (MCTQ), Pittsburgh Sleep Quality Index Questionnaire (PSQI), Harvard Light Exposure 
(HLEQ) Questionnaire, International Physical Activity Questionnaire (IPAQ), 3 days dietary record, Chrononutrition Profile 
Questionnaire (CPQ), Omron Karada Scan (HBF-375). 
 
 
 
 
 
 

 
 
                             
 
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Participants will be undergoing OGTT, FBS and HbA1c tests after an overnight fast of 
8-10 hours. This is a routine universal test for prediabetes/ diabetes diagnosis. 
Participants will be informed to eat their usual diet for three days prior to the test. The 
diagnostic value for diabetes on plasma glucose. the diagnostic values for prediabetes 
and diabetes based on OGTT, and the diagnostic values for prediabetes and diabetes 
based on HbA1c have been shown in Table 1, Table 2 and Table 3, respectively. 
Fasting blood sample will be taken for FBS and HbA1c tests. Subsequently, 
participants will be given 75-gram glucose water to drink within 5 minutes. Blood 
sample will be taken after 2 hours for glucose determination. Participants should rest 
throughout test with only plain water is allowed to drink. Figure 4 shows the procedure 
of OGTT. All the tests will be conducted in the healthcare clinic lab. Results will be 
traced from medical record. 
 
Table 4: Summary of data collection and timeline 
Data 
Baseline 
3 months 
6 months 
Sociodemographic 
 
 
 
Age 
· 
 
 
Date of Birth 
· 
 
 
Marital Status 
· 
 
 
Education Level 
· 
 
 
Occupation 
· 
 
 
Monthly Household Income 
· 
 
 
Health History 
· 
 
 
Smoking Habit 
· 
 
 
Supplementary Consumption  
· 
 
 
 
 
 
 
Anthropometry 
 
 
 
Weight 
· 
· 
· 
Height 
· 
· 
· 
Waist Circumference 
· 
· 
· 
Visceral Fat 
· 
· 
· 
Body Fat 
· 
· 
· 
Step counts 
 
 
· 
 
Questionnaires 
 
 
 
Munich Chronotype (MCTQ) 
· 
· 
· 
Pittsburgh Sleep Quality Index (PSQI) 
· 
· 
· 
Harvard Light Exposure (HLEQ) 
· 
· 
· 
International Physical Activity IPAQ) 
· 
· 
· 
Chrononutrition Profile Questionnaire (CPQ) 
· 
· 
· 
3 days dietary record (3DDR) 
 
· 
· 
· 
Glycemic Measurements 
 
 
 
Continuous Glucose Monitoring (CGM)  
 
· 
 
Fasting Plasma Glucose (FPG) 
· 
 
· 
2-hour Post-load Plasma Glucose (2hPPG) 
· 
 
· 
Glycated Hemoglobin (HbA1c) 
· 
 
· 
 
 
 
 

 
 
                             
 
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Figure 4 Procedure of OGTT 24-hour  
 
Continuous glucose monitoring system 24-hour CGMS (Freestyle Libre Pro, Abbott, 
Germany) is a glucose monitoring device that measures interstitial glucose levels and 
its indicated for detecting trends and tracking patterns in persons with prediabetes/ 
diabetes. Freestyle Libre Pro is not a usual/ normal Freestyle Libre. The normal 
version of CGMS can be easily purchased in the market, but CGMS Pro version can 
only be purchased direct from Abbott Germany. For the usual/normal Freestyle Libre, 
reading must be read by reader every 8 hourly and participants may easily check their 
blood glucose, resulting the unnecessary bias, where participants might change their 
diet and lifestyle habit to control the blood sugar. Whereas, pro version can only be 
used for clinical trial purpose, cannot be commercialized out of clinical trial use. 
Readings from the 24-hour CGMS Pro version will not be made available to 
participants in real time, hence, it will prevent the bias that may arise from unmasked 
real-time glucose reading. Besides, blood sugar can be kept record for up to 14 days 
for pro version, easier for researcher to collect the data and save the cost of reader. 
Figure 5 shows the example of the daily glucose summary from 24-hour CGMS. 24-
hour CGMS aids in understanding the person glucose profile and detecting episodes 
of hyperglycemia and hypoglycemia. Figure 6 shows the example of the daily pattern 
outcome from 24-hour CGMS. 
 
The FreeStyle Libre Pro CGM system consists of a disposable sensor, an applicator, 
and a reader; that is used to start the sensor on the participant and gather the glucose 
data at the end of the CGMS period. The Sensor can be worn for up to 14 days, on 
the back of their upper arm (Figure 7). Once applied, a sensor will measure and store 
glucose readings every 15 minutes. The 24-hour CGMS does not require any 
participant action as calibration for the sensor is not needed. Readings from the 24-
hour CGMS will not be made available to participants in real time, hence, it will prevent 
the bias that may arise from unmasked real-time glucose readings. The data from all 
the 24-hour CGMS (Freestyle Libre Pro, Abbott, Germany) sensors is easily 
accessible through the FreeStyle Libre Pro Software or The LibreView Cloud. In the 
present study, the 24-hour CGMS reading will be taken 14-day prior to second visit/ 
second-round OGTT reading. All the data from 24-hour CGMS will be analyzed to 

 
 
                             
 
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investigate to obtain the optimal-meal-timing. The 24-hour CGMS data will be match 
with 3-day food diary too. 
 
Exposure measures Meal-timing and chrononutrition 
 
At the baseline visit, the researcher will guide the participants to fill out the 3-day food 
diary covering two weekdays and one weekend day (consecutive Sunday-Tuesday or 
Thursday-Saturday). Three-day food diary will be taken twice in the entire study. At 
the baseline visit, 3-day food diary will be interviewed by researcher to the participants. 
This food diary data will be served as baseline meal-timing data. Subsequently, 
participant will be given another 3-days daily dietary at second visit, 14-day prior to 
third visit. Participants are required to record the time, type, description and number 
of foods and beverages consumed throughout the day. Brand information, ingredients 
and cooking method will be recorded where applicable, particularly for home-cooked 
food. Pictures of household measuring utensils and various food portion sizes are 
printed in the food diary to assist participants in quantifying their food intake. For 14 
day return the CGMS, researcher will be interviewed participants on the completeness 
of 3 days daily dietary intake.  
 
Energy and macronutrients analysis of dietary record will be performed using 
Nutritionist ProTM (Axxya Systems, Stafford, TX, USA), based principally on the 
Nutrient Composition of Malaysian Food and the food product labels. Energy intake 
will be compared with estimated basal metabolic rate (BMR) to exclude participants 
who are under-reporting or overreporting their energy intake in their 3-day food diary. 
BMR is calculated using standard equations based on sex and age provided by 
FAO/WHO/UNU (1985) (FAO/WHO/UNU 1985). For participants in a non-dieting 
population, Torun et al. (1996) proposed that a ratio between energy intake and BMR 
of less than 1.39 and more than 2.24 be considered as under-reporting and over-
reporting respectively. These cut-off points will be applied in the present trial. From the 
3-day food diary data, The investigator will investigate the dietary intake as reported 
on the second day of recording. The second day will be selected over the first one to 
ensure that participants have also include night-time eating in the records. Compare 
to the later days, which may have been burdened by increasing exhaustion related to 
the record-keeping, the second day better represents the habitual dietary intake (Ahola 
et al. 2019). To investigate the energy and macronutrient intakes over the course of 
the day, five periods will be performed as follows: night (from 00:00 to 04:49), morning 
(from 05:00 to 09:59), midday (from 10:00 to 13:59), afternoon (from 14:00 to 16:59) 
and evening (from 17:00 to 23:59), adapted from Ahola et al. (2019). As these periods 
differed in their duration, energy intake per hour will also be calculated for each of the 
five periods. In addition, energy and macronutrient intakes per hour (e.g. intakes 
reported between 10:00 and 10:59 contributed towards the hour “10:00”). Diet quality 
will be derived from a 177 food items FFQ at second visit, where the Healthy Eating 
Index (HEI) will be calculated. This FFQ is adapted from the FFQ used by the 
Malaysian Adults Nutrition Survey (MANS) 2014 (IPH 2014) (Appendix C). Participants 
will be required to indicate frequency of foods consumed in the last 1 month. Individual 
portion size will be asked for each food, and pictures of the various portion size will be 

 
 
                             
 
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provided for more accurate quantification. A validated Malaysian HEI will be applied 
to determine the HEI scoring (Lee et al. 2011; Goh & Norimah 2012). The instrument 
consists of nine components, which is make up of seven food groups and two nutrient 
groups, as shown in Table 5. The scoring of these components will be calculated 
based on the recommended serving size and nutrient intake in the Malaysian Dietary 
Guideline (MDG) (NCCFN 2010). The score of each food group will be calculated 
using the formula: (actual serving consumed based on participant’s diet record 
/recommended serving size based on MDG) × 10. The score of each nutrient ranged 
from 0 to 10, which will be calculated proportionately for the in-between whole number 
responses, as shown in Table 6. The total score of HEI is obtained by summing up the 
score of each component. The composite score in percentage is calculated using the 
formula: (total score obtained from 9 components/maximum score of 90) × 100%. 
Therefore, the total score is 100%, in which less than 51% indicated poor diet, 51 to 
80% indicated diet requiring improvement, and more than 80% indicated good diet 
(Lee et al. 2011). 
 
 
 
Physical activity, sedentary behaviours, sleep and light exposure questionnaire on 
physical activity, sedentary behavior, sleep and light exposure are also administered 
at the first visit. Participants are interviewed using the modified International Physical 
Activity Questionnaire-Short Form (IPAQ-SF)(Appendix C) to self-report their physical 
activity in the last 7 days (IPAQ 2005). The modified questionnaire evaluates the 
vigorous physical activity, the moderate physical activity and the walking time. Loy et 

 
 
                             
 
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al. (2019) removed question asking about the sitting time from the original IPAQ-SF 
and included it in the questionnaire used to assess sedentary behavior. The data will 
be computed in metabolic equivalents (MET-min/ week) scores. Questionnaire on 
sedentary behavior which is modified from the Adult Sedentary Behavior 
Questionnaire is performed (Chu et al. 2018). The questionnaire evaluates time spent 
sedentary in the last 7 days, including sitting time at work, sitting/ lying down time to 
watch television, to use electronic devices at mealtime, while driving or reading. 
Participants also self-administer the Pittsburgh Sleep Quality Index questionnaire to 
assess their sleep habits in the last month (Buysse et al. 1989)(Appendix H), and the 
Harvest Light Exposure Assessment questionnaire (Appendix G) to assess their main 
light sources exposure in hourly basis on a typical weekday and weekend day (Bajaj 
et al. 2011).  
 
Anthropometric measurements (Appendix J) will be measured at the first, second and 
third visit. Body weight, body fat percentage and visceral fat of each participant will be 
measured twice using a body fat analyzer (HBF-375, Karada) and recorded to the 
nearest 0.1 kg, 0.1 % and 1 unit, respectively. Participants will be weighted with their 
minimal cloths on, barefoot, without belt and emptied pockets. They will be asked to 
stand still with the body weight equally distributed on both feet. Participants have to 
be in the Frankfurt plane, where the body is upright, upper limbs are at the body’s 
sides with the palms facing forward, feet flat and directed forward, directly facing the 
researcher assistant. The height of each participant will be measured twice using a 
SECA portable stadiometer Model 217 (SECA GmbH & Co., Hamburg, Germany) 
attached to a smooth wall and recorded to the nearest 0.1 cm. Participants will be 
asked to stand erect, in their bare feet, with their heels, buttocks, head and shoulder 
blades in a vertical line against the wall. Height will be measured in the upright position 
against a vertical scare and with the head positioned so that the top of the external 
auditory meatus is in the level with the inferior margin of the bone orbit. Waist and hip 
circumferences of the respondents will be measured twice, according to the 
standardized protocol by the WHO (2008). Waist circumference will be measured at 
the approximate midpoint between the lower margin of the last palpable rib and the 
top of the iliac crest. Hip circumference will be measured around the widest portion of 
the buttocks, with the tape parallel to the floor. For both measurements, the 
participants should stand with feet close together, arms at the side and body weight 
evenly distributed, and should wear little clothing. Both waist and hip circumferences 
will be measured to the nearest 0.1 cm by using a Lufkin tape model W606PM (Apex 
Tool Group, Sparks, MD, USA). The reported measurements are the average values 
from both readings.  
 
Study Outcomes 
 
The main outcome of the study is the glycemic outcome including FPG (mmol/L), 
2hPPG (mmol/L), HbA1c (%), and glucose variability from CGMS. The secondary 
outcomes are chronotype from the validated questionnaire MCTQ, and chrononutrition 
from the validated questionnaire CPQ, 3 days dietary record, anthropometry 
measurements, physical activity level from the validated questionnaire IPAQ, sleep 

 
 
                             
 
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pattern from the validated questionnaires PSIQ and light exposure from the validated 
questionnaire HLEQ. 
 
Statistical Analysis 
 
All data will be performed statistical analysis using the SPSS software version 20 
(SPSS Inc., Chicago, IL, USA). The socio-demographic will be presented as mean, 
standard deviations, median, interquartile range, frequency, and percentage. Data 
cleaning will be performed to exclude the outlier data before the normality is checked 
using Kolmogorov-Smirnov Test. The investigator considered p<0.05 to be statistically 
significant. Chronotype, sleep quality, and light exposure will be analyzed as 
categorical variables whereas dietary intake, chrononutrition, anthropometry, glycemic 
measure, and physical activity will be analyzed as continuous variables.   
 
The investigator will perform a multivariable generalized linear model to 
examine the association between night meal pattern (last night mealtime either dinner 
or supper with calories intake, frequency of night snacking, and the total number of the 
night snacking) and glycemic outcome (HbA1c, FPG, 2hPPG, CGM profile) by 
adjusting for the potential covariates. Specifically, nighttime will be characterized by 
the time range from 1900 and 0659 hours based on Malaysia solar time. The 
investigator will explore the late-night meal timing in 2000, 2100, and 2200 to examine 
its association with glycemic outcomes. The potential confounders include 
sociodemographic characteristics, physical activity, sleep pattern, sedentary behavior, 
diet quality, and light exposure will be controlled. ANCOVA test will be performed to 
understand the association between chrononutrition (breakfast skipping, meal 
frequency, eating window, sleep timing, chronotype, and fasting pattern) with glycemic 
variables, controlling for potential covariates (sociodemographic characteristics, light 
exposure, diet quality, physical activity and sleep pattern). 
 
To investigate the association of physical activity (MET score and steps count), 
sedentary behaviors (MET score), sleep pattern (sleep duration), diet quality 
(distribution of total energy, carbohydrate, protein, and fat), and light exposure (timing 
responded to a different type of light) with glycemic outcome, the multivariable 
generalized linear model will be conducted. Meanwhile, anthropometric measures 
(body mass index, body fat, and waist circumference) will be categorized as either 
normal or overweight and obesity group, followed by using logistic regression to 
examine the association between anthropometry status and glycemic outcome (non-
diabetes or diabetes). In addition, the glycemic outcome will be categorized into 
diabetes incidence (diabetes and non-diabetes) to determine the participants who had 
been diagnosed with diabetes at 6 months. A logistic regression test will be used to 
examine the association between early and late-night mealtime and diabetes 
incidence.  
 
Quality control 
 
To ensure that the database accurately reflects the data reported in the questionnaires, 
a pre-test will be carried out. The research assistant trained to conduct the study 
procedures included interviewing administrative questionnaires, CGMS device, 3 days 
dietary record, and pedometer. Monthly meetings are held with the principal 

 
 
                             
 
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investigator to review study procedures and progression. A monthly report will be 
documented after the meeting. 
 
Data monitoring and management 
 
Participants are anonymized and assigned with a specific ID at study entry. To ensure 
accuracy and completeness of data entry, data are checked by identifying if there is 
any outlier or missing value. The data checking process is performed in the first, third 
and sixth month of the data collection, such that the experience gained can be used 
to train the research assistant for improvement. Paper documents are kept in a locked 
cabinet and electronic data are stored on password-protected computers which can 
only be accessed by research team members. All records will be kept for at least 5 
years after completing the study. After 5 years, all papers will be shredded using an 
office shredder. Extra care should be taken with sensitive or confidential information 
and a secure paper destruction service bin used. Digital data will be destroyed by 
deleting or overwriting information and destroying the physical media, such as CD 
rom.  
 
4. PROPOSED RESEARCH SCHEDULE 
 
Research Activities 
 
Activities 
Start Date 
End Date 
Systematic review. Research and methodology classes 07/09/2021 06/03/2022 
Baseline recruitment, collection of FBS, anthropometric 
measurements and lifestyle habits; distribute 24- hour 
CGMS 
07/03/2022 06/11/2022 
Second visit, collection of FBS, anthropometric 
measurements and lifestyle habits; distribute 24-hour 
CGMS 
07/11/2022 06/07/2023 
Third visit, collection of FBS, anthropometric 
measurements, lifestyle habits and collect the 24-hour 
CGMS 
07/07/2023 06/03/2024 
data key in, data analyses to investigate the optimal-
meal-timing, anthropometric measurements, lifestyle 
habits and the associations between these variables; 
publication 
07/03/2024 06/09/2024 
 
Milestones 
 
Activities 
Date 
Cumulative 
Project 
Completion 
Percentage 
(%) 
Completion of systematic review to study optimal-meal-
timing, chrononutrition, lifestyle factors and 
31/03/2022 10 

 
 
                             
 
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anthropometric measurements in prediabetes 
individuals 
Baseline recruitment completed, by using convenient 
sampling method. OGTT, FBS and HbA1c traced from 
medical record. Anthropometric measurements and 
lifestyle habit information collected. 3- day food diary 
and CGMS distributed. 
30/11/2022 35 
Second visit completed. Anthropometric 
measurements and lifestyle habit information collected. 
3-day food diary and CGMS distributed. 
31/07/2023 60 
Third visit completed. OGTT, FBS and HbA1c traced 
from medical record. Anthropometric measurements 
and lifestyle habit information collected. 3-day food 
diary and CGMS colleted 
31/03/2024 85 
Data key in, data analyses and publication 
31/08/2024 100 
 
 
 
 
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APPENDIX A:  INFORMATION SHEET AND CONSENT FORM 
 
Research Title 
Chronotype, Chrononutrition and Glucose Tolerance Among Prediabetic Individuals: 
Chrono-DMTM. 
 
Introduction 
There is a growing body of knowledge associating alterations in biological clock with the 
development of T2DM. Perhaps, it is not what you eat but when you choose to eat it. Although 
the importance of biology clock in diabetes prevention had been recognized; however, such 
relevant information are not included in any diabetes guidelines, particularly in Malaysia.  
 
Objective 
This study aimed to determine the associations of chronotype and chrononutrition with 
glucose tolerance among prediabetic individuals in Malaysia. 
 
What should I do? 
This study that targets to recruit 166 prediabetes individuals who have received conventional 
medical nutrition therapy, from all the healthcare clinics in Malacca. Participants will be 
followed-up up to 6-month times:  
 
Table 1 The overall study flow 
Timeline 
Services 
Measurements 
Baseline  
(first diagnosed 
prediabetes) 
Routine Appointment 
in 
Community 
Service: 
Fasting Plasma Glucose, Oral Glucose Tolerance Test, Liver 
function test, HbA1c test, Medical Officer consultation and dietitian 
consultation. 
 
Research Protocol: 
 
1) 
Information data: Social-demographic Questionnaire 
2) 
Anthropometry Measurement: Weight, Height, Body Fat 
Percentage, Visceral Fat, Waist Circumference  
3) 
Pedometer Counting 
4) 
Munich Chronotype Questionnaire (MCTQ) 
5) 
Pittsburgh Sleep Quality Index (PSQI) 
6) 
Harvard Light Exposure Assessment Questionnaire(H-LEA) 
7) 
3 days Daily Diet Record (2 weekdays and one weekend 
day; consecutive Sunday to Tuesday or Thursday to 
Saturday, within CGMS wearing period) 
8) 
International Physical Activity Questionnaire (IPAQ) 
Second visit  
(at 3rd month) 
Routine Appointment 
in 
Community 
Service: 
Fasting Plasma Glucose, Oral Glucose Tolerance Test, HbA1c 
test, Dietitian consultation 
Research Protocol: 
 
1) 
Anthropometry Measurement: Weight, Height, Body Fat 
Percentage, Visceral Fat, Waist Circumference  
2) 
Pedometer Counting 
3) 
Munich Chronotype Questionnaire (MCTQ) 
4) 
Pittsburgh Sleep Quality Index (PSQI) 
5) 
Harvard Light Exposure Assessment Questionnaire(H-LEA) 
6) 
3 days Daily Diet Record (2 weekdays and one weekend 
day; consecutive Sunday to Tuesday or Thursday to 
Saturday, within CGMS wearing period) 
7) 
International Physical Activity Questionnaire (IPAQ) 
8) 
Chrononutrition Profile – Questionnaire (CPQ) 
9) 
Continuous Glucose Monitoring Service (CGMS) 
Third visit  
(at 6th month) 
Routine Appointment 
in 
Community 
Service: 
Fasting Plasma Glucose, Oral Glucose Tolerance Test, HbA1c 
test, Medical Officer consultation and Dietitian consultation. 
 
Research Protocol: 
 
1) 
Anthropometry Measurement: Weight, Height, Body Fat 
Percentage, Visceral Fat, Waist Circumference  
2) 
Pedometer Counting 
3) 
Munich Chronotype Questionnaire (MCTQ) 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 36 of 58 
 
4) 
Pittsburgh Sleep Quality Index (PSQI) 
5) 
Harvard Light Exposure Assessment Questionnaire(H-LEA) 
6) 
3 days Daily Diet Record (2 weekdays and one weekend 
day; consecutive Sunday to Tuesday or Thursday to 
Saturday, within CGMS wearing period) 
7) 
International Physical Activity Questionnaire (IPAQ) 
8) 
Chrononutrition Profile – Questionnaire (CPQ) 
 
The interview will be like a conversation, and you can decide to stop the interview at any time. 
There are no right or wrong answers. The investigator are interested in learning from your 
personal experiences. 
 
You will not know the reading in real time because the CGMS pro system is designed research 
observation and the reading will not made available to participants in real time. FDA Summary 
of Safety and Effectiveness Data (PMA P150021) indicated that Freestyle Libre CGMS pro 
version may inaccurately indicate hypoglycemia at a greater rate than other approved CGMs. 
The results of the clinical study conducted for this device showed that 40 percent of the time 
when the device indicated that user sensor glucose values were at or below 60 mg/dL(3.3 
mmol/L), user glucose values were actually in the range of 81- 160 mg/dL (4.5-8.9 mmol/L). A 
glucometer shall be performed if you are suspect you have abnormal glucose level anytime. 
You will get your personal glucose result according to routine appointment with medical officer 
upon your request. Your personal CGMS and all measurement results will be given after 6 
months measurements through email upon your request.   
 
Benefits of Research 
There are no direct benefits to you for participating in this study. However, your input will 
provide the vital information regarding to meal timing and glucose control in pre-diabetes 
patients.  
 
Confidentiality 
Your answer and information will be kept confidential by the investigators and will not made 
public unless disclosure is required by law. All information will be kept confidentially in Tunku 
Abdul Rahman University College for 3 years and then safely disposed of after 3 years. You 
will inform the study finding through email if there are any new publications using your 
information.  
 
Risk to participants 
CGMS pro system is continuous glucose monitoring system approved by US Food Drug and 
Administration. The investigator used this system fully to observe glucose variability 
personality but not the purpose to diagnose hyperglycemia or hypoglycemia. The FreeStyle 
Libre Pro System must be removed prior to Magnetic Resonance Imaging (MRI), Computed 
Tomography (CT) scan, or high-frequency electrical heat (diathermy) treatment. Potential 
device-related, non-serious events related to continuous glucose monitor use include: local 
infection, skin irritation or redness, skin inflammation, pain or discomfort, bleeding, bruising, 
skin edema, skin rash, itching, scarring or skin discoloration, allergic reactions to the sensor 
needle or adhesives, sensor or needle fracture during insertion, wear or removal. Sensor 
breakage with fragments retained under the skin is a potential procedure-related complication. 
However, based on post-market experience with this and similar devices, and the results 
observed in the clinical study, this event is rare and its severity does not raise major concerns. 
 
The investigator believe participation in this study is of minimal risk. However, if you ever feel 
uncomfortable during the study, you are free to stop at any time. As with any study that collects 
information about you, there is possible risk of loss of confidentiality. However, as described 
below, The investigator have taken several measures to help prevent this.  
 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 37 of 58 
 
Voluntary Participation 
You are free to decline to participate, to end participation at any time for any reason, or to 
refuse to answer any individual question without penalty. Your decision whether to participate 
or not will not affect your relationship with this university and the community clinical services 
it may provide to you. 
 
Publication 
Permission will be obtained from the Director General of Health, Malaysia prior to publication. 
The publication will send to subject upon on their requirement.  
 
Payment and allowance  
You will not be charged any conduction fees to participate in this research study. You will not 
be paid any allowance in this research study. If the outcome of this research study involved in 
any product launch in the market in the future, you has no right to claim copyright and 
intellectual property from the profit of the product. 
 
Enquiry 
If you has any question regarding to this research study, please contact  
Name and Institution 
of Principal 
Investigator 
Dr Koo Hui Chin 
Department of Bioscience 
Faculty of Applied Sciences (FOAS) 
Tunku Abdul Rahman University Management and Technology (TARUMT)  
koohc@tarc.edu.my 
Name and Institution 
of Co-Researchers 
Dr Satvinder Kaur D/O Nachatar Singh 
Assistant Professor  
Department of Food Science and Nutrition 
UCSI University, Malaysia 
satvinderkaur@ucsiuniversity.edu.my 
 
Dr Loy See Ling 
Assistant Professor 
Department of Reproductive Medicine 
Duke-NUS Medical School, Singapore 
loy.see.ling@kkh.com.sg 
 
Dr Tan Hui Yin 
Deputy Dean 
Faculty of Applied Sciences 
Tunku Abdul Rahman University Management and Technology (TARUMT)  
hytan@tarc.edu.my 
 
Dr Sarjit Singh A/L Dr Harjit Singh 
Physician 
Department of Emergency and Trauma 
Hospital Serdang, Malaysia 
sarjitsingh83@hotmail.com 
 
Prof. Dr. Ruzita Abd Talib 
Professor, Deputy Dean of Graduate School, Lecturer 
Faculty of Health Sciences  
Universiti Kebangsaan Malaysia 
rzt@ukm.edu.my 
 
Sub investigators at 
the site and Co-
Researchers 
Dr Rosmiza Binti Abdullah  
Pakar Perubatan Keluarga  
Community Clinic Batu Berendam, 
rosmiza1@hotmail.com 
 
Dr Hanisah Binti Mahmud 
Pengawai Perubatan  
Community Clinic Batu Berendam 
hanisahbtemahmud@gmail.com 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 38 of 58 
 
Siah Woan Yie 
Clinical/ Community Dietitian 
Community Clinic Kuala Sungai Baru 
Ministry of Health 
siahwoanyie@gmail.com 
 
Principal investigators 
at the site and Name 
of PhD Student 
Chong Guey Yong 
Department of Bioscience 
Faculty of Applied Sciences (FOAS) 
Tunku Abdul Rahman University Management and Technology (TARUMT)  
chonggy-wr21@student.tarc.edu.my 
 
If you have any 
questions about your 
rights as a participant 
in this study, please 
contact 
The Secretary, Medical Research & Ethics Committee, Ministry of Health Malaysia, at 
telephone number 03-3362 8407/8205/8888. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 39 of 58 
 
Letter of consent for research study  
 
Give consent, Subject ID: __________ 
 
I,____________________________, ID card Number_________________________,  
• 
Has read the Participant Information Sheet and understand regarding to the 
title of the research by listening to explanation from the researcher.  
• 
Has given time for consideration and answered all question from the 
questionnaires.  
• 
Understand that I can withdraw anytime during the research without giving any 
reason.  
• 
Understand that all information given will stay anonymous.   
  
I, hereby agree to take part in this research project and will follow all the research 
procedure and give all the related information if necessary.  
  
  
____________________                                             _______________  
(Signature)                                                                   (Date)  
  
  
  
____________________                                              ____________________  
Witness by,                                                                   Researcher  
  
____________________                                              ____________________  
(Signature)                                                                    (Signature)     
  
____________________                                             ____________________   
(I/C number)                                                                (I/C number)  
  
____________________                                              ____________________  
(Date)                                                                            (Date) 
 
 
 
 
 
 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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APPENDIX B:  SOCIO-DEMOGRAPHY 
 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 
Section 1.0 Socio-demography 
1.1 
What is the highest level of education that you have completed? 
 
 
0: None(skip to Q1.3) 
 
 
1: Primary (eg. PSLE) 
 
 
2: Secondary (eg. GCE ‘O’ / ‘N’ level) 
 
 
3: Junior College / Centralised Institute (GCE 'A' Level / International Baccalaureate) 
 
 
4: Institute of Technical Education [ITE/NTC (NITEC, higher NITEC or equivalent)] 
 
 
5: Diploma/ Advanced diploma / Polytechnic  
 
 
6: Trade or work qualification not from university 
 
 
7: University Bachelor’s Degree / Postgrad Diploma / Professional Degree 
 
 
8: Postgraduate (Master Degree / Doctorate) 
 
1.2 
How many years of education have you received? (Including home schooling but excluding 
pre-school, kindergarten or years spent repeating individual grades) 
 
 
years 
 
 
months 
 
1.3 
What is your current job status? 
 
 
0: Not employed (skip to Q1.5) 
 
 
1: Self-employed 
 
 
2: Part-time employed 
 
 
3: Full-time employed 
 
1.4 
During the past 1 month, did you require to work overtime (until after 7pm)? 
 
 
0: No 
 
 
1: Less than once a week 
 
 
2: Once or twice a week 
 
 
3: Three or more times a week 
 
1.5 
What was your weight before prediabetes diagnosis ? 
 
 
 
. 
 
 
 
 
 
 
 
 

 
 
                             
 
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1.6 
What is your ethnic group? 
 
 
0: Chinese 
 
 
1: Malay 
 
 
2: Indian 
 
 
3: Other, please specify: _________________________________ 
 
Section 2.0 Lifestyle 
2.1 
Have you smoked in the past? 
 
 
0: Not at all for entire life 
 
 
1: Yes, but stopped smoking  before conceiving for this pregnancy 
 
 
2: Yes, but stopped smoking since conceived for this pregnancy 
 
 
3: Yes, but stopped smoking 1 month ago  
 
 
4: Yes, during the past 1 month and/ or currently smoking 
2.2 
During the past 1 month, did anyone smoke in indoor areas where you work and/ or 
stay?(Excluding area which are not fully enclosed. Should answer ‘yes’ if smelling the smoke). 
 
 
0: No 
 
 
1: Yes 
 
2.3 
How often did you have a drink containing alcohol during the past 3 months before 
conceiving for this pregnancy?(Including traditional wine, e.g. Youmeishu, DOM Benedictine) 
 
 
0: never or less than once per month 
 
 
1: 1-3 times per month 
 
 
2: 1-2 times per week 
 
 
3: 3-4 times per week 
 
 
4: 5-6 times per week 
 
 
5: 1 time or more per day 
 
2.4 
Have you consumed any drink containing alcohol since your current pregnancy?(Including 
traditional wine, e.g. Youmeishu, DOM Benedictine) 
 
 
0: No 
 
 
1: Yes, but stopped drinking 1 month ago 
 
 
2: Yes, current and during the past 1 month 
 
2.5 
Did you take any pills, tonics or tablets to supplement your diet (e.g. vitamin, minerals, iron 
tablets, folic acid, fish oils etc.)?(can be more than 1 options, except if selecting ‘Never’) 
 
 
0: Never or without supplement for at least 3 months ago before conceiving for this 
pregnancy 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 42 of 58 
 
 
 
1: Yes, since 3 months before conceivingfor this pregnancy 
 
 
2: Yes, since conceivedfor this pregnancy 
 
 
3: Yes, current and during the past 1 month 
 
2.6 
During the past 1 month, how often did you skip your breakfast, lunch and dinner? 
 
Breakfast 
Lunch 
Dinner 
0: never 
 
 
 
 
 
 
 
 
 
 
1: 1-3 times per month 
2: 1-2 times per week 
3: 3-4 times per week 
4: 5-6 times per week 
5: Every day 
 
2.7 
During the past 1 month, how often did you delay your breakfast, lunch and dinner for more 
than 2 hours from your regular meal timings?   
 
Breakfast 
Lunch 
Dinner 
0: never 
 
 
 
 
 
 
 
 
 
 
1: 1-3 times per month 
2: 1-2 times per week 
3: 3-4 times per week 
4: 5-6 times per week 
5: Every day 
 
2.8 
During the past 1 month, how often did you have snack(s) taken after 7pm? (Snack is 
defined as a portion of food often smaller than a regular meal, including beverage such as milk. 
Snacking frequency is defined with a time interval between episodes of at least 15 min) 
 
 
0: never 
 
 
1: 1-3 times per month 
 
 
2: 1-2 times per week 
 
 
3: 3-4 times per week 
 
 
4: 5-6 times per week 
 
 
5: 1 time per night 
 
 
6: 2 or more times per night 
 
 
 
 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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3.0 Physical activity 
I am going to ask you about the time you spent being physically active. Think about only those 
physical activities that you did for at least 10 minutes at a time over the past week. 
 
During the last 7 days, how many days have you done the following kind of physical activities? 
 
3.1 
Vigorous physical activities which take hard physical effort and make you breathe much 
harder than normal.(E.g. heavy lifting,aerobics, fast swimming or fast bicycling) 
 
 
(If answers ‘0’, skip to Q 3.2) 
 
3.1.1 On average about how much time did you usually spend on those activities? 
 
3.1.2 
During which period(s) of the day did you usually perform those activities? (Can be more than 
1 options) 
 
 
1: Early morning (5am – 6:59am) 
 
 
2: Morning (7am – 11:59am)  
 
 
3: Afternoon (12pm – 4:59pm) 
 
 
4: Evening (5pm – 6:59pm) 
 
 
5: Night (7pm – 11:59pm) 
 
 
6: Late-night (12am – 4:59am) 
 
3.2 
Moderate physical activities which take moderate physical effort and make you breathe 
somewhat harder than normal.(E.g. carrying light loads, sweeping, scrubbing floors, washing 
windows, dancing, or bicycling/swimming at a regular pace. Do not include walking) 
 
(If answers ‘0’, skip to Q 3.3) 
 
3.2.1 On average about how much time did you usually spend on those activities? 
 
 
3.2.2 
During which period(s) of the day did you usually perform those activities? (Can be more than 
1 options) 
 
 
1: Early morning (5am – 6:59am) 
 
 
2: Morning (7am – 11:59am)  
 
 
3: Afternoon (12pm – 4:59pm) 
 
 
4: Evening (5pm – 6:59pm) 
 
 
5: Night (7pm – 11:59pm) 
 
 
6: Late-night (12am – 4:59am) 
 
3.3 
How many days did you walk for at least 10 minutes at a time? (Includes at work and at 
home, walking from place to place, and any other walking that you have done solely for recreation, 
sport, exercise, or leisure) 
APPENDIX C 
International Physical Activity Questionniare 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 
 
 
 
days in last 7 days 
 
 
 
 
hrs 
 
 
 
mins per day 
(or) 
 
 
 
hrs 
 
 
 
mins per week 
 
 
 
days in last 7 days 
 
 
 
 
hrs 
 
 
 
mins per day 
(or) 
 
 
 
hrs 
 
 
 
mins per week 
 
 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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(If answers ‘0’, skip to Q 4.1) 
 
3.3.1 On average about how much time did you usually spend on walking? 
 
3.3.2 
During which period(s) of the day did you usually spend on walking? (Can be more than 1 
options, select as appropriate) 
 
 
1: Early morning (5am – 6:59am) 
 
 
2: Morning (7am – 11:59am)  
 
 
3: Afternoon (12pm – 4:59pm) 
 
 
4: Evening (5pm – 6:59pm) 
 
 
5: Night (7pm – 11:59pm) 
 
 
6: Late-night (12am – 4:59am) 
 
 
Section 4.0 Sedentary behaviour 
 
The following questions are about time spent sitting or lying down while being awake, at least 10 
minutes at a time over the past week. This may include time spent sitting at a desk, visiting friends, 
reading or sitting or lying down to watch television. 
 
4.1 
[For those who previously answered Yes to work] 
During the last week, on an average working day,how 
much time did you spend sitting at work? 
 
4.1.1 During the last week, on an average working day, 
how much time did you spend on electronic devices 
such as social media, computer, tablet, mobile phone 
at work? 
 
 
 
 
 
 
hrs 
 
 
 
mins per day 
 
 
 
 
 
 
hrs 
 
 
 
mins per day 
 
4.2 
[For those who previously answered Yes to work] 
Excluding any time at work, during the last week, on average how much time did you spend…… 
 
[For those who previously answered No to work] 
During the last week, on average how much time did you spend…… 
 
 
4.2.1 sitting or lying down and watching television? 
 
 
hrs 
 
 
mins per day 
(or) 
 
 
hrs 
 
 
mins per week 
 
 
4.2.2sitting or lying down and viewing electronic devices 
other than television in your leisure time (e.g watching 
online video, internet surfing, social media, electronic 
games on computer, tablet or mobile phone etc.)? Do not 
include time spent on computer at work. 
 
 
 
 
hrs 
 
 
mins per day 
(or) 
 
 
hrs 
 
 
mins per week 
 
 
 
4.2.3sitting or lying down at mealtimes, driving or  
reading or other time sitting [excluding TV /electronic 
device time] 
 
 
 
hrs 
 
 
mins per day 
(or) 
 
 
hrs 
 
 
mins per week 
 
 
 
days in last 7 days 
 
 
 
hrs 
 
 
mins per day 
(or) 
 
 
hrs 
 
 
mins per week 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
Page 45 of 58 
 
Section 5.0 Electronic media use before bedtime 
1 
During the last 7 days, on average how much time did you spend on the below electronic devices before going to sleep in bed at night (after 
2 
7pm)? 
3 
 
Electronic devices 
How many 
days in past 
week (0-7) 
Duration per day or per week 
(If the durations of using the device are inconsistent every  
night, sum up the duration spent for each night to obtain 
 total time spent per week) 
Used in 
bedroom 
0: No ; 1: Yes 
 
 
 
 
 
5.1 
Television 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.2 
Computer: surfing, online 
video, playing, reading 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.3 
Computer: movie, TV series 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.4 
Tablet/ mobile phone: surfing, 
online video, playing, reading, 
texting 
 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
 
5.5 
Tablet/ mobile phone: movie, 
TV series 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.6 
Tablet/ mobile phone: talking 
only 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.7 
Audio player (music, radio) 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.8 
Gaming console 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
5.9 
Partner’s media use  
 
 
 
 
 
hrs  
 
mins per day 
 
 
 
 
 
Reference: See Ling Loy, Yin Bun Cheung, Mary Chong, Falk Müller-Riemenschneider, Ngee Lek, YS Lee, Kok Hian Tan, Bernard Chern, Fabian Yap, Jerry 
4 
Chan. 2019. Maternal night-eating pattern and glucose tolerance during pregnancy: study protocol for a longitudinal study. BMJ Open. 9:e030036. 
5 
doi:10.1136/bmjopen-2019-030036. 
6 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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7 
 
8 
 
9 
 
10 
 
11 
 
12 
 
13 
 
14 
 
15 
 
16 
 
 
 
Munich Chronotype Questionnaire (MCTQ) 
17 
 
18 
This questionnaire requires you to report your sleep patterns over the past 4 weeks. Working 
19 
day and non -working day sleep patterns were asked separately. Please answer this 
20 
question according to your perceptions of your weekly habits, workday sleep patterns and 
21 
non -working days. 
22 
 
23 
I have regular working hours (this includes housewives): 
24 
 
25 
 
Yes, I work 
 
1 
 
2 
 
3 
 
4 
 
5 
 
6 
 
7 
 
Day/week 
 
No 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
If your answer is ‘Yes, 7 days’ or ‘No’, please consider whether your bedtime may differ between 
normal weekdays and weekends and fill out the MCTQ accordingly. 
 
26 
 
27 
Based on the following picture, answer the question below (Please answer on a 24 -hour 
28 
scale, for example; 23:00): 
29 
 
30 
Working Days 
Picture 1 
I entered the bedroom at: ___________ 
Picture 2 
Some people stay awake even after lying in bed. 
Picture 3 
I'm ready to go to bed at (turn off the lights and go to 
sleep):_________ 
Picture 4 
How many minutes do I need to sleep: ___________ 
Picture 5 
I woke up in the morning at: __________ 
Picture 6 
I got out of bed after a few minutes: _______ 
I use an alarm clock on 
weekdays 
              Yes            No 
 
If YES, I usually wake up 
BEFORE the alarm clock rings: 
             
              Yes            No 
Weekend 
Picture 1 
I entered the bedroom at: ___________ 
Picture 2 
Some people stay awake even after lying in bed. 
APPENDIX D 
Munich Chronotype Questionnaire 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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Picture 3 
I'm ready to go to bed at (turn off the lights and go to 
sleep):_________ 
Picture 4 
How many minutes do I need to sleep: ___________ 
Picture 5 
I woke up in the morning at: __________ 
Picture 6 
I got out of bed after a few minutes: _______ 
My waking hours were due to the 
use of an alarm clock (Figure 5): 
 
              Yes            No 
There are certain reasons I can't 
determine my bedtime 
independently on holidays: 
 
              Yes            No 
If ‘Yes’, among the factors are 
 
 
Child/husband/pet 
 
Hobby 
 
Solat/morning prayer/meditation 
 
Others (please state): _____________________________________ 
 
 
Will I go back to sleep after doing the activity, on holidays? 
 
Yes 
 
No 
If ‘Yes’ to the previous question, what time do you go to bed and wake up? 
Time to sleep again:_________________ 
Time to wake up again: __________________ 
 
31 
 
32 
 
33 
 
34 
 
35 
 
36 
 
37 
 
38 
 
39 
 
40 
 
41 
 
42 
 
43 
 
44 
 
45 
 
46 
 
47 
 
48 
Reference:  
49 
 
50 
Ms. Fatin Hanani Mazri, Zahara Abdul Manaf, Suzana Shahar, Arimi Fitri Mat Ludin, Norwahidah Abdul Karim, 
51 
Andrea Yu-Lin Ban & Rose Azzlinda Osman (2021): Modified Munich chronotype questionnaire for application to 
52 
short-interval split sleep of non-shift workers, Chronobiology International, DOI: 
53 
10.1080/07420528.2021.1887209
54 

 
 
                             
 
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55 
 
56 
 
57 
 
58 
 
59 
 
60 
 
 
 
3 days dietary record guidelines: 
61 
1. Please fill in this food intake log book as completely as possible for 2 weekdays and 1 
62 
weekend.  
63 
2. Subjects were not allowed to change food habits while food intake records were being 
64 
conducted. 
65 
3. For food records, please indicate the time, type and quantity/ size of all food and beverages 
66 
taken immediately after meal time. 
67 
4. If you have any further enquiry, please contact: 
68 
Livy Chong Guey Yong  017-7780620     chonggy-wr21@student.tarc.edu.my 
69 
 
70 
Household Measurements   
71 
A) Spoons   
72 
 
73 
 
74 
 
75 
 
76 
 
77 
 
78 
 
79 
 
80 
 
81 
 
82 
 
83 
 
84 
 
85 
B) Plate and Bowls  
86 
 
87 
 
88 
 
89 
 
90 
 
91 
 
92 
 
93 
 
94 
 
95 
 
96 
 
97 
 
98 
 
99 
 
100 
C) Cups, mugs and glassess   
101 
 
102 
APPENDIX E 
Three Days Dietary Record 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 
Teaspoon 
Table Spoon 
10ml 
Table Spoon 
10ml 
Scoop 
30ml 
Scoop 
15ml 
Scoop 
80ml 
Table Spoon 
20ml 
Sauce plate 
Small Bowl 
Diameter=9cm 
Volume=150ml 
Medium Bowl 
Diameter=11cm 
Volume=250ml 
Big Bowl 
Diameter=13cm 
Volume=450ml 

 
 
                             
 
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103 
 
104 
 
105 
 
106 
 
107 
 
108 
 
109 
 
110 
 
111 
 
112 
 
113 
 
114 
Date 
 
Monday / Tuesday / Wednesday / Thursday / Friday / Saturday/ Sunday 
Time  
Food & Beverage 
Quantity 
Note 
Breakfast 
(     :     am ) 
 
 
 
 
 
Morning Tea 
 (   :      am ) 
 
 
 
 
Lunch 
(   :      pm ) 
  
 
 
Afternoon 
Tea 
(   :       pm ) 
 
  
 
 
Dinner 
(   :      pm ) 
 
 
 
 
 
Supper 
(    :      pm ) 
 
 
 
 
Date 
 
Monday / Tuesday / Wednesday / Thursday / Friday / Saturday/ Sunday 
Time  
Food & Beverage 
Quantity 
Note 
Breakfast 
(     :     am ) 
 
 
 
 
Morning Tea 
 (   :      am ) 
 
 
 
 
Lunch 
(   :      pm ) 
 
  
 
 
Afternoon 
Tea 
(   :       pm ) 
 
  
 
 
Dinner 
(   :      pm ) 
 
  
 
 
Supper 
(    :      pm ) 
 
 
 
 
115 
150ml 
280ml 200ml 350ml 300ml 300ml 250ml 
200ml 
280ml 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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Date 
 
Monday / Tuesday / Wednesday / Thursday / Friday / Saturday/ Sunday 
Time  
Food & Beverage 
Quantity 
Note 
Breakfast 
(     :     am ) 
 
 
 
 
Morning Tea 
 (   :      am ) 
 
 
 
 
 
Lunch 
(   :      pm ) 
  
 
 
Afternoon 
Tea 
(   :       pm ) 
 
  
 
 
 
Dinner 
(   :      pm ) 
 
  
 
 
Supper 
(    :      pm ) 
 
 
 
 
 
 
116 
 
117 
 
118 
 
119 
 
120 
 
121 
 
122 
 
123 
 
124 
 
125 
 
126 
 
127 
APPENDIX G 
Havard Light Exposure Questionnaire 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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128 
 
129 
 
 
 
Harvard Light Exposure Assessment (H-LEA) Questionnaire 
130 
During a typical day, describe your exposure to the below specified light sources. Please fill in 
131 
applies, for each single day of your 7 days trial and circle the hours at which you had a meal, like 
132 
indicated in the example below. 
133 
H=Halogen Lamp 
 
 
F=Fluorescent Lamp 
134 
N=Natural Light (Indoors) 
 
S=Sunlight, Natural Light (Outdoors) 
135 
O=Other Artificial Light Sources  
D=Darkness 
136 
 
137 
 
138 
 
139 
 
140 
 
141 
 
142 
 
143 
 
144 
 
145 
 
 
146 
 
147 
 
148 
 
149 
 
150 
 
151 
 
152 
 
153 
 
154 
 
155 
 
156 
 
157 
 
158 
 
159 
 
160 
 
161 
 
162 
 
163 
 
164 
 
165 
 
166 
 
167 
 
168 
 
169 
 
170 
 
171 
 
172 
 
173 
 
174 
 
175 
Date: 
 
Night Shift Workhours From                     To               
 
Day Shift Workhours From                       To 
 
Off Work 
Time 
Exposure to Specified light sources 
1am 
 
2am 
 
3am 
 
4am 
 
5am 
 
6am 
 
7am 
 
8am 
 
9am 
 
10am 
 
11am 
 
Noon 
 
1pm 
 
2pm 
 
3pm 
 
4pm 
 
5pm 
 
6pm 
 
7pm 
 
8pm 
 
9pm 
 
10pm 
 
11pm 
 
12pm 
 
Reference: 
Archna 
Bajaj, 
Bernard 
Rosner, Steven W. Lockley, 
and Eva S. Schernhamme. 
2011. Validation of a Light 
Questionnaire with Real-life 
Photopic 
Illuminance 
Measurements: the Harvard 
Light Exposure Assessment 
Questionnaire. 
Cancer 
Epidemiology 
Biomarkers 
Prevention; 20(7); 1341–9.  

 
 
                             
 
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176 
 
177 
 
178 
 
179 
 
180 
 
181 
 
182 
Pittsburgh Sleep Quality Index 
183 
 
184 
Instructions: The following questions relate to your workday sleep habits over the past month 
185 
only. You need to state the most accurate answer for most of the days and nights of the past 
186 
month. Please answer all questions. 
187 
 
188 
1.  In the past month, what time did you usually go to bed at night on weekdays? 
189 
_____________ a.m / p.m 
190 
 
191 
2.  In the past month, how many minutes did it usually take you to fall asleep each night on a 
192 
weekday?_____________ minutes 
193 
 
194 
3. In the past month, what time do you usually get up in the morning on 
195 
weekdays?_____________a.m  
196 
 
197 
4. In the past month, how many hours did you get actual sleep at night on weekdays? (This 
198 
may be different from the number of hours you lie in bed). 
199 
_____________ hours 
200 
 
201 
Instructions: The following questions relate to your sleep habits on rest days during the past 
202 
month only. You need to state the most accurate answer for most of the days and nights of the 
203 
past month. Please answer all questions. 
204 
 
205 
5. In the past month, what time do you usually sleep at night on rest days? 
206 
_____________ a.m / p.m 
207 
 
208 
6.  In the past month, how many minutes did it usually take you to fall asleep each night on a 
209 
day off?_____________ minutes 
210 
 
211 
7. In the past month, what time do you usually get up in the morning on a day 
212 
off?_____________a.m  
213 
 
214 
8. In the past month, how many hours did you get actual sleep at night on a day off? (This may 
215 
be different from the number of hours you lie in bed)._____________ hours 
216 
 
217 
 
218 
 
219 
 
220 
 
221 
Instructions: The following questions relate to your normal sleep habits over the past month 
222 
only. You need to state the most accurate answer for most of the days and nights of the past 
223 
month. Please answer all questions. 
224 
 
225 
APPENDIX H 
Pittsburgh Sleep Quality Index Questionnaire 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 

 
 
                             
 
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9. In the past month, how often did you have trouble sleeping because you .... (Please tick √ 
226 
on the appropriate answer) 
227 
 
228 
a. Can't sleep in 30 minutes 
229 
☐ No for last month 
230 
☐ Less than once a week 
231 
☐ Once or twice a week 
232 
☐ Three or more times a week 
233 
 
234 
b. Wake up in the middle of the night or early in the morning 
235 
☐ No for last month 
236 
☐ Less than once a week 
237 
☐ Once or twice a week 
238 
☐ Three or more times a week 
239 
 
240 
c. Need to get up to use the bathroom 
241 
☐ No for last month 
242 
☐ Less than once a week 
243 
☐ Once or twice a week 
244 
☐ Three or more times a week 
245 
 
246 
d. Cannot breathe comfortably 
247 
☐ No for last month 
248 
☐ Less than once a week 
249 
☐ Once or twice a week 
250 
☐ Three or more times a week 
251 
 
252 
e. Coughing or snoring loudly 
253 
☐ No for last month 
254 
☐ Less than once a week 
255 
☐ Once or twice a week 
256 
☐ Three or more times a week 
257 
 
258 
f. Feeling too cold 
259 
☐ No for last month 
260 
☐ Less than once a week 
261 
☐ Once or twice a week 
262 
☐ Three or more times a week 
263 
 
264 
g. Feeling too hot 
265 
☐ No for last month 
266 
☐ Less than once a week 
267 
☐ Once or twice a week 
268 
☐ Three or more times a week 
269 
 
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h. Having bad dream 
271 
☐ No for last month 
272 
☐ Less than once a week 
273 
☐ Once or twice a week 
274 
☐ Three or more times a week 
275 
 
276 
i. Having pain 
277 
☐ No for last month 
278 
☐ Less than once a week 
279 
☐ Once or twice a week 
280 
☐ Three or more times a week 
281 
 
282 
j. Other reasons, please explain: 
283 
_____________________________________________________________________
284 
_____________________________________________________________________ 
285 
 
286 
10. In the past month, how often have you taken medication to help you sleep (on the doctor’s 
287 
instructions or bought yourself at the pharmacy)? 
288 
☐ No for last month 
289 
☐ Less than once a week 
290 
☐ Once or twice a week 
291 
☐ Three or more times a week 
292 
 
293 
11. In the past month, how often have you had trouble staying awake while driving, eating food, 
294 
or engaging in social activities? 
295 
☐ No for last month 
296 
☐ Less than once a week 
297 
☐ Once or twice a week 
298 
☐ Three or more times a week 
299 
 
300 
12. In the past month, how much trouble did you have to maintain enough enthusiasm in getting 
301 
things done? 
302 
☐ No Problem 
303 
☐ A little problem 
304 
☐ Somewhat problematic 
305 
☐ Big trouble 
306 
 
307 
13. In the past month, how have you assessed the quality of your sleep overall? 
308 
☐ Very good 
309 
☐ Quite good 
310 
☐ A little bad 
311 
☐ Very bad 
312 
 
313 
14. Do you have a sleeping partner or roommate? 
314 
☐ No sleeping partner or roommate → (You can stop answering) 
315 
☐ Sleeping partner or roommate in another room 
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☐ Couple in the same room but not in the same bed 
317 
☐ Couple sleeping in the same bed 
318 
 
319 
15. If you have a sleeping partner or roommate, ask him or her how often in the last month you 
320 
have: 
321 
 
322 
a. Loud snoring 
323 
☐ Not at all last month 
324 
☐ Less than once a week 
325 
☐ Once or twice a week 
326 
☐ Three or more times a week 
327 
 
328 
b. Long pauses between breaths during sleep 
329 
☐ Not at all last month 
330 
☐ Less than once a week 
331 
☐ Once or twice a week 
332 
☐ Three or more times a week 
333 
 
334 
c. Legs moving or jerking when you are sleeping 
335 
☐ Not at all last month 
336 
☐ Less than once a week 
337 
☐ Once or twice a week 
338 
☐ Three or more times a week 
339 
 
340 
 
341 
 
342 
 
343 
d. Episodes of disorientation or confusion during sleep 
344 
☐ Not at all last month 
345 
☐ Less than once a week 
346 
☐ Once or twice a week 
347 
☐ Three or more times a week 
348 
 
349 
 
350 
e. Other 
anxieties 
when 
you 
are 
sleeping, 
please 
explain: 
351 
________________________________________________________________ 
352 
 
353 
 
354 
Copyright notice:  
355 
The Pittsburgh Sleep Quality Index (PSQI) is copyrighted by Daniel J. Buysse, M.D. Permission has been granted to 
356 
reproduce the scale on this website for clinicians to use in their practice and for researchers to use in nonindustry studies. For 
357 
other uses of the scale, the owner of the copyright should be contacted. 
358 
 
359 
Reference: Buysse, DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ: The Pittsburgh Sleep Quality Index (PSQI): A new 
360 
instrument for psychiatric research and practice. Psychiatry Research 28:193-213, 1989 
361 
 
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363 
 
364 
 
365 
 
366 
 
367 
 
368 
 
369 
 
370 
Chrononutrition Profile – Questionnaire (CP-Q) 
371 
 
372 
Directions: The following questions are designed to assess the general timing of your eating. 
373 
Please choose the one response that best fits your typical behavior and preferences.  
374 
The term “eating event” refers to any time you eat something that contains calories. For 
375 
example, this could be a meal, a snack, or a drink. 
376 
 
377 
If you were entirely free to plan your day,  
378 
 
379 
A1. What time would you prefer to wake up?  
380 
Please indicate A.M. or P.M. as part of your response. 
381 
_______________________________________________ A.M./P.M. 
382 
 
383 
A2. How soon after waking up would you prefer to have your first eating event of the day? 
384 
________________________________ hours _______________________ minutes 
385 
 
386 
A3. How soon before bed would you prefer to stop eating? 
387 
________________________________ hours _______________________ minutes 
388 
 
389 
A4. What time would you prefer to fall asleep? Please indicate A.M. or P.M. as part of your 
390 
response. _______________________________________________ A.M./P.M. 
391 
 
392 
B1. On average, in a typical week (a 7-day period), B1. How often do you eat breakfast?  
393 
_____ 0 days _____ 1 day _____ 2 days_____ 3 days _____ 4 days _____ 5 days  
394 
_____ 6 days _____ 7 days 
395 
 
396 
B2. What is your largest meal of the day?  
397 
_____ Breakfast _____ Lunch _____ Dinner/Supper  
398 
_____ Other meal (Please describe: __________________________________________)  
399 
 
400 
B3. How often do you eat a snack after your last meal of the day?  
401 
_____ 0 days _____ 1 day _____ 2 days _____ 3 days _____ 4 days _____ 5 days _____ 6 
402 
days _____ 7 days 
403 
 
404 
B4. How often do you wake up in the night to eat?  
405 
_____ 0 days _____ 1 day _____ 2 days _____ 3 days _____ 4 days _____ 5 days _____ 6 
406 
days _____ 7 day 
407 
 
408 
 
409 
On average, on a typical workday or school day,  
410 
 
411 
C1. What time do you wake up?  
412 
Please indicate A.M./P.M. as part of your response. 
413 
_______________________________________________ A.M./P.M.  
414 
APPENDIX I 
Chrononutrition Profile Questionniare 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y 

 
 
                             
 
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415 
C2. What time is your first eating event of the day?  
416 
Please indicate A.M./P.M. as part of your response. 
417 
_______________________________________________ A.M./P.M.  
418 
 
419 
C3. What time do you eat lunch?  
420 
Please indicate A.M./P.M. as part of your response.  
421 
Select “I do not eat lunch” if you do not typically eat lunch. 
422 
________________________________ A.M./P.M. ______ I do not eat lunch.  
423 
 
424 
C4. What time is your last eating event before bed?  
425 
Please indicate A.M./P.M. as part of your response. 
426 
_______________________________________________ A.M./P.M.  
427 
 
428 
C5. What time do you fall asleep?  
429 
Please indicate A.M./P.M. as part of your response. 
430 
_______________________________________________ A.M./P.M. 
431 
 
432 
On average, on a typical weekend day or free day,  
433 
 
434 
D1. What time do you wake up?  
435 
Please indicate A.M./P.M. as part of your response. 
436 
_______________________________________________ A.M./P.M.  
437 
 
438 
D2. What time is your first eating event of the day?  
439 
Please indicate A.M./P.M. as part of your response. 
440 
_______________________________________________ A.M./P.M.  
441 
 
442 
D3. What time do you eat lunch? Please indicate A.M./P.M. as part of your response.  
443 
Select “I do not eat lunch” if you do not typically eat lunch. 
444 
_______________________________________________ A.M./P.M.  
445 
______ I do not eat lunch.  
446 
 
447 
D4. What time is your last eating event of the day before bed?  
448 
Please indicate A.M./P.M. as part of your response. 
449 
_______________________________________________ A.M./P.M.  
450 
 
451 
D5. What time do you fall asleep?  
452 
Please indicate A.M./P.M. as part of your response. 
453 
_______________________________________________ A.M./P.M. 
454 
 
455 
Reference:  
456 
Allison C. Veronda, Kelly C. Allison, Ross D. Crosby, and Leah A. Irish. 2019. Development, validation and 
457 
reliability of Chrononutrition Profile Questionnaire. Chronobiology International. DOI: 
458 
10.1080/07420528.2019.1692349 
459 
 
460 
 
461 
 
462 
 
463 
 
464 

 
 
                             
 
Version 1.0, Dated 6 May 2024 
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Anthropometry 
Measurement  
Reading 1 
Reading 2 
Reading 3 
Average 
ANTHROPOMETRY 
Height (cm) 
 
 
 
 
Weight (kg) 
 
 
 
 
Body Mass Index (kg/m2) 
 
 
 
 
Waist Circumference (cm) 
 
 
 
 
Hip Circumference (cm) 
 
 
 
 
Body Composition 
Body Fat percentage (%) 
 
 
 
 
Visceral Fat 
 
 
 
 
Subcutaneous Fat (Whole Body) 
 
 
 
 
Subcutaneous Fat (Trunk) 
 
 
 
 
Subcutaneous Fat (Arm) 
 
 
 
 
Subcutaneous Fat (Leg) 
 
 
 
 
Skeletal Muscle (Leg) 
 
 
 
 
Skeletal Muscle (Arm) 
 
 
 
 
Skeletal Muscle (Trunk) 
 
 
 
 
Skeletal Muscle (Whole Body) 
 
 
 
 
Resting Metabolism 
 
 
 
 
Body Age 
 
 
 
 
Medical Record 
Date 
 
 
 
 
HbA1C (%) 
 
 
 
 
Fasting Plasma Glucose (mmol/L) 
 
 
 
 
OGTT Plasma Glucose Value(mmol/L) 0 hour 
 
 
 
 
OGTT Plasma Glucose Value(mmol/L) 2 hours 
 
 
 
 
Blood Pressure (mm/Hg) 
 
 
 
 
Alanine Transaminase ALT (IU/L) 
 
 
 
 
 
APPENDIX J 
Anthropometry Measurement and Biochemistry 
Parameters 
Project Name:  
Meal Timing and Glucose Tolerance 
Date of interview: 
 
 
/ 
 
 
 
/ 
 
 
 
 
 
d 
d 
 
m 
m 
m 
 
y 
y 
y 
y