PhD Student, King's College London
I am investigating how sleep impacts determinants of weight and metabolic disease.
Short sleep duration and poor sleep quality have been associated with a higher risk of weight gain and development of metabolic diseases. These links are based on large observational studies that rely on self-reported measures of sleep duration. My research aims to validate these links by objectively measuring sleep using wrist-worn activity measurement devices, and investigating associations with diet, energy expenditure, activity levels and markers of metabolic disease risk. To understand whether the links are causal, I also conduct human clinical trials that manipulate sleep duration, and study how this may energy balance, and cardio-metabolic risk. The outcomes of this research may inform future public health messages, and suggest sleep may be a novel platform in addition to diet and exercise to more effectively target weight management and metabolic disease prevention.
Abstract: Pre-diabetes and diabetes occur secondary to a constellation of pathophysiological abnormalities that culminate in insulin resistance, which results in reduced cellular glucose uptake and increased glucose production. Although pre-diabetes and diabetes have a strong genetic basis, they are largely environmentally driven through lifestyle factors. Traditional lifestyle factors such as diet and physical activity do not fully explain the dramatic rise in the incidence and prevalence of diabetes mellitus. Sleep has emerged as an additional lifestyle behavior, important for metabolic health and energy homeostasis. In this article, we review the current evidence surrounding the sleep-diabetes association.
Pub.: 06 Nov '15, Pinned: 30 Jun '17
Abstract: Emerging evidence has assigned an important role to sleep as a modulator of metabolic homeostasis. The impact of variations in sleep duration, sleep-disordered breathing, and chronotype to cardiometabolic function encompasses a wide array of perturbations spanning from obesity, insulin resistance, type 2 diabetes, the metabolic syndrome, and cardiovascular disease risk and mortality in both adults and children. Here, we critically and extensively review the published literature on such important issues and provide a comprehensive overview of the most salient pathophysiologic pathways underlying the links between sleep, sleep disorders, and cardiometabolic functioning.
Pub.: 08 Sep '16, Pinned: 30 Jun '17
Abstract: Weight gain, obesity and diabetes have reached alarming levels in the developed world. Traditional risk factors such as over-eating, poor nutritional choices and lack of exercise cannot fully account for the high prevalence of metabolic disease. This review paper examines the scientific evidence on two novel risk factors that contribute to dys-regulated metabolic physiology: sleep disruption and circadian misalignment. Specifically, fundamental relationships between energy metabolism and sleep and circadian rhythms and the impact of sleep and circadian disruption on metabolic physiology are examined. Millions of individuals worldwide do not obtain sufficient sleep for healthy metabolic function, and many participate in shift work and social activities at times when the internal physiological clock is promoting sleep. These behaviours predispose an individual for poor metabolic health by promoting excess caloric intake in response to reduced sleep, food intake at internal biological times when metabolic physiology is not prepared, decreased energy expenditure when wakefulness and sleep are initiated at incorrect internal biological times, and disrupted glucose metabolism during short sleep and circadian misalignment. In addition to the traditional risk factors of poor diet and exercise, disturbed sleep and circadian rhythms represent modifiable risk factors for prevention and treatment of metabolic disease and for promotion of healthy metabolism.
Pub.: 07 Feb '17, Pinned: 30 Jun '17
Abstract: Objectives - To examine associations between sleep duration and health outcomes among distinct groups of sexual minority adults. Methods - Using data from the 2014 Behavioral Risk Factor Surveillance System, we compared sleep duration (very short: ≤5 hours, short: 6 hours, normal: 7-8 hours, and long: ≥9 hours per day) between cisgender straight adults and distinct groups of sexual minorities. We further examined associations between sleep duration and 10 chronic health conditions among sexual minorities. Results - Of 146,893 respondents, 142,507 (96.2%) were cisgender straight and 4,386 (3.8%) were lesbian, gay, bisexual, transgender (LGBT). Overall, 17.3% of LGBT respondents reported very short sleep per day, compared with 12.2% for cisgender straight respondents (p < 0.0001). Among LGBT populations, the prevalence of very short sleep varied significantly among distinct groups, ranging from 13.2% among transgender female to male adults to 35.5% among transgender gender nonconforming adults. Very short sleep was further associated with increased odds of having stroke (aOR = 4.1, 95% CI [2.2-7.6]), heart attack (aOR = 3.0, CI [1.6-5.8]), coronary heart disease (aOR = 3.1, 95% CI [1.5-6.2]), asthma (aOR = 1.7, 95% CI [1.1-2.4]), chronic obstructive pulmonary disease (aOR = 2.5, CI [1.5-4.0]), arthritis (aOR = 2.1, CI [1.4-3.0]), and cancer (aOR = 1.8, 95% CI [1.0-3.2]) among sexual minorities. Disparities in the prevalence of stroke, heart attack, coronary health disease, COPD, diabetes, obesity, arthritis and cancer were found among LGBT populations. Conclusions - Sexual minorities have a higher prevalence of sleep deprivation as compared with their straight counterparts. Sleep deprivation varies by sexual identity and gender. Very short sleep duration is associated with some chronic health conditions among LGBT populations. Promotion of sleep health education and routine medical assessment of sleep disorders are critically needed for sexual minority adults.
Pub.: 29 Jun '17, Pinned: 30 Jun '17
Abstract: The aim of the study was to investigate the accuracy of Sleep On Cue: a novel iPhone application that uses behavioural responses to auditory stimuli to estimate sleep onset. Twelve young adults underwent polysomnography recording while simultaneously using Sleep On Cue. Participants completed as many sleep-onset trials as possible within a 2-h period following their normal bedtime. On each trial, participants were awoken by the app following behavioural sleep onset. Then, after a short break of wakefulness, commenced the next trial. There was a high degree of correspondence between polysomnography-determined sleep onset and Sleep On Cue behavioural sleep onset, r = 0.79, P < 0.001. On average, Sleep On Cue overestimated sleep-onset latency by 3.17 min (SD = 3.04). When polysomnography sleep onset was defined as the beginning of N2 sleep, the discrepancy was reduced considerably (M = 0.81, SD = 1.96). The discrepancy between polysomnography and Sleep On Cue varied between individuals, which was potentially due to variations in auditory stimulus intensity. Further research is required to determine whether modifications to the stimulus intensity and behavioural response could improve the accuracy of the app. Nonetheless, Sleep On Cue is a viable option for estimating sleep onset and may be used to administer Intensive Sleep Retraining or facilitate power naps in the home environment.
Pub.: 29 Jun '17, Pinned: 30 Jun '17
Abstract: This meta-analysis examined the mean sleep duration and patterns in Chinese older adult population. A literature search was systematically conducted covering major English (PubMed, Embase and PsycINFO) and Chinese (Chinese National Knowledge Infrastructure (CNKI), WanFang and SinoMed) databases. Data in studies with the mean and standard deviation of sleep duration and/or the proportion of short and long sleep durations in Chinese older adults were extracted and pooled using random-effects models. Subgroup analyses were conducted according to gender, region, area, survey time and sample size. A total of 36 studies with 150,616 subjects were included for analyses. The pooled mean sleep duration of 21 studies with available data was 6.82 hours/day (95% CI: 6.59-7.05 hours/day). The estimated proportions of sleep duration <5 hours/day, <6 hours/day, <7 hours/day were 18.8% (95% CI: 1.7%-35.9%), 26.7% (95% CI: 19.7%-33.7%) and 42.3% (95% CI: 34.8%-49.8%), respectively. The pooled proportions for long sleepers were 22.6% (95% CI: 13.9%-31.4%) (>8 hours/day) and 17.6% (95% CI: 12.4%-22.9%) (>9 hours/day). Given the adverse effects of unhealthy sleep patterns, health professionals should pay more attention to sleep patterns in this population in China.
Pub.: 29 Jun '17, Pinned: 30 Jun '17
Abstract: It is unknown whether short sleep duration causatively contributes to weight gain. Studies investigating effects of partial sleep deprivation (PSD) on energy balance components report conflicting findings. Our objective was to conduct a systematic review and meta-analysis of human intervention studies assessing the effects of PSD on energy intake (EI) and energy expenditure (EE).EMBASE, Medline, Cochrane CENTRAL, Web of Science and Scopus were searched. Differences in EI and total EE following PSD compared with a control condition were generated using the inverse variance method with random-effects models. Secondary outcomes included macronutrient distribution and resting metabolic rate. Heterogeneity was quantified with the I(2)-statistic.Seventeen studies (n=496) were eligible for inclusion in the systematic review, and 11 studies (n=172) provided sufficient data to be included in meta-analyses. EI was significantly increased by 385 kcal (95% confidence interval: 252, 517; P<0.00001) following PSD compared with the control condition. We found no significant change in total EE or resting metabolic rate as a result of PSD. The observed increase in EI was accompanied by significantly higher fat and lower protein intakes, but no effect on carbohydrate intake.The pooled effects of the studies with extractable data indicated that PSD resulted in increased EI with no effect on EE, leading to a net positive energy balance, which in the long term may contribute to weight gain.European Journal of Clinical Nutrition advance online publication, 2 November 2016; doi:10.1038/ejcn.2016.201.
Pub.: 03 Nov '16, Pinned: 30 Jun '17
Abstract: There is a need to develop sound healthcare practices where patients and providers are able to succeed in meeting weight management goals. The aim of this analysis is to develop a better understanding the concept of weight management.Obesity is a rapidly growing healthcare issue, reaching epidemic levels around the world. According to the World Health Organization, the current incident rate of obesity makes it the leading risk for death across the globe.Walker and Avant's model for concept analysis.A literature search was accomplished using Cumulative Index to Nursing and Allied Health, Health Source: Nursing Academic Edition, Medline, and ProQuest Health and Medical Complete.Keywords included weight management, weight control, weight loss, obesity, weight, and management.Weight management is complex concept. Strategies to develop successful weight management programs need to be multifaceted to have impact on this healthcare crisis.The critical attributes for weight management are dietary measures, physical activity, behavior modification, motivation, education, and lifelong changes. Unsuccessful weight management results in metabolic disorders and increased risk of mortality. Successful weight management practices include the prevention of weight gain, weight loss, and maintenance of ideal body weight.
Pub.: 29 Jun '17, Pinned: 30 Jun '17