Short sleep and social jetlag are associated with higher intakes of non-milk extrinsic sugars, and social jetlag is associated with lower fibre intakes in those with adequate sleep duration: a cross-sectional analysis from the National Diet and Nutrition Survey Rolling Programme (Years 1-9).

OBJECTIVE: To investigate associations and interactions between sleep duration and social jetlag status with nutrient intake, nutrient status, body composition and cardio-metabolic risk factors in a nationally representative UK adult population. DESIGN: A cross-sectional study using 4-d food diary and self-reported sleep data from the UK National Diet and Nutrition Survey Rolling Programme 2008-2017. SETTING: UK free-living population. SUBJECTS: Totally, 5015 adults aged 19-64 years. RESULTS: Thirty-four per cent were short sleepers (< 7 h); 7 % slept ≥ 9 h; 14 % had > 2 h difference in average sleep duration between weeknights and weekend nights (social jetlag). Compared to those reporting optimal sleep duration (≥ 7-< 9 h), short sleep was associated with higher intakes of non-milk extrinsic sugars (NMES) (0·9 % energy, 95 % CI: 0·4, 1·4), total carbohydrate (0·8 % energy, 95 % CI: 0·2, 1·4) and a lower non-starch polysaccharides fibre intake (-0·5 g/d, 95 % CI -0·8, -0·2). There was a significant interaction between short sleep and social jetlag for fibre intakes, where adequate sleepers with social jetlag as well as all short sleepers (regardless of social jetlag) had lower fibre intakes than adequate sleepers with no social jetlag. Short sleep, but not social jetlag, was associated with greater adiposity, but there were no differences in other markers of cardiometabolic disease risk. CONCLUSIONS: The present study reports that both short sleep and social jetlag are associated with higher intakes of NMES, but only sleep duration is associated with markers of adiposity. Social jetlag was associated with lower fibre intakes even in individuals with adequate weekly sleep duration, suggesting catch-up sleep does not prevent the adverse impact of irregular sleep habits on food choices.

Blue poo: impact of gut transit time on the gut microbiome using a novel marker.

BACKGROUND AND AIMS: Gut transit time is a key modulator of host-microbiome interactions, yet this is often overlooked, partly because reliable methods are typically expensive or burdensome. The aim of this single-arm, single-blinded intervention study is to assess (1) the relationship between gut transit time and the human gut microbiome, and (2) the utility of the 'blue dye' method as an inexpensive and scalable technique to measure transit time. METHODS: We assessed interactions between the taxonomic and functional potential profiles of the gut microbiome (profiled via shotgun metagenomic sequencing), gut transit time (measured via the blue dye method), cardiometabolic health and diet in 863 healthy individuals from the PREDICT 1 study. RESULTS: We found that gut microbiome taxonomic composition can accurately discriminate between gut transit time classes (0.82 area under the receiver operating characteristic curve) and longer gut transit time is linked with specific microbial species such as Akkermansia muciniphila, Bacteroides spp and Alistipes spp (false discovery rate-adjusted p values <0.01). The blue dye measure of gut transit time had the strongest association with the gut microbiome over typical transit time proxies such as stool consistency and frequency. CONCLUSIONS: Gut transit time, measured via the blue dye method, is a more informative marker of gut microbiome function than traditional measures of stool consistency and frequency. The blue dye method can be applied in large-scale epidemiological studies to advance diet-microbiome-health research. Clinical trial registry website https://clinicaltrials.gov/ct2/show/NCT03479866 and trial number NCT03479866.

A comparison of heart rate variability, n-3 PUFA status and lipid mediator profile in age- and BMI-matched middle-aged vegans and omnivores.

Low heart rate variability (HRV) predicts sudden cardiac death. Long-chain (LC) n-3 PUFA (C20-C22) status is positively associated with HRV. This cross-sectional study investigated whether vegans aged 40-70 years (n 23), whose diets are naturally free from EPA (20 : 5n-3) and DHA (22 : 6n-3), have lower HRV compared with omnivores (n 24). Proportions of LC n-3 PUFA in erythrocyte membranes, plasma fatty acids and concentrations of plasma LC n-3 PUFA-derived lipid mediators were significantly lower in vegans. Day-time interbeat intervals (IBI), adjusted for physical activity, age, BMI and sex, were significantly shorter in vegans compared with omnivores (mean difference -67 ms; 95 % CI -130, -3·4, P50 % and high-frequency power) were similarly lower in vegans, with no differences during sleep. In conclusion, vegans have higher 24 h SDNN, but lower day-time HRV and shorter day-time IBI relative to comparable omnivores. Vegans may have reduced availability of precursor markers for pro-resolving lipid mediators; it remains to be determined whether there is a direct link with impaired cardiac function in populations with low-n-3 status.

Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition.

BACKGROUND: Continuous glucose monitor (CGM) devices enable characterization of individuals' glycemic variation. However, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application in personalized nutrition recommendations. OBJECTIVES: We aimed to evaluate the concordance of 2 simultaneously worn CGM devices in measuring postprandial glycemic responses. METHODS: Within ZOE PREDICT (Personalised Responses to Dietary Composition Trial) 1, 394 participants wore 2 CGM devices simultaneously [n = 360 participants with 2 Abbott Freestyle Libre Pro (FSL) devices; n = 34 participants with both FSL and Dexcom G6] for ≤14 d while consuming standardized (n = 4457) and ad libitum (n = 5738) meals. We examined the CV and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Within-subject meal ranking was assessed using Kendall τ rank correlation. Concordance between paired devices in time in range according to the American Diabetes Association cutoffs (TIRADA) and glucose variability (glucose CV) was also investigated. RESULTS: The CV of glucoseiAUC0-2 h for standardized meals was 3.7% (IQR: 1.7%-7.1%) for intrabrand device and 12.5% (IQR: 5.1%-24.8%) for interbrand device comparisons. Similar estimates were observed for ad libitum meals, with intrabrand and interbrand device CVs of glucoseiAUC0-2 h of 4.1% (IQR: 1.8%-7.1%) and 16.6% (IQR: 5.5%-30.7%), respectively. Kendall τ rank correlation showed glucoseiAUC0-2h-derived meal rankings were agreeable between paired CGM devices (intrabrand: 0.9; IQR: 0.8-0.9; interbrand: 0.7; IQR: 0.5-0.8). Paired CGMs also showed strong concordance for TIRADA with a intrabrand device CV of 4.8% (IQR: 1.9%-9.8%) and an interbrand device CV of 3.2% (IQR: 1.1%-6.2%). CONCLUSIONS: Our data demonstrate strong concordance of CGM devices in monitoring glycemic responses and suggest their potential use in personalized nutrition.This trial was registered at clinicaltrials.gov as NCT03479866.

Human postprandial responses to food and potential for precision nutrition.

Metabolic responses to food influence risk of cardiometabolic disease, but large-scale high-resolution studies are lacking. We recruited n = 1,002 twins and unrelated healthy adults in the United Kingdom to the PREDICT 1 study and assessed postprandial metabolic responses in a clinical setting and at home. We observed large inter-individual variability (as measured by the population coefficient of variation (s.d./mean, %)) in postprandial responses of blood triglyceride (103%), glucose (68%) and insulin (59%) following identical meals. Person-specific factors, such as gut microbiome, had a greater influence (7.1% of variance) than did meal macronutrients (3.6%) for postprandial lipemia, but not for postprandial glycemia (6.0% and 15.4%, respectively); genetic variants had a modest impact on predictions (9.5% for glucose, 0.8% for triglyceride, 0.2% for C-peptide). Findings were independently validated in a US cohort (n = 100 people). We developed a machine-learning model that predicted both triglyceride (r = 0.47) and glycemic (r = 0.77) responses to food intake. These findings may be informative for developing personalized diet strategies. The ClinicalTrials.gov registration identifier is NCT03479866.

Sleep extension is a feasible lifestyle intervention in free-living adults who are habitually short sleepers: a potential strategy for decreasing intake of free sugars? A randomized controlled pilot study.

Background: Evidence suggests that short sleep duration may be a newly identified modifiable risk factor for obesity, yet there is a paucity of studies to investigate this. Objective: We assessed the feasibility of a personalized sleep extension protocol in adults aged 18-64 y who are habitually short sleepers (5 to <7 h), with sleep primarily measured by wrist actigraphy. In addition, we collected pilot data to assess the effects of extended sleep on dietary intake and quality measured by 7-d food diaries, resting and total energy expenditure, physical activity, and markers of cardiometabolic health. Design: Forty-two normal-weight healthy participants who were habitually short sleepers completed this free-living, 4-wk, parallel-design randomized controlled trial. The sleep extension group (n = 21) received a behavioral consultation session targeting sleep hygiene. The control group (n = 21) maintained habitual short sleep. Results: Rates of participation, attrition, and compliance were 100%, 6.5%, and 85.7%, respectively. The sleep extension group significantly increased time in bed [0:55 hours:minutes (h:mm); 95% CI: 0:37, 1:12 h:mm], sleep period (0:47 h:mm; 95% CI: 0:29, 1:05 h:mm), and sleep duration (0:21 h:mm; 95% CI: 0:06, 0:36 h:mm) compared with the control group. Sleep extension led to reduced intake of free sugars (-9.6 g; 95% CI: -16.0, -3.1 g) compared with control (0.7 g; 95% CI: -5.7, 7.2 g) (P = 0.042). A sensitivity analysis in plausible reporters showed that the sleep extension group reduced intakes of fat (percentage), carbohydrates (grams), and free sugars (grams) in comparison to the control group. There were no significant differences between groups in markers of energy balance or cardiometabolic health. Conclusions: We showed the feasibility of extending sleep in adult short sleepers. Sleep extension led to reduced free sugar intakes and may be a viable strategy to facilitate limiting excessive consumption of free sugars in an obesity-promoting environment. This trial was registered at www.clinicaltrials.gov as NCT02787577.