Obesity is a significant health issue in Aotearoa; effective and pragmatic strategies to facilitate weight loss are urgently required. Growing recognition of the circadian rhythm’s impact on metabolism has popularised diets like time-restricted eating (TRE)(1). The 16:8 TRE method involves limiting food intake to an 8-hour daily eating window and can lead to weight loss without other substantial changes to diet(2). Nonetheless, TRE requires accountability and tolerating hunger for short periods. Continuous glucose monitors (CGM) are small wearable biofeedback devices that measure interstitial glucose levels scanned via smartphones. By providing immediate feedback on the physiological effects of eating and fasting, CGM use may promote adherence to TRE(3). This pilot study aimed to 1) investigate how CGM affects adherence to TRE and 2) assess the feasibility of CGM use while undertaking TRE. This two-arm randomised controlled trial enrolled healthy adults from Dunedin, assigning them to TRE-only or TRE+CGM groups for 14 days. Successful adherence to TRE was defined a priori as maintaining an 8-hour eating window on 80% of days. CGM feasibility was defined a priori as scanning the glucose monitor thrice daily on 80% of days. Secondary outcomes included well-being, anthropometry, glucose levels, and overall TRE and CGM experiences via semi-structured interviews. Twenty-two participants were randomised into two groups: TRE-only (n = 11) and TRE+CGM (n = 11, with n = 2 excluded from analysis post-randomisation for medical reasons). Participants had a diverse range of ethnicities, the mean age was 32 (+/-14.9) years, and 55% were female. The TRE+CGM group adhered to the 8-hour eating window for an average of 10.0 days (range 2-14) compared with 8.6 days (range 2-14) in the TRE-only group. Both groups had similar mean eating window durations of 8.1 hours. Five (56%) participants in the TRE+CGM group achieved the a priori criteria for TRE adherence, compared to 3 (27%) in the TRE-only group. Participants in the TRE+CGM group performed an average of 8.2 (+/-5.6) daily scans, with n = 7 (78%) of participants meeting the a priori CGM feasibility criteria. Neither group reported consistent adverse psychological impacts in DASS-21 and WHO-5 scores. Interviews highlighted that CGM increased hunger tolerance during fasting as participants felt reassured by their normal glucose levels. CGM aided TRE accountability by acting as a biological tracker of food intake. Participants reported that TRE led to improved energy and self-efficacy, a more productive daily routine, and healthier food choices. Promisingly, 72% of participants would use CGM and undertake TRE in future. This study demonstrates that using CGM while undertaking TRE is feasible and can improve adherence by enhancing hunger tolerance and accountability. Overall, participants experienced increased awareness of eating habits and physiological mechanisms. Over the longer term, this simple and synergistic approach may be a helpful weight loss strategy.

Advances in genomics generated the concept that a better understanding of individual characteristics, e.g. genotype, will lead to improved tailoring of pharmaceutical and nutritional therapies. Subsequent developments in proteomics and metabolomics, in addition to wearable technologies for tracking parameters, such as dietary intakes, physical activity, heart rate and blood glucose, have further driven this idea. Alongside these innovations, there has been a rapid rise in companies offering direct-to-consumer genetic and/or microbiome testing, in combination with the marketing of personalised nutrition services. Key scientific questions include how disparate datasets are integrated, how accurate are current predictions and how these may be developed in the future. In this regard, lessons can be learned from systems biology, which aims both to integrate data from different levels of organisation (e.g. genomic, proteomic and metabolomic) and predict the emergent behaviours of biological systems or organisms as a whole. The present paper reviews the origins and recent advancement of ‘big data’ and systems approaches in medicine and nutrition. Conclusions are that systems integration of multiple technologies has generated mechanistic insights and informed the evolution of precision medicine and personalised nutrition. Pertinent ethical issues include who is entitled to access new technologies and how commercial companies are storing, using and/or re-mining consumer data. Questions about efficacy (both long-term behavioural change and health outcomes), cost-benefit and impacts on health inequalities remain to be fully addressed.

There is emerging evidence that glycaemic variability (GV) plays an important role in the development of diabetic complications. The current study aimed to compare the effects of lifestyle intervention (LI) with and without partial meal replacement (MR) on GV. A total of 123 patients with newly diagnosed and untreated type 2 diabetes (T2D) were randomised to receive either LI together with breakfast replacement with a liquid formula (LI+MR) (n 62) or LI alone (n 61) for 4 weeks and completed the study. Each participant was instructed to have three main meals per d and underwent 72-h continuous glucose monitoring (CGM) both before and after intervention. Measures of GV assessed by CGM included the incremental AUC of postprandial blood glucose (AUCpp), standard deviation of blood glucose (SDBG), glucose CV and mean amplitude of glycaemic excursions (MAGE). After a 4-week intervention, the improvements in systolic blood pressure (P=0·046) and time in range (P=0·033) were more pronounced in the LI+MR group than in the LI group. Furthermore, LI+MR caused significantly greater improvements in all GV metrics including SDBG (P=0·005), CV (P=0·002), MAGE (P=0·016) and AUCpp (P<0·001) than did LI. LI+MR (v. LI) was independently associated with improvements in GV after adjustment of covariates (all P<0·05). Our study showed that LI+MR led to significantly greater improvements in GV compared with LI, suggesting that LI+MR could be an effective treatment to alleviate glucose excursions.

The aim of the present study was to validate the Glucoday® continuous interstitial ambulatory glucose-monitoring device (AGD) against plasma glucose measured from arterialised venous (AV) and glucose from capillary whole blood (finger prick, FP) in non-diabetic subjects in response to an oral glucose tolerance test. Fifteen healthy overweight men (age 30–49 years, BMI 26–31 kg/m2) participated. Glucose levels were measured before, during and after consumption of an oral 75 g glucose load using twelve FP samples and forty-four 1 ml AV blood samples during 180 min. Interstitial glucose was measured via the AGD. Three venous samples for fasting insulin were taken to estimate insulin resistance. Profiles of AGD, AV and FP glucose were generated for each participant. Glucose values for each minute of the measurement period were interpolated using a locally weighted scatterplot smoother. Data were compared using Bland–Altman plots that showed good correspondence between all pairs of measurements. Concordance between the three methods was 0·8771 (Kendall's W, n 15, P < 0·001). Concordance was greater between AV and FP (W = 0·9696) than AGD and AV (W = 0·8770) or AGD and FP (W = 0·8764). Analysis of time to peak glucose indicated that AGD measures lagged approximately 15 min behind FP and AV measures. Percent body fat was significantly correlated with time to peak glucose levels for each measure, while BMI and estimated insulin resistance (homeostatic model assessment, HOMA) were not. In conclusion, AGD shows good correspondence with FP and AV glucose measures in response to a glucose load with a 15 min time lag. Taking this into account, AGD has potential application in nutrition and behaviour studies.

Elevated postprandial glycaemia has been linked to CVD in a number of different epidemiological studies involving predominantly non-diabetic volunteers. The MiniMed continuous glucose monitor, which measures blood glucose every 5 min, over a 24 h period, was used to investigate changes in blood glucose readings before and after instigating a diet with low glycaemic index (GI) for 1 week in free-living healthy individuals. Nine healthy people (age 27 (sem 1·3) years, BMI 23·7 (sem 0·7) kg/m2, one male, eight females) completed the study. A reduction in GI (59·7 (sem 2) v. 52·1 (sem 2), P<0·01) occurred in all nine subjects while energy and other macronutrients remained constant. A significant reduction was also observed in fasting glucose at 06·00 hours (5·4 (sem 0·2) v. 4·4 (sem 0·3) mmol/l, P<0·001), mean glucose (5·6 (sem 0·2) v. 5·1 (sem 0·2) mmol/l, P=0·004), area under the 24 h glucose curve (8102 (sem 243) v. 750 (sem 235) mmol/l per min, P=0·004) and area under the overnight, 8 h glucose curve (2677 (sem 92) v. 2223 (sem 121) mmol/l per min, P=0·01). The present study provides important data on how a simple adjustment to the diet can improve glucose profiles that, if sustained in the long term, would be predicted from epidemiological studies to have a favourable influence on CVD.