Glycaemic Response to a Nut-Enriched Diet in Asian Chinese Adults with Normal or High Glycaemia: The Tu Ora RCT.

Nut-based products are a good source of high-quality plant protein in addition to mono- and polyunsaturated fatty acids, and may aid low-glycaemic dietary strategies important for the prevention of type 2 diabetes (T2D). In particular, they may be advantageous in populations susceptible to dysglycaemia, such as Asian Chinese. The present study aimed to compare effects of a higher-protein nut bar (HP-NB, also higher in total fibre and unsaturated fats, comprising mixed almonds and peanuts) vs. an isoenergetic higher-carbohydrate cereal bar (HC-CB) within the diet of 101 Chinese adults with overweight and normo- or hyperglycaemia. Ectopic pancreas and liver fat were characterised using magnetic resonance imaging and spectroscopy (MRI/S) as a secondary outcome. Participants were randomized to receive HP-NB or HC-CB daily as a 1 MJ light meal or snack replacement, in addition to healthy eating advice. Anthropometry and clinical indicators of T2D risk were assessed fasted and during an oral glucose tolerance test (OGTT), pre- and post-intervention. No significant difference was observed between diet groups for body weight, body mass index, waist or hip circumference, blood pressure, glucoregulatory markers, lipid profile or inflammatory markers over 12 weeks (all, p > 0.05). No difference was observed between glycaemic subgroups or those with normal versus high ectopic organ fat. Although HP-NB can attenuate postprandial glycaemia following a meal, no effects were observed for either fasting or glucose-mediated outcomes following longer-term inclusion in the habitual diet of Chinese adults with overweight, including at-risk subgroups.

Effect of a Higher-Protein Nut versus Higher-Carbohydrate Cereal Enriched Diet on the Gut Microbiomes of Chinese Participants with Overweight and Normoglycaemia or Prediabetes in the Tu Ora Study.

Global increases in metabolic disorders such as type 2 diabetes (T2D), especially within Asian populations, highlight the need for novel approaches to dietary intervention. The Tu Ora study previously evaluated the effects on metabolic health of including a nut product into the diet of a New Zealand cohort of Chinese participants with overweight and normoglycaemia or prediabetes through a 12-week randomised, parallel-group clinical trial. In this current study, we compared the impact of this higher-protein nut bar (HP-NB) versus a higher-carbohydrate cereal bar (HC-CB) on the faecal microbiome by employing both 16S rRNA gene amplicon and shotgun metagenomic sequencing of pre- and post-intervention pairs from 84 participants. Despite the higher fibre, protein, and unsaturated fat content of nuts, there was little difference between dietary groups in gut microbiome composition or functional potential, with the bacterial phylum Firmicutes dominating irrespective of diet. The lack of observed change suggests the dietary impact of the bars may have been insufficient to affect the gut microbiome. Manipulating the interplay between the diet, microbiome, and metabolic health may require a more substantial and/or prolonged dietary perturbation to generate an impactful modification of the gut ecosystem and its functional potential to aid in T2D risk reduction.

A Polynesian-specific SLC22A3 variant associates with low plasma lipoprotein(a) concentrations independent of apo(a) isoform size in males.

Lipoprotein(a) (Lp(a)) is a low-density lipoprotein (LDL)-like particle in which the apolipoprotein B component is covalently linked to apolipoprotein(a) (apo(a)). Lp(a) is a well-established independent risk factor for cardiovascular diseases. Plasma Lp(a) concentrations vary enormously between individuals and ethnic groups. Several nucleotide polymorphisms in the SLC22A3 gene associate with Lp(a) concentration in people of different ethnicities. We investigated the association of a Polynesian-specific (Maori and Pacific peoples) SLC22A3 gene coding variant p.Thr44Met) with the plasma concentration of Lp(a) in a cohort of 302 healthy Polynesian males. An apo(a)-size independent assay assessed plasma Lp(a) concentrations; all other lipid and apolipoprotein concentrations were measured using standard laboratory techniques. Quantitative real-time polymerase chain reaction was used to determine apo(a) isoforms. The range of metabolic (HbA1c, blood pressure, and blood lipids) and blood lipid variables were similar between the non-carriers and carriers in age, ethnicity and BMI adjusted models. However, rs8187715 SLC22A3 variant was significantly associated with lower Lp(a) concentrations. Median Lp(a) concentration was 10.60 nmol/L (IQR: 5.40-41.00) in non-carrier group, and was 7.60 nmol/L (IQR: 5.50-12.10) in variant carrier group (P<0.05). Lp(a) concentration inversely correlated with apo(a) isoform size. After correction for apo(a) isoform size, metabolic parameters and ethnicity, the association between the SLC22A3 variant and plasma Lp(a) concentration remained. The present study is the first to identify the association of this gene variant and low plasma Lp(a) concentrations. This provides evidence for better guidance on ethnic specific cut-offs when defining 'elevated' and 'normal' plasma Lp(a) concentrations in clinical applications.

A randomised controlled trial of additional bolus insulin using an insulin-to-protein ratio compared with insulin-to-carbohdrate ratio alone in people with type 1 diabetes following a carbohydrate-restricted diet.

AIMS: Postprandial hyperglycemia can be problematic for people with type 1 diabetes (T1DM) following carbohydrate-restricted diets. Bolus insulin calculated for meal protein plus carbohydrate may help. This study evaluated the effect of additional bolus insulin using an insulin-to-protein ratio (IPR) on glycaemic control. MATERIALS AND METHODS: Participants with T1DM aged ≥18-years were randomly allocated (1:1) to either carbohydrate and protein-based, or carbohydrate-based insulin dosing alone for 12 weeks while following a carbohydrate-restricted diet (50-100 g/day). Measurement of HbA1c and continuous glucose monitoring occurred at baseline and 12 weeks, with assessment of participant experience at 12 weeks. RESULTS: Thirty-four participants were randomised, 22 female, mean(SD): age 39.2 years (12.6) years; diabetes duration 20.6 years (12.9); HbA1c 7.3 % (0.8), 56.7 mmol/mol (9.2). Seven in each group used insulin pump therapy. HbA1c reduced at 12 weeks with no difference between treatments: mean (SD) control 7.2 % (1.0), 55.7 mmol/mol (10.6); intervention 6.9 % (0.7), 52.3 mmol/mol (7.2) (p = 0.65). Using additional protein-based insulin dosing compared with carbohydrate alone, there was no difference in glycaemic variability, time spent in euglycemic range (TIR), or below range. Participants using IPR reported more control of their diabetes, but varying levels of distress. CONCLUSIONS: Additional bolus insulin using an IPR did not improve glycaemic control or TIR in patients with well controlled T1DM following a carbohydrate-restricted diet. Importantly, the use of the IPR does not increase the risk of hypoglycemia and may be preferred.

He Rourou Whai Painga, an Aotearoa New Zealand dietary pattern for metabolic health and whanau wellbeing: protocol for a randomized controlled trial.

Background: Cardiometabolic diseases are highly prevalent in Aotearoa New Zealand. Dietary intake is a modifiable risk factor for such diseases and certain dietary patterns, specifically the Mediterranean diet (MedDiet), are associated with improved metabolic health. This study aims to test whether an intervention including a Mediterranean dietary pattern incorporating high quality New Zealand foods (NZMedDiet pattern) and behavior change science can improve the metabolic health of participants and their household/whanau. Methods and analysis: This is a multi-center, three-stage trial with two parallel group superiority randomized controlled trials (RCTs), and a longitudinal cohort study embedded within the trial design. The first RCT (RCT 1) is a comparison of the NZMedDiet pattern compared to usual diet for 12 weeks. The Behavior Change Wheel was used to select and implement strategies to support participant adherence to the NZMedDiet, such as web-based nutrition education on healthy shopping and cooking. The second (RCT 2) compares online social support to no online social support for 12 weeks, administered to participants immediately following RCT 1. The third stage is a longitudinal cohort study where all participants are followed from the beginning of their start of the active intervention for 12 months in total. The primary outcome measure for each stage is the metabolic syndrome severity score (MetSSS). The duration of enrolment is 12-15 months. The total recruitment target is 200 index participants and their household/whanau members who participate with them, and the primary analyses will be intention to treat on index participants. Discussion: The trial will test whether the NZMedDiet pattern and behavior change support improves the cardiometabolic health of people in Aotearoa New Zealand. Clinical trial registration: https://www.anzctr.org.au/Default.aspx, identifier ACTRN12622000906752 and https://www.isrctn.com/, identifier ISRCTN89011056 (Spirit 2).

Habitual Dietary Patterns, Nutrient Intakes, and Adherence to the Mediterranean Diet among New Zealand Adults: The NZ MED Cross-Sectional Study.

There is increasing evidence that adherence to a Mediterranean dietary pattern reduces the incidence of diet-related diseases. To date, the habitual dietary intake of New Zealand (NZ) adults has not been examined in relation to its alignment with a Mediterranean-style dietary pattern. This study aimed to define the habitual dietary patterns, nutrient intakes, and adherence to the Mediterranean Diet in a sample of 1012 NZ adults (86% female, mean age 48 ± 16 years) who had their diabetes risk defined by the Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK). Dietary intakes were collected using a validated semi-quantitative NZ food frequency questionnaire, and dietary patterns were identified using principal component analysis. Reported intakes from the FFQ were used in conjunction with the Mediterranean-Style Dietary Pattern Score (MSDPS) to determine adherence to a Mediterranean dietary pattern. Mixed linear models were used to analyze the association between dietary patterns and MSDPS with demographics, health factors, and nutrient intakes. Two distinct dietary patterns were identified: Discretionary (positive loadings on processed meat, meat/poultry, fast food, sweet drinks, and sugar, sweets, and baked good) and Guideline (positive loadings on vegetables, eggs/beans, and fruits). Adherence to dietary patterns and diet quality was associated with age and ethnicity. Dietary patterns were also associated with sex. Adherence to a Mediterranean dietary pattern defined by the MSDPS was low, indicating that a significant shift in food choices will be required if the Mediterranean Diet is to be adopted in the NZ population.

Metabolic syndrome severity score (MetSSS) associates with metabolic health status in multi-ethnic Aotearoa New Zealand cohorts.

AIM: To investigate the relationship of metabolic syndrome severity score (MetSSS) with glucose regulatory and cardiovascular disease (CVD) status in Aotearoa New Zealand. METHODS: MetSSS and MetSSS component coefficients were calculated for participants from the cross-sectional Workforce Diabetes Study (WDS) (n = 5,806) and Diabetes, Heart and Health Survey (DHAH) (n = 4,010) and compared by ethnicity (European, Maori, Pacific and Asian), glucose regulatory status [impaired fasting glucose, impaired glucose tolerance and type 2 diabetes) and history of cardiovascular disease. RESULTS: MetSSS positively associated with impaired glucose regulatory status and history of cardiovascular disease for all ethnic groups. Ethnicity significantly affected different coefficients of the MetSSS components, however all ethnicities had an approximately normal MetSSS distribution, with Maori and Pacific curves being right-shifted compared to European. While the MetSSS thresholds that capture 80% of participant with type 2 diabetes (T2D) were higher for Maori and Pacific, the difference in MetSSS between those participants with and without type 2 diabetes within an ethnicity group was similar across ethnicities. CONCLUSION: MetSSS may have utility as a tool to quantify an individual's cardiometabolic disease risk within the multi-ethnic population of Aotearoa New Zealand, however ethnic-specific categories for disease risk are likely to be required.

Very low carbohydrate (ketogenic) diets in type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials.

AIM: Very low carbohydrate/ketogenic diets (VLC/KDs) are popular but their role in managing pre-diabetes and type 2 diabetes (T2D) is uncertain. This study uses a systematic review and meta-analysis of randomized controlled trials to estimate the effect of these diets in this population. MATERIALS AND METHODS: A systematic review identified randomized controlled trials of at least 6 months duration comparing efficacy and safety of VLC/KDs (≤50 g carbohydrate or ≤10% total energy from carbohydrate per day) with a control diet (carbohydrate above the VLC/KD threshold) in adults with pre-diabetes or T2D. The primary outcome variable was glycated haemoglobin (HbA1c) after 12 months. The meta-analysis method was inverse variance weighting of mean values for continuous variables. RESULTS: Key word searches identified 2290 studies; 2221 were not in scope. A full text review of 69 studies identified eight meeting inclusion criteria; in total, it involved 606 participants. Six studies reported HbA1c (%) at 12 months; four as change from baseline with a fixed effects estimate (95% confidence interval): VLC/KD minus control of 0.01% (-0.22 to 0.25), p = .91; and two as change from baseline: -0.65% (-0.99; -0.31) [-7.1 mmol/mol (-10.8; -3.4)], p < .001. Serum triglycerides were lower with VLC/KD versus control: -0.28 mmol/L (-0.44 to -0.11), p < .001. High-density lipoprotein was higher with an estimate of 0.04 mmol/L (0.01 to 0.08), p = .03, in the five studies reporting 12-month summary data. CONCLUSIONS: A VLC/KD may cause reductions in HbA1c and triglycerides in those with pre-diabetes or T2D but evidence of an advantage over other strategies is limited. More well-designed studies are required to provide certain evidence.

The minor allele of the CREBRF rs373863828 p.R457Q coding variant is associated with reduced levels of myostatin in males: Implications for body composition.

OBJECTIVE: The minor allele (A) of the rs373863828 variant (p.Arg457Gln) in CREBRF is restricted to indigenous peoples of the Pacific islands (including New Zealand Maori and peoples of Polynesia), with a frequency of up to 25% in these populations. This allele associates with a large increase in body mass index (BMI) but with significantly lower risk of type-2 diabetes (T2D). It remains unclear whether the increased BMI is driven by increased adiposity or by increased lean mass. METHODS: We undertook body composition analysis using DXA in 189 young men of Maori and Pacific descent living in Aotearoa New Zealand. Further investigation was carried out in two orthologous Arg458Gln knockin mouse models on FVB/NJ and C57BL/6j backgrounds. RESULTS: The rs373863828 A allele was associated with lower fat mass when adjusted for BMI (p < 0.05) and was associated with significantly lower circulating levels of the muscle inhibitory hormone myostatin (p < 0.05). Supporting the human data, significant reductions in adipose tissue mass were observed in the knockin mice. This was more significant in older mice in both backgrounds and appeared to be the result of reduced age-associated increases in fat mass. The older male knockin mice on C57BL/6j background also had increased grip strength (p < 0.01) and lower levels of myostatin (p < 0.05). CONCLUSION: Overall, these results prove that the rs373863828 A-allele is associated with a reduction of myostatin levels which likely contribute to an age-dependent lowering of fat mass, at least in males.

Where can you wear your Libre? Using the FreeStyle Libre continuous glucose monitor on alternative sites.

AIM: To investigate the accuracy and acceptability of the FreeStyle Libre Flash continuous glucose monitoring system (FSL-CGM) at alternative sites during free living and under experimental conditions. MATERIALS AND METHODS: Participants with type 1 diabetes were provided with three FSL-CGM sensors applied to the upper arm, the lower back, and the anterior chest. On day 2 or 3, FSL-CGM sensor glucose was compared with venous glucose following a standard meal, during and after an exercise test, and after skin cooling. Participants completed 14-day use of the sensors with concomitant sensor scanning at all sites and capillary glucose tests. The primary outcome was accuracy between sensor sites of 14-day mean glucose. Clarke's error grids, precision absolute relative deviation, and mean absolute relative deviation were calculated. RESULTS: In the 20 participants, compared with the arm sensor, the accuracy of the back sensor and the chest sensor was 97.9% and 98%, respectively. Under experimental conditions, the arm sensor was more accurate than that of the back and chest. All the sensors recorded higher glucose concentration than venous samples during exercise. The arm and chest sites were most preferred, with the greatest sensor failures from the back. CONCLUSIONS: The FSL-CGM is clinically accurate when the sensors are applied to alternate chest or back sites. Greater variability occurs during rapid changes in glucose concentration with all sensor sites compared with venous glucose. Understanding these variabilities allows appropriate use of an economically viable continuous glucose monitor.

The Impact of COVID-19 on diet and lifestyle behaviours for pregnant women with diabetes.

BACKGROUND/AIMS: A self-reported online survey was performed to investigate the immediate effect of COVID-19 lockdown restrictions in New Zealand on dietary intake, and lifestyle behaviours among pregnant women with diabetes. PARTICIPANTS/METHODS: The survey was sent to 82 pregnant women who had Type 1, Type 2 Diabetes, or Gestational Diabetes and attended the Diabetes in Pregnancy Clinic in Wellington, New Zealand in May 2020, while the most restrictive COVID-19 lockdown measures were in place. All women received standard pregnancy nutrition advice provided by a dietitian, were monitoring blood glucose levels with nursing support, and seeing specialist endocrinologists and obstetricians for their pregnancy care. RESULTS: Fifty women (61%) responded to the survey. There was no evidence of differences in dietary intake during the restrictions, compared to before, for most food items. During the restriction's women consumed more bread (Odds Ratio (95% CI): 0.39 (0.18-0.83) p = 0.02); less battered fish: 3.11 (1.20-8.05) p = 0.02; and less hot chips/fries: 6.32 (2.67-14.93) p < 0.0001. During the restriction's women consumed more meals at home: 0.05 (0.14-0.15) p < 0.0001; less takeaways: 3.63 (1.54-7.34) p = 0.003; and less restaurant and café meals: 15.05 (6.03-37.59) p < 0.0001, when the services reopened. CONCLUSIONS: The nutrition of pregnant women with diabetes was not compromised during a brief COVID-19 lockdown restriction. This finding is reassuring, with countries worldwide adopting brief intermittent lockdown periods to restrict the spread of the COVID-19 virus.

The CREBRF diabetes-protective rs373863828-A allele is associated with enhanced early insulin release in men of Maori and Pacific ancestry.

AIMS/HYPOTHESIS: The minor A allele of rs373863828 (CREBRF p.Arg457Gln) is associated with increased BMI, but reduced risk of type 2 and gestational diabetes in Polynesian (Pacific peoples and Aotearoa New Zealand Maori) populations. This study investigates the effect of the A allele on insulin release and sensitivity in overweight/obese men without diabetes. METHODS: A mixed meal tolerance test was completed by 172 men (56 with the A allele) of Maori or Pacific ancestry, and 44 (24 with the A allele) had a frequently sampled IVGTT and hyperinsulinaemic-euglycaemic clamp. Mixed linear models with covariates age, ancestry and BMI were used to analyse the association between the A allele of rs373863828 and markers of insulin release and blood glucose regulation. RESULTS: The A allele of rs373863828 is associated with a greater increase in plasma insulin 30 min following a meal challenge without affecting the elevation in plasma glucose or incretins glucagon-like polypeptide-1 or gastric inhibitory polypeptide. Consistent with this point, following an i.v. infusion of a glucose bolus, participants with an A allele had higher early (p < 0.05 at 2 and 4 min) plasma insulin and C-peptide concentrations for a similar elevation in blood glucose as those homozygous for the major (G) allele. Despite increased plasma insulin, rs373863828 genotype was not associated with a significant difference (p > 0.05) in insulin sensitivity index or glucose disposal during hyperinsulinaemic-euglycaemic clamp. CONCLUSIONS/INTERPRETATION: rs373863828-A allele associates with increased glucose-stimulated insulin release without affecting insulin sensitivity, suggesting that CREBRF p.Arg457Gln may increase insulin release to reduce the risk of type 2 diabetes.

Cardiovascular risk prediction in type 2 diabetes before and after widespread screening: a derivation and validation study.

BACKGROUND: Until recently, most patients with diabetes worldwide have been diagnosed when symptomatic and have high cardiovascular risk, meaning most should be prescribed cardiovascular preventive medications. However, in New Zealand, a world-first national programme led to approximately 90% of eligible adults being screened for diabetes by 2016, up from 50% in 2012, identifying many asymptomatic patients with recent-onset diabetes. We hypothesised that cardiovascular risk prediction equations derived before widespread screening would now significantly overestimate risk in screen-detected patients. METHODS: New Zealanders aged 30-74 years with type 2 diabetes and without known cardiovascular disease, heart failure, or substantial renal impairment were identified from the 400 000-person PREDICT primary care cohort study between Oct 27, 2004, and Dec 30, 2016, covering the period before and after widespread screening. Sex-specific equations estimating 5-year risk of cardiovascular disease were developed using Cox regression models, with 18 prespecified predictors, including diabetes-related and renal function measures. Equation performance was compared with an equivalent equation derived in the New Zealand Diabetes Cohort Study (NZDCS), which recruited between 2000 and 2006, before widespread screening. FINDINGS: 46 652 participants were included in the PREDICT-1° Diabetes subcohort, of whom 4114 experienced first cardiovascular events during follow-up (median 5·2 years, IQR 3·3-7·4). 14 829 (31·8%) were not taking oral hypoglycaemic medications or insulin at baseline. Median 5-year cardiovascular risk estimated by the new equations was 4·0% (IQR 2·3-6·8) in women and 7·1% (4·5-11·2) in men. The older NZDCS equation overestimated median cardiovascular risk by three times in women (median 14·2% [9·7-20·0]) and two times in men (17·1% [4·5-20·0]). Model and discrimination performance measures for PREDICT-1° Diabetse equations were also significantly better than for the NZDCS equation (eg, for women: R2=32% [95% CI 29-34], Harrell's C=0·73 [0·72-0·74], Royston's D=1·410 [1·330-1·490] vs R2=24% [21-26], C=0·69 [0·67-0·70], and D=1·147 [1·107-1·187]). INTERPRETATION: International treatment guidelines still consider most people with diabetes to be at high cardiovascular risk; however, we show that recent widespread diabetes screening has radically changed the cardiovascular risk profile of people with diabetes in New Zealand. Many of these patients have normal renal function, are not dispensed glucose-lowering medications, and have low cardiovascular risk. These findings have clear international implications as increased diabetes screening is inevitable due to increasing obesity, simpler screening tests, and the introduction of new-generation glucose-lowering medications that prevent cardiovascular events. Cardiovascular risk prediction equations derived from contemporary diabetes populations, with multiple diabetes-related and renal function predictors, will be required to better differentiate between low-risk and high-risk patients in this increasingly heterogeneous population and to inform appropriate non-pharmacological management and cost-effective targeting of expensive new medications. FUNDING: Health Research Council of New Zealand, Heart Foundation of New Zealand, and Healthier Lives National Science Challenge.

The effect of additional mealtime insulin bolus using an insulin-to-protein ratio compared to usual carbohydrate counting on postprandial glucose in those with type 1 diabetes who usually follow a carbohydrate-restricted diet: A randomized cross-over trial.

This randomized controlled cross-over study compared postprandial glucose concentrations and incidence of hypoglycaemia for mealtime bolus insulin calculated for both meal protein and carbohydrate content, with ordinary dosing for carbohydrate content alone, in adults with type 1 diabetes who usually follow a carbohydrate-restricted diet. All 16 participants completed three test meals under each of the two conditions. The primary outcome was the time normalized Area Under the Curve (AUC) of glucose measurements. The mean (SD) AUC glucose concentration for insulin dosing for both protein and carbohydrate was 8.3 (2.1) mmol/L compared with 10.0 (2.2) mmol/L for carbohydrate alone. The difference (95% CI) was -1.76 mmol/L (-2.87 to -0.65), P = .003. The mean (SD) glucose concentration ≥ 8.0 mmol/L was 54.8 (32.4)% for dosing for protein and carbohydrate and 73.7 (26.3)% for carbohydrate alone, rate ratio (95% CI) 0.75 (0.62 to 0.89), P = .002. For glucose concentration < 4.0 mmol/L 5.5 (15.1)% and 2.8 (11.7)%; rate ratio (95% CI): 1.97 (0.90 to 4.27), P = .087. Calculating the meal insulin requirements based on the carbohydrate and protein content may have advantages over calculations based on carbohydrate alone. Further studies are required to determine how to best optimize this.

Optimizing the management of hypoglycaemia in individuals with type 2 diabetes: A randomized crossover comparison of a weight-based protocol compared with two fixed-dose glucose regimens.

AIMS: To determine whether an individualized body weight-based glucose treatment in adults with type 2 diabetes (T2DM) is more likely to resolve hypoglycaemia with a single treatment without excessive rebound hyperglycaemia compared to fixed doses of 12 or 30 g of glucose. METHODS: Adults with T2DM were enrolled in a cross-over study. Each episode of hypoglycaemia (capillary glucose <4.0 mmol/L) was randomly assigned to 1 of 3 treatment protocols: 0.3 g glucose/kg body-weight or a fixed dose of either 12 or 30 g glucose, independent of weight. All participants received each treatment in random order for up to 15 hypoglycaemic episodes. Glucose was re-tested 10 minutes after treatment, with a repeat dose if still <4 mmol/L. RESULTS: Mean (SD) age of the 30 participants was 68 (8.1) years, mean weight was 91.5 (16.8) kg and mean HbA1c was 58.7 (9.2) mmol/mol. Among a total of 244 episodes of hypoglycaemia, 10 participants had 15 treatment episodes and 18 participants had fewer than 10 treatment episodes. The odds ratio, adjusted for multiple comparisons, for resolution of hypoglycaemia at 10 minutes, comparing weight-based treatment and 12 g treatment was 3.2 (95% CI, 1.1-9.0), P = .009, comparing 30 g treatment and 12 g treatment was 8.9 (95% CI, 2.2-36.6), P < .001, and comparing weight-based treatment and 30 g treatment was 0.36 (95% CI, 0.08-1.67) P = .10. CONCLUSION: In T2DM, both a weight-based 0.3 g/kg treatment and a fixed 30 g glucose treatment result in higher blood glucose than a 12 g treatment, along with increased probability of resolution of hypoglycaemia after 10 minutes. Both treatments result in an excess of mild rebound hyperglycaemia (>8 mmol/L) at 30 minutes.

The Need to Calculate Target Glucose Levels When Measuring Changes in Insulin Sensitivity During Interventions for Individuals With Type 2 Diabetes.

BACKGROUND: Physiological models that are used with dynamic test data to assess insulin sensitivity (SI) assume that the metabolic target glucose concentration ( GTARGET) is equal to fasting glucose concentration ( G0). However, recent research has implied that irregularities in G0 in diabetes may cause erroneous SI values. This study quantifies the magnitude of these errors. METHODS: A clinically validated insulin/glucose model was used to calculate SI with the standard fasting assumption (SFA) G0 = GTARGET. Then GTARGET was treated as a variable in a second analysis (VGT). The outcomes were contrasted across twelve participants with established type 2 diabetes mellitus that were recruited to take part in a 24-week dietary intervention. Participants underwent three insulin-modified intravenous glucose tolerance tests (IM-IVGTT) at 0, 12, and 24 weeks. RESULTS: SIVGT had a median value of 3.36×10-4 L·mU-1·min-1 (IQR: 2.30 - 4.95×10-4) and were significantly lower ( P < .05) than the median SISFA (6.38×10-4 L·mU-1·min-1, IQR: 4.87 - 9.39×10-4). The VGT approach generally yielded lower SI values in line with expected participant physiology and more effectively tracked changes in participant state over the 24-week trial. Calculated GTARGET values were significantly lower than G0 values (median GTARGET = 5.48 vs G0 = 7.16 mmol·L-1 P < .001) and were notably higher in individuals with longer term diabetes. CONCLUSIONS: Typical modeling approaches can overestimate SI when GTARGET does not equal G0. Hence, calculating GTARGET may enable more precise SI measurements in individuals with type 2 diabetes, and could imply a dysfunction in diabetic metabolism.

Increasing rates of people identifying as transgender presenting to Endocrine Services in the Wellington region.

AIMS: Overseas clinics specialising in management of transgender people have noted a marked increase in the numbers of people requesting therapy in the last few years. No data has been presented for New Zealand. We therefore reviewed the number of transgender people seen in the Wellington Endocrine Service to assess if the pattern was similar and assess any potential problems for service delivery. METHODS: Using hospital records, we reviewed the new appointments of people who were referred for advice on gender reassignment and seen in the Wellington Endocrine Service from 1990 to 2016. RESULTS: In total, 438 people who identified as transgender attended the clinic at least once in this period. There has been a progressive increase in number of people identifying as transgender presenting to the clinic, particularly since 2010. In addition to increasing overall numbers, there has been in particular increase in referrals for people under age 30, as well as an increasing proportion of people requesting female-to-male (FtM) therapy so that it is now approaching the number of people requesting male-to-female therapy (MtF). CONCLUSION: The pattern observed is comparable to changes reported overseas. These changes have practical consequences for the delivery of both secondary and primary level healthcare, requiring an increased focus on clinical coordination between the relevant medical services and their links to the primary services sector.

Development of a structured diabetes self-management education program specific to the cultural and ethnic population of New Zealand.

AIM: To develop and pilot a diabetes self-management education (DSME) program specific to the needs of New Zealanders with type 2 diabetes mellitus (T2DM). METHODS: There were two parts in the present study. The first was the development of the program. This involved a literature review, consultation with end-user groups and drafting the content of the program. In the second part, the program was tested and modified according to feedback provided by both participants and facilitators. RESULTS: The present study achieved its primary goal of developing, piloting and modifying a DSME program specific to the New Zealand population. The DSME program was developed using concepts and content of international DSME programs. The content and concept was extensively tested via discussion groups with 71 individuals with T2DM and practice nurses to ensure the program met the unique cultural needs of New Zealanders with T2DM. Twenty-seven participants with T2DM were recruited into the pilot, of which 13 attended four of six sessions. Feedback from participants, observing nurses and facilitators was incorporated into the final program. CONCLUSIONS: DSME programs are an effective vehicle for providing individuals with T2DM the initial information and support to start self-managing their diabetes. However, to ensure DSME programs help individuals with the highest rates of diabetes and diabetes-related complications, it is important end-users participate in the development of the program. This DSME program now requires longitudinal trial to determine if in the New Zealand context it is able generate the same improvements in both clinical and qualitative outcomes as seen in similar international programs.

Use of and Beliefs About Mobile Phone Apps for Diabetes Self-Management: Surveys of People in a Hospital Diabetes Clinic and Diabetes Health Professionals in New Zealand.

BACKGROUND: People with diabetes mellitus (DM) are using mobile phone apps to support self-management. The numerous apps available to assist with diabetes management have a variety of functions. Some functions, like insulin dose calculators, have significant potential for harm. OBJECTIVES: The study aimed to establish (1) whether people with DM in Wellington, New Zealand, use apps for DM self-management and evaluate desirable features of apps and (2) whether health professionals (HPs) in New Zealand treating people with DM recommend apps to patients, the features HPs regard as important, and their confidence with recommending apps. METHODS: A survey of patients seen at a hospital diabetes clinic over 12 months (N=539) assessed current app use and desirable features. A second survey of HPs attending a diabetes conference (n=286) assessed their confidence with app recommendations and perceived usefulness. RESULTS: Of the 189 responders (35.0% response rate) to the patient survey, 19.6% (37/189) had used a diabetes app. App users were younger and in comparison to other forms of diabetes mellitus, users prominently had type 1 DM. The most favored feature of the app users was a glucose diary (87%, 32/37), and an insulin calculator was the most desirable function for a future app (46%, 17/37). In non-app users, the most desirable feature for a future app was a glucose diary (64.4%, 98/152). Of the 115 responders (40.2% response rate) to the HPs survey, 60.1% (68/113) had recommended a diabetes app. Diaries for blood glucose levels and carbohydrate counting were considered the most useful app features and the features HPs felt most confident to recommend. HPs were least confident in recommending insulin calculation apps. CONCLUSIONS: The use of apps to record blood glucose was the most favored function in apps used by people with diabetes, with interest in insulin dose calculating function. HPs do not feel confident in recommending insulin dose calculators. There is an urgent need for an app assessment process to give confidence in the quality and safety of diabetes management apps to people with diabetes (potential app users) and HPs (potential app prescribers).