Another goal of this blog is to give you a behind-the-scenes look at what the Association does on a daily basis to fulfill its mission: To prevent and cure diabetes and improve the lives of all people living with diabetes.  Our staff’s dedication – combined the stories that provide them with inspiration through the day – is a critical part of the Stop Diabetes movement.

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Statistical analyses were performed by SAS version 9.4 (SAS Institute). All statistical tests were two sided at a 5% significance level. Analyses were performed on the principle of intention to treat, including all randomised participants who provided at least one valid measure on the primary outcome after randomisation. Demographics and baseline characteristics of all participants were first summarised by treatment group with descriptive statistics. No formal statistical tests were conducted at baseline, because any baseline imbalance observed between two groups could have occurred by chance with randomisation.
Mobile phone ownership rates are increasing. Similar to trends seen in the United States and Canada, where mobile phone ownership is 72% and 67%, respectively [20], 70% of New Zealanders own a mobile phone, making diabetes apps potentially available to most people [21]. Limited research exists into the use of diabetes apps in New Zealand. However with increasing rates of both diabetes prevalence and mobile phone ownership, access to safe apps is essential for both HPs as potential app prescribers and patients as app users [21,22]. In Scotland, a survey of people with diabetes found high mobile phone ownership (67%) with over half reporting an interest in using apps for self-management of diabetes, but app usage in only 7% of responders [23]. The objectives of this study were (1) To establish whether people with diabetes use apps to assist with diabetes self-management and which features are useful or desirable, and (2) To establish whether HPs treating people with diabetes recommend diabetes apps, which features were thought to be useful, and which features were they confident to recommend.
The look of the Dario appealed straight away to me. Small and compact. Easy for me to carry with my phone which goes everywhere with me. Love the fantastic app on my phone. Clear, informative and easy to use. Love it! I can look back at previous readings to see any patterns. Sara and Assaf have been brilliant at helping out with any issues I have come across, which I thank them hugely for. The Dario Lounge is a great community for all users, who all share advice.
Most people know that diabetes involves the inability to control glucose, or blood sugar, by not producing enough insulin or not managing it correctly. This leads to elevated levels of glucose in the body, which can result in very serious complications, such as heart attack, stroke, kidney disease, nerve damage, hardening of the arteries, foot and leg amputation and blindness. (more…)

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: support from Waitemata District Health Board for the development of SMS4BG, and support from the Health Research Council of New Zealand in partnership with the Waitemata District Health Board and Auckland District Health Board, and the New Zealand Ministry of Health for the randomised controlled trial; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.
Diabetes Depot carries a full line insulin pump supplies, including all major insulin infusions sets, insulin reservoirs and cartridges available in Canada, all at significant discounts below the manufacturer's list price. Our product line of diabetic supplies, required daily by people living with diabetes, include blood glucose meters, glucose test strips, lancets, insulin pen needles, insulin products, Dex-4 glucose tablets and Emla anesthetic cream. We also carry accessories such as pump clips, pump cases & pouches, prep pads, battery caps, diabetic socks, and helpful books on diabetes… everything an insulin pump user would require. Plus, because the Diabetes Depot is located within Stutt's Pharmacy, we also offer a complete prescription service.
The 1177 people with diabetes attending clinics at Capital and Coast District Health Board (CCDHB), Wellington, New Zealand over a 12-month period (10th September 2014 to 10th September 2015) were the sample population. Out of the total patients, 521 patients with an email address in the hospital management system were invited to participate via email. To include a representation of people without a recorded email address in the sample (n=656), every 5th person was telephoned (up to twice) and invited to provide an email address. Of the 131 patients telephoned, 54 (41.2%) were reached, of whom 49 (91%) agreed to participate. Patients without phone numbers or unable to provide an email address were excluded. This generated a sample population of 570 people.
This cross-sectional observational study used two surveys (see Multimedia Appendices 1 and 2), one for people with diabetes attending a secondary care diabetes outpatient clinic and the second for HPs (who treat people with diabetes) attending a national diabetes conference. Both surveys were multi-choice format, collected, and managed using REDCap electronic data capture tools. REDCap (Research Electronic Data Capture) is a secure, Web-based app designed to support data capture for research studies [24]. The survey questions were derived from criteria in the Mobile app rating scale [25] to address attitudes and practices of both the people with diabetes and HPs. The list of apps was compiled by searching Apple and Android App stores and included the first consecutive ten diabetes apps. We eliminated any apps not specific to diabetes by reviewing app store descriptions. We reviewed the main features from these apps to develop the list of app features. The patient survey asked responders to select any useful app features from a list. Responders could select more than one useful app feature. The HP survey listed app features and used a scale to assess usefulness of app features (from 1 [not at all useful] to 5 [extremely useful]) and their confidence in recommending apps (from 1 [not at all confident] to 5 [extremely confident]).
The 1177 people with diabetes attending clinics at Capital and Coast District Health Board (CCDHB), Wellington, New Zealand over a 12-month period (10th September 2014 to 10th September 2015) were the sample population. Out of the total patients, 521 patients with an email address in the hospital management system were invited to participate via email. To include a representation of people without a recorded email address in the sample (n=656), every 5th person was telephoned (up to twice) and invited to provide an email address. Of the 131 patients telephoned, 54 (41.2%) were reached, of whom 49 (91%) agreed to participate. Patients without phone numbers or unable to provide an email address were excluded. This generated a sample population of 570 people.
This study shows that the incidence of type 1 diabetes in the Auckland region has increased steadily over the last two decades. However, unlike other studies [3], [4], [5], the rate of increase in incidence has been particularly marked in older children (10–14 yr), which was approximately 2.5-fold greater than that in children 0–4 yr. Interestingly, the incidence of type 1 diabetes in children 0–4 and 10–14 in Auckland are very similar to those reported in Australia, our closest geographical and ethnic neighbours [19], both of which had very high case ascertainment levels (close to 100%).
Funding: The development of SMS4BG was funded by Waitemata District Health Board. The randomised controlled trial was funded by the Health Research Council of New Zealand in partnership with the Waitemata District Health Board and Auckland District Health Board (through the Research Partnerships for New Zealand Health Delivery initiative), and the New Zealand Ministry of Health. The funders were not involved in any way in the preparation of the manuscript or analysis of the study results. No payment has been received for writing this publication.
Data were imported into SPSS version 24 (IBM). Incomplete responses were included in the analysis. In the patient survey, independent sample t tests were conducted to compare mean clinical variables (age, BP, C:HDL, LDL, HbA1c) by type of diabetes, method of recruitment, and whether the responder used a diabetes mobile phone app. Adjustment was made for unequal variances. Normal distribution was assumed for all variables, apart from urinary microalbumin to creatinine for which a Wilcoxin test was used. No statistically significant differences in these variables or in mobile phone app use were found between patients with recorded email addresses and patients phoned for their email address. Therefore, all 189 responses were combined for further analysis. Chi-square tests were used to compare medications and survey responses by type of diabetes. Statistical significance was determined by exact 2-sided P values less than .05. In the HP survey, mean values on the usefulness and confidence Likert scales were calculated to compare app features.

Today’s first post is titled “Why ‘Stop Diabetes’?” can be found at www.diabetesstopshere.org. This initial post seeks to explain why the Stop Diabetes movement was created and its goal for engaging the public.  “The goal of the Stop Diabetes movement is to grow to epic proportions, to be bigger than the disease itself,” the blog explains. “In short, it’s the answer to why the Association does the work that it does.”
The reasons underpinning the considerable increase in incidence over the study period are unclear. This may reflect an actual change in the type 1 diabetes incidence in patients <15 yr. Alternatively, it may reflect an earlier age of onset without change in incidence over all ages, so that greater numbers of people are being diagnosed with type 1 diabetes in adolescence rather than in young adulthood. This would be consistent with the ‘accelerator hypothesis’, which suggests that an increasing rate of obesity is a primary driver for an earlier age of diabetes onset [6]. Studies have shown an association between higher BMI and younger age at diagnosis [9], [10], [11], indicating greater adiposity in childhood may hasten the onset of diabetes mellitus. The ‘accelerator hypothesis’ predicts an early onset rather than increased risk [11], and a Swedish study examining type 1 diabetes incidence on a nation-wide cohort 0–34 yr showed a shift in age of onset towards younger ages, rather than an increase in incidence per se across the whole population [20]. Although we cannot rule out a similar phenomenon in Auckland, we did not observe an increase in BMI SDS among children recently diagnosed with type 1 diabetes, or an association between BMI SDS and age at diagnosis. In fact, we observed an actual increase in age at diagnosis which is inconsistent with the ‘accelerator hypothesis’. Thus, our data suggest a true increase in the incidence of type 1 diabetes in the Auckland region, and not changes driven by increasing adiposity.
The main treatment effect on the primary outcome is presented in table 2. The reduction in HbA1c from baseline to nine month follow-up was significantly greater in the intervention group than in the control group (mean −8.85 mmol/mol (standard deviation 14.84) v −3.96 mmol/mol (17.02), adjusted mean difference −4.23 (95% confidence interval −7.30 to −1.15), P=0.007). The adjusted mean difference on change in HbA1c at three and six months were −4.76 (−8.10 to −1.43), P=0.005) and −2.36 (−5.75 to 1.04), P=0.17), respectively (table 2).
Today’s first post is titled “Why ‘Stop Diabetes’?” can be found at www.diabetesstopshere.org. This initial post seeks to explain why the Stop Diabetes movement was created and its goal for engaging the public.  “The goal of the Stop Diabetes movement is to grow to epic proportions, to be bigger than the disease itself,” the blog explains. “In short, it’s the answer to why the Association does the work that it does.”

We saw no significant interaction between the treatment group and any of the prespecified subgroups: type 1 versus type 2 diabetes (P=0.82), non-Māori/non-Pacific versus Māori/Pacific ethnicity (P=0.60), high urban versus high rural/remote region (P=0.38). Adjusted mean differences on change in HbA1c from baseline to nine months for patients with type 1 and type 2 diabetes were −5.75 mmol/mol (95% confidence interval −10.08 to −1.43, P=0.009) and −3.64 mmol/mol (−7.72 to 0.44, P=0.08), respectively. Adjusted mean differences for non-Māori/non-Pacific and Māori/Pacific people were −4.97 mmol/mol (−8.51 to −1.43, P=0.006) and −3.21 mmol/mol (−9.11 to 2.70, P=0.28), respectively. Adjusted mean differences for participants living in high urban and high rural/remote areas were −4.54 mmol/mol (−8.40 to −0.68, P=0.02) and −3.94 mmol/mol (−9.00 to 1.12, P=0.13), respectively (table 3).


The majority of responders were not using diabetes apps (80.4%, 152/189), although 60.5% (89/147) reported they would be interested in trying one. Of the 118 people who answered the question, the reasons for not using an app was not knowing they existed (66.9%, 79/118), feeling confident without one (16.9%, 20/118), discontinued use after having used an app previously 16.9% (20/118).


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