There were 884 new cases of type 1 diabetes, and age at diagnosis rose from 7.6 yr in 1990/1 to 8.9 yr in 2008/9 (r2 = 0.31, p = 0.009). There was a progressive increase in type 1 diabetes incidence among children <15 yr (p<0.0001), reaching 22.5 per 100,000 in 2009. However, the rise in incidence did not occur evenly among age groups, being 2.5-fold higher in older children (10–14 yr) than in the youngest group (0–4 yr). The incidence of new cases of type 1 diabetes was highest in New Zealand Europeans throughout the study period in all age groups (p<0.0001), but the rate of increase was similar in New Zealand Europeans and Non-Europeans. Type 1 diabetes incidence and average annual increase were similar in both sexes. There was no change in BMI SDS shortly after diagnosis, and no association between BMI SDS and age at diagnosis.


Main outcome measures Primary outcome measure was change in glycaemic control (HbA1c) from baseline to nine months. Secondary outcomes included change in HbA1c at three and six months, and self efficacy, diabetes self care behaviours, diabetes distress, perceptions and beliefs about diabetes, health related quality of life, perceived support for diabetes management, and intervention engagement and satisfaction at nine months. Regression models adjusted for baseline outcome, health district category, diabetes type, and ethnicity.
Overall, all five potential app features were considered useful, with more than 60% of responders selecting that these features were useful, very useful, or extremely useful on the scale of scale 1 (not at all useful) to 5 (extremely useful). Equally, the mean usefulness score was higher than 3 for all 5 features. Blood glucose and carbohydrate intake diaries were rated as being the most useful app feature (Figure 1), with the highest mean score of 3.64 (SD 0.948) for usefulness (Table 7).

There are three forms of the disease. People with Type 1 Diabetes typically make none of their own insulin and therefore require insulin injections for survival. People with Type 2 Diabetes, the form that comprises the majority of all cases, usually produce their own insulin, but not enough or they are unable to use it properly. Then there is Gestational Diabetes; globally, 1 in 7 births is affected by gestational diabetes. While maternal blood glucose levels usually return to normal after the baby is born, there is an increased risk of both mother and child developing Type 2 Diabetes later in life.

The World Health Organisation (WHO) has mandated November 14 as World Diabetes Day, an international event to raise awareness about diabetes. Close to 350 million people in the world have diabetes and WHO reports that a person dies from this disease every 6 seconds – that’s 5 million deaths. Currently 1 in 11 adults have diabetes worldwide and this is predicted to increase to 1 adult in 10 (652 million) by 2040. Sobering statistics indeed.
The features most frequently used by current app users were blood glucose diaries (87%, 32/37), followed by carbohydrate/meal diaries (38%, 14/37) with 22% (8/37) reporting insulin dose calculation devices to be useful (Table 3). Table 3 demonstrates the features app users found useful in their current apps. App users reported the most desired feature for future use in an app was an insulin dose calculator (46%, 17/37; Table 4). Table 5 shows that non-app users reported insulin dose calculators to be the third most desired feature (54.6%, n=83/152). Blood glucose diaries were the most desired app feature amongst non-app users (64.4%, 98/152; Table 5). Non app users with T1DM were more likely to desire an insulin dose calculation device, than non-app users with T2DM, P=.01).
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.
The survey was completed by 189 of the 539 patients (35.0% response rate, 158/491 from participants with email addresses, 31/48 from telephone contact). Table 1 shows the characteristics of responders. Responders (N=189) were older, with a mean age of 50.0 years (SD 15.7) than non-responders (N=350), who had a mean age of 45.9 years (SD 16.1; P=.004) and had lower HbA1c of 62.2 mmol/mol (SD 14.0) (7.8, SD 1.1%) than non-responders (N=325) with mean of 68.9 mmol/mol (SD 18.2; 8.5, SD 2.3%; P<.001). There were no significant differences in the rate and type of anti-hypertensive, lipid lowering, and anti-hyperglycemic medications used between responders and non-responders (P=.28, −.32, and −.17, respectively). Clinical variables by type of diabetes are shown in Table 2. As expected, responders with T1DM were more likely to be on Insulin than those with T2DM (P<.001) whereas responders with T2DM were more likely to be on anti-hypertensive (P<.001) and lipid lowering medication (P<.001).
Ethnicity was recorded by self-report using a prioritised system, such that if multiple ethnicities were selected, the patient was assigned to a single category, following a hierarchical system of classification [18]. Patients were assigned to European, Maori, Pacific Islander, or Other (Asian/Middle Eastern/Latin American/African) groups, which match national census classifications.
In conclusion, there has been a steady increase in type 1 diabetes incidence in children <15 yr in Auckland over a 20-year span. However, in contrast to observations elsewhere, age at diagnosis in Auckland has increased over the study period. Our data do not support the ‘accelerator hypothesis’, and factors other than simply increasing adiposity are likely to be at play.

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.

There were 884 new cases of type 1 diabetes, and age at diagnosis rose from 7.6 yr in 1990/1 to 8.9 yr in 2008/9 (r2 = 0.31, p = 0.009). There was a progressive increase in type 1 diabetes incidence among children <15 yr (p<0.0001), reaching 22.5 per 100,000 in 2009. However, the rise in incidence did not occur evenly among age groups, being 2.5-fold higher in older children (10–14 yr) than in the youngest group (0–4 yr). The incidence of new cases of type 1 diabetes was highest in New Zealand Europeans throughout the study period in all age groups (p<0.0001), but the rate of increase was similar in New Zealand Europeans and Non-Europeans. Type 1 diabetes incidence and average annual increase were similar in both sexes. There was no change in BMI SDS shortly after diagnosis, and no association between BMI SDS and age at diagnosis.
One of the most important aspects of diabetes management is to maintain a healthy body weight. Being overweight not only increases your risk of heart disease, stroke and some cancers, it also makes your diabetes harder to manage. Small changes in your diet such as reducing your portion sizes and swapping to low-fat dairy products can help you to achieve a healthy body weight and manage your diabetes.
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).

ED is a failure to obtain/maintain penile erection sufficient for intercourse is more prevalent in men with diabetes and increases with age.  It is important to distinguish erectile failure from premature ejaculation, decreased libido and other problems as these have different causes and treatment. ED in diabetes is largely due to failure of vascular smooth muscle relaxation secondary to endothelial dysfunction and/or autonomic neuropathy.
‘I was very pleased to contact your service. I was feeling overwhelmed with my current situation however knew that I needed to get a diabetes test done. While I was waiting for my turn to be tested Susan welcomed me, helped my overwhelming feelings calm down, she was very approachable and understanding. Sandy followed through by assisting me with assurance that things were going to be okay and was very understanding. She encouraged that I seek more medical advice for my blood pressure results. She phoned my manager and found me a local GP that I could visit right away. I was very appreciative of these ladies and all the help, care and advice they gave me. Thank you so much!’

In contrast with the extensive app problems presented in the literature, over half of the responders with an app reported no problems [5,11-13,15]. This discrepancy may be due to false self-report or responders may have tried multiple apps before finding the one they like. Our study is unable to add significantly to literature about insulin dose calculation problems [15], as only 7 responders reported using their app for insulin calculation. However it is notable that this feature is desired by users and reinforces the importance of having a regulated environment to ensure safety.
A total of 884 new patients aged <15 yr were diagnosed with type 1 diabetes over the 20-year period covered by this study. There was an increase in the mean age at diagnosis from 7.6 yr in 1990/1 to 8.9 yr in 2008/9 (0.07/yr, r2 = 0.31, p = 0.009). This was observed in both males (0.07/yr, r2 = 0.22, p = 0.04) and females (0.06/yr, r2 = 0.13, p = 0.12).
Your health professional at the Centre may suggest that they make a referral for you, if there are problems affecting your diabetes management or your overall health and management. Alternatively you can ask your family doctor or nurse to refer you. If you are uncertain about whether it would be helpful to see us, you are most welcome to phone us directly to discuss this. Phone 3640 860 ext 89113.
The A1C is a common blood test that measures the amount of glucose that is attached to the hemoglobin in our red blood cells. It has a variety of other names, including glycated hemoglobin, glycosylated hemoglobin, hemoglobin A1C and HbA1 and is used in the diagnosis and monitoring of diabetes. Unlike the traditional blood glucose test, the A1C does not require fasting, and blood can be drawn at any time of day. It is hoped that this will result in more people getting tested and decreasing the number of people with undiagnosed diabetes, which is currently estimated to be more than 7 million adults in the U.S. (more…)
New Zealand Europeans had a significantly higher incidence rate than Non-Europeans, which is consistent with other studies [21], [22]. There was a marked decrease in the proportion of Europeans in Auckland over the study period, so that the increase in type 1 diabetes incidence was not due to a shift in ethnic distribution. Furthermore, the incidence has been increasing in both Europeans and non-Europeans. A number of studies have shown that immigrant groups display higher rates of type 1 diabetes than in their countries of origin, particularly those that move into societies with a westernised lifestyle [23], [24]. For example, although type 1 diabetes in Polynesia is extremely rare, an abrupt increase in incidence occurs in Pacific Island peoples who migrate to New Zealand [25]. Our study provides evidence that the factors leading to an increase in incidence are operating across all ethnicities. Indeed, the incidence of type 1 diabetes has been remarkably similar over time for the indigenous Maori and the largely newly immigrant Pacific Island and Other ethnic groups.
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.

Wednesday Walks are a joint venture between Korowhai Aroha Health Centre and Diabetes NZ Rotorua Branch. Join Mary every Wednesday morning for some gentle exercise in good company. The idea is to have fun and encourage each other to exercise. Our Wednesday Walks set out from the Waka on the Lakefront at 9am sharp. The walk lasts for up to an hour. You can go at your own pace and there is no minimum level of fitness required. Wear a hat and bring walking shoes, water & extra carbohydrate foods if you are prone to low blood sugar levels. Bring your partner, friend, kids or mokopuna.

×