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.
Data sharing: The research team will consider reasonable requests for sharing of deidentified patient level data. Requests should be made to the corresponding author. Consent for data sharing was not obtained but the presented data are anonymised and risk of identification is low. The original protocol30 is available from the corresponding author on request.
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.

I am passionate about diabetes education, so when you purchase from the Diabetes Depot, you also have at your disposal the resources of a pharmacist, a Certified Diabetes Educator and a fellow pumper. I am a member of a Peterborough Family Health Team, where I have the opportunity to help clients manage their diabetes. I have given many lectures on the management and prevention of diabetes complications to both patient groups and health care professionals throughout Canada, and am the proud recipient of numerous awards for this work. I hope my effort to provide lower-cost insulin pump supplies to Canadians will help you, and I again invite you to contact me with your specific diabetes questions.
This study shows the potential of SMS4BG to provide a low cost, scalable solution for increasing the reach of diabetes self management support. It showed that a text messaging programme can increase a patient’s feelings of support without the need for personal contact from a healthcare professional. Half of the intervention group reported sharing the messages with others. Traditional education for diabetes self management is delivered to individual patients, but there is benefit of support from other people being involved.45 This is particularly pertinent to ethnic populations such as Māori groups, in whom family have an important role in supporting diabetes self management.46
Additional data on all patients were collected from the hospital management system, including age, and the most recent values within the previous 12 months from date of survey for blood pressure (BP), glycated hemoglobin (HbA1c), urinary microalbumin to Creatinine ratio (ACR), low density lipoprotein cholesterol (LDL), and total cholesterol to HDL ratio (C:HDL). Prescription of lipid lowering drugs, anti-hypertensive drugs, insulin, or other hypoglycemic medication were also extracted from the medication list from the last visit within the sample period. Type of diabetes was self-reported in the survey (type 1 [T1DM], type 2 [T2DM], other or unknown) and in four participants who had selected ‘other’ or ‘unknown’ diabetes type was determined by examination of the clinical records. For categorization of participants by app use, 4 responders who did not indicate if they had a mobile phone or not were included in the non-app group.

New Zealand celebrates Diabetes Action Month – and the results of last year’s risk factor assessment highlight the importance of getting involved: Last year, more than 3,500 people undertook an assessment of their risk factors during the month, with 68% learning they potentially have a greater propensity for type 2 diabetes. The core purpose of the first Diabetes Action Month was to alert New Zealand that everyone is at risk of diabetes. Activities in November included a national roadshow that visited 33 locations in 14 towns and cities, and the launch of an online version of the risk awareness tool, so everyone could assess their risk
This study found that a tailored, theoretically based, SMS based, diabetes self management support programme led to modest improvements in glycaemic control. The effects of intervention were also seen in four of 21 secondary outcomes, including foot care behaviour and ratings of diabetes support. The programme showed a high level of acceptability with the overwhelming majority of participants finding the intervention useful and willing to recommend it to others.
Eligible participants were randomised to either an intervention or control group in a 1:1 ratio. Randomisation was stratified by health district category (high urban or high rural/remote), diabetes type (1 or 2), and ethnicity (Māori and Pacific, or non-Māori/non-Pacific). The randomisation sequence was generated by computer programme using variable block sizes of two or four, and overseen by the study statistician. Following participant consent and completion of the baseline interview, the research assistant then randomised the participant to intervention or control, using the REDCap randomisation module. The REDCap randomisation module ensured that treatment allocation was concealed until the point of randomisation. Due to the nature of the intervention, participants were aware of their treatment allocation. Research assistants conducting the phone interviews were also aware of the treatment allocation. However, the objective primary outcome was measured by blinded assessors throughout the study period.
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.
The incidence of type 1 diabetes was higher in New Zealand Europeans than other ethnic groups throughout the study period (Figure 2, p<0.0001). There was little difference in incidence among non-European ethnic groups. The annual incidences (per 100,000) by 2009 were: Europeans 32.5 (95% CI 23.8–43.3), Non-Europeans 14.4 (95% CI 9.2–21.4), Maori 13.9 (95% CI 5.2–29.7), Pacific Islanders 15.4 (95% CI 7.3–28.5), and Other 13.5 (95% CI 5.8–26.8). The rate of increase in incidence over the study period was very similar across all ethnicities, as illustrated by the slopes in Figure 2. However, while the average increase in incidence was higher for Europeans than Non-Europeans in children of all age groups (Table 1), the increase was proportionally lower in Europeans (2-fold) than Non-Europeans (3-fold) due to a lower baseline incidence in the latter group (Figure 2). Nonetheless, in both ethnic groups type 1 diabetes incidence in children 10–14 yr increased at a higher rate than in the youngest 0–4 yr group, with a >2-fold difference observed among both Europeans and Non-Europeans (Table 1). Age at diagnosis across the study period was similar in both ethnic groups (p = 0.47).
From 1994 onwards, anthropometric data were recorded at each clinic visit, and for the purposes of this study we used data from the first post-diagnosis clinic that usually occurred 3–4 months afterwards. Standard deviation scores (SDS) were calculated based on the British 1990 Growth Reference Data [17] to obtain height SDS, weight SDS, and body mass index (BMI) SDS.
24. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009 Apr;42(2):377–81. doi: 10.1016/j.jbi.2008.08.010. http://linkinghub.elsevier.com/retrieve/pii/S1532-0464(08)00122-6. [PMC free article] [PubMed] [CrossRef]
A large patient sample size was obtained by contacting all patients seen in the last 12 months with an email address. The risk of overrepresentation by more technology-literate responders through recruitment via email was minimized by also recruiting via telephone and by providing paper surveys at the HPs’ conference. The demographic and clinical data of responders and non-responders were compared, and most variables showed no difference. Responders were actually older than non-responders and had better glycemic control. This study focused on the beliefs and opinions of people with diabetes (potential app users) and HPs (potential app prescribers) rather than simply describing apps for diabetes . It is one of the first papers to describe app use in people with diabetes in New Zealand.
The incidence of type 1 diabetes was higher in New Zealand Europeans than other ethnic groups throughout the study period (Figure 2, p<0.0001). There was little difference in incidence among non-European ethnic groups. The annual incidences (per 100,000) by 2009 were: Europeans 32.5 (95% CI 23.8–43.3), Non-Europeans 14.4 (95% CI 9.2–21.4), Maori 13.9 (95% CI 5.2–29.7), Pacific Islanders 15.4 (95% CI 7.3–28.5), and Other 13.5 (95% CI 5.8–26.8). The rate of increase in incidence over the study period was very similar across all ethnicities, as illustrated by the slopes in Figure 2. However, while the average increase in incidence was higher for Europeans than Non-Europeans in children of all age groups (Table 1), the increase was proportionally lower in Europeans (2-fold) than Non-Europeans (3-fold) due to a lower baseline incidence in the latter group (Figure 2). Nonetheless, in both ethnic groups type 1 diabetes incidence in children 10–14 yr increased at a higher rate than in the youngest 0–4 yr group, with a >2-fold difference observed among both Europeans and Non-Europeans (Table 1). Age at diagnosis across the study period was similar in both ethnic groups (p = 0.47).
-Learn to eat well-balanced meals that include healthful food choices (vegetables, fruits, whole grains, etc.) and watch your portion sizes. Even foods that are good for you can add pounds to your waistline, if you consume too much of them. Losing those extra pounds will help you manage not only your diabetes, but also other health problems you may have.

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.


This study showed that a tailored and automated SMS self management support programme has potential for improving glycaemic control in adults with poorly controlled diabetes. Although the clinical significance of these results is unclear, and the full duration of these effects is yet to be determined, exploration of SMS4BG to supplement current practice is warranted.
Owing to time restrictions, longer term follow-up of participants was not feasible within the current study, although it is hoped that a two year follow-up of the present study’s participants is possible. The significant group difference seen at three months, dropping slightly at six months, but reaching significance again at nine months, could be an indication of sustained change. Another limitation of the study design was that secondary outcome assessors were not blinded to treatment allocation, which could have introduced bias in follow-up data collection of secondary variables.

Like my customers, I use an insulin pump to control my diabetes because it allows me to be spontaneous and flexible in managing my diabetes while reducing hypoglycemia. Reaching target blood glucose levels is not always easy, but being a Pharmacist, as well as a Certified Diabetes Educator and Certified Pump Trainer, I know the importance of managing my blood glucose to reduce long-term complications. You are welcome to contact me about any aspect of insulin pump therapy or with any questions about specific insulin pump supplies.
To obtain data on HPs’ knowledge and recommendation of apps to people with diabetes, a second survey was conducted of the HPs attending the annual scientific meeting of the New Zealand Society for the Study of Diabetes (NZSSD) in May 2016. Immediately prior to the meeting all registered attendees (n=286) were invited to participate in the online survey via email. The data from the patient survey was presented at the conference in a 15-min oral presentation and attendees were encouraged to complete the survey. Paper copies of the survey were also available at the meeting. This survey remained open for 2 weeks, with a reminder sent at 1 week.
Increase your physical activity. Exercise is a very important tool to help lower your blood glucose. Prior to starting any exercise program, you will need to consult with your doctor. Make exercise routine with activities you enjoy. In addition to helping manage your blood glucose, exercise helps lower blood pressure and improves balance, flexibility and muscle strength. Exercise may even help to reduce anxiety and depression. Go out and play!
It’s heart-wrenching to watch all that people go through as natural disasters play out on our television screens. Tucked away, along with sympathy for those in the midst of a hurricane, earthquake, flood or other catastrophic events, is the very understandable thought, “I’m so glad that’s not happening to me!”. The truth is, however, that we are all susceptible to major life-changing events, and they can happen with very little notice. Those with a chronic medical condition, like diabetes, are especially vulnerable and should take seriously the advice to be prepared.    (more…)

Phoenix Health Centre carries out pre employment medical assessments for several large employers in Whakatane. These give a base line recording of an employee’s health status at the time they were employed. It is then possible to monitor the employee’s health in relation to the hazards they may be exposed to in the workplace. If required we also undertake monitored urine sampling for ESR drug testing.
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