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…)
The American Diabetes Association launched its first official blog today to help put a face on a disease that kills more people each year than breast cancer and AIDS combined.  The blog, called Diabetes Stops Here: Living with Diabetes; Inspired to Stop It, aims to document the Stop Diabetes® movement by reaching and engaging the 23.6 million Americans living with diabetes as well as the 57 million who are at risk for developing type 2 diabetes. 
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.
I act as a care giver for my grandparents who both suffer from type 2 diabetes. This article is right on point with having to make changes to one’s diet to help control blood glucose and overall health such as heart disease as well as staying active and exercising. The two naturally go hand in hand, but many diabetics like my grandparents have foot complications with swelling and neuropathy, requiring proper fitting footwear that is hard to find if you don’t know where to look. I found this guide on shoes for diabetics that helps explain what they are and their importance, especially for diabetics. Hopefully others find it as helpful as I did when caring for those diagnosed with diabetes.

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 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.

The 60.2% of HPs in our survey who had recommended a diabetes app is significantly higher than previously documented amongst physicians across a range of specialties [28], although it is similar to HPs’ recommendation for any type of health app [19]. We did not observe any effect of HPs’ age on app recommendation, although it is previously well established that younger HPs are more likely to adopt mHealth for diabetes [28].
Some of the most vocal diabetes stories come from blogs and other social media platforms which create a broad online community of people who have diabetes or whose loved ones are living with the disease.  “By means of this blog,” noted Hausner, “we hope to add our voice to this dialogue and further engage with those who may be well aware of the effects diabetes can have on their lives.”
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.
Owing to individual tailoring, participants in the intervention group received varying numbers of messages. Half the participants (92/183) received messages for three months, an additional 18% (33/183) chose to continue the messages for six months, and the remaining 32% (58/183) chose to continue the messages to the maximum nine months. Only three participants chose to stop their messages early. A total number of 76 523 messages were sent by the system to participants (median number of messages per participant 242 (interquartile range 122-511; range 14-2050)), and 16 251 messages of blood glucose results were sent into the system by participants receiving the reminders (68 (1-169; 0-917)).
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.
‘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!’

Almost two-thirds of HPs responding had recommended a diabetes app to patients. Dieticians were more likely to recommend an app than others. Blood glucose and carbohydrate diaries were considered the most useful feature and HPs were most confident to recommend blood glucose diaries. HPs are the least confident recommending insulin dose calculation functions. Over one-third of HPs desire guidance with app recommendations.

Lack of insulin results in ketoacidosis. Ketones are acids that develop in the blood and appear in the urine. Ketones could poison the body and this is a warning sign that the diabetes is out of control. Symptoms of diabetes involve nausea, shortness of breath, vomiting, fruity flavor in breath, dry mouth, and high glucose levels. Complications associated with diabetes are retinopathy, neuropathy, nephropathy, heart disease and gangrene. Hypoglycemia or low blood sugar is yet another problem associated with diabetes mellitus. Symptoms include hunger, tremor, seizure, sweating, dizziness, jerks, tingling sensation and pale skin color. Improper management of diabetes causes low blood sugar, which in turn causes hypoglycemic coma. It is a life threatening condition.

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