Diabetes mellitus and the risk of depressive and anxiety disorders in Australian women: A longitudinal study

Background Longitudinal studies examining the risk of depressive and anxiety disorders associated with diabetes are limited. This study examined the association between diabetes and the risk of depressive and anxiety disorders in Australian women using longitudinal data. Methods Datawere froma sample of women who were part of anAustralian pregnancy and birth cohort study. Data comprised self-reported diabetes mellitus and the subsequent reporting of depressive and anxiety disorders. Mood disorders were assessed according to the Diagnostic and Statistical Manual of Mental Disorders, fourth edition, obtained from participants using Composite International Diagnostic Interview (CIDI)-Auto (WHO WMH-CIDI CAPI, version 21.1.3). Multiple regression models with adjustment for important covariates were used. Results Women with diabetes had a higher lifetime prevalence of any depressive and/or anxiety disorder than women without diabetes. About 3 in 10 women with diabetes experienced a lifetime event of any depressive disorder, while 1 in 2 women with diabetes experienced a lifetime event of any anxiety disorder. In prospective analyses, diabetes was only significantly associated with a 30-day episode of any anxiety disorder (odds ratio [OR] 1.53, 95% confidence interval [CI] 1.09–2.15). In the case of lifetime disorders, diabetes was significantly associated with any depressive disorder (OR 1.37, 95% CI 1.03–1.84), major depressive disorder (OR 1.36, 95% CI 1.01–1.85), and posttraumatic stress disorder (OR 1.42, 95% CI 1.01–2.02). Conclusions The findings suggest that the presence of diabetes is a significant risk factor for women experiencing current anxiety disorders. However, in the case of depression, the association with diabetes only held for women who had experienced past episodes, there was no association with current depression. This suggests that the evidence is not strong enough to support a direct effect of diabetes as a cause of mood disorders.

Manifestations of type 2 diabetes in corneal endothelial cell density, corneal thickness and intraocular pressure

We sought to evaluate central corneal thickness (CCT), corneal endothelial cell density (ECD) and intraocular pressure (IOP) in patients with type 2 diabetes mellitus (DM) and to associate potential differences with diabetes duration and treatment modality in a prospective, randomized study. We measured ECD, CCT and IOP of 125 patients with type 2 DM (mean age 57.1¡11.5 years) and compared them with 90 age-matched controls. Measured parameters were analyzed for association with diabetes duration and glucose control modalities (insulin injection or oral medication) while controlling for age. In the diabetic group, the mean ECD (2511¡252 cells/mm2), mean CCT (539.7¡33.6 mm) and mean IOP (18.3¡2.5 mmHg) varied significantly from those the control group [ECD: 2713¡132 cells/mm2 (P,0.0001), CCT: 525.0¡45.3 mm (P50.003) and IOP: 16.7¡1.8 mmHg (P,0.0001)]. ECD was significantly reduced by about 32 cell/mm2 for diabetics with duration of .10 years when compared with those with duration of ,10 years (P,0.05). CCT was thicker and IOP was higher for diabetics with duration of .10 years than those with duration of ,10 years (P.0.05). None of the measured parameters was significantly associated with diabetes duration and treatment modality (P.0.05). In conclusion, subjects with type 2 DM exhibit significant changes in ECD, IOP and CCT, which, however, are not correlated with disease duration or if the patients receive on insulin injection or oral medications.

Using mobile technology to motivate adolescents with type 1 diabetes mellitus: A systematic review of recent literature

Introduction Behavioural interventions have been shown to improve outcomes in patients with type 1 diabetes mellitus (T1DM). There are a small number of studies that suggest text-messages (TM), native mobile applications (NMAs), and other mobile tools may be useful platforms for delivering behavioural interventions to adolescents. Aim The aim of this study was to explore, by way of a systematic review of available literature, (a) the outcomes of interventions using mobile technology for youth with T1DM and (b) what mobile technologies, functional design elements and aesthetic design elements have the best evidence to support their use. Methods A search of six online databases returned 196 unique results, of which 13 met the inclusion criteria. Results Four studies were randomised controlled trials (RCTs), and all others prospective cohort studies. TM (10) was the most common intervention technology, while NMAs were used in four studies. The most common outcome measured was HbA1c (9); however, only three studies showed a significant decrease. Similarly, the results reported for other outcome measures were mixed. The studies included in this review suggest that interventions which have data collection and clinician support functionality may be more effective in improving adherence and glycaemic control, but more evidence is needed. Further, the evidence base supporting the use of NMAs in T1DM management for adolescents is weak, with most studies adopting TM as the intervention tool. Overall, the studies lack adequate descriptions of their methodology, and better quality studies are required to inform future intervention design.

Evaluation of physical activity among adults with diabetes mellitus from Sri Lanka

We evaluated the patterns of physical activity (PA) and the prevalence of physical inactivity among Sri Lankan adults with diabetes mellitus. Data were collected as part of a wider cross-sectional national study on diabetes in Sri Lanka. PA during the past week was assessed using the short version of the IPAQ. Overall prevalence of physical inactivity was 13.9%. Females (3091 ± 2119) had a significantly higher mean weekly total MET minutes than males (2506 ± 2084) (p < 0.01). Inactivity of those residing in urban (17.2%) areas was higher than rural (12.6%) in all adults. Participants from Moor ethnicity were more inactive compared to others. Adults who were physically active had significantly low waist and hip circumferences, BMI and systolic blood pressure.

Prevalence of retinopathy among adults with self-reported diabetes mellitus: the Sri Lanka diabetes and Cardiovascular Study

Background: At present there are no large scale nationally-representative studies from Sri Lanka on the prevalence and associations of Diabetic Retinopathy (DR). The present study aims to evaluate the prevalence and risk factors for DR in a community-based nationally-representative sample of adults with self-reported diabetes mellitus from Sri Lanka. Methods: A cross-sectional community-based national study among 5,000 adults (≥18 years) was conducted in Sri Lanka, using a multi-stage stratified cluster sampling technique. An interviewer-administered questionnaire was used to collect data. Ophthalmological evaluation of patients with ‘known’ diabetes (previously diagnosed at a government hospital or by a registered medical practitioner) was done using indirect ophthalmoscopy. A binary-logistic regression analysis was performed with ‘presence of DR’ as the dichotomous dependent variable and other independent covariates. Results: Crude prevalence of diabetes was 12.0%(n=536),of which 344 were patients with ‘known’ diabetes.Mean age was 56.4 ± 10.9 years and 37.3% were males. Prevalence of any degree of DR was 27.4% (Males-30.5%, Females-25.6%; p = 0.41). In patients with DR, majority had NPDR (93.4%), while 5.3% had maculopathy. Patients with DR had a significantly longer duration of diabetes than those without. In the binary-logistic regression analysis in all adults duration of diabetes (OR:1.07), current smoking (OR:1.67) and peripheral neuropathy (OR:1.72)all were significantly associated with DR. Conclusions: Nearly 1/3rd of Sri Lankan adults with self-reported diabetes are having retinopathy. DR was associated with diabetes duration, cigarette smoking and peripheral neuropathy. However, further prospective follow up studies are required to establish causality for identified risk factors

Peripartum management of glycemia in women with type 1 diabetes

OBJECTIVE We aimed to 1) describe the peripartum management of type 1 diabetes at an Australian teaching hospital and 2) discuss factors influencing the apparent transient insulin independence postpartum. RESEARCH DESIGN AND METHODS We conducted a retrospective review of women with type 1 diabetes delivering singleton pregnancies from 2005 to 2010. Information was collected regarding demographics, medical history, peripartum management and outcome, and breast-feeding. To detect a difference in time to first postpartum blood glucose level (BGL) >8 mmol/L between women with an early (<4 h) and late (>12 h) requirement for insulin postpartum, with a power of 80% and a type 1 error of 0.05, at least 24 patients were required. RESULTS An intravenous insulin infusion was commenced in almost 95% of women. Univariate analysis showed that increased BMI at term, lower creatinine at term, longer duration from last dose of long- or intermediate-acting insulin, and discontinuation of an insulin infusion postpartum were associated with a shorter time to first requirement of insulin postpartum (P = 0.005, 0.026, 0.026, and <0.001, respectively). There was a correlation between higher doses of insulin commenced postpartum and number of out-of-range BGLs (r[36] = 0.358, P = 0.030) and hypoglycemia (r[36] = 0.434, P = 0.007). Almost 60% had at least one BGL <3.5 mmol/L between delivery and discharge. CONCLUSIONS Changes in the pharmacodynamic profile of insulin may contribute to the transient insulin independence sometimes observed postpartum in type 1 diabetes. A dose of 50–60% of the prepregnancy insulin requirement resulted in the lowest rate of hypoglycemia and glucose excursions. These results require validation in a larger, prospective study.

Resistance training for obese, type 2 diabetic adults: A review of the evidence

In both developed and developing countries, increased prevalence of obesity has been strongly associated with increased incidence of type 2 diabetes mellitus (T2DM) in the adult population. Previous research has emphasized the importance of physical activity in the prevention and management of obesity and T2DM, and generic exercise guidelines originally developed for the wider population have been adapted for these specific populations. However, the guidelines traditionally focus on aerobic training without due consideration to other exercise modalities. Recent reviews on resistance training in the T2DM population have not compared this modality with others including aerobic training, or considered the implications of resistance training for individuals suffering from both obesity and T2DM. In short, the optimal mix of exercise modalities in the prescription of exercise has not been identified for it benefits to the metabolic, body composition and muscular health markers common in obesity and T2DM. Similarly, the underlying physical, social and psychological barriers to adopting and maintaining exercise, with the potential to undermine the efficacy of exercise interventions, have not been addressed in earlier reviews. Because it is well established that aerobic exercise has profound effects on obesity and T2DM risk, the purpose of this review was to address the importance of resistance training to obese adults with T2DM.

What works elsewhere? A review of physical activity intervention studies

Obesity and type 2 diabetes mellitus (T2D) have reached epidemic proportions in many parts of the world with numbers projected to rise dramatically in coming decades (Wang and Lobstein, 2006; Zaninotto et al., 2006). In Australia, and consistent with much of the developed world, the problem has been described as a ‘juggernaut’ that is out of control (Zimmet and James, 2007). Unfortunately the burgeoning problem of non-communicable diseases, including obesity and T2D, is also impacting developing nations as populations are undergoing a nutrition transition (Caballero, 2005). The increased prevalence of overweight and obesity in children, adolescents and adults in both the developed and developing world is consistent with reductions in all forms of physical activity (Brownson et al., 2005). This brief paper provides an overview of the importance of physical activity and an outline of physical activity intervention studies with particular reference to the growing years. As many interventions studies involving physical activity have been undertaken in the context of childhood obesity prevention (Lobstein et al., 2004), and an increasing proportion of the childhood population is overweight or obese, this is a major focus of discussion.

Physical and environmental determinants

This chapter describes physical and environmental determinants of the health of Australians, providing a background to the development of successful public health activity. Health determinants are the biomedical, genetic, behavioural, socio-economic and environmental factors that impact on health and wellbeing. These determinants can be influenced by interventions and by resources and systems (AIHW 2006). Many factors combine to affect the health of individuals and communities. People’s circumstances and the environment determine whether the population is healthy or not. Factors such as where people live, the state of their environment, genetics, their education level and income, and their relationships with friends and family, all are likely to impact on their health. The determinants of population health reflect the context of people’s lives; however, people are very unlikely to be able to control many of these determinants (WHO 2007). This chapter and Chapter 6 illustrate how various determinants can relate to, and influence other determinants, as well as health and wellbeing. We believe it is particularly important to provide an understanding of determinants and their relationship to health and illness in order to provide a structure in which a broader conceptualisation of health can be placed. Determinants of health do not exist in isolation from one another. More frequently they work together in a complex system. What is clear to anyone who works in public health is that many factors impact on the health and wellbeing of people. For example, in the next chapter we discuss factors such as living and working conditions, social support, ethnicity and class, income, housing, work stress and the impact of education on the length and quality of people’s lives. In 1974, the influential ‘Lalonde Report’ (Lalonde 1974) described key factors that impact on health status. These factors included lifestyle, environment, human biology and health services. Taking a population health approach builds on the Lalonde Report, and recognises that a range of factors, such as living and working conditions and the distribution of wealth in society, interact to determine the health status of a population. Tackling health determinants has great potential to reduce the burden of disease and promote the health of the general population. In summary, we understand very clearly now that health is determined by the complex interactions between individual characteristics, social and economic factors and physical environments; the entire range of factors that impact on health must be addressed if we are to make significant gains in population health, and focussing interventions on the health of the population or significant sub-populations can achieve important health gains. In 2007, the Australian Government included in the list of National Health Priority Areas the following health issues: cancer control, injury prevention and control, cardiovascular health, diabetes mellitus, mental health, asthma, and arthritis and musculoskeletal conditions. The National Health Priority Areas set the agenda for the Commonwealth, States and Territories, Local Governments and not-for-profit organisations to place attention on those areas considered to be the major foci for action. Many of these health issues are discussed in this chapter and the following chapter.

Prandial subcutaneous injections of glucagon-like peptide-1 cause weight loss in obese human subjects

Recombinant glucagon-like peptide-1 (7–36)amide (rGLP-1) was recently shown to cause significant weight loss in type 2 diabetics when administered for 6 weeks as a continuous subcutaneous infusion. The mechanisms responsible for the weight loss are not clarified. In the present study, rGLP-1 was given for 5d by prandial subcutaneous injections (PSI) (76nmol 30min before meals, four times daily; a total of 302·4nmol/24h) or by continuous subcutaneous infusion (CSI) (12·7nmol/h; a total of 304·8nmol/24h). This was performed in nineteen healthy obese subjects (mean age 44·2 (sem 2·5) years; BMI 39·0 (sem 1·2)kg/m2) in a prospective randomised, double-blind, placebo-controlled, cross-over study. Compared with the placebo, rGLP-1 administered as PSI and by CSI generated a 15% reduction in mean food intake per meal (P=0·02) after 5d treatment. A weight loss of 0·55 (sem 0·2) kg (P<0·05) was registered after 5d with PSI of rGLP-1. Gastric emptying rate was reduced during both PSI (P<0·001) and CSI (P<0·05) treatment, but more rapidly and to a greater extent with PSI of rGLP-1. To conclude, a 5d treatment of rGLP-1 at high doses by PSI, but not CSI, promptly slowed gastric emptying as a probable mechanism of action of increased satiety, decreased hunger and, hence, reduced food intake with an ensuing weight loss.