Vincent L. Versace

Scaling up diabetes prevention in Victoria, Australia: policy development, implementation and evaluation

OBJECTIVE The Australian lifestyle intervention program Life! is only the second reported, large-scale diabetes prevention program. This article describes the genesis and the successful establishment of Life! and its key outcomes for participants and implementation. RESEARCH DESIGN AND METHODS Life!, a behavior-change intervention, comprises six group sessions over 8 months. The Victorian Department of Health funded Diabetes Australia–Victoria to implement the program. Experience of the Greater Green Triangle diabetes prevention implementation trial was used for intervention design, workforce development, training, and infrastructure. Clinical and anthropometric data from participants, used for program evaluation, were recorded on a central database. RESULTS Life! has a statewide workforce of 302 trained facilitators within 137 organizations. Over 29,000 Victorians showed interest in Life!, and 15,000 individuals have been referred to the program. In total, 8,412 participants commenced a Life! program between October 2007 and June 2011, and 37% of the original participants completed the 8-month program. Participants completing sessions 1 to 5 lost an average of 1.4 kg weight (P < 0.001) and waist circumference of 2.5 cm (P < 0.001). Those completing six sessions lost an average of 2.4 kg weight (P < 0.001) and waist circumference of 3.8 cm (P < 0.001). The weight loss of 2.4 kg represents 2.7% of participants’ starting body weight. CONCLUSIONS The impact of Life! is attributable to applying available evidence for the system’s design of the intervention and collaboration between policy makers, implementers, and evaluators using the principles of continuous quality improvement to support successful, large-scale recruitment and implementation.

Ocean currents influence the genetic structure of an intertidal mollusc in southeastern Australia – implications for predicting the movement of passive dispersers across a marine biogeographic barrier

Major disjunctions among marine communities in southeastern Australia have been well documented, although explanations for biogeographic structuring remain uncertain. Converging ocean currents, environmental gradients, and habitat discontinuities have been hypothesized as likely drivers of structuring in many species, although the extent to which species are affected appears largely dependent on specific life histories and ecologies. Understanding these relationships is critical to the management of native and invasive species, and the preservation of evolutionary processes that shape biodiversity in this region. In this study we test the direct influence of ocean currents on the genetic structure of a passive disperser across a major biogeographic barrier. Donax deltoides (Veneroida: Donacidae) is an intertidal, soft-sediment mollusc and an ideal surrogate for testing this relationship, given its lack of habitat constraints in this region, and its immense dispersal potential driven by year-long spawning and long-lived planktonic larvae. We assessed allele frequencies at 10 polymorphic microsatellite loci across 11 sample locations spanning the barrier region and identified genetic structure consistent with the major ocean currents of southeastern Australia. Analysis of mitochondrial DNA sequence data indicated no evidence of genetic structuring, but signatures of a species range expansion corresponding with historical inundations of the Bassian Isthmus. Our results indicate that ocean currents are likely to be the most influential factor affecting the genetic structure of D. deltoides and a likely physical barrier for passive dispersing marine fauna generally in southeastern Australia.

Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions.

Assessment of Spatiotemporal Varying Relationships Between Rainfall, Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R2 and lower corrected Akaike information criterion (AICC). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R2 and lower AICC. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.

Mothers after Gestational Diabetes in Australia (MAGDA): A Randomised Controlled Trial of a Postnatal Diabetes Prevention Program

Background Gestational diabetes mellitus (GDM) is an increasingly prevalent risk factor for type 2 diabetes. We evaluated the effectiveness of a group-based lifestyle modification program in mothers with prior GDM within their first postnatal year. Methods and Findings In this study, 573 women were randomised to either the intervention (n = 284) or usual care (n = 289). At baseline, 10% had impaired glucose tolerance and 2% impaired fasting glucose. The diabetes prevention intervention comprised one individual session, five group sessions, and two telephone sessions. Primary outcomes were changes in diabetes risk factors (weight, waist circumference, and fasting blood glucose), and secondary outcomes included achievement of lifestyle modification goals and changes in depression score and cardiovascular disease risk factors. The mean changes (intention-to-treat [ITT] analysis) over 12 mo were as follows: −0.23 kg body weight in intervention group (95% CI −0.89, 0.43) compared with +0.72 kg in usual care group (95% CI 0.09, 1.35) (change difference −0.95 kg, 95% CI −1.87, −0.04; group by treatment interaction p = 0.04); −2.24 cm waist measurement in intervention group (95% CI −3.01, −1.42) compared with −1.74 cm in usual care group (95% CI −2.52, −0.96) (change difference −0.50 cm, 95% CI −1.63, 0.63; group by treatment interaction p = 0.389); and +0.18 mmol/l fasting blood glucose in intervention group (95% CI 0.11, 0.24) compared with +0.22 mmol/l in usual care group (95% CI 0.16, 0.29) (change difference −0.05 mmol/l, 95% CI −0.14, 0.05; group by treatment interaction p = 0.331). Only 10% of women attended all sessions, 53% attended one individual and at least one group session, and 34% attended no sessions. Loss to follow-up was 27% and 21% for the intervention and control groups, respectively, primarily due to subsequent pregnancies. Study limitations include low exposure to the full intervention and glucose metabolism profiles being near normal at baseline. Conclusions Although a 1-kg weight difference has the potential to be significant for reducing diabetes risk, the level of engagement during the first postnatal year was low. Further research is needed to improve engagement, including participant involvement in study design; it is potentially more effective to implement annual diabetes screening until women develop prediabetes before offering an intervention. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12610000338066

Population Genetic Structuring in Acanthopagrus butcheri (Pisces: Sparidae): Does Low Gene Flow Among Estuaries Apply to Both Sexes?

Acanthopagrus butcheri completes its entire life history within estuaries and coastal lakes of southern Australia, although adults occasionally move between estuaries via the sea. Consequently, it is expected that populations of A. butcheri in different estuaries will be genetically distinct, with the magnitude of genetic divergence increasing with geographic isolation. However, previous genetic studies of A. butcheri from southeast Australia yielded conflicting results; allozyme variation exhibited minimal spatial structuring (θ = 0.012), whereas mitochondrial DNA distinguished the majority of populations analyzed (θ = 0.263) and genetic divergence was positively correlated with geographic isolation. This discrepancy could reflect high male gene flow, which impacts nuclear but not mitochondrial markers. Here we estimated allele frequencies at five nuclear microsatellite loci across 11 southeast Australian populations (595 individuals). Overall structuring of microsatellite variation was weaker (θ = 0.088) than that observed for mitochondrial DNA, but was able to distinguish a greater number of populations and was positively correlated with geographic distance. Therefore, we reject high male gene flow and invoke a stepping-stone model of infrequent gene flow among estuaries for both sexes. Likewise, management of A. butcheri within the study range should be conducted at the scale of individual or geographically proximate estuaries for both sexes. The lack of allozyme structuring in southeast Australia reflects either the large variance in structuring expected among loci under neutral conditions and the low number of allozymes surveyed or a recent colonization of estuaries such that some but not all nuclear loci have approached migration-drift equilibrium.

A comparison of Australian rural and metropolitan cardiovascular risk and mortality: the Greater Green Triangle and North West Adelaide population surveys

Objectives Cardiovascular (CVD) mortality disparities between rural/regional and urban-dwelling residents of Australia are persistent. Unavailability of biomedical CVD risk factor data has, until now, limited efforts to understand the causes of the disparity. This study aimed to further investigate such disparities. Design Comparison of (1) CVD risk measures between a regional (Greater Green Triangle Risk Factor Study (GGT RFS, cross-sectional study, 2004–2006) and an urban population (North West Adelaide Health Study (NWAHS, longitudinal cohort study, 2004–2006); (2) Australian Bureau of Statistics (ABS) CVD mortality rates between these and other Australian regions; and (3) ABS CVD mortality rates by an area-level indicator of socioeconomic status, the Index of Relative Socioeconomic Disadvantage (IRSD). Setting Greater Green Triangle (GGT, Limestone Coast, Wimmera and Corangamite Shires) of South-Western Victoria and North-West Adelaide (NWA). Participants 1563 GGT RFS and 3036 NWAHS stage 2 participants (aged 25–74) provided some information (self-administered questionnaire +/− anthropometric and biomedical measurements). Primary and secondary outcome measures Age-group specific measures of absolute CVD risk, ABS CVD mortality rates by study group and Australian Standard Geographical Classification (ASGC) region. Results Few significant differences in CVD risk between the study regions, with absolute CVD risk ranging from approximately 5% to 30% in the 35–39 and 70–74 age groups, respectively. Similar mean 2003–2007 (crude) mortality rates in GGT (98, 95% CI 87 to 111), NWA (103, 95% CI 96 to 110) and regional Australia (92, 95% CI 91 to 94). NWA mortality rates exceeded that of other city areas (70, 95% CI 69 to 71). Lower measures of socioeconomic status were associated with worse CVD outcomes regardless of geographic location. Conclusions Metropolitan areas do not always have better CVD risk factor profiles and outcomes than rural/regional areas. Needs assessments are required for different settings to elucidate relative contributions of the multiple determinants of risk and appropriate cardiac healthcare strategies to improve outcomes.

Socio-Cultural Disparities in GDM Burden Differ by Maternal Age at First Delivery

Aims Several socio-cultural and biomedical risk factors for gestational diabetes mellitus (GDM) are modifiable. However, few studies globally have examined socio-cultural associations. To eliminate confounding of increased risk of diabetes in subsequent pregnancies, elucidating socio-cultural associations requires examination only of first pregnancies. Methods Data for all women who delivered their first child in Victoria, Australia between 1999 and 2008 were extracted from the Victorian Perinatal Data Collection. Crude and adjusted GDM rates were calculated. Multivariate logistic regression was used to examine odds of GDM within and between socio-cultural groups. Results From 1999 to 2008, 269,682 women delivered their first child in Victoria. GDM complicated 11,763 (4.4%) pregnancies and burden increased with maternal age, from 2.1% among women aged below 25 years at delivery to 7.0% among those aged 35 years or more. Among younger women, GDM rates were relatively stable across socioeconomic levels. Amongst older women GDM rates were highest in those living in most deprived areas, with a strong social gradient. Asian-born mothers had highest GDM rates. All migrant groups except women born in North-West Europe had higher odds of GDM than Australian-born non-Indigenous women. In all ethnic groups, these differences were not pronounced among younger mothers, but became increasingly apparent amongst older women. Conclusions Socio-cultural disparities in GDM burden differ by maternal age at first delivery. Socio-cultural gradients were not evident among younger women. Health and social programs should seek to reduce the risk amongst all older women to that of the least deprived older mothers.

Mothers after gestational diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) post-natal intervention: study protocol for a randomized controlled trial

BackgroundGestational diabetes mellitus (GDM) is defined as glucose intolerance with its onset or first recognition during pregnancy. Post-GDM women have a life-time risk exceeding 70% of developing type 2 diabetes mellitus (T2DM). Lifestyle modifications reduce the incidence of T2DM by up to 58% for high-risk individuals.Methods/DesignThe Mothers After Gestational Diabetes in Australia Diabetes Prevention Program (MAGDA-DPP) is a randomized controlled trial aiming to assess the effectiveness of a structured diabetes prevention intervention for post-GDM women. This trial has an intervention group participating in a diabetes prevention program (DPP), and a control group receiving usual care from their general practitioners during the same time period. The 12-month intervention comprises an individual session followed by five group sessions at two-week intervals, and two follow-up telephone calls. A total of 574 women will be recruited, with 287 in each arm. The women will undergo blood tests, anthropometric measurements, and self-reported health status, diet, physical activity, quality of life, depression, risk perception and healthcare service usage, at baseline and 12 months. At completion, primary outcome (changes in diabetes risk) and secondary outcome (changes in psychosocial and quality of life measurements and in cardiovascular disease risk factors) will be assessed in both groups.DiscussionThis study aims to show whether MAGDA-DPP leads to a reduction in diabetes risk for post-GDM women. The characteristics that predict intervention completion and improvement in clinical and behavioral measures will be useful for further development of DPPs for this population.Trial registrationAustralian New Zealand Clinical Trials Registry ANZCTRN 12610000338066

Evaluation of AUSDRISK as a screening tool for lifestyle modification programs: international implications for policy and cost-effectiveness.

Objective To evaluate the current use of Australian Type 2 Diabetes Risk Assessment Tool (AUSDRISK) as a screening tool to identify individuals at high risk of developing type 2 diabetes for entry into lifestyle modification programs. Research Design and Methods AUSDRISK scores were calculated from participants aged 40–74 years in the Greater Green Triangle Risk Factor Study, a cross-sectional population survey in 3 regions of Southwest Victoria, Australia, 2004–2006. Biomedical profiles of AUSDRISK risk categories were determined along with estimates of the Victorian population included at various cut-off scores. Sensitivity, specificity, positive predictive value (PPV), negative predictive value, and receiver operating characteristics were calculated for AUSDRISK in determining fasting plasma glucose (FPG) ≥6.1 mmol/L. Results Increasing AUSDRISK scores were associated with an increase in weight, body mass index, FPG, and metabolic syndrome. Increasing the minimum cut-off score also increased the proportion of individuals who were obese and centrally obese, had impaired fasting glucose (IFG) and metabolic syndrome. An AUSDRISK score of ≥12 was estimated to include 39.5% of the Victorian population aged 40–74 (916 000), while a score of ≥20 would include only 5.2% of the same population (120 000). At AUSDRISK≥20, the PPV for detecting FPG≥6.1 mmol/L was 28.4%. Conclusions AUSDRISK is powered to predict those with IFG and undiagnosed type 2 diabetes, but its effectiveness as the sole determinant for entry into a lifestyle modification program is questionable given the large proportion of the population screened-in using the current minimum cut-off of ≥12. AUSDRISK should be used in conjunction with oral glucose tolerance testing, fasting glucose, or glycated hemoglobin to identify those individuals at highest risk of progression to type 2 diabetes, who should be the primary targets for lifestyle modification.