Alison J. Hayes

Sustainability of Effects of an Early Childhood Obesity Prevention Trial Over Time: A Further 3-Year Follow-up of the Healthy Beginnings Trial

IMPORTANCE Little evidence exists on whether effects of an early obesity intervention are sustainable. OBJECTIVE To assess the sustainability of effects of a home-based early intervention on childrens body mass index (BMI) and BMI z score at 3 years after intervention. DESIGN, SETTING, AND PARTICIPANTS A longitudinal follow-up study of the randomized clinical Healthy Beginnings Trial was conducted with 465 participating mothers consenting to be followed up at 3 years after intervention until their children were age 5 years. This study was conducted in socially and economically disadvantaged areas of Sydney, Australia, from March 2011 to June 2014. INTERVENTIONS No further intervention was carried out in this Healthy Beginnings Trial phase 2 follow-up study. The original intervention in phase 1 comprised 8 home visits from community nurses delivering a staged home-based intervention, with one visit in the antenatal period and 7 visits at 1, 3, 5, 9, 12, 18, and 24 months after birth. MAIN OUTCOMES AND MEASURES Primary outcomes were childrens BMI and BMI z score. Secondary outcomes included dietary behaviors, quality of life, physical activity, and TV viewing time of children and their mothers. RESULTS In total, 369 mothers and their children completed the follow-up study, a phase 2 completion rate of 79.4% (80.9% for the intervention group and 77.7% for the control group). The differences between the intervention and control groups at age 2 years in childrens BMI and BMI z score disappeared over time. At age 2 years, the difference (intervention minus control) in BMI (calculated as weight in kilograms divided by height in meters squared) was -0.41 (95% CI, -0.71 to -0.10; P = .009), but by age 5 years it was 0.03 (95% CI, -0.30 to 0.37). No effects of the early intervention on dietary behaviors, quality of life, physical activity, and TV viewing time were detected at age 5 years. CONCLUSIONS AND RELEVANCE The significant effect of this early life home-visiting intervention on child BMI and BMI z score at age 2 years was not sustained at age 5 years without further intervention. Obesity prevention programs need to be continued or maintained during the early childhood years.

Estimating equations to correct self‐reported height and weight: implications for prevalence of overweight and obesity in Australia

Objective: To derive correction equations based on nationally representative data, for the error associated with self‐reported height and weight and to apply these to recent estimates of overweight and obesity in the Australian adult population.

Using the EQ-5D index score as a predictor of outcomes in patients with type 2 diabetes.

Objective:To examine whether index scores based on the EQ-5D, a 5-item generic health status measure, are an independent predictor of vascular events, other major complications and mortality in people with type 2 diabetes and to quantify the relationship between these scores and future survival. Subjects:Five-year cohort study involving 7348 patients with type 2 diabetes, aged between 50–75 years who had been recruited to the FIELD (Fenofibrate Intervention and Event Lowering in Diabetes) study from Australia and New Zealand. Measures:Multivariate Cox proportional hazard regression models were used to estimate the hazard ratio associated with index scores derived from the EQ-5D on: (1) cardiovascular events (including coronary heart disease event, stroke, hospitalization for angina, or cardiovascular death); (2) other major diabetes-related complications (heart failure, amputation, renal dialysis, and lower extremity ulcer); and (3) death from any cause. Life table methods were used to derive expected survival for patients with different index scores. Results:After adjusting for standard risk factors, a 0.1 higher index score (derived from the UK algorithm) was associated with an additional 7% (95% CI: 4–11%) lower risk of vascular events, a 13% (95% CI: 9–17%) lower risk of complications, and up to 14% (95% CI: 8–19%) lower rate of all-cause mortality. Conclusions:Index scores derived from the EQ-5D are an independent predictor of the risk of mortality, future vascular events, and other complications in people with type 2 diabetes. This should be taken into account when extrapolating health outcomes such as quality-adjusted life years (QALYs).

A meta-analysis of health state valuations for people with diabetes: explaining the variation across methods and implications for economic evaluation

PurposeTo review published studies on the effect of diabetes and its complications on utility scores to establish whether there is systematic variation across studies and to examine the implications for the estimation of quality-adjusted life years (QALYs).MethodsA systematic review was performed using studies reporting QALY measures elicited from people with diabetes including those with a history of complications. Meta-analysis was used to obtain the average utility, and meta-regression was employed to examine the impact of study characteristics and elicitation methods on these values. The effect of different utility scores on QALYs was examined using diabetes simulation models.ResultsIn the meta-analysis based on 45 studies reporting 66 values, the average utility score was 0.76 (95% CI 0.75–0.77). A meta-regression showed significant variation due to age, method of elicitation and the proportion of males. The average utility score for individual complications ranged from 0.48 (95% CI 0.25, 0.71) for chronic renal disease to 0.75 (95% CI 0.73, 0.78) for myocardial infarction, and these differences produced meaningful changes in simulated QALYs. There was significant heterogeneity between studies.ConclusionsWe provide summary utility scores for diabetes and its major complications that could help inform economic evaluation and policy analysis.

Estimating the cost of diabetes mellitus-related events from inpatient admissions in Sweden using administrative hospitalization data.

AbstractBackground and aims: To estimate short- and long-term costs of inpatient hospitalization in Sweden for major diabetes mellitus-related events.Materials and methods: Costs were estimated using administrative hospital data from the Swedish National Board of Health and Welfare, which is linked to the Swedish National Diabetes Register. Data were available for 179 749 patients with diabetes in Sweden from 1998 to 2003 (mean and median duration of 6 years’ follow-up). Costing of inpatient admissions was based on Nordic diagnosis-related groups (NordDRG). Multiple regression analysis (linear and generalizing estimating equation models) was used to estimate inpatient care costs controlling for age, sex and co-morbidities. The data on hospitalizations were converted to costs (€) using 2003 exchange rates.Results: The average annual costs (linear model) associated with inpatient admissions for a 60-year-old male in the year the first event first occurred were as follows: €6488 (95% CI 5034, 8354) for diabetic coma; €6850 (95% CI 6514, 7204) for heart failure; €7853 (95% CI 7559, 8144) for non-fatal stroke; €8121 (95% CI 7104, 9128) for peripheral circulatory complications; €8736 (95% CI 8474, 9001) for non-fatal myocardial infarction (MI); €10 360 (95% CI 10 085, 10 643) for ischaemic heart disease; €11 411 (95%CI 10 298, 12 654) for renal failure; and €14 949 (95% CI 13 849, 16 551) for amputation. On average, the costs were higher when co-morbidity was accounted for (e.g. MI with co-morbidity was twice as costly as MI alone).Conclusions: Average hospital inpatient costs associated with common diabetes-related events can be estimated using panel data regression methods. These could assist in modelling of long-term costs of diabetes and in evaluating the cost effectiveness of improving care.

Change in bias in self-reported body mass index in Australia between 1995 and 2008 and the evaluation of correction equations.

BackgroundMany studies have documented the bias in body mass index (BMI) determined from self-reported data on height and weight, but few have examined the change in bias over time.MethodsUsing data from large, nationally-representative population health surveys, we examined change in bias in height and weight reporting among Australian adults between 1995 and 2008. Our study dataset included 9,635 men and women in 1995 and 9,141 in 2007-2008. We investigated the determinants of the bias and derived correction equations using 2007-2008 data, which can be applied when only self-reported anthropometric data are available.ResultsIn 1995, self-reported BMI (derived from height and weight) was 1.2 units (men) and 1.4 units (women) lower than measured BMI. In 2007-2008, there was still underreporting, but the amount had declined to 0.6 units (men) and 0.7 units (women) below measured BMI. The major determinants of reporting error in 2007-2008 were age, sex, measured BMI, and education of the respondent. Correction equations for height and weight derived from 2007-2008 data and applied to self-reported data were able to adjust for the bias and were accurate across all age and sex strata.ConclusionsThe diminishing reporting bias in BMI in Australia means that correction equations derived from 2007-2008 data may not be transferable to earlier self-reported data. Second, predictions of future overweight and obesity in Australia based on trends in self-reported information are likely to be inaccurate, as the change in reporting bias will affect the apparent increase in self-reported obesity prevalence.

A Meta-Analysis of the Relative Risk of Mortality for Type 1 Diabetes Patients Compared to the General Population: Exploring Temporal Changes in Relative Mortality

Aims Type 1 diabetes has been associated with an elevated relative risk (RR) of mortality compared to the general population. To review published studies on the RR of mortality of Type 1 diabetes patients compared to the general population, we conducted a meta-analysis and examined the temporal changes in the RR of mortality over time. Methods Systematic review of studies reporting RR of mortality for Type 1 diabetes compared to the general population. We conducted meta-analyses using a DerSimonian and Laird random effects model to obtain the average effect and the distribution of RR estimates. Sub-group meta-analyses and multivariate meta-regression analysis was performed to examine heterogeneity. Summary RR with 95% CIs was calculated using a random-effects model. Results 26 studies with a total of 88 subpopulations were included in the meta-analysis and overall RR of mortality was 3.82 (95% CI 3.41, 3.4.29) compared to the general population. Observations using data prior to 1971 had a much larger estimated RR (5.80 (95% CI 4.20, 8.01)) when compared to: data between; 1971 and 1980 (5.06 (95% CI 3.44, 7.45)); 1981–90 (3.59 (95% CI 3.15, 4.09)); and those after 1990 (3.11 (95% CI 2.47, 3.91)); suggesting mortality of Type 1 diabetes patients when compared to the general population have been improving over time. Similarly, females (4.54 (95% CI 3.79–5.45)) had a larger RR estimate when compared to males (3.25 (95% CI 2.82–3.73) and the meta-regression found evidence for temporal trends and sex (p<0.01) accounting for heterogeneity between studies. Conclusions Type 1 diabetes patients’ mortality has declined at a faster rate than the general population. However, the largest relative improvements have occurred prior to 1990. Emphasis on intensive blood glucose control alongside blood pressure control and statin therapy may translate into further reductions in mortality in coming years.

Predicting mortality in people with Type 2 diabetes mellitus after major complications: a study using Swedish National Diabetes Register data

To predict mortality risk and life expectancy for patients with Type 2 diabetes after a major diabetes‐related complication.

Healthy Beginnings Trial Phase 2 study: follow-up and cost-effectiveness analysis.

BACKGROUND In 2007, we commenced the Healthy Beginnings Trial (HBT) Phase 1 study, which is the first randomised controlled trial (RCT) to test the effectiveness of an early childhood obesity intervention in children aged up to 2 years. The results were promising with significant improvements in infant feeding practices and a lower mean body mass index (BMI). The aims of this proposed Phase 2 study are to determine if the early intervention will lead to a lower mean BMI, lower screen time, improved dietary behaviours and demonstrated cost-effectiveness of the intervention, in children aged 3½ and 5 years. METHODS/DESIGN In Phase 1 of HBT 667 families participated in the RCT. No further intervention will be carried out in HBT Phase 2. In this study the intervention and control groups will be compared for childrens outcomes at ages 3½ and 5 years. Primary outcome measures will be 1) BMI, 2) selected dietary measures using a validated survey tool, and 3) physical activity and screen time using a new generation of tri-axial accelerometers. Intention to treat principles will be used in the analysis. Multiple imputation will be used to impute outcomes for subjects lost to follow-up. A cost-effectiveness analysis (CEA) and cost-utility analysis for both HBT Phase 1 and 2 will also be conducted. DISCUSSION This is the first time that a home-based early intervention strategy has been implemented to prevent the development of childhood obesity and obesity-conducive behaviours. The results of this trial will ascertain whether early intervention during the first 2 years of life is effective and cost-effective in preventing childhood overweight and obesity at 3½ and 5 years old.

Changes in Quality of Life Associated with Complications of Diabetes: Results from the ADVANCE Study.

OBJECTIVE To measure the impact of complications on summary measures of health-related quality of life among people with type 2 diabetes. METHODS Patients participating in the Action in Diabetes and Vascular Disease:Preterax and Diamicron MR Controlled Evaluation (ADVANCE) trial were administered a health-related quality-of-life questionnaire, the three-level EuroQol five-dimensional questionnaire (EQ-5D-3L), on four occasions over a 5-year period. We used two-way fixed-effects longitudinal regression models to investigate the impact of incident diabetes complications (stroke, heart failure, myocardial infarction, ischemic heart disease, renal failure, blindness, and amputation) on EQ-5D-3L utility score (where 1 = perfect health), while controlling for characteristics of individuals that do not vary over time. RESULTS The effect of having any one of the seven complications was to reduce the EQ-5D-3L utility score by 0.054 (95% confidence interval 0.044-0.064), and this was not significantly affected by baseline age, sex, economic region, or the value set used to derive utilities. The complication with the largest disutility was amputation (0.122), followed by stroke (0.099), blindness (0.083), renal failure (0.049), heart failure (0.045), and myocardial infarction (0.026). Ischemic heart disease did not significantly reduce the utility score. Quality of life also declined with elapsed time-by an average of 0.006 per year, in addition to the effect of complications. CONCLUSIONS Common complications significantly reduce health-related quality of life. Utility scores derived from the EQ-5D-3L provide a potential measure that can be used to summarize patient-reported outcomes and inform health economic models. Prevention of complications is critical to reduce the progressive burden of declining quality of life for people with diabetes.