Healthy together Victoria and childhood obesity-a methodology for measuring changes in childhood obesity in response to a community-based, whole of system cluster randomized control trial

BACKGROUND: Healthy Together Victoria (HTV) - a complex 'whole of system' intervention, including an embedded cluster randomized control trial, to reduce chronic disease by addressing risk factors (physical inactivity, poor diet quality, smoking and harmful alcohol use) among children and adults in selected communities in Victoria, Australia (Healthy Together Communities).

OBJECTIVES: To describe the methodology for: 1) assessing changes in the prevalence of measured childhood obesity and associated risks between primary and secondary school students in HTV communities, compared with comparison communities; and 2) assessing community-level system changes that influence childhood obesity in HTC and comparison communities.

METHODS: Twenty-four geographically bounded areas were randomized to either prevention or comparison (2012). A repeat cross-sectional study utilising opt-out consent will collect objectively measured height, weight, waist and self-reported behavioral data among primary [Grade 4 (aged 9-10y) and Grade 6 (aged 11-12y)] and secondary [Grade 8 (aged 13-14y) and Grade 10 (aged 15-16y)] school students (2014 to 2018). Relationships between measured childhood obesity and system causes, as defined in the Foresight obesity systems map, will be assessed using a range of routine and customised data.

CONCLUSION: This research methodology describes the beginnings of a state-wide childhood obesity monitoring system that can evolve to regularly inform progress on reducing obesity, and situate these changes in the context of broader community-level system change.

Sleep duration and risk of obesity among a sample of Victorian school children

BACKGROUND: Insufficient sleep is potentially an important modifiable risk factor for obesity and poor physical activity and sedentary behaviours among children. However, inconsistencies across studies highlight the need for more objective measures. This paper examines the relationship between sleep duration and objectively measured physical activity, sedentary time and weight status, among a sample of Victorian Primary School children.

METHODS: A sub-sample of 298 grades four (n = 157) and six (n = 132) Victorian primary school children (aged 9.2-13.2 years) with complete accelerometry and anthropometry data, from 39 schools, were taken from a pilot study of a larger state based cluster randomized control trial in 2013. Data comprised: researcher measured height and weight; accelerometry derived physical activity and sedentary time; and self-reported sleep duration and hypothesised confounding factors (e.g. age, gender and environmental factors).

RESULTS: Compared with sufficient sleepers (67 %), those with insufficient sleep (<10 hrs/day) were significantly more likely to be overweight (OR 1.97, 95 % CI:1.11-3.48) or obese (OR 2.43, 95 % CI:1.26-4.71). No association between sleep and objectively measured physical activity levels or sedentary time was found.

CONCLUSION: The strong positive relationship between weight status and sleep deprivation merits further research though PA and sedentary time do not seem to be involved in the relationship. Strategies to improve sleep duration may help obesity prevention initiatives in the future.

Empowering primary care to tackle the obesity epidemic: the Counterweight Programme

Subjects: Obese patients (body mass index greater than or equal to30 kg/m2) or BMIgreater than or equal to28 kg/m2 with obesity-related comorbidities in 80 general practices.

Intervention: The model consists of four phases: (1) audit and project development, (2) practice training and support, (3) nurse-led patient intervention, and (4) evaluation. The intervention programme used evidence-based pathways, which included strategies to empower clinicians and patients. Weight Management Advisers who are specialist obesity dietitians facilitated programme implementation.

Main outcome measures: Proportion of practices trained and recruiting patients, and weight change at 12 months.

Results: By March 2004, 58 of the 62 (93.5%) intervention practices had been trained, 47 (75.8%) practices were active in implementing the model and 1549 patients had been recruited. At 12 months, 33% of patients achieved a clinically meaningful weight loss of 5% or more. A total of 49% of patients were classed as 'completers' in that they attended the requisite number of appointments in 3, 6 and 12 months. 'Completers' achieved more successful weight loss with 40% achieving a weight loss of 5% or more at 12 months.

Conclusion: The Counterweight programme provides a promising model to improve the management of obesity in primary care.

Sponsorship: Educational grant-in-aid from Roche Products Ltd.

Obesity impacts on general practice appointments

Objective: To quantify the impact of obesity on the number of visits to both primary and secondary care teams.

Research Methods and Procedures: The adult populations of 80 general practices throughout the United Kingdom were classified according to their BMI. We undertook a cross-sectional survey of computer-generated and handwritten records of 6150 obese people (BMI ≥ 30 kg/m2) and 1150 normal weight (BMI = 18.5 to 24.9 kg/m2) control subjects over an 18-month retrospective period.

Results: Obese patients made significantly more visits to the general practitioner (GP), practice nurse (PN), and hospital outpatient units than normal weight patients (all p < 0.001), and they were admitted to the hospital more often (p = 0.034). For both GP and PN visits, the relationship remained after adjusting for age, sex, social deprivation category, country, and number of comorbidities. Among obese patients, there was an increasing relationship between frequent GP visits (at least four appointments) and greater BMI, which remained significant after adjustment had been made for age, sex, deprivation, country, and number of comorbidities.

Discussion: The human resource burden to general practice is significantly higher in the obese population than in the normal weight population, even when adjusted for confounding factors. The increase in prevalence of obesity will continue to put pressure on GP and PN time unless appropriate action is taken.

The impact of obesity on drug prescribing in primary care

Background

Healthcare costs attributable to obesity have previously involved estimations based on costs of diseases commonly considered as having obesity as an underlying factor.

Aim

To quantify the impact of obesity on total primary care drug prescribing.

Design of study

Review of computer generated and handwritten prescriptions to determine total prescribing volume for all drug classes.

Setting

Twenty-three general practice surgeries in the UK.

Method

Stratified random selection of 1150 patients who were obese (body mass index [BMI]>30 kg/m2) and 1150 age- and sex-matched controls of normal weight (BMI 18.5–<25 kg/m2). Retrospective review of medical records over an 18-month period.

Results

A higher percentage of patients who were obese, compared with those of normal weight, were prescribed at least one drug in the following disease categories: cardiovascular (36% versus 20%), central nervous system (46% versus 35%), endocrine (26% versus 18%), and musculoskeletal and joint disease (30% versus 22%). All of these categories had a P-value of <0.001. Other categories, such as gastrointestinal (24% versus 18%), infections (42% versus 35%), skin (24% versus 19%) had a P-value of <0.01, while respiratory diseases (18% versus 21%) had a P-value of <0.05. Total prescribing volume was significantly higher for the group with obesity and was increased in the region of two- to fourfold in a wide range of prescribing categories: ulcer healing drugs, lipid regulators, β-adrenoreceptor drugs, drugs affecting the rennin angiotensin system, calcium channel blockers, antibacterial drugs, sulphonylureas, biguanides, non-steroidal anti-inflammatories (NSAIDs) (P<0.001) and fibrates, angiotensin II antagonists, and thyroid drugs (P<0.05). The main impact on prescribing volumes is from numbers of patients treated, although in some areas there is an effect from greater dosage or longer treatment in those who are obese including calcium channel blockers, antihistamines, hypnotics, drugs used in the treatment of nausea and vertigo, biguanides, and NSAIDs (P<0.05) reflected in significantly increased defined daily dose prescribing.

Current approaches to obesity management in UK Primary Care: the Counterweight Programme

Background/Aims Primary care is expected to develop strategies to manage obese patients as part of coronary heart disease and diabetes national service frameworks. Little is known about current management practices for obesity in this setting. The aim of this study is to examine current approaches to obesity management in UK primary care and to identify potential gaps in care.

Method A total of 141 general practitioners (GPs) and 66 practice nurses (PNs) from 40 primary care practices participated in structured interviews to examine clinician self-reported approaches to obesity management. Medical records were also reviewed for 100 randomly selected obese patients from each practice [body mass index (BMI) ≥30 kg m−2, n = 4000] to review rates of diet counselling, dietetic or obesity centre referrals, and use of anti-obesity medication. Computerized medical records for the total practice population (n = 206 341, 18–75 years) were searched to examine the proportion of patients with a weight/BMI ever recorded.

Results Eighty-three per cent of GPs and 97% of PNs reported that they would raise weight as an issue with obese patients (P < 0.01). Few GPs (15%) reported spending up to 10 min in a consultation discussing weight-related issues, compared with PNs (76%; P < 0.001). Over 18 months, practice-based diet counselling (20%), dietetic (4%) and obesity centre (1%) referrals, and any anti-obesity medication (2%) were recorded. BMI was recorded for 64.2% of patients and apparent prevalence of obesity was less than expected.

Conclusion Obesity is under-recognized in primary care even in these 40 practices with an interest in weight management. Weight management appears to be based on brief opportunistic intervention undertaken mainly by PNs. While clinicians report the use of external sources of support, few patients are referred, with practice-based counselling being the most common intervention.

Child obesity prevention in primary health care: the role of practice nurses

Aim

Overweight and obesity affects approximately 20% of Australian pre-schoolers. The general practice nurse (PN) workforce has increased in recent years; however, little is known of PN capacity and potential to provide routine advice for the prevention of child obesity. This mixed methods pilot study aims to explore the current practices, attitudes, confidence and training needs of Australian PNs surrounding child obesity prevention in the general practice setting.

Methods

PNs from three Divisions of General Practice in New South Wales were invited to complete a questionnaire investigating PN roles, attitudes and practices in preventive care with a focus on child obesity. A total of 59 questionnaires were returned (response rate 22%). Semi-structured qualitative interviews were also conducted with a subsample of PNs (n = 10).

Results

Questionnaire respondent demographics were similar to that of national PN data. PNs described preventive work as enjoyable despite some perceived barriers including lack of confidence. Number of years working in general practice did not appear to strongly influence nurses' perceived barriers. Seventy per cent of PNs were interested in being more involved in conducting child health checks in practice, and 85% expressed an interest in taking part in child obesity prevention training.

Conclusions

Findings from this pilot study suggest that PNs are interested in prevention of child obesity despite barriers to practice and low confidence levels. More research is needed to determine the effect of training on PN confidence and behaviours in providing routine healthy life-style messages for the prevention of child obesity.

Evaluation of the Counterweight Programme for obesity management in primary care: a starting point for continuous improvement

Background Evaluation for obesity management in primary care is limited, and successful outcomes are from intensive clinical trials in hospital settings.

Aim To determine to what extent measures of success seen in intensive clinical trials can be achieved in routine primary care. Primary outcome measures were weight change and percentage of patients achieving ≤5% loss at 12 and 24 months.

Design of study Prospective evaluation of a new continuous improvement model for weight management in primary care.

Setting Primary care, UK.

Method Primary care practice nurses from 65 UK general practices delivered interventions to 1906 patients with body mass index (BMI) ≥30 kg/m2 or ≥28 kg/m2 with obesity-related comorbidities.

Results Mean baseline weight was 101.2 kg (BMI 37.1 kg/m2); 25% of patients had BMI ≥40 kg/m2 and 74% had ≥1 major obesity-related comorbidity. At final data capture 1419 patients were in the programme for ≥12 months, and 825 for ≥24 months. Mean weight change in those who attended and had data at 12 months (n = 642) was −3.0 kg (95% CI = −3.5 to −2.4 kg) and at 24 months (n = 357) was −2.3 kg (95% CI = −3.2 to −1.4 kg). Among attenders at specific time-points, 30.7% had maintained weight loss of ≥5% at 12 months, and 31.9% at 24 months. A total of 761 (54%) of all 1419 patients who had been enrolled in the programme for >12 months provided data at or beyond 12 months.

Conclusion This intervention achieves and maintains clinically valuable weight loss within routine primary care.

Research to practice: application of an evidence building framework to a childhood obesity prevention initiative in New South Wales, Australia

Issue addressed: Building evidence-based health promotion programs involves a number of steps. This paper aims to develop a set of criteria for assessing the evidence available according to a five-stage evidence-building framework, and apply these criteria to current child obesity prevention programs in NSW to determine the usefulness of the framework in identifying gaps in evidence and opportunities for future research and evaluation. Methods: A set of scoring criteria were developed for application within the five stages of an 'evidence-building' framework: problem definition, solution generation, intervention testing (efficacy), intervention replication, and dissemination research. The research evidence surrounding the 10 childhood obesity prevention programs planned for state-wide implementation in the New South Wales Healthy Children Initiative (HCI) was identified and examined using these criteria within the framework. Results: The evidence for the component programs of the HCI is at different stages of development. While problem definition and, to a lesser extent, solution generation was thoroughly addressed across all programs, there were a number of evidence gaps, indicating research opportunities for efficacy testing and intervention replication across a variety of settings and populations. Conclusions: The five-stage evidence-building framework helped identify important research and evaluation opportunities that could improve health promotion practice in NSW. More work is needed to determine the validity and reliability of the criteria for rating the extent and quality of the evidence for each stage.