Opal program sa

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This paper aims to determine the effectiveness of a South Australian community-based, multi-setting, multi-strategy intervention, OPAL Obesity Prevention and Lifestyle , in increasing healthy weight prevalence in 9 to year-olds. A quasi-experimental repeated cross-sectional design was employed. Consenting children from primary schools 20 intervention communities, INT; 20 matched comparison communities, COMP completed self-report questionnaires on diet, activity and screen time behaviours.

A multilevel mixed-effects model, accounting for clustering in schools, was implemented to determine intervention effect. Sequential Bonferroni adjustment was used to allow for multiple comparisons of the secondary outcomes. At baseline and final, respectively, and children completed questionnaires and and had anthropometric measures taken.

There were also no significant differences between groups at final for behavioural outcomes. Long-term, flexible community-based program evaluation approaches are required. Peer Review reports. Childhood obesity is a serious public health concern worldwide [ 1 ]. Specifically, with evidence of a greater burden of obesity in the most disadvantaged in developed countries [ 4 ], obesity-prevention strategies targeting socio-economically disadvantaged communities are required.

Despite childhood obesity prevention programs to date having shown, in general, moderate effectiveness in reducing adiposity [ 5 ], innovative, population-level approaches that are more effective, flexible, economical and, importantly, sustainable are urgently needed [ 6 , 7 ]. Comprehensive community-based obesity prevention interventions offer promise due to their focus on the broader social, cultural and environmental contexts rather than individual behaviour change [ 8 , 9 , 10 , 11 ] and their potential for sustainability and scalability [ 7 , 9 , 12 , 13 ].

Such programs have shown positive impacts on anthropometric outcomes in pre-schoolers [ 15 ], primary school children [ 6 , 17 ] and adolescents [ 8 ]. Modest improvements in diet and activity behaviours have also been observed [ 7 , 15 , 17 , 18 , 19 ]. Together, these findings demonstrate that community-based interventions can be effective [ 6 ].

The EWBA Community Programs — funded by, and based in, health services [ 16 , 20 ] and engaging primarily in pre-schools and schools led the way for community-based obesity prevention in South Australia. OPAL was a systems-wide, multi-strategy, community-based childhood obesity prevention program funded by local, State and Australian governments and based in local government. The OPAL program selected disadvantaged communities and was informed by social marketing, community development and social ecological systems theory.

The latter is a framework that relates to the multiple environments within which an individual interacts, operationalised in OPAL as individuals, families, organisations, communities and environments [ 21 , 22 ]. Evidence on the effectiveness of community-based, capacity-building approaches such as OPAL are needed [ 7 ].

To determine the effectiveness of the OPAL approach, a comprehensive evaluation framework was developed [ 22 , 23 ]. Secondary outcomes were eating and activity-related behaviours, attitudes and environments. OPAL was implemented in 20 lower socio-economic status SES communities not necessarily geographically separate in South Australia Index of Relative Socio-economic Disadvantage IRSD [ 27 ], a measure of socio-economic status based on income- and education-related measures, was utilised and scores lower than , i.

With guidance from a Scientific Advisory Committee, the staff used a community development approach to develop and deliver annual social marketing theme messages and goal-related interventions to improve: 1 dietary intake and 2 physical activity.

The intended mechanisms for reducing the consumption of energy-dense, nutrient-poor items and increasing healthy eating were to increase availability of healthy food in the home and at outlets and improving healthy food production, access and distribution [ 28 ].

The mechanisms for increasing physical activity and reducing sedentariness were to increase active travel, active leisure participation and use of parks and places [ 20 ]. A suite of centrally coordinated social marketing materials was produced and complemented by Council-led activity with community stakeholders to create structural, program, educational and policy changes in support of the themes and goals [ 20 ].

Examples of activities introduced in communities are; community gardens, installation of drinking water fountains in public places, extension of bike paths, improved facilities in sporting clubs, family fun days, and education and workplaces that promote healthy eating and physical activity programs [ 20 ]. A comprehensive evaluation framework reported in detail elsewhere [ 21 , 22 , 26 ] was developed to determine the effectiveness of the OPAL program. An internal evaluation manager oversaw the evaluation and this component of the evaluation was contracted to a local university for their high-level expertise and independence [ 21 ].

Communities were the primary evaluation unit and a partial stepped wedge design was adopted. However, due to significant budget cuts to the OPAL program and evaluation on two occasions, limits were placed on the planned scale and scope of the final evaluation [ 21 ].

Phase 1 OPAL intervention communities ran for a period of 5 years while Phase 2 ran for a shortened period of 4. This paper reports the 9—year-old survey and measures for phase 1 and 2 communities at baseline and final Table 1.

The data collection methods from baseline are reported elsewhere [ 25 ]. An introductory letter was sent to primary school Principals from the Ministers for Health and Ageing, and Education and Child Development outlining the importance of the evaluation, seeking school-level consent and providing an information pack containing an information letter and brochure, checklist and participation form.

Consenting children from INT and COMP provided data through self-report questionnaires completed online or in hard copy and anthropometric measures completed on the same day as the questionnaires obtained by trained data collectors details provided below.

Socio-demographic data including age, sex, and postcode or town of residence were collected via child-completed questionnaire. School-level demographic data were also collected. Area of residence was classified as urban or rural, based on the location of the school the child attended and according to the Australian Bureau of Statistics ABS remoteness areas for Australia [ 30 ], where major cities of Australia were classified as urban; and inner and outer regional areas classified as rural.

ICSEA was created by the Australian Curriculum, Assessment and Reporting Authority ACARA from four characteristics: 1 socio-economic characteristics of the census collection districts where children in a school live, 2 whether a school is in a regional or remote area, 3 proportion of children from a language background other than English, and 4 the proportion of Aboriginal children enrolled at the school.

Each consenting child was measured without shoes or heavy outer garments by trained data collectors, in line with the Body Image Guidelines developed and endorsed by the OPAL Scientific Advisory Committee. Data collectors were trained in body image, cultural sensitivities, mandatory reporting and anthropometry; one data collector on the team was required to be a registered teacher.

Height Invicta Stadiometer and weight Tanita BWB portable electronic scales measures were taken by the same data collector on one occasion and final measures determined as the mean of two measures, or the median if three measures were taken in the case that the first two measures differed by more than 0.

Body Mass Index BMI was calculated as weight kg divided by height m squared and converted to age- and sex-specific z-scores using the UK reference data [ 32 ]. Health-related quality of life HRQoL , a multidimensional construct that measures the impact of health or disease on physical and psychosocial functioning [ 35 , 36 ], was measured using the Child Health Utility 9D CHU9D [ 37 , 38 ].

The CHU9D is a generic preference-based HRQoL instrument designed specifically for application within cost utility analyses of health care treatment and preventive programs targeted at young people [ 37 , 38 ]. The CHU9D contains a health state classification system which has nine dimensions: worried, sad, pain, tired, annoyed, schoolwork, sleep, daily routine, ability to join in activities, with five different levels representing increasing levels of severity within each dimension i.

The CHU9D was scored using the newly developed Australian adolescent-specific scoring algorithm [ 45 , 46 ]. The overall HRQoL score derived from a preference-based instrument is called the health state utility and can be used to adjust the life years to calculate the quality adjusted life year QALY.

Photographs of serve sizes were provided to assist estimation. These questions were drawn, where possible, from existing instruments with either proven validity or reliability [ 13 , 47 ] or which have been used in national [ 48 ] or state [ 2 ] surveys in order to provide comparability or benchmarking with OPAL evaluation findings. Vegetable intake referred to all potato, other vegetables and legumes and excluded fried potato classified as a discretionary food [ 49 ].

Fruit intake excluded fruit juice. Children were classified according to whether they met the recommended intake 2 or more serves of fruit and 5 or more serves of vegetables based on the revised food modelling of the Australian Dietary Guidelines [ 49 ].

A serve of each discretionary food was a standard portion or pre-packaged amount e. To estimate the percentage of children meeting the physical activity recommendations i.

Sedentary behaviour was operationalised as screen time, reported to be an acceptable surrogate for overall level of sitting in children [ 54 ]. To estimate the percentage of children meeting the sedentary behaviour guideline i.

The normality assumption was visually checked by frequency histogram and normal Q-Q plot for continuous measurements. The Anderson-Darling test was also performed to test the normality assumption. Given the study sample was not the full sample intended due to no final evaluation of Phase 3 and 4 children, a retrospective power calculation was undertaken. Demographic data were analysed using t-tests or chi-squared tests.

A multivariate multilevel mixed-effects model two-level random slope model was used to analyse outcomes due to the hierarchical structure of the data children nested in schools.

Thus, models were accounted for the clustering in schools using xtmixed for interval scale data - BMI and BMI z-score and xtmelogit for binary outcomes — weight status. Schools were treated as random effects, and main effects were group intervention or comparison , time baseline and final and group x time interaction. Weight status categories were treated as a series of dichotomous outcomes for example healthy weight vs.

Models were adjusted by age as a child level characteristic; continuous variable and ICSEA score as a school level characteristic , as they were statistically significant in the univariate models and clinically important. Unadjusted estimates are also presented. In this paper, the proportion of healthy weight children was considered the primary outcome variable. Exploratory analyses of secondary outcomes i.

A total of per community, 1—20 and 94 per community, 0—14 schools were recruited at baseline and final respectively. At both time points the average SD age of children was Overall, more than one fifth of students at baseline Nearly three-quarters were of healthy weight baseline Table 3 shows the anthropometric details of the sample at each time point.

However, this was no longer significant after adjustment for multiple comparisons. This was no longer significant after adjustment for multiple comparisons. The reduced probability of children with obesity, increased probability of children meeting the discretionary food guideline i. These findings are similar to those reported previously for local community-based initiatives, yet different to interstate and international initiatives.

Long-term evaluation is thus warranted. Despite a relatively improved HRQoL amongst intervention children compared to comparison children. These differential results may be partly explained by the choice of HRQoL instrument. Our findings indicate a more positive impact on HRQOL, with children from intervention communities gaining in health state utility when compared to comparison children, and thus demonstrate the added value of including this outcome measure alongside anthropometric measures to provide evidence on the effectiveness including cost-effectiveness of future child obesity prevention initiatives.

Overall, few positive behaviour changes were observed in this study. There was no intervention effect on the proportion of children meeting the fruit or vegetable guidelines. This is similar to that observed in EWBA [ 19 ] but in contrast to the BAEW program [ 7 ] which resulted in significant improvements in fruit intake at home [ 7 , 18 ] but not on fruit and vegetables brought to school [ 18 ] , and the APPLE program which had a significant effect on fruit, but not vegetable intake [ 17 ].

This may further explain the intervention effect on children meeting the discretionary food guideline i. However, given this was no longer significant after adjustment for multiple comparisons, findings should be interpreted with caution. This is similar to BAEW [ 18 ] and EWBA [ 19 ] which observed no significant differences between groups in TV watching [ 18 ], playing computer games [ 18 ], screen time [ 19 ] and physical activity [ 19 ].

However, intervention children spent more time playing outside after school after the BAEW intervention [ 18 ] compared to less time in comparison children , and had significantly higher accelerometer counts than control children at 1 but not 2 years of the APPLE program [ 17 ].

It is possible that these changes in physical activity in BAEW and APPLE contributed to the significant impacts on BMI z-score observed in these programs, although these studies were not designed, nor powered, to identify whether changes in these components explain changes in anthropometric measures [ 17 ].

Importantly, the self-report measures used in OPAL also required a level of literacy and cognitive ability that was not achievable by some children, evidenced by the removal of implausible results, which may have affected the accuracy of reporting and thus the outcomes observed in this study. Nonetheless, the lack of a consistent effect on dietary fruit, vegetables and discretionary intake and behaviour activity, screen time across several community-based programs OPAL, BAEW, EWBA , despite the inclusion of healthy eating and activity messages, highlights the need for more effective ways of changing consumption towards healthier eating patterns [ 18 ], in particular vegetable consumption, and screen time activities.

There are several possible reasons for these findings. The broader sociocultural-political context within which OPAL operated may have also impacted on the success of the program. Although OPAL was the only program to incorporate social marketing campaigns, this occurred within an environment saturated with multi-national companies advertising energy-dense nutrient-poor foods directly to children [ 60 ].

Politically, in the McCann review of South Australian health promotion services [ 61 ] resulted in substantial cuts to the sector and in , at the Federal level, the government change minimised the prevention and primary health care agendas [ 62 , 63 ]. The effects of the sociocultural-political context on the OPAL program cannot be under-estimated.

Limitations of the evaluation may have also contributed to the lack of intervention effect seen in OPAL. The effect of these limitations on the outcomes observed cannot be underestimated. In addition, the evaluation was also not able to measure the dose of the OPAL intervention received by children and parents within intervention communities, nor how well it was adopted [ 64 ].

However, cross-contamination of OPAL messages between intervention and comparison may have occurred, for example in those children who lived in a comparison community but attended school in an intervention community, or vice versa.

Importantly, measures may not have been robust enough to capture the impact of a multi-component community-based trial. Although questionnaire items assessing behaviours were mostly adapted from validated questionnaires [ 13 , 47 , 53 ], or national [ 48 ] or state [ 2 ] surveys to allow for comparability, the psychometric properties of OPAL questionnaires have not been tested due to budget and time restrictions.

The anthropometric analysis is also limited by the use of dichotomous weight status outcomes in the multilevel mixed effect model which results in a loss of precision and power. To change the feedback I entered in the past, Is it possible? If possible, please let me know how. I would like to change my feedback on Bravoopal Store's item from neutral to positive. I have a set of cufflinks that were made by my grandfather mr alf tyack in He told me that they are black opal.

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