Catherine R. Chittleborough

How valid are self-reported height and weight? A comparison between CATI self-report and clinic measurements using a large cohort study

Objective: To examine the relationship between self‐reported and clinical measurements for height and weight in adults aged 18 years and over and to determine the bias associated with using household telephone surveys.

The North West Adelaide Health Study: detailed methods and baseline segmentation of a cohort for selected chronic diseases

The North West Adelaide Health Study is a population-based biomedical cohort study investigating the prevalence of a number of chronic conditions and health-related risk factors along a continuum. This methodology may assist with evidence-based decisions for health policy makers and planners, and inform health professionals who are involved in chronic disease prevention and management, by providing a better description of people at risk of developing or already diagnosed with selected chronic conditions for more accurate targeting groups for health gain and improved health outcomes. Longitudinal data will provide information on progression of chronic conditions and allow description of those who move forward and back along the continuum over time. Detailed methods are provided regarding the random recruitment and examination of a representative sample of participants (n = 4060), including the rationale for various processes and valuable lessons learnt. Self-reported and biomedical data were obtained on risk factors (smoking, alcohol consumption, physical activity, family history, body mass index, blood pressure, cholesterol) and chronic conditions (asthma, chronic obstructive pulmonary disease, diabetes) to classify participants according to their status along a continuum. Segmenting this population sample along a continuum showed that 71.5% had at least one risk factor for developing asthma, chronic obstructive pulmonary disease or diabetes. Almost one-fifth (18.8%) had been previously diagnosed with at least one of these chronic conditions, and an additional 3.9% had at least one of these conditions but had not been diagnosed. This paper provides a novel opportunity to examine how a cohort study was born. It presents detailed methodology behind the selection, recruitment and examination of a cohort and how participants with selected chronic conditions can be segmented along a continuum that may assist with health promotion and health services planning.

Effect of intervention aimed at increasing physical activity, reducing sedentary behaviour, and increasing fruit and vegetable consumption in children: Active for Life Year 5 (AFLY5) school based cluster randomised controlled trial

Objective To investigate the effectiveness of a school based intervention to increase physical activity, reduce sedentary behaviour, and increase fruit and vegetable consumption in children. Design Cluster randomised controlled trial. Setting 60 primary schools in the south west of England. Participants Primary school children who were in school year 4 (age 8-9 years) at recruitment and baseline assessment, in year 5 during the intervention, and at the end of year 5 (age 9-10) at follow-up assessment. Intervention The Active for Life Year 5 (AFLY5) intervention consisted of teacher training, provision of lesson and child-parent interactive homework plans, all materials required for lessons and homework, and written materials for school newsletters and parents. The intervention was delivered when children were in school year 5 (age 9-10 years). Schools allocated to control received standard teaching. Main outcome measures The pre-specified primary outcomes were accelerometer assessed minutes of moderate to vigorous physical activity per day, accelerometer assessed minutes of sedentary behaviour per day, and reported daily consumption of servings of fruit and vegetables. Results 60 schools with more than 2221 children were recruited; valid data were available for fruit and vegetable consumption for 2121 children, for accelerometer assessed physical activity and sedentary behaviour for 1252 children, and for secondary outcomes for between 1825 and 2212 children for the main analyses. None of the three primary outcomes differed between children in schools allocated to the AFLY5 intervention and those allocated to the control group. The difference in means comparing the intervention group with the control group was –1.35 (95% confidence interval –5.29 to 2.59) minutes per day for moderate to vigorous physical activity, –0.11 (–9.71 to 9.49) minutes per day for sedentary behaviour, and 0.08 (–0.12 to 0.28) servings per day for fruit and vegetable consumption. The intervention was effective for three out of nine of the secondary outcomes after multiple testing was taken into account: self reported time spent in screen viewing at the weekend (–21 (–37 to –4) minutes per day), self reported servings of snacks per day (–0.22 (–0.38 to –0.05)), and servings of high energy drinks per day (–0.26 (–0.43 to –0.10)) were all reduced. Results from a series of sensitivity analyses testing different assumptions about missing data and from per protocol analyses produced similar results. Conclusion The findings suggest that the AFLY5 school based intervention is not effective at increasing levels of physical activity, decreasing sedentary behaviour, and increasing fruit and vegetable consumption in primary school children. Change in these activities may require more intensive behavioural interventions with children or upstream interventions at the family and societal level, as well as at the school environment level. These findings have relevance for researchers, policy makers, public health practitioners, and doctors who are involved in health promotion, policy making, and commissioning services. Trial registration Current Controlled Trials ISRCTN50133740.

Inequalities in child healthy development: Some challenges for effective implementation

0277-9536/

Underdiagnosed asthma in South Australia

e see front matter 2010 Elsevier Ltd. doi:10.1016/j.socscimed.2010.07.008 The reports Closing the Gap in a Generation (CSDH, 2009) and Fair Society, Healthy Lives (The Marmot Review, 2010) are important for several reasons. First, they provide a framework of broad policy recommendations on which to base efforts to reduce both social and health inequalities. Second, they provide a clarion call for action to develop integrated policy responses that are both deep and broad, and span portfolios and jurisdictions. Third, they synthesize over 30 years of accumulated research on social factors relevant to health inequalities. Many readers of Social Science & Medicine helped generate the more than 1000 references in these documents. The current reports are not the first of their kind (Acheson, 1998; Townsend & Davidson, 1982) and they have their own particular histories as products of public, intellectual and political recognition of the importance of acting to reduce health inequalities. Our purpose here is to reflect on the implications of the reports, and while they are wide-ranging in scope, our comments are limited to aspects dealing with inequalities in early childhood development (ECD). Improving healthy development of children under 5 by giving them the best start in life is the number one recommendation of the UK report (The Marmot Review, 2010) and features prominently in the WHO Commission report (CSDH, 2009). These reports recommend building on preand post-natal programs that ensure child survival and better health (Victora, 2009), and extending interventions to include integrated programs of social, emotional, language, behavioural and cognitive

Effects of area deprivation on health risks and outcomes: a multilevel, cross-sectional, Australian population study

Background: The prevalence of undiagnosed asthma in the general population and the clinical and demographic characteristics of these patients compared with those with diagnosed asthma are unclear. Methods: The North West Adelaide Health Survey (NWAHS) is a population household interview survey of adults (age >18 years) in the north western suburbs of Adelaide, South Australia (regional population 0.6 million). Data obtained were weighted to the closest census data to provide population representative estimates. Positive answers to: “Have you ever had asthma?”; “Has it been confirmed by a doctor?”; ”Do you still have asthma?” determined current physician diagnosed asthma. A positive bronchodilator response on spirometric testing according to ATS criteria without a physician’s diagnosis determined undiagnosed asthma. Other measures included the SF-12 health survey questionnaire, the Selim index of severity of chronic lung disease, skin allergy tests, and demographic data. Results: Of the 3422 individuals interviewed, 2523 (74%) agreed to participate in the clinical assessment. Of these, 292 (11.6%) had asthma, 236 (9.3%) with a doctor’s diagnosis of asthma and 56 (2.3%) with undiagnosed asthma defined on spirometric criteria; thus, 19.2% of the total asthma group were undiagnosed. Those undiagnosed were more likely (p<0.05) to be >40 years old, on government benefits, with an income <AUD

A life-course approach to measuring socioeconomic position in population health surveillance systems

40 000. Symptom frequency was similar in the two asthma groups, but mean spirometric values were lower in the undiagnosed group (p<0.05) while positive skin allergy tests were more common in the diagnosed group (p<0.05). SF-12 component summary scores were significantly lower in both asthma groups than in the non-asthma population. Undiagnosed asthma was frequent in men and in those aged >65 years. Health service use over the previous year was similar for both asthma groups. Conclusion: Undiagnosed asthma is common among the Australian population, with a similar clinical spectrum to those with diagnosed asthma.

Do people with risky behaviours participate in biomedical cohort studies

Objectives:Our aim was to examine the effect of local area socio-economic disadvantage after accounting for individual socio-economic status (SES), and to determine if these differ between various health and risk factor variables.Methods:The North West Adelaide Health Study (NWAHS) is a biomedical representative population study of adults. The Index of Relative Socio-Economic Disadvantage (IRSD), produced from the Australian Bureau of Statistics (ABS) Census data at the level of Collector Districts (200 dwellings) was used as an indicator of local area disadvantage. Multi-level modeling techniques examined the effects of IRSD level on a variety of health outcomes and risk factors, after accounting for individual socio-economic factors.Results:Significant, independent associations were seen between IRSD and obesity, smoking, and health-related quality of life, with 5 % to 7.2 % of the variance located at the neighborhood level. No independent associations were seen between IRSD and estimated cardiovascular disease risk, diabetes, physical activity, or at-risk alcohol use.Conclusions:Aggregated area-level characteristics make modest, but significant independent contributions to smoking, obesity and quality of life, but not for other health outcomes.

Independent Association of HbA1c and Incident Cardiovascular Disease in People Without Diabetes

Measuring socioeconomic position (SEP) in population chronic disease and risk factor surveillance systems is essential for monitoring socioeconomic inequalities in health over time. Life-course measures are an innovative way to supplement other SEP indicators in surveillance systems. A literature review examined the indicators of early-life SEP that could potentially be used in population health surveillance systems. The criteria of validity, relevance, reliability and deconstruction were used to determine the value of potential indicators. Early-life SEP indicators used in cross-sectional and longitudinal studies included education level, income, occupation, living conditions, family structure and residential mobility. Indicators of early-life SEP should be used in routine population health surveillance to monitor trends in the health and SEP of populations over time, and to analyse long-term effects of policies on the changing health of populations. However, these indicators need to be feasible to measure retrospectively, and relevant to the historical, geographical and sociocultural context in which the surveillance system is operating.

Obesity in South Australian adults--prevalence, projections and generational assessment over 13 years.

BackgroundAnalysis was undertaken on data from randomly selected participants of a bio-medical cohort study to assess representativeness. The research hypotheses was that there was no difference in participation and non-participations in terms of health-related indicators (smoking, alcohol use, body mass index, physical activity, blood pressure and cholesterol readings and overall health status) and selected socio-demographics (age, sex, area of residence, education level, marital status and work status).MethodsRandomly selected adults were recruited into a bio-medical representative cohort study based in the north western suburbs of the capital of South Australia – Adealide. Comparison data was obtained from cross-sectional surveys of randomly selected adults in the same age range and in the same region. The cohort participants were 4060 randomly selected adults (18+ years).ResultsThere were no major differences between study participants and the comparison population in terms of current smoking status, body mass index, physical activity, overall health status and proportions with current high blood pressure and cholesterol readings. Significantly more people who reported a medium to very high alcohol risk participated in the study. There were some demographic differences with study participants more likely to be in the middle level of household income and education level.ConclusionPeople with risky behaviours participated in this health study in the same proportions as people without these risk factors.