A whole-of-population study of term and post-term gestational age at birth and children's development.

OBJECTIVE: To examine the risk of poor child development according to week of gestation at birth, among children born ≥ 37 weeks' gestation. DESIGN: Population-based study using linked data (n = 12,601). SETTING: South Australia. POPULATION: All births ≥ 37 weeks' gestation. METHODS: Relative risks of developmental vulnerability for each week of gestation were calculated with adjustment for confounders and addressing missing information. MAIN OUTCOME MEASURES: Child development was documented by teachers during a national census of children attending their first year of school in 2009, using the Australian Early Development Index (AEDI). Children scoring in the lowest 10% of the AEDI were categorised as developmentally vulnerable. RESULTS: The percentage of children vulnerable on one or more AEDI domains for the following gestational ages 37, 38, 39, 40, 41, 42-45 weeks was 24.8, 22.3, 20.6, 20.0, 20.4 and 24.2, respectively. Compared with children born at 40 weeks, the adjusted relative risks [(95% confidence interval (CI)] for vulnerability on ≥ 1 AEDI domain were; 37 weeks 1.13 (0.99-1.28), 38 weeks 1.05 (0.96-1.15), 39 weeks 1.02 (0.94-1.12), 41 weeks 1.00 (0.90-1.11) and 42-45 weeks 1.20 (0.84-1.72). CONCLUSIONS: Children born at 40-41 weeks' gestation may have the lowest risk of developmental vulnerability at school entry, reinforcing the importance of term birth in perinatal care. Early term or post-term gestational age at birth can help clinicians, teachers and parents recognise children with potential developmental vulnerabilities at school entry.

Are trajectories of self-regulation abilities from ages 2-3 to 6-7 associated with academic achievement in the early school years?

BACKGROUND: The aim of this study was to estimate the association between two key aspects of self-regulation, 'task attentiveness' and 'emotional regulation' assessed from ages 2-3 to 6-7 years, and academic achievement when children were aged 6-7 years. METHODS: Participants (n = 3410) were children in the Longitudinal Study of Australian Children. Parents rated children's task attentiveness and emotional regulation abilities when children were aged 2-3, 4-5 and 6-7. Academic achievement was assessed using the Academic Rating Scale completed by teachers. Linear regression models were used to estimate the association between developmental trajectories (i.e. rate of change per year) of task attentiveness and emotional regulation, and academic achievement at 6-7 years. RESULTS: Improvements in task attentiveness between 2-3 and 6-7 years, adjusted for baseline levels of task attentiveness, child and family confounders, and children's receptive vocabulary and non-verbal reasoning skills at age 6-7 were associated with greater teacher-rated literacy [B = 0.05, 95% confidence interval (CI) = 0.04-0.06] and maths achievement (B = 0.04, 95% CI = 0.03-0.06) at 6-7 years. Improvements in emotional regulation, adjusting for baseline levels and covariates, were also associated with better teacher-rated literacy (B = 0.02, 95% CI = 0.01-0.04) but not with maths achievement (B = 0.01, 95% CI = -0.01-0.02) at 6-7 years. For literacy, improvements in task attentiveness had a stronger association with achievement at 6-7 years than improvements in emotional regulation. CONCLUSIONS: Our study shows that improved trajectories of task attentiveness from ages 2-3 to 6-7 years are associated with improved literacy and maths achievement during the early school years. Trajectories of improving emotional regulation showed smaller effects on academic outcomes. Results suggest that interventions that improve task attentiveness when children are aged 2-3 to 6-7 years have the potential to improve literacy and maths achievement during the early school years.

Missing data on retrospective recall of early-life socio-economic position in surveillance systems: an additional disadvantage?

OBJECTIVES: Inclusion of information on early-life socio-economic position (SEP) in population chronic disease and risk factor surveillance systems enables better monitoring of effects of policies and interventions on health inequities and intergenerational disadvantage. Examining data quality, in terms of item non-response, informs choices about which indicators of early-life SEP to include in surveillance questionnaires. This study examined differences in recall of indicators of early-life SEP between different socio-economic groups. STUDY DESIGN: Cross-sectional population survey. METHODS: A representative population of people aged 18 years and over living in South Australia (n=2999) was selected at random from the electronic white pages, and a computer-assisted telephone interview was administered. RESULTS: Respondents with missing data on early-life SEP indicators were disadvantaged in terms of current SEP compared with those who provided this information. Among all respondents, the highest proportions of missing data were observed for maternal grandfather's main occupation (27.2%), and mother's (20.1%) and father's (19.6%) highest level of education. Family structure, housing tenure and family financial situation when the respondent was 10 years old, and mother's and father's main occupation were the indicators of early-life SEP that performed best in terms of recall. CONCLUSIONS: The differential response to early-life SEP questions according to current circumstances has implications for chronic disease surveillance examining the life-course impact of socio-economic disadvantage.

The increasing prevalence of diabetes in South Australia: the relationship with population ageing and obesity.

OBJECTIVES: To use representative population surveillance data to monitor and project changes in the prevalence of diabetes for different age and body mass index (BMI) groups. STUDY DESIGN: Representative, annual, face-to-face South Australian Health Omnibus Surveys, 1991-2003 (n=3000 per year). METHODS: Trends in self-reported diabetes prevalence by age group and BMI were examined. Separate projections were made on the basis of predicted changes in population demography and diabetes prevalence. RESULTS: The age-sex standardized absolute prevalence of self-reported diabetes among people aged 15 years and over increased from 3.5% in 1991 to 6.7% in 2003. If this current trend continues, the prevalence is expected to increase to 10.5% by 2016. The prevalence of diabetes was significantly higher among those classified as obese (6.5% in 1991 to 12.2% in 2003) than those with normal BMI. The greatest relative percentage increase in prevalence between 1991 and 2003 (169%) was seen among people aged 15-39 years. Taking both age group and BMI classification into account, the greatest relative percentage increases over this time were seen among those with normal BMI aged 60 years or older (148%), and those who were obese and aged less than 60 years (139%). CONCLUSIONS: The prevalence of diabetes and obesity increased significantly between 1991 and 2003. Population ageing and an increase in diabetes prevalence in the future will further increase the burden of diabetes. Future increases in diabetes prevalence are not inevitable, however, if investments are made in public health prevention programmes, particularly those addressing obesity.

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

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.

Underdiagnosed asthma in South Australia.

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 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.

Multiple respiratory symptoms predict quality of life in chronic lung disease: a population-based study of Australian adults.

STUDY OBJECTIVES: Previous studies have shown that it is possible to improve the health-related quality of life (HRQoL) of chronic lung disease (CLD) patients without a concurrent change in morbidity. A valid CLD index that discriminates between different levels of CLD severity and is associated with HRQoL status is an important tool for primary care settings. In this study a symptom-based CLD index was assessed for its validity and relationship with HRQoL in a representative Australian population sample. The study also measured the prevalence of self-reported CLD. DESIGN: Representative population survey of adults aged 18 years and over using a multistage, systematic, clustered area sample. SETTING: Metropolitan Adelaide and country centres in South Australia with a population of over 1000 persons. PARTICIPANTS: Three hundred twenty-nine adults with CLD identified through a representative population survey of 3010 South Australians. MEASUREMENTS AND RESULTS: The CLD index and the SF-36 were administered to participants to assess the association between each subscale of the CLD index with each HRQoL scale. The CLD index was also used to assess the prevalence of CLD and the distribution of severity in self-reported CLD in the South Australian population. Each symptom sub-scale of the CLD index was significantly correlated with all scales of the SF-36. The prevalence of CLD as measured by the CLD index was 7.7% (mild), 2.2% (moderate) and 1.0% (severe). CONCLUSIONS: In the Australian context the CLD index is a reliable patient interview instrument that can be used to assess the effects of CLD on general HRQoL, improve assessment, and lead to interventions for physicians and their patients.