Receptive vocabulary development is a component of the human language system that emerges in the first year of life and is characterised by onward expansion throughout life. Beginning in infancy, children's receptive vocabulary knowledge builds the foundation for oral language and reading skills. The foundations for success at school are built early, hence the public health policy focus on reducing developmental inequalities before children start formal school. The underlying assumption is that children's development is stable, and therefore predictable, over time. This study investigated this assumption in relation to children's receptive vocabulary ability. We investigated the extent to which low receptive vocabulary ability at 4 years was associated with low receptive vocabulary ability at 8 years, and the predictive utility of a multivariate model that included child, maternal and family risk factors measured at 4 years. The study sample comprised 3,847 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Multivariate logistic regression was used to investigate risks for low receptive vocabulary ability from 4–8 years and sensitivity-specificity analysis was used to examine the predictive utility of the multivariate model. In the multivariate model, substantial risk factors for receptive vocabulary delay from 4–8 years, in order of descending magnitude, were low receptive vocabulary ability at 4 years, low maternal education, and low school readiness. Moderate risk factors, in order of descending magnitude, were low maternal parenting consistency, socio-economic area disadvantage, low temperamental persistence, and NESB status. The following risk factors were not significant: One or more siblings, low family income, not reading to the child, high maternal work hours, and Aboriginal or Torres Strait Islander ethnicity. The results of the sensitivity-specificity analysis showed that a well-fitted multivariate model featuring risks of substantive magnitude does not do particularly well in predicting low receptive vocabulary ability from 4–8 years.
Australia, Canada, and New Zealand are all developed nations that are home to Indigenous populations which have historically faced poorer outcomes than their non-Indigenous counterparts on a range of health, social, and economic measures. The past several decades have seen major efforts made to close gaps in health and social determinants of health for Indigenous persons. We ask whether relative progress toward these goals has been achieved.
We used census data for each country to compare outcomes for the cohort aged 25–29 years at each census year 1981–2006 in the domains of education, employment, and income.
The percentage-point gaps between Indigenous and non-Indigenous persons holding a bachelor degree or higher qualification ranged from 6.6% (New Zealand) to 10.9% (Canada) in 1981, and grew wider over the period to range from 19.5% (New Zealand) to 25.2% (Australia) in 2006. The unemployment rate gap ranged from 5.4% (Canada) to 16.9% (Australia) in 1981, and fluctuated over the period to range from 6.6% (Canada) to 11.0% (Australia) in 2006. Median Indigenous income as a proportion of non-Indigenous median income (whereby parity = 100%) ranged from 77.2% (New Zealand) to 45.2% (Australia) in 1981, and improved slightly over the period to range from 80.9% (Canada) to 54.4% (Australia) in 2006.
Australia, Canada, and New Zealand represent nations with some of the highest levels of human development in the world. Relative to their non-Indigenous populations, their Indigenous populations were almost as disadvantaged in 2006 as they were in 1981 in the employment and income domains, and more disadvantaged in the education domain. New approaches for closing gaps in social determinants of health are required if progress on achieving equity is to improve.
Indigenous; Inequality; Social determinants of health; Education; Unemployment; Income
It is well known that children of parents with mental illness are at greater risk of mental illness themselves. However the patterns of familial mental health problems across multiple generations in families are less clear. This study aimed to examine mental health relationships across three generations of Australian families.
Mental health data, along with a range of family demographic information, were collected from over 4600 families in Growing Up in Australia: The Longitudinal Study of Australian Children, a nationally representative cohort study. The social and emotional wellbeing of two cohorts of children aged 4–5 years and 8–9 years was measured using the parent-rated Strengths and Difficulties Questionnaire (SDQ). The mental health of mothers and fathers was measured using the Kessler 6-item K6 scale, and the mental health history of maternal and paternal grandmothers and grandfathers was measured using a dichotomous parent-report item. Multivariate linear regression analyses were used assess the relationships between grandparent and parent mental health and child social and emotional wellbeing at ages 4–5 years and 8–9 years.
Both cohorts of children had greater mental health distress with higher SDQ scores on average if their mother or father had a mental health problem. For children aged 8–9 years, a history of mental health problems in maternal grandmothers and grandfathers was associated with higher SDQ scores in grandchildren, after controlling for maternal and paternal mental health and other family characteristics. For children aged 4–5 years, only a mental health history in paternal grandfathers was associated with higher SDQ scores.
The mental health histories of both parents and grandparents play an important role in the social and emotional wellbeing of young children.
Intergenerational transfer; Mental health; Children and families
Receptive vocabulary develops rapidly in early childhood and builds the foundation for language acquisition and literacy. Variation in receptive vocabulary ability is associated with variation in children's school achievement, and low receptive vocabulary ability is a risk factor for under-achievement at school. In this study, bivariate and multivariate growth curve modelling was used to estimate trajectories of receptive vocabulary development in relation to a wide range of candidate child, maternal and family level influences on receptive vocabulary development from 4–8 years. The study sample comprised 4332 children from the first nationally representative Longitudinal Study of Australian Children (LSAC). Predictors were modeled as risk variables with the lowest level of risk as the reference category. In the multivariate model, risks for receptive vocabulary delay at 4 years, in order of magnitude, were: Maternal Non- English Speaking Background (NESB), low school readiness, child not read to at home, four or more siblings, low family income, low birthweight, low maternal education, maternal mental health distress, low maternal parenting consistency, and high child temperament reactivity. None of these risks were associated with a lower rate of growth from 4–8 years. Instead, maternal NESB, low school readiness and maternal mental health distress were associated with a higher rate of growth, although not sufficient to close the receptive vocabulary gap for children with and without these risks at 8 years. Socio-economic area disadvantage, was not a risk for low receptive vocabulary ability at 4 years but was the only risk associated with a lower rate of growth in receptive vocabulary ability. At 8 years, the gap between children with and without socio-economic area disadvantage was equivalent to eight months of receptive vocabulary growth. These results are consistent with other studies that have shown that social gradients in children's developmental outcomes increase over time.
High consumption of refined carbohydrate, in particular sugar, has been identified as a possible contributory factor in greater risk of excess weight gain. In spite of data limitations, one recent paper suggests that Australian sugar consumption has decreased over the same time period that obesity has increased, a so called ‘Australian Paradox’. Given the significant public health focus on nutrition, we aimed to estimate Australian sugar supply and consumption over recent decades, to determine whether these data could be used to make any conclusions about sugar’s role in obesity.
Foods high in sugar were identified. Data relating to sugar supply and consumption from 1988 to 2010 were obtained from multiple sources. Using these data we attempted to generate a time series estimate of sugar in Australia’s food supply.
Australia produces and exports sugar from sugar cane and the sugar in imported foods has received little attention. We were unable to produce a reliable and robust estimate of total sugars in the Australian diet due to data limitations and a lack of current data sources. However, available Import data showed large increases in the volume and value of imported sweetened products between 1988 and 2010 to over 30 grams of sugar per person per day. Value estimates of local production of sweetened products also show substantial increases in this period.
The Australian Paradox assertion is based on incomplete data, as it excludes sugar contained in imported processed foods, which have increased markedly. A major Australian public health target is to improve the quality of the food supply, and actions have been set in terms of achieving broader environmental changes. However, evaluation of progress is hampered by lack of high quality data relating to supply and consumption. We recommend the regular collection of comprehensive food supply statistics, which include both local production and imports. This would provide an inexpensive addition to survey data and could assist in monitoring sugar consumption trends in food supply. Such information would also help inform public health policy.
Public health; Sugar; Obesity; Food supply
High rates of smoking and lower rates of smoking cessation are known to be associated with common mental disorders such as anxiety and depression, and with individual and community measures of socioeconomic status. It is not known to what extent mental illness and socioeconomic status might be jointly associated with smoking behaviour. We set out to examine the relationship between mental illness, measures of socioeconomic disadvantage and both current smoking and smoking cessation rates.
We used data from the 2007 Australian National Survey of Mental Health and Wellbeing to examine the relationship between mental illness, socioeconomic status and both current smoking and smoking cessation. We used cross-classified tables and logistic regression to examine the relationship between psychosocial and sociodemographic predictors and current smoking. We also used proportional hazards regression to examine the relationship between the factors and smoking cessation.
Both mental illness and socioeconomic status were independently associated with current smoking and with lower likelihood of smoking cessation, with gradients in smoking by mental health status being observed within levels of socioeconomic indicators and vice versa. Having a mental illness in the past 12 months was the most prevalent factor strongly associated with smoking, affecting 20.0% of the population, associated with increased current smoking (OR 2.43; 95% CI: 1.97-3.01) and reduced likelihood of smoking cessation (HR: 0.77; 95% CI: 0.65-0.91).
The association between mental illness and smoking is not explained by the association between mental illness and socioeconomic status. There are strong socioeconomic and psychosocial gradients in both current smoking and smoking cessation. Incorporating knowledge of the other adverse factors in smokers’ lives may increase the penetration of tobacco control interventions in population groups that have historically benefitted less from these activities.
Despite the increasing understanding of the mechanisms relating to weight loss and maintenance, there are currently no validated public health interventions that are able to achieve sustained long-term weight loss or to stem the increasing prevalence of obesity in the population. We aimed to examine the models of energy balance underpinning current research about weight-loss intervention from the field of public health, and to determine whether they are consistent with the model provided by basic science. EMBASE was searched for papers published in 2011 on weight-loss interventions. We extracted details of the population, nature of the intervention, and key findings for 27 articles.
Most public health interventions identified were based on a simple model of energy balance, and thus attempted to reduce caloric consumption and/or increase physical activity in order to create a negative energy balance. There appeared to be little consideration of homeostatic feedback mechanisms and their effect on weight-loss success. It seems that there has been a lack of translation between recent advances in understanding of the basic science behind weight loss, and the concepts underpinning the increasingly urgent efforts to reduce excess weight in the population.
Public health weight-loss interventions seem to be based on an outdated understanding of the science. Their continued failure to achieve any meaningful, long-term results reflects the need to develop intervention science that is integrated with knowledge from basic science. Instead of asking why people persist in eating too much and exercising too little, the key questions of obesity research should address those factors (environmental, behavioral or otherwise) that lead to dysregulation of the homeostatic mechanism of energy regulation. There is a need for a multidisciplinary approach in the design of future weight-loss interventions in order to improve long-term weight-loss success.
Energy balance; obesity; public health; weight-loss intervention
The burden of mental health problems among Aboriginal and Torres Strait Islander children is a major public health problem in Australia. While socioeconomic factors are implicated as important determinants of mental health problems in mainstream populations, their bearing on the mental health of Indigenous Australians remains largely uncharted across all age groups.
We examined the relationship between the risk of clinically significant emotional or behavioural difficulties (CSEBD) and a range of socioeconomic measures for 3993 Indigenous children aged 4–17 years in Western Australia, using a representative survey conducted in 2000–02. Analysis was conducted using multivariate logistic regression within a multilevel framework.
Almost one quarter (24%) of Indigenous children were classified as being at high risk of CSEBD. Our findings generally indicate that higher socioeconomic status is associated with a reduced risk of mental health problems in Indigenous children. Housing quality and tenure and neighbourhood-level disadvantage all have a strong direct effect on child mental health. Further, the circumstances of families with Indigenous children (parenting quality, stress, family composition, overcrowding, household mobility, racism and family functioning) emerged as an important explanatory mechanism underpinning the relationship between child mental health and measures of material wellbeing such as carer employment status and family financial circumstances.
Our results provide incremental evidence of a social gradient in the mental health of Aboriginal and Torres Strait Islander children. Improving the social, economic and psychological conditions of families with Indigenous children has considerable potential to reduce the mental health inequalities within Indigenous populations and, in turn, to close the substantial racial gap in mental health. Interventions that target housing quality, home ownership and neighbourhood-level disadvantage are likely to be particularly beneficial.
Socioeconomic; Social disparities; Social gradient; Aboriginal; Mental health; Indigenous; Inequality; Australia
Statistical time series derived from administrative data sets form key indicators in measuring progress in addressing disadvantage in Aboriginal and Torres Strait Islander populations in Australia. However, inconsistencies in the reporting of Indigenous status can cause difficulties in producing reliable indicators. External data sources, such as survey data, provide a means of assessing the consistency of administrative data and may be used to adjust statistics based on administrative data sources.
We used record linkage between a large-scale survey (the Western Australian Aboriginal Child Health Survey), and two administrative data sources (the Western Australia (WA) Register of Births and the WA Midwives’ Notification System) to compare the degree of consistency in determining Indigenous status of children between the two sources. We then used a logistic regression model predicting probability of consistency between the two sources to estimate the probability of each record on the two administrative data sources being identified as being of Aboriginal and/or Torres Strait Islander origin in a survey. By summing these probabilities we produced model-adjusted time series of neonatal outcomes for Aboriginal and/or Torres Strait Islander births.
Compared to survey data, information based only on the two administrative data sources identified substantially fewer Aboriginal and/or Torres Strait Islander births. However, these births were not randomly distributed. Births of children identified as being of Aboriginal and/or Torres Strait Islander origin in the survey only were more likely to be living in urban areas, in less disadvantaged areas, and to have only one parent who identifies as being of Aboriginal and/or Torres Strait Islander origin, particularly the father. They were also more likely to have better health and wellbeing outcomes. Applying an adjustment model based on the linked survey data increased the estimated number of Aboriginal and/or Torres Strait Islander births in WA by around 25%, however this increase was accompanied by lower overall proportions of low birth weight and low gestational age babies.
Record linkage of survey data to administrative data sets is useful to validate the quality of recording of demographic information in administrative data sources, and such information can be used to adjust for differential identification in administrative data.
High consumption of sugar sweetened beverages (SSBs) has been linked to unhealthy weight gain and nutrition related chronic disease. Intake of SSB among children remains high in spite of public health efforts to reduce consumption, including restrictions on marketing to children and limitations on the sale of these products in many schools. Much extant literature on Australian SSB consumption is out-dated and lacks information on several key issues. We sought to address this using a contemporary Australian dataset to examine purchase source, consumption pattern, dietary factors, and demographic profile of SSB consumption in children.
Data were from the 2007 Australian National Children's Nutrition and Physical Activity Survey, a representative random sample of 4,834 Australian children aged 2-16 years. Mean SSB intake by type, location and source was calculated and logistic regression models were fitted to determine factors associated with different levels of consumption.
SSB consumption was high and age-associated differences in patterns of consumption were evident. Over 77% of SSB consumed was purchased via supermarkets and 60% of all SSB was consumed in the home environment. Less than 17% of SSB was sourced from school canteens and fast food establishments. Children whose parents had lower levels of education consumed more SSB on average, while children whose parents had higher education levels were more likely to favour sweetened juices and flavoured milks.
SSB intake by Australian children remains high and warrants continued public health attention. Evidence based and age-targeted interventions, which also recognise supermarkets as the primary source of SSB, are recommended to reduce SSB consumption among children. Additionally, education of parents and children regarding the health consequences of high consumption of both carbonated and non-carbonated SSBs is required.
It is well established that smoking rates in people with common mental disorders such as anxiety or depressive disorders are much higher than in people without mental disorders. It is less clear whether people with these mental disorders want to quit smoking, attempt to quit smoking or successfully quit smoking at the same rate as people without such disorders.
We used data from the 2005 Cancer Control Supplement to the United States National Health Interview Survey to explore the relationship between psychological distress as measured using the K6 scale and smoking cessation, by comparing current smokers who had tried unsuccessfully to quit in the previous 12 months to people able to quit for at least 7 to 24 months prior to the survey. We also used data from the 2007 Australian National Survey of Mental Health and Wellbeing to examine the relationship between psychological distress (K6) scores and duration of mental illness.
The majority of people with high K6 psychological distress scores also meet diagnostic criteria for mental disorders, and over 90% of these people had first onset of mental disorder more than 2 years prior to the survey. We found that people with high levels of non-specific psychological distress were more likely to be current smokers. They were as likely as people with low levels of psychological distress to report wanting to quit smoking, trying to quit smoking, and to have used smoking cessation aids. However, they were significantly less likely to have quit smoking.
The strong association between K6 psychological distress scores and mental disorders of long duration suggests that the K6 measure is a useful proxy for ongoing mental health problems. As people with anxiety and depressive disorders make up a large proportion of adult smokers in the US, attention to the role of these disorders in smoking behaviours may be a useful area of further investigation for tobacco control.
A prior episode of deliberate self-harm (DSH) is one of the strongest predictors of future completed suicide. Identifying antecedents of DSH may inform strategies designed to reduce suicide rates. This study aimed to determine whether individual and socio-ecological factors collected in childhood and adolescence were associated with later hospitalisation for DSH.
Longitudinal follow-up of a Western Australian population-wide random sample of 2,736 children aged 4-16 years, and their carers, from 1993 until 2007 using administrative record linkage. Children were aged between 18 and 31 years at end of follow-up. Proportional hazards regression was used to examine the relationship between child, parent, family, school and community factors measured in 1993, and subsequent hospitalisation for DSH.
There were six factors measured in 1993 that increased a child's risk of future hospitalisation with DSH: female sex; primary carer being a smoker; being in a step/blended family; having more emotional or behavioural problems than other children; living in a family with inconsistent parenting style; and having a teenage mother. Factors found to be not significant included birth weight, combined carer income, carer's lifetime treatment for a mental health problem, and carer education.
The persistence of carer smoking as an independent risk factor for later DSH, after adjusting for child, carer, family, school and community level socio-ecological factors, adds to the known risk domains for DSH, and invites further investigation into the underlying mechanisms of this relationship. This study has also confirmed the association of five previously known risk factors for DSH.
Many western nations continue to have high rates of teenage pregnancies and births, which can result in adverse outcomes for both mother and child. This study identified possible antecedents of teenage pregnancy using linked data from administrative sources to create a 14-year follow-up from a cross-sectional survey.
Data were drawn from two sources - the 1993 Western Australian Child Health Survey (WACHS), a population-based representative sample of 2,736 children aged 4 to 16 years (1,374 girls); and administrative data relating to all their subsequent births and hospital admissions. We used weighted population estimates to examine differences between rates for teenage pregnancy, motherhood and abortion. We used Cox proportional hazards regression to model risk for teenage pregnancy.
There were 155 girls aged less than 20 years at the time of their first recorded pregnancy. Teenage pregnancy was significantly associated with: family type; highest school year completed by primary carer; combined carer income; whether the primary carer was a smoker; and whether the girl herself displayed aggressive and delinquent behaviours. An age-interaction analysis on the association with aggressive and delinquent behaviours found that while girls with aggressive and delinquent behaviours who were older at the time of the survey were at highest risk of teenage pregnancy, there was elevated risk for future teenage pregnancy across all ages.
Our findings suggest that interventions to reduce teenage pregnancy rates could be introduced during primary school years, including those that are focused on the prevention and management of aggressive and delinquent behaviour.
Smoking has been associated with a range of mental disorders including schizophrenia, anxiety disorders and depression. People with mental illness have high rates of morbidity and mortality from smoking related illnesses such as cardiovascular disease, respiratory diseases and cancer. As many people who meet diagnostic criteria for mental disorders do not seek treatment for these conditions, we sought to investigate the relationship between mental illness and smoking in recent population-wide surveys.
Survey data from the US National Comorbidity Survey-Replication conducted in 2001–2003, the 2007 Australian Survey of Mental Health and Wellbeing, and the 2007 US National Health Interview Survey were used to investigate the relationship between current smoking, ICD-10 mental disorders and non-specific psychological distress. Population weighted estimates of smoking rates by disorder, and mental disorder rates by smoking status were calculated.
In both the US and Australia, adults who met ICD-10 criteria for mental disorders in the 12 months prior to the survey smoked at almost twice the rate of adults without mental disorders. While approximately 20% of the adult population had 12-month mental disorders, among adult smokers approximately one-third had a 12-month mental disorder – 31.7% in the US (95% CI: 29.5%–33.8%) and 32.4% in Australia (95% CI: 29.5%–35.3%). Female smokers had higher rates of mental disorders than male smokers, and younger smokers had considerably higher rates than older smokers. The majority of mentally ill smokers were not in contact with mental health services, but their rate of smoking was not different from that of mentally ill smokers who had accessed services for their mental health problem. Smokers with high levels of psychological distress smoked a higher average number of cigarettes per day.
Mental illness is associated with both higher rates of smoking and higher levels of smoking among smokers. Further, a significant proportion of smokers have mental illness. Strategies that address smoking in mental illness, and mental illness among smokers would seem to be important directions for tobacco control. As the majority of smokers with mental illness are not in contact with mental health services for their condition, strategies to address mental illness should be included as part of population health-based mental health and tobacco control efforts.
Canada, the United States, Australia, and New Zealand consistently place near the top of the United Nations Development Programme's Human Development Index (HDI) rankings, yet all have minority Indigenous populations with much poorer health and social conditions than non-Indigenous peoples. It is unclear just how the socioeconomic and health status of Indigenous peoples in these countries has changed in recent decades, and it remains generally unknown whether the overall conditions of Indigenous peoples are improving and whether the gaps between Indigenous peoples and other citizens have indeed narrowed. There is unsettling evidence that they may not have. It was the purpose of this study to determine how these gaps have narrowed or widened during the decade 1990 to 2000.
Census data and life expectancy estimates from government sources were used to adapt the Human Development Index (HDI) to examine how the broad social, economic, and health status of Indigenous populations in these countries have changed since 1990. Three indices – life expectancy, educational attainment, and income – were combined into a single HDI measure.
Between 1990 and 2000, the HDI scores of Indigenous peoples in North America and New Zealand improved at a faster rate than the general populations, closing the gap in human development. In Australia, the HDI scores of Indigenous peoples decreased while the general populations improved, widening the gap in human development. While these countries are considered to have high human development according to the UNDP, the Indigenous populations that reside within them have only medium levels of human development.
The inconsistent progress in the health and well-being of Indigenous populations over time, and relative to non-Indigenous populations, points to the need for further efforts to improve the social, economic, and physical health of Indigenous peoples.