Search

: Objective: To quantify the prevalence of known health‐related risk factors for severe COVID‐19 illness among Aboriginal and Torres Strait Islander adults, and their relationship with social determinants. Methods: Weighted cross‐sectional analysis of the 2018‐19 National Aboriginal and Torres Strait Islander Health Survey; Odds Ratios for cumulative risk count category (0, 1, or ≥2 health‐related risk factors) by social factors calculated using ordered logistic regression. Results: Of the adult population, 42.9%(95%CI:40.6,45.2) had none of the examined health‐related risk factors; 38.9%(36.6,41.1) had 1, and 18.2%(16.7,19.7) had ≥2. Adults experiencing relative advantage across social indicators had significantly lower cumulative risk counts, with 30‐70% lower odds of being in a higher risk category. Conclusions: Aboriginal and Torres Strait Islander peoples must continue to be recognised as a priority population in all stages of pandemic preparedness and response as they have disproportionate exposure to social factors associated with risk of severe COVID‐19 illness. Indigeneity itself is not a ‘risk’ factor and must be viewed in the wider context of inequities that impact health Implications for public health: Multi‐sectoral responses are required to improve health during and after the COVID‐19 pandemic that: enable self‐determination; improve incomes, safety, food security and culturally‐safe healthcare; and address discrimination and trauma., The COVID‐19 pandemic has again put a spotlight on health inequities across populations globally, including differential risk of COVID‐19 exposure and transmission, consequences of infection, access to vaccines and consequences [...]

The first key use of a nation's Census is to count its resident population. A Census will have counting errors, often referred to as over-coverage and under-coverage. So it is common practice in many countries to conduct an independent count of its residents, a so-called coverage survey, and estimate or adjust for these counting errors within the capture-recapture framework. In recent times, many censuses and coverage surveys have faced challenges in counting the population efficiently and effectively due to rising costs, declining response rates, and respondent burden. This has led to a shift toward exploring the role that administrative registers could play in counting the population within the capture-recapture framework. Administrative registers are relatively inexpensive and can have high coverage of a nation's population. This paper explores methods to overcome common problems with the use of administrative registers within this framework, including linking errors and scoping the register to only capture residents. These methods are empirically assessed in the context of the Australian population. [ABSTRACT FROM AUTHOR]

Chronic childhood undernutrition, known as stunting, is an important population health problem with short- and long-term adverse outcomes. Bangladesh has made strides to reduce chronic childhood undernutrition, yet progress is falling short of the 2030 Sustainable Development Goals targets. This study estimates trends in age-specific chronic childhood undernutrition in Bangladesh's 64 districts during 1997–2018, using underlying direct estimates extracted from seven Demographic and Health Surveys in the development of small area time-series models. These models combine cross-sectional, temporal, and spatial data to predict in all districts in both survey and non-survey years. Nationally, there has been a steep decline in stunting from about three in five to one in three children. However, our results highlight significant inequalities in chronic undernutrition, with several districts experiencing less pronounced declines. These differences are more nuanced at the district-by-age level, with only districts in more socio-economically advantaged areas of Bangladesh consistently reporting declines in stunting across all age groups. [ABSTRACT FROM AUTHOR]

The study sought to determine the effects of teacher-introduced multimodal representations and discourse on students' task engagement and scientific language during cooperative, inquiry-based science. The study involved eight Year 6 teachers in two conditions (four very effective teachers and four effective teachers) who taught two units of inquiry-based science across two school terms. The results show that the very effective teachers spent significantly more time engaged in using embodied representations to illustrate points or communicate information. They also spent significantly more time engaged in interrogating students' understandings and scaffolding and challenging their thinking than the effective teachers. In turn, the students in the very effective teachers' classes spent significantly more time on-task and used significantly more relevant basic and scientific language to explain the phenomena they were investigating than their peers in the effective teachers' classes. These are behaviours and language that are associated with successful learning in science.

This study examined associations between loneliness, a construct associated with serious adverse mental health outcomes, and positive mental wellbeing. Validated measures of loneliness (represented by friendship-related loneliness, isolation, positive attitude to solitude, and negative attitude to solitude) and positive mental wellbeing were administered to 1,143 adolescents from urban and rural schools. Confirmatory factor analyses revealed satisfactory model fit for both measures. A structural equation model confirmed significant positive associations between positive mental wellbeing and friendship-related loneliness and positive attitude to solitude; a significant negative association was found for isolation. Regression analyses provided support for significant differences in these associations according to gender, age, and geographical location (although only marginally). The implications of these findings during adolescence are reviewed.

District-representative data are rarely collected in the surveys for identifying localised disparities in Bangladesh, and so district-level estimates of undernutrition indicators – stunting, wasting and underweight – have remained largely unexplored. This study aims to estimate district-level prevalence of these indicators by employing a multivariate Fay–Herriot (MFH) model which accounts for the underlying correlation among the undernutrition indicators. Direct estimates (DIR) of the target indicators and their variance–covariance matrices calculated from the 2019 Bangladesh Multiple Indicator Cluster Survey microdata have been used as input for developing univariate Fay–Herriot (UFH), bivariate Fay–Herriot (BFH) and MFH models. The comparison of the various model-based estimates and their relative standard errors with the corresponding direct estimates reveals that the MFH estimator provides unbiased estimates with more accuracy than the DIR, UFH and BFH estimators. The MFH model-based district level estimates of stunting, wasting and underweight range between 16 and 43%, 15 and 36%, and 6 and 13% respectively. District level bivariate maps of undernutrition indicators show that districts in north-eastern and south-eastern parts are highly exposed to either form of undernutrition, than the districts in south-western and central parts of the country. In terms of the number of undernourished children, millions of children affected by either form of undernutrition are living in densely populated districts like the capital district Dhaka, though undernutrition indicators (as a proportion) are comparatively lower. These findings can be used to target districts with a concurrence of multiple forms of undernutrition, and in the design of urgent intervention programs to reduce the inequality in child undernutrition at the localised district level. [ABSTRACT FROM AUTHOR]