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.
SummaryA national census provides important information on a country's population that is used in government planning and to underpin the national statistical system. Therefore, the quality of such information is paramount but is not as simple as the crude accuracy of population totals. Furthermore, changes in the pace and nature of modern life, such as the growing geographical mobility of the population, increasingly pose challenges to census practice and data quality. More recently, even the need for a census has been questioned on grounds of financial austerity and widespread availability of alternative population information sources. This article reviews how the modern census originated and how it evolved to confront these challenges, driven by indicators of quality and needs of users, and provides reflections on the future of the census within the national statistical infrastructure. To illustrate our discussions, we use case studies from a diverse range of national contexts. We demonstrate the implications that a country's needs, circumstances and experiences have on the census approach and practice while identifying the fundamental demographic assumptions.
Australia is a major immigration country and immigrants currently represent around 28% of the total population. The aim of this research is to understand the long-term consequences of this immigration and, particularly, how migrants respond to opportunities within the country after arriving through the process of subsequent (internal) migration. The focus is on major immigrant groups in Australia, including persons born in the United Kingdom, New Zealand, China and India, and how their patterns differ from persons born in Australia. To conduct this analysis, we have gathered data for a 35-year period based on quinquennial census data. We also obtained birthplace-specific mortality data for constructing multiregional life tables for the immigrant populations. Subsequent migration is important for understanding population redistribution, and the relative attractiveness of destinations within host countries. Our results highlight the importance of subsequent migration and the diversity of migration behaviours amongst different immigrant groups in the context of overall declines in internal migration since 1981.
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.
Comparable survey data on Indigenous and non-Indigenous Australians are highly sought after by policymakers to inform policies aimed at closing ethnic socio-economic gaps. However, collection of such data is compromised by group differences in socio-economic status and cultural norms. We use data from the Household, Income and Labour Dynamics in Australia Survey and multiple-membership multilevel regression models that allow for individual and interviewer effects to examine differences between Indigenous and non-Indigenous Australians in approximate measures of the quality of the interview process. We find that there are both direct and indirect ethnic effects on different dimensions of interview process quality, with Indigenous Australians faring worse than non-Indigenous Australians in all outcomes ceteris paribus . This indicates that nationwide surveys must feature interview protocols that are sensitive to the needs and culture of Indigenous respondents to improve the quality of the survey information gathered from this subpopulation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.