Socioeconomic inequalities in mental health in Australia: Explaining life shock exposure

Socioeconomic inequalities in child and adolescent mental health in Australia: the role of parenting style and parents' relationships

BACKGROUND

Socioeconomic inequalities in health and their determinants have been studied extensively over the past few decades. However, the role of parenting style and parents' couple relationships in explaining mental health inequalities is limited. Therefore, this study aims to investigate the distributional impact of parenting style (angry parenting, consistent parenting, and inductive parenting) and parents' couple relationships (e.g., argumentative, happy relationships) on socioeconomic inequalities and by extension on mental health status of Australian children and adolescents.

METHODS

This study utilized data from the Longitudinal Study of Australian Children (Waves 1-7), specifically focusing on intact biological parent families, while excluding single-parent and blended-family households. We applied the decomposition index and the Blinder Oaxaca method to investigate the extent of the contribution and temporal impact of parenting style and parents' couple relationships on the mental health status of Australian children and adolescents.

RESULTS

This study revealed that poor parenting style is the single most important factor that leads to developing mental health difficulties in children and adolescents, especially from low socioeconomic status, and it contributes almost 52% to socioeconomic inequalities in mental health status. Conversely, household income, maternal education, employment status, and parents' couple relationships contributed 28.04%, 10.67%, 9.28%, and 3.34%, respectively, to mental health inequalities in children and adolescents.

CONCLUSION

Overall, this study underscores the importance of parenting style and parents' couple relationships as significant predictors of mental health outcomes in children and adolescents. These results highlight the need for targeted interventions to support families from low socioeconomic backgrounds to address the significant mental health inequalities observed in the study population.

Trend of Correlations between Psychological Symptoms and Socioeconomic Inequalities among Italian Adolescents: Cross-Sectional Study from 2006 to 2018 in Tuscany Region

Adolescence is a critical moment in life; people become individuals, create new relationships, develop social skills and learn behaviours that they will use for the rest of their lives. During this phase, adolescents establish patterns of behaviour that can protect their health. This study aims to 1. assess the presence of psychological disorders in adolescents of both genders, 2. determine their relation to socio-economic differences based on the Family Affluence Scale (FAS), and 3. assess trends from 2006 to 2018. Data were collected from the Italian Health Behaviour in School-aged Children survey given to a representative sample of Tuscan adolescents aged 11-15 years. Participants (n. 12,550) filled out questionnaires to assess whether psychological symptoms such as feeling low, irritability, nervousness, or sleeping difficulties manifested weekly or more often over the past six months. For the study we utilized a cross-sectional survey method and linear regression to examine the association between psychological symptoms (dependent variable measured on an interval scale (0-16)), gender and FAS. We conducted similar analyses using logistic regressions for each of the four symptoms. An increase in psychological symptoms in both genders was revealed between 2006 and 2018, with a statistically significant presence in females: 0.29 (95% Confidence Interval [CI], 0.17 to 0.41), 1.43 (95% CI, 1.37 to 1.48) and 1.43 (95% CI, 1.34 to 1.52) in low-, medium- and high-affluence families, respectively; whereas males presented 0.14 (95% CI, 0.01 to 0.27), 0.71 (95% CI, 0.65 to 0.77) and 0.31 (95% CI, 0.22 to 0.39), respectively. The probability of a predictive episode of psychological symptoms (feeling low, irritability, nervousness, sleeping difficulties) occurring weekly, or more, often was greatly increased in females of all socioeconomic classes. These findings suggest that the increase in psychological disorders in adolescents should be considered a public health problem and further investigated through longitudinal studies and continuous monitoring of health trends.

Inequity in psychiatric healthcare use in Australia

BACKGROUND

Despite recent substantial mental healthcare reforms to increase the supply of healthcare, mental health inequality in Australia is rising. Understanding of the level of inequity (unmet need gap) in psychiatric service use in Australia's mixed public-private health care system is lacking.

OBJECTIVE

To present a novel method to measure inequity in the delivery of psychiatric care.

METHODS

Data came from wave 9 (year 2009, n = 11,563) and wave 17 (year 2017, n = 16,194) of the Household, Income and Labour Dynamics in Australia (HILDA) survey. Multiple logistic regression was employed to estimate the psychiatric care utilisation compared to its need and the Gini index was used to estimate the standardised distribution of utilisation to measure the extent of inequity.

RESULTS

The results show the inequity indices (need-standardised Gini) in psychiatric care utilisation were significant and found to be 0.066 and 0.096 in 2009 and 2017, respectively, for all individuals. In 2009, the inequity indices were found to be 0.051 and 0.078 for males and females, respectively, and 0.045 and 0.068 for rural and urban residents, respectively. In 2017, the indices were calculated to be 0.081 and 0.109 for males and females, respectively, and 0.086 and 0.097 for rural and urban residents, respectively.

CONCLUSIONS

This study showed a marked increase in unmet needs in psychiatric care utilisation since 2009. There is a greater need to develop policies to improve equity in psychiatric care utilisation in Australia.

Psychological status of medical staff dedicated to nucleic acid collection in COVID-19 epidemic during closed-loop management: A cross-sectional study

Background

To investigate the depression, anxiety and somnipathy situation occurred in the nucleic acid collection staff during the closed-loop management period of COVID-19. And try to understand the influencing factors of related psychological status.

Methods

A cross-sectional study of 1,014 nucleic acid collection staff from seven Chinese hospitals was conducted. Various investigation methods were involved in the questionnaires to collect data, including 12-items self-made questionnaire survey of basic demographic information, 9-items patient health questionnaire depression scale (PHQ-9), 7-items generalized anxiety disorder scale (GAD-7) and Pittsburgh sleep quality index (PSQI). Data analysis was performed using SPSS version 26.0 and Excel software. Mann-Whitney U-test, Chi-square test, correlation analysis, mono-factor analysis and binary logistic regression were applied accordingly for further analysis.

Results

The positive rate of depression, anxiety and sleep disorder of 1,014 nucleic acid collectors under closed-loop management were 33.5, 27.2, and 50.1%, respectively. Depression was significantly positively correlated with anxiety and sleep (P < 0.05). The scores of depression scale were positively correlated with the age and the fear for infection (r = 0.106, 0.218, both P < 0.05); The scores of anxiety scale were also positively correlated with the age and the fear for infection (r = 0.124, 0.225, both P < 0.05); The length of service, collection time and the degree of worry about infection and was positively correlated with the score of sleep scale (r = 0.077, 0.074, 0.195, both P < 0.05); Education level had a significant negative association with PHQ-9, GAD-7 and PSQI (r = −0.167,−0.172, both P < 0.05). Binary logistic regression analysis showed that age, technical title, education level, collection time, collection frequency, collection location, fear for infection and external environment were important influencing factors of depression, anxiety and sleep disorders.

Conclusion

The results of this study suggested that when carrying out nucleic acid collection mission, managers should intervene to optimize the collection location, control the duration of each collection mission, replace the collection staff in time and pay close attention to the psychological state of the collection staff.

Perceived social support on postpartum mental health: An instrumental variable analysis

The postpartum period is a challenging transition period with almost one in ten mothers experiencing depression after childbirth. Perceived social support is associated with mental health. Yet empirical evidence regarding the causal effects of social support on postpartum mental health remains scarce. In this paper, we used a nationally representative panel data of women to examine causality between perceived social support and postpartum mental health. We used fixed-effect method and included dependent variable lags to account for past mental health condition before birth (i.e., the pre-pregnancy and prenatal periods). The study also used an instrumental variable approach to address endogeneity. We find a declining trend in postpartum mental health between 2002 to 2018. Our study also showed that past mental health (i.e., before childbirth) is positively correlated with postpartum mental health. A universal routine mental health screening for expectant and new mothers should remain a key priority to ensure mental wellbeing for the mothers and their infants.

Do family and maternal background matter? A multilevel approach to modelling mental health status of Australian youth using longitudinal data

Purpose

Most previous research place great importance on the influence of family and maternal background on child and adolescents’ mental health. However, age of onset studies indicates that the majority of the mental health disease prevalence occurs during the youth years. This study investigates the relationship of family and maternal background, as well as individual circumstance on youth mental health status.

Method

Data from 975 participants and 4632 observations of aged cohort 15 to 19 years in the Household, Income and Labour Dynamics in Australia (HILDA) longitudinal study were followed for 10 years (2007–2017). Multilevel logistic regression models were used to analyse the impact of youth circumstances on mental health status.

Results

The findings suggests that not all dimensions of family and maternal background (especially maternal education) have impacts on youth mental health. We found low household income (AOR: 1.572, 95% CI: 1.017–2.43) and adverse living arrangement (AOR: 1.586, 95% CI: 1.097–2.294) significantly increases mental disorder odds whereas maternal education or occupation fixed effects were not significant. Individual level circumstances have much stronger impact on youth mental health. We found financial shock (AOR: 1.412, 95% CI: 1.277–1.561), life event shock (AOR: 1.157, 95% CI: 1.01–1.326), long term health conditions (AOR: 2.855, 95% CI: 2.042–3.99), smoking (AOR: 1.676, 95% CI: 1.162–2.416), drinking (AOR: 1.649, 95% CI: 1.286–2.114) and being female (AOR: 2.021, 95% CI: 1.431–2.851) have significant deteriorating effects on youth mental health.

Conclusions

Our finding is in contrast to the majority of studies in the literature which give a preeminent role to maternal characteristics in child and youth mental health status. Mental health interventions should consider heterogeneity of adverse youth circumstances and health-related behaviours.

Obesity, Disability and Self-Perceived Health Outcomes in Australian Adults: A Longitudinal Analysis Using 14 Annual Waves of the HILDA Cohort

BACKGROUND

Both obesity and disability have been widely recognised as major public health challenges because they play significant roles in determining self-perceived general and mental health. Longitudinal studies of the relationship between obesity and disability with self-reported health outcomes are scarce. Therefore, the objective of the present study is to examine the relationship between obesity and disability with self-perceived general and mental health among Australian adults aged 15 years and above.

METHODS

Data were extracted from the most recent 14 waves (waves 6 through 19) of the annual individual person dataset of the Household, Income and Labour Dynamics in Australia (HILDA) survey. The longitudinal random-effects logistic regression model was adopted to investigate the relationships between obesity and disability with self-reported health outcomes.

RESULTS

The results revealed that obese individuals and adults with some form of disability are more likely to report poor or fair general and mental health. The odds of self-reporting poor or fair general health were 2.40 and 6.07 times higher among obese (aOR: 2.40, 95% CI: 2.22-2.58) and adults with some form of disability (aOR: 6.07, 95% CI: 5.77-6.39), respectively, relative to adults with healthy weight and those without disability . The results also showed that self-rated poor or fair mental health were 1.22 and 2.40 times higher among obese adults (aOR: 1.22, 95% CI: 1.15-1.30) and adults with disability (aOR: 2.40, 95% CI: 2.30-2.51), respectively, compared to their healthy weight peers and peers without disability.

CONCLUSION

As governmental and non-governmental organisations seek to improve the community's physical and mental well-being, these organisations need to pay particular attention to routine health care prevention, specific interventions, and treatment practices, especially for obese and/or people with disabilities.

Community Environment Perception on Depression: The Mediating Role of Subjective Social Class

Depression has become a major social issue of global concern, which has seriously threatened the quality of an individual’s life. Although the relationship between community environment and depression has aroused heated debate, the empirical research on the relationship between community environment perception and public depression is still relatively insufficient. Data for this study are from China Family Panel Studies in 2016, which were conducted by the institute of Social Science Survey, Peking University. This paper has tested group differences in the influence of community environment on public depression, as well as the mediating role of subjective social class between community environment perception and depression, so as to further explore the social psychological effect of community environment. The empirical study found that there are group differences in the impacts of community environment perception on depression. Specifically, men, rural residents, and people aged 60 and under are more likely to be depressed which were affected by the perception of community environment. Furthermore, we have found that the subjective social class can partly mediate community environment perception and depression. That is to say, the perception of community environment can induce depression by influencing the individual’s subjective social class. Among them, community living environment and community public facilities have the greatest impact, community emotional attachment and community security situation have the second impact, and neighborhood mutual aid and neighborhood relationship have the least impact. In other words, the community environment is deeply endowed with a social psychological effect. To ameliorate the public’s depression, it is necessary to consider the construction of community physical environment and the cultivation of harmonious community culture as powerful measures not to be ignored. In short, the important role of community environmental intervention in alleviating the public’s depression caused by social class cognition deserves attention.

Australia in 2030: what is our path to health for all?

CHAPTER 1: HOW AUSTRALIA IMPROVED HEALTH EQUITY THROUGH ACTION ON THE SOCIAL DETERMINANTS OF HEALTH: Do not think that the social determinants of health equity are old hat. In reality, Australia is very far away from addressing the societal level drivers of health inequity. There is little progressive policy that touches on the conditions of daily life that matter for health, and action to redress inequities in power, money and resources is almost non-existent. In this chapter we ask you to pause this reality and come on a fantastic journey where we envisage how COVID-19 was a great disruptor and accelerator of positive progressive action. We offer glimmers of what life could be like if there was committed and real policy action on the social determinants of health equity. It is vital that the health sector assists in convening the multisectoral stakeholders necessary to turn this fantasy into reality. CHAPTER 2: ABORIGINAL AND TORRES STRAIT ISLANDER CONNECTION TO CULTURE: BUILDING STRONGER INDIVIDUAL AND COLLECTIVE WELLBEING: Aboriginal and Torres Strait Islander peoples have long maintained that culture (ie, practising, maintaining and reclaiming it) is vital to good health and wellbeing. However, this knowledge and understanding has been dismissed or described as anecdotal or intangible by Western research methods and science. As a result, Aboriginal and Torres Strait Islander culture is a poorly acknowledged determinant of health and wellbeing, despite its significant role in shaping individuals, communities and societies. By extension, the cultural determinants of health have been poorly defined until recently. However, an increasing amount of scientific evidence supports what Aboriginal and Torres Strait Islander people have always said - that strong culture plays a significant and positive role in improved health and wellbeing. Owing to known gaps in knowledge, we aim to define the cultural determinants of health and describe their relationship with the social determinants of health, to provide a full understanding of Aboriginal and Torres Strait Islander wellbeing. We provide examples of evidence on cultural determinants of health and links to improved Aboriginal and Torres Strait Islander health and wellbeing. We also discuss future research directions that will enable a deeper understanding of the cultural determinants of health for Aboriginal and Torres Strait Islander people. CHAPTER 3: PHYSICAL DETERMINANTS OF HEALTH: HEALTHY, LIVEABLE AND SUSTAINABLE COMMUNITIES: Good city planning is essential for protecting and improving human and planetary health. Until recently, however, collaboration between city planners and the public health sector has languished. We review the evidence on the health benefits of good city planning and propose an agenda for public health advocacy relating to health-promoting city planning for all by 2030. Over the next 10 years, there is an urgent need for public health leaders to collaborate with city planners - to advocate for evidence-informed policy, and to evaluate the health effects of city planning efforts. Importantly, we need integrated planning across and between all levels of government and sectors, to create healthy, liveable and sustainable cities for all. CHAPTER 4: HEALTH PROMOTION IN THE ANTHROPOCENE: THE ECOLOGICAL DETERMINANTS OF HEALTH: Human health is inextricably linked to the health of the natural environment. In this chapter, we focus on ecological determinants of health, including the urgent and critical threats to the natural environment, and opportunities for health promotion arising from the human health co-benefits of actions to protect the health of the planet. We characterise ecological determinants in the Anthropocene and provide a sobering snapshot of planetary health science, particularly the momentous climate change health impacts in Australia. We highlight Australia's position as a major fossil fuel producer and exporter, and a country lacking cohesive and timely emissions reduction policy. We offer a roadmap for action, with four priority directions, and point to a scaffold of guiding approaches - planetary health, Indigenous people's knowledge systems, ecological economics, health co-benefits and climate-resilient development. Our situation requires a paradigm shift, and this demands a recalibration of health promotion education, research and practice in Australia over the coming decade. CHAPTER 5: DISRUPTING THE COMMERCIAL DETERMINANTS OF HEALTH: Our vision for 2030 is an Australian economy that promotes optimal human and planetary health for current and future generations. To achieve this, current patterns of corporate practice and consumption of harmful commodities and services need to change. In this chapter, we suggest ways forward for Australia, focusing on pragmatic actions that can be taken now to redress the power imbalances between corporations and Australian governments and citizens. We begin by exploring how the terms of health policy making must change to protect it from conflicted commercial interests. We also examine how marketing unhealthy products and services can be more effectively regulated, and how healthier business practices can be incentivised. Finally, we make recommendations on how various public health stakeholders can hold corporations to account, to ensure that people come before profits in a healthy and prosperous future Australia. CHAPTER 6: DIGITAL DETERMINANTS OF HEALTH: THE DIGITAL TRANSFORMATION: We live in an age of rapid and exponential technological change. Extraordinary digital advancements and the fusion of technologies, such as artificial intelligence, robotics, the Internet of Things and quantum computing constitute what is often referred to as the digital revolution or the Fourth Industrial Revolution (Industry 4.0). Reflections on the future of public health and health promotion require thorough consideration of the role of digital technologies and the systems they influence. Just how the digital revolution will unfold is unknown, but it is clear that advancements and integrations of technologies will fundamentally influence our health and wellbeing in the future. The public health response must be proactive, involving many stakeholders, and thoughtfully considered to ensure equitable and ethical applications and use. CHAPTER 7: GOVERNANCE FOR HEALTH AND EQUITY: A VISION FOR OUR FUTURE: Coronavirus disease 2019 has caused many people and communities to take stock on Australia's direction in relation to health, community, jobs, environmental sustainability, income and wealth. A desire for change is in the air. This chapter imagines how changes in the way we govern our lives and what we value as a society could solve many of the issues Australia is facing - most pressingly, the climate crisis and growing economic and health inequities. We present an imagined future for 2030 where governance structures are designed to ensure transparent and fair behaviour from those in power and to increase the involvement of citizens in these decisions, including a constitutional voice for Indigenous peoples. We imagine that these changes were made by measuring social progress in new ways, ensuring taxation for public good, enshrining human rights (including to health) in legislation, and protecting and encouraging an independent media. Measures to overcome the climate crisis were adopted and democratic processes introduced in the provision of housing, education and community development.

Prevalence of Mental Disorders by Socioeconomic Status in Australia: A Cross-Sectional Epidemiological Study

PURPOSE

To present the prevalence of 3 broad categories of mental disorder (anxiety-related, affective and other disorders) by socioeconomic status and examine the associated socioeconomic risk factors of mental disorders in Australia.

DESIGN

A population-based, cross-sectional national health survey on mental health and its risk factors across Australia.

SETTING

National Health Survey (NHS), 2017-2018 conducted by the Australian Bureau of Statistics (ABS).

PARTICIPANTS

Under aged: 4,945 persons, Adult: 16,370 persons and total: 21,315 persons.

MEASURES

Patient-reported mental disorder outcomes.

ANALYSIS

Weighted prevalence rates by socioeconomic status (equivalised household income, education qualifications, Socio-Economic Index for Areas (SEIFA) scores, labor force status and industry sector where the adult respondent had their main job) were estimated using cross-tabulation. Logistic regression utilizing subsamples of underage and adult age groups were analyzed to test the association between socioeconomic status and mental disorders.

RESULTS

Anxiety-related disorders were the most common type of disorders with a weighted prevalence rate of 20.04% (95% CI: 18.49-21.69) for the poorest, 13.85% (95% CI: 12.48-15.35) for the richest and 16.34% (95% CI: 15.7-17) overall. The weighted prevalence rate for mood/affective disorders were 20.19% (95% CI: 18.63-21.84) for the poorest, 9.96% (95% CI: 8.79-11.27) for the richest, and 13.57% (95% CI: 12.99-14.17) overall. Other mental disorders prevalence were for the poorest: 9.07% (95% CI: 7.91-10.39), the richest: 3.83% (95% CI: 3.14-4.66), and overall: 5.93% (95% CI: 5.53-6.36). These patterns are also reflected if all mental disorders were aggregated with the poorest: 30.97% (95% CI: 29.15-32.86), the richest: 19.59% (95% CI: 18.02-21.26), and overall: 23.93% (95% CI: 23.19-24.69). The underage logistic regression model showed significant lower odds for the middle (AOR: 0.75, 95% CI: 0.53 -1.04, p < 0.1), rich (AOR: 0.71, 95% CI: 0.5-0.99, p < 0.05) and richest (AOR: 0.6, 95% CI: 0.41-0.89, p < 0.01) income groups. Similarly, in the adult logistic model, there were significant lower odds for middle (AOR: 0.84, 95% CI: 0.72-0.98, p < 0.05), rich (AOR: 0.73, 95% CI: 0.62-0.86, p < 0.01) and richest (AOR: 0.76, 95% CI: 0.63-0.91, p < 0.01) income groups.

CONCLUSION

The prevalence of mental disorders in Australia varied significantly across socioeconomic groups. Knowledge of different mental health needs in different socioeconomic groups can assist in framing evidence-based health promotion and improve the targeting of health resource allocation strategies.