In a recent study published in PLoS ONE, Using data from the Household, Income and Labor Dynamics of Australia (HILDA) Survey, a group of researchers used data from the Household, Income and Labor Dynamics of Australia (HILDA) Survey to determine the impact of marital/relationship perceptions, economic hardship and socio-demographic factors on the mental health of Australian adults. investigated.
study: Relationships between marital attitudes, economic hardship, and socio-demographic factors and mental health status among Australian adults: An analysis of the Household, Income and Labor Dynamics of Australia (HILDA) Survey.. Image credit: SewCreamStudio/Shutterstock.com
background
Mental health is critical to an individual's well-being, defined as managing life's stresses, fulfilling one's potential, working productively, and contributing to one's community.
They are affected by a variety of life challenges, including financial hardship, employment struggles, and domestic violence, which can significantly increase their risk of dying in hospital.
Recent research has highlighted the influence of social determinants on mental health, revealing differences by gender, age, and socio-economic factors. In Australia, one in five people suffer from a mental health problem.
Further research is needed to unravel the complex interactions between sociodemographic factors, marital status, economic stress, and mental health and to inform targeted interventions and policies.
About research
This study utilized data from the HILDA survey, a comprehensive source of information launched in 2001. The survey includes information on wealth, labor market outcomes, household and family dynamics, health, and education.
We employed a multistage sampling strategy, beginning with the selection of census collection districts and then selecting households within these districts to ensure broad representation of the Australian population.
Over the years, the survey has been adapted to include new household members and children of respondents, maintaining a dynamic and growing dataset. This analysis used the most recent wave available (Wave 19), focused specifically on mental health variables, and excluded incomplete records, resulting in a final sample of 6,846 participants.
Mental health status is measured in the Short-Form (SF)-36 Mental Health Survey, a widely recognized tool for measuring quality of life related to mental health, with a scoring system to convert responses. It was measured using the Component Summary (MCS) subscale. It is converted into a composite score indicating mental health status.
Financial hardship was assessed through direct questions regarding the participant's ability to meet essential payments and needs. At the same time, perceptions about marriage and relationships were measured through questions about marital status, relationship quality, and satisfaction.
This analysis uses hierarchical multiple linear regression to identify socio-demographic factors, using a systematic approach that first considers the influence of socio-demographic characteristics before introducing economic and marital variables. , investigated the effects of financial hardship, and perceptions about marriage/relationships on mental health.
This methodological framework allowed us to better understand the relative contributions of these factors to mental health outcomes.
Ethical considerations are thorough, with access to data granted to authorized researchers based on strict guidelines to ensure confidentiality and consent.
research result
The study analyzed 6,846 people to understand the relationship between socio-demographic factors, marital/relationship attitudes, financial hardship and mental health among Australian adults.
The demographic profile of the participants showed a preponderance of individuals aged 42 years and older (60.9%), with women comprising 51.4% of the sample.
The majority were born in Australia (77.5%) and were married (78.2%). In terms of education, 27.7% had attained her grade 11 qualification or below, and approximately 70% were employed.
The average MCS score, which measures mental health, was 76.4 with a standard deviation of 15.8, indicating that participants were generally in good mental health. However, 7.1% of participants were identified as having poor mental health (MCS score <50).
Analysis revealed that a small portion (2.1%) of the variance in mental health scores was explained by demographic characteristics. Older participants (over 60 years) showed higher mental health scores compared to the youngest cohort (under 25 years), suggesting that mental health improves with age.
Conversely, being female, being born outside Australia, being retired and being a student were factors associated with lower mental health scores. Financial hardship had a significant impact on mental health, accounting for an additional 3.2% of the variance in MCS scores.
Challenges such as difficulty paying bills, having to pawn or sell belongings, and seeking financial assistance from friends, family, and welfare/community organizations were associated with lower mental health scores.
Marital and relationship factors were particularly influential, explaining 9.8% of the variance in mental health scores. Positive perceptions of the quality of relationships and the extent to which they met initial expectations were associated with improved mental health.
Conversely, negative aspects such as frequent thoughts of not wanting to get married or in a relationship, problems within the relationship, and the intensity of love for a spouse or partner were correlated with lower mental health scores. .
