Associations of nuptiality perceptions, financial difficulties, and socio-demographic factors with mental health status in Australian adults: Analysis of the Household, Income and Labour Dynamics in Australia (HILDA) survey
This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults. Cross-sectional quantitative study design. Using data from the Household, Income and Labour Dynamics in Australia (HILDA) sur...
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| Published in: | PloS one Vol. 19; no. 2; p. e0296941 |
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| Format: | Journal Article |
| Language: | English |
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14-02-2024
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| Abstract | This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults.
Cross-sectional quantitative study design.
Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status.
Overall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status.
The study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia. |
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| AbstractList | OBJECTIVEThis study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults.DESIGNCross-sectional quantitative study design.SETTINGS, PARTICIPANTS, AND INTERVENTIONSUsing data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status.RESULTSOverall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status.CONCLUSIONThe study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia. Objective This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults. Design Cross-sectional quantitative study design. Settings, participants, and interventions Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status. Results Overall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status. Conclusion The study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia. This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults. Cross-sectional quantitative study design. Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status. Overall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status. The study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia. This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of Australian adults. Cross-sectional quantitative study design. Using data from the Household, Income and Labour Dynamics in Australia (HILDA) survey wave 19, 6846 adults were included in the analysis. Mental health was measured using the mental component summary (MCS) subscale of the Short-Form Health Survey SF-36. Hierarchical multiple linear regressions were used to examine the predictors of mental health status. Overall, 7.1% of the participants reported poor mental health status. Individual financial difficulty factors explained 3.2% (p<0.001) of the variance in mental health scores. In addition, financial difficulties were negatively associated with mental health status. Nuptiality and relationship factors accounted for 9.8% (p<0.001) of the variance in mental health status. The study suggests negative marital or relationship perceptions and financial difficulties are significant factors accounting for poor mental health. This finding suggests the need for more policy attention toward the social determinants of poor mental health especially nuptiality or relationship perceptions which have received less policy and research attention in Australia. |
| Audience | Academic |
| Author | Addo, Isaac Yeboah Yeboah Asiamah-Asare, Bernard Kwadwo Peprah, Prince Adu, Collins Ahinkorah, Bright Opoku |
| AuthorAffiliation | 9 Concord Clinical School, University of Sydney, Sydney, Australia 2 Curtin School of Population Health, Curtin University, Perth, Western Australia, Australia 4 Centre for Primary Health Care and Equity, UNSW, Sydney, Australia 8 School of Clinical Medicine, UNSW Sydney, Sydney, Australia 1 Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, Scotland 5 Department of Health Promotion, Education and Disability Studies, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana 3 Social Policy Research Centre, UNSW, Sydney, Australia 7 School of Public Health, University of Technology Sydney, Sydney, Australia Khulna University, BANGLADESH 6 Centre for Social Research in Health; UNSW Sydney, Sydney, Australia |
| AuthorAffiliation_xml | – name: 5 Department of Health Promotion, Education and Disability Studies, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana – name: 8 School of Clinical Medicine, UNSW Sydney, Sydney, Australia – name: 7 School of Public Health, University of Technology Sydney, Sydney, Australia – name: 4 Centre for Primary Health Care and Equity, UNSW, Sydney, Australia – name: 6 Centre for Social Research in Health; UNSW Sydney, Sydney, Australia – name: Khulna University, BANGLADESH – name: 1 Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, Scotland – name: 2 Curtin School of Population Health, Curtin University, Perth, Western Australia, Australia – name: 9 Concord Clinical School, University of Sydney, Sydney, Australia – name: 3 Social Policy Research Centre, UNSW, Sydney, Australia |
| Author_xml | – sequence: 1 givenname: Bernard Kwadwo surname: Yeboah Asiamah-Asare fullname: Yeboah Asiamah-Asare, Bernard Kwadwo organization: Curtin School of Population Health, Curtin University, Perth, Western Australia, Australia – sequence: 2 givenname: Prince surname: Peprah fullname: Peprah, Prince organization: Centre for Primary Health Care and Equity, UNSW, Sydney, Australia – sequence: 3 givenname: Collins orcidid: 0000-0002-1300-6327 surname: Adu fullname: Adu, Collins organization: Centre for Social Research in Health; UNSW Sydney, Sydney, Australia – sequence: 4 givenname: Bright Opoku surname: Ahinkorah fullname: Ahinkorah, Bright Opoku organization: School of Clinical Medicine, UNSW Sydney, Sydney, Australia – sequence: 5 givenname: Isaac Yeboah surname: Addo fullname: Addo, Isaac Yeboah organization: Concord Clinical School, University of Sydney, Sydney, Australia |
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| Cites_doi | 10.1016/j.ssmph.2021.100765 10.1016/j.socscimed.2008.02.025 10.1136/bmj.i4588 10.1093/aje/kwr161 10.1146/annurev-publhealth-040617-013629 10.1186/s12889-016-2720-y 10.1080/03075079.2017.1356281 10.1097/YCO.0000000000000182 10.1016/j.maturitas.2019.09.004 10.2105/AJPH.2019.305278 10.1016/j.jpsychires.2015.03.017 10.1371/journal.pone.0253046 10.1016/j.avb.2015.05.005 10.1016/j.socscimed.2015.01.022 10.1371/journal.pone.0178138 10.1002/aur.2162 10.1111/1467-8462.00252 10.1192/bjp.bp.110.085100 10.1007/s11920-018-0969-9 10.1016/j.sleep.2018.10.008 10.1016/j.ssmmh.2021.100025 10.1177/0961203319828519 10.1016/j.cpr.2019.101749 10.1007/s00127-018-1591-1 10.1016/j.burns.2017.08.013 10.1038/s41598-021-89700-8 10.1016/j.socscimed.2020.113452 10.1136/oem.2010.059030 |
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| Snippet | This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health status of... Objective This study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health... OBJECTIVEThis study examined the association of nuptial/relationship factors, financial difficulties, and socio-demographic factors with the mental health... |
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| Title | Associations of nuptiality perceptions, financial difficulties, and socio-demographic factors with mental health status in Australian adults: Analysis of the Household, Income and Labour Dynamics in Australia (HILDA) survey |
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