Chen Jiao1,2, Anli Leng3, Stephen Nicholas4,5,6,7, Elizabeth Maitland8, Jian Wang9,10, Qinfeng Zhao1,2, Lizheng Xu11,12, Chaofan Gong13. 1. Centre for Health Management and Policy Research, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, China. 2. NHC Key Lab of Health Economics and Policy Research, Shandong University, Jinan 250012, China. 3. School of Political Science and Public Administration, Institute of Governance, Shandong University, 72 Binhai Rd, Qingdao 266237, Shandong, China. 4. Australian National Institute of Management and Commerce, 1 Central Avenue, Australian Technology Park, Sydney, NSW 2015, Australia. 5. Guangdong Institute for International Strategies, Guangdong University of Foreign Studies, 2 Baiyun North Avenue, Guangzhou 510420, Guangdong, China. 6. School of Economics and School of Management, Tianjin Normal University, No. 339 Binshui West Avenue, Tianjin 300387, China. 7. Newcastle Business School, University of Newcastle, Newcastle, NSW 2308, Australia. 8. School of Management, University of Liverpool, Chatham Building, Chatham Street, Liverpool L697ZH, UK. 9. Dong Fureng Institute of Economics and Social Development, Wuhan University, No. 54 Dongsi Lishi Hutong, Dongcheng District, Beijing 100010, China. 10. Center for Health Economics and Management, Economics and Management School, Wuhan University, Luojia Hill, Wuhan 430072, China. 11. The George Institute for Global Health, Sydney, NSW 2052, Australia. 12. UNSW Medicine, UNSW Sydney, Sydney, NSW 2052, Australia. 13. Center for Digital Health, School of Medicine, Stanford University, Palo Alto, CA 94305, USA.
Abstract
(1) Background: The association between multimorbidity and mental health is well established. However, the role of gender in different populations remains unclear. Currently, China is facing an increased prevalence of multimorbidity, especially in its disease-causing poverty population. The present study explores the gender-based differences in the relationship between multimorbidity and mental health using data from the rural, disease-causing poverty, older-age population in Shandong province, China, as a case study. (2) Methods: The data were obtained from the survey on the health and welfare of disease-causing poverty households in rural Shandong province. We identified 936 rural participants who were over 60 years old from disease-causing poverty households. The mental health status was measured using the Kessler Psychological Distress Scale (K10) instrument. Using a multivariable linear regression model, including the interaction of gender and multimorbidity, gender differences in the association between multimorbidity and mental health were explored. (3) Results: Multimorbidity was a serious health problem in rural, disease-causing poverty, older-age households, with the prevalence of multimorbidity estimated as 40% for women and 35.4% for men. There was a strong association between multimorbidity and mental health, which was moderated by gender. Women had higher K10 scores than men, and the mean K10 score was highest in women with three or more chronic diseases. Compared with men, women with multimorbidity had a higher risk of mental health problems. (4) Conclusions: The prevalence of multimorbidity in older-age rural disease-causing poverty subpopulations is a severe public health problem in China. The association between multimorbidity and mental health differed by gender, where multimorbid women suffered an increased mental health risk compared with men. Gender differences should be addressed when delivering effective physical and mental healthcare support to disease-causing poverty, older-age, rural households.
(1) Background: The association between multimorbidity and mental health is well established. However, the role of gender in different populations remains unclear. Currently, China is facing an increased prevalence of multimorbidity, especially in its disease-causing poverty population. The present study explores the gender-based differences in the relationship between multimorbidity and mental health using data from the rural, disease-causing poverty, older-age population in Shandong province, China, as a case study. (2) Methods: The data were obtained from the survey on the health and welfare of disease-causing poverty households in rural Shandong province. We identified 936 rural participants who were over 60 years old from disease-causing poverty households. The mental health status was measured using the Kessler Psychological Distress Scale (K10) instrument. Using a multivariable linear regression model, including the interaction of gender and multimorbidity, gender differences in the association between multimorbidity and mental health were explored. (3) Results: Multimorbidity was a serious health problem in rural, disease-causing poverty, older-age households, with the prevalence of multimorbidity estimated as 40% for women and 35.4% for men. There was a strong association between multimorbidity and mental health, which was moderated by gender. Women had higher K10 scores than men, and the mean K10 score was highest in women with three or more chronic diseases. Compared with men, women with multimorbidity had a higher risk of mental health problems. (4) Conclusions: The prevalence of multimorbidity in older-age rural disease-causing poverty subpopulations is a severe public health problem in China. The association between multimorbidity and mental health differed by gender, where multimorbid women suffered an increased mental health risk compared with men. Gender differences should be addressed when delivering effective physical and mental healthcare support to disease-causing poverty, older-age, rural households.