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Background <p>Multimorbidity substantially increases health and economic burdens, and reduces productivity in working-age individuals. We conducted a study using data from 393,170 working-age inpatients (18–59&#xa0;years) in Shaanxi, China, collected from 1998 to 2018. We aimed to identify multimorbidity profiles by sex and age and explore multimorbidity patterns using network analysis.</p> Methods <p>The sampling technique in our study involved forming two cohorts—blood donor and non-blood donor groups—from Shaanxi Province, China, based on age, sex, and region using a 1:1 matching method, resulting in 393,170 inpatient hospitalisation records for the working-age population. A total of 223,524 logistic regressions were conducted to explore statistically significant multimorbidity patterns, combined with network analysis, to create sex-specific and age-sex-stratified multimorbidity networks, identifying hub diseases with the most distinct multimorbidity patterns.</p> Results <p>Our study found that 46.61% of working-age inpatients had multimorbidity in the baseline hospitalisation dataset, with a higher prevalence in males (51.40%) than in females (41.46%). Males exhibited more complex multimorbidity networks with 1,233 unique multimorbidity patterns compared to 881 in females. Unemployment was associated with a higher multimorbidity risk (OR = 1.09, 95%CI: 1.02–1.15) in males, but had the opposite effect in females (OR = 0.93, 95%CI: 0.89–0.98). Hub diseases common to both sexes included liver diseases, dyslipidemia, fluid/electrolyte/acid–base balance disorders, type-2 diabetes mellitus, hypertension, heart failure, atherosclerosis, and gastritis/duodenitis. Hub diseases’ associated patterns accounted for 66.44% of patterns in males and 58.63% in females. With age, both sexes experienced an increase in multimorbidity proportion and network complexity. Males shifted from respiratory, infectious/parasitic and genitourinary disease-associated patterns to endocrine/nutritional/metabolic and circulatory disease-associated patterns. Females experienced a similar shift, with a notable increase in musculoskeletal/connective tissue disease-associated patterns. Digestive disease-associated patterns remained prevalent across all ages and sexes.</p> Conclusions <p>Multimorbidity networks in working-age inpatients exhibited greater complexity in males than females, growing with age. Hub diseases’ associated multimorbidity patterns dominated the network and multimorbidity patterns shifted toward endocrine/nutritional/metabolic and circulatory disease-associated patterns with age. Our study could contribute to the development of clinical interventions targeting working-age inpatient multimorbidity.</p>

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Sex and age-specific multimorbidity profiles among working-age inpatients in China: a comparative network analysis

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月24日

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  • Yining Bao,
  • Yang Sun,
  • Mengjie Wang,
  • Christopher K·Fairley,
  • Pengyi Lu,
  • Terence J. O’Brien,
  • Shu Su,
  • Xin Liu,
  • Lin Wang,
  • Hanting Liu,
  • Xueli Zhang,
  • Xianwen Shang,
  • Zhuoting Zhu,
  • Qianhui Lu,
  • Zengbin Li,
  • Hao Lai,
  • Jing Wang,
  • Ting Ma,
  • Liqin Wang,
  • Xinxin Xie,
  • Wenhua Wang,
  • Wenjie Wu,
  • Jiangcun Yang,
  • Lei Zhang

摘要

Background

Multimorbidity substantially increases health and economic burdens, and reduces productivity in working-age individuals. We conducted a study using data from 393,170 working-age inpatients (18–59 years) in Shaanxi, China, collected from 1998 to 2018. We aimed to identify multimorbidity profiles by sex and age and explore multimorbidity patterns using network analysis.

Methods

The sampling technique in our study involved forming two cohorts—blood donor and non-blood donor groups—from Shaanxi Province, China, based on age, sex, and region using a 1:1 matching method, resulting in 393,170 inpatient hospitalisation records for the working-age population. A total of 223,524 logistic regressions were conducted to explore statistically significant multimorbidity patterns, combined with network analysis, to create sex-specific and age-sex-stratified multimorbidity networks, identifying hub diseases with the most distinct multimorbidity patterns.

Results

Our study found that 46.61% of working-age inpatients had multimorbidity in the baseline hospitalisation dataset, with a higher prevalence in males (51.40%) than in females (41.46%). Males exhibited more complex multimorbidity networks with 1,233 unique multimorbidity patterns compared to 881 in females. Unemployment was associated with a higher multimorbidity risk (OR = 1.09, 95%CI: 1.02–1.15) in males, but had the opposite effect in females (OR = 0.93, 95%CI: 0.89–0.98). Hub diseases common to both sexes included liver diseases, dyslipidemia, fluid/electrolyte/acid–base balance disorders, type-2 diabetes mellitus, hypertension, heart failure, atherosclerosis, and gastritis/duodenitis. Hub diseases’ associated patterns accounted for 66.44% of patterns in males and 58.63% in females. With age, both sexes experienced an increase in multimorbidity proportion and network complexity. Males shifted from respiratory, infectious/parasitic and genitourinary disease-associated patterns to endocrine/nutritional/metabolic and circulatory disease-associated patterns. Females experienced a similar shift, with a notable increase in musculoskeletal/connective tissue disease-associated patterns. Digestive disease-associated patterns remained prevalent across all ages and sexes.

Conclusions

Multimorbidity networks in working-age inpatients exhibited greater complexity in males than females, growing with age. Hub diseases’ associated multimorbidity patterns dominated the network and multimorbidity patterns shifted toward endocrine/nutritional/metabolic and circulatory disease-associated patterns with age. Our study could contribute to the development of clinical interventions targeting working-age inpatient multimorbidity.