Exploring multimorbidity profiles in middle-aged inpatients: a network-based comparative study of China and the United Kingdom

Multimorbidity, affecting 33.1% of adults globally in 2021, is a significant and rapidly growing public health concern worldwide [1, 2], with rising prevalence in England [3], Southern Europe [4], and China [5]. Multimorbidity leads to polypharmacy and adverse drug events [1, 6]. Furthermore, managing and treating multimorbidity puts a substantial strain on healthcare resources and increases health expenditure [1, 6, 7]. The World Health Organization recognizes the magnitude of the global multimorbidity challenge and has prioritized the goal of reducing the burden of multimorbidity [7].

Preventing multimorbidity in younger age is a more effective and economically viable strategy than treating it in older age. Elderly individuals with multimorbidity experience worse clinical outcomes, lower quality of life, reduced functionality, and increased hospitalization and mortality compared to single-disease counterparts [1, 6]. The likelihood of poor health status and limited physical capacity in the elderly increases by 3–9 times with multimorbidity [4]. Interventions in the early stages of life can reduce the subsequent disease burden of multimorbidity in later life stages. Middle age may be the perfect stage of life for prevention and early intervention, as severe chronic ailments are either absent or only in their early stages of development. Prevention and treatment for multimorbidity are much more efficient in this stage of life. Comprehending multimorbidity patterns in middle-aged populations has crucial implications for effective interventions that may reduce the subsequent disease and economic burden of multimorbidity [8, 9].

The current research on multimorbidity is riddled with significant knowledge gaps, despite numerous efforts. Existing studies are largely limited to developed countries, with only limited research from developing countries [10‐13]. Besides, the current research has focused on older adults [14‐16] but not the younger middle-aged population. More importantly, most existing studies have focused on a small group of chronic diseases, with limited exploration of multimorbidity on a wider spectrum of diseases, except only a handful of studies in Southwest China [17], Denmark [11], America [12], and Austria [13]. To date, no studies comprehensively compared comorbidity patterns at a population level between developed and developing countries.

Complex disease interactions significantly influence diagnosis and treatment and pivotal inpatient care. Untangling these less-understood relationships is crucial [13, 18]. Our study employed network analysis, an innovative tool revealing intricate interconnections among diseases [10‐13]. We used this approach to construct multimorbidity networks in China and the UK, identifying hub diseases with numerous comorbidity patterns. This innovation enhances our understanding of disease interactions and enables the development of targeted surveillance and prevention strategies, benefiting clinical practice.

Our study aims to compare the comorbidity patterns among inpatients in China and the United Kingdom (UK) to enhance the understanding of the differences in disease profiles in these countries. We facilitate the comparison based on two sizable population datasets in middle-aged populations from Northwest China and the UK-Biobank. The diagnosis of diseases is according to the International Statistical Classification of Diseases and Related Health Problems 10th revision (ICD-10) [19]. We included 14 systematic chapters on diseases and used sophisticated network analysis to develop multimorbidity networks, compare comorbidity patterns, and identify hub diseases between China and the UK [13]. Our findings are pivotal in global healthcare by highlighting disease disparities across countries with different economic development statuses. Our study will inform decision-makers to understand regional health challenges and endorse targeted strategies for multimorbidity prevention and treatment. Our findings will also guide global health institutes and governments, aiding in the formulation of more effective multimorbidity prevention strategies, thereby reducing both disease and economic burden caused by multimorbidity.

This study is the first to compare comorbidity patterns in Chinese and UK inpatients using multimorbidity networks. We observed higher per-capita disease counts and a greater proportion of multimorbidity among aging Chinese inpatients compared to their UK counterparts. Chinese inpatients consistently exhibit more complex multimorbidity networks. Comorbidities involving essential hypertension (I10), dyslipidemia (E78), type 2 diabetes mellitus (E11), and gastritis and duodenitis (K29) are most common in both populations. However, Chinese inpatients consistently demonstrate a higher frequency of comorbidities in circulatory diseases and endocrine/nutritional/metabolic diseases. In the UK, digestive diseases-related and genitourinary diseases-related comorbidities are also common, particularly the latter among female inpatients.

Our investigation reveals that Chinese inpatients exhibit a higher proportion of multimorbidity and a more intricate multimorbidity network compared to their UK counterparts. Notably, the lower socio-economic status of China, coupled with environmental and early life stressors associated with poverty and inadequate social infrastructure, may lead to the earlier onset of diseases, consequently resulting in a higher frequency of multimorbidity [1]. Besides, lower health literacy in China leads to delayed diagnosis and treatment of chronic diseases and comorbidities [1, 27, 28]. Lifestyle factors, such as tobacco use, unhealthy diets, and physical inactivity, are also more common in China [28, 29]. Furthermore, limited healthcare access and the absence of state-driven multimorbidity prevention programs in China result in greater disease burden and complexity [1]. Conversely, the UK has implemented comprehensive type 2 diabetes mellitus-related complication surveillance to manage multimorbidity in diabetic individuals [30]. The National Institute for Health and Care Excellence provides key healthcare services for adults with multimorbidity [31], a key resource currently lacking in China.

Our study confirms previous findings that circulatory and endocrine/nutritional/metabolic diseases-related comorbidities are prevalent in China [17, 32]. These patterns were echoed by a recent systematic review by Prados-Torres et al., where similar findings have been reported in 10 of the 14 multimorbidity studies [32]. The heightened prevalence of these comorbidities in China may be linked to the swift transformation of dietary patterns in the population. Western-style diets, increasingly popular in developed Chinese regions, have led to greater red and processed meat consumption [1, 33, 34]. Additionally, our data from Shaanxi Province may also indicate a common “starchy” dietary pattern, characterized by rice, noodles, and flour products in this Chinese region [35]. This dietary pattern may contribute to overweight and obesity, resulting in abnormal adipocytokine secretion and elevated risk of related comorbidities [36, 37]. Other lifestyle issues, including tobacco use, sedentary behavior, abnormal sleep duration, and low social participation, have also been identified as contributing risk factors to circulatory and endocrine/nutritional/metabolic diseases-related comorbidities in China [29, 34, 38, 39].

In the UK, there are multiple underlying reasons for the notable comorbidities related to digestive and genitourinary diseases. First, UK inpatients exhibit higher awareness of and greater access to clinics for diagnostic testing due to good public health literacy. UK clinicians also place greater emphasis on managing genitourinary and digestive diseases, resulting in more frequent diagnoses of these comorbidities. Second, the population-wide average of standard drinks consumed per day is higher in the UK than in China [40], with excessive alcohol consumption contributing to alterations in the gut microbiome and gut epithelial integrity that increase the likelihood of digestive disorders and their associated comorbidities [41‐43]. Excessive alcohol consumption may also cause urinary system diseases such as chronic kidney disease [44, 45]. It may also contribute to risky sexual behavior and increased risk of sexually transmitted infections, leading to the development of genitourinary diseases and associated comorbidities [46]. Female UK inpatients have a high prevalence of genitourinary disease-related comorbidities, likely attributed to their older age. The older age means a higher likelihood of experiencing menopause, which is associated with a decrease in estrogen stimulation and the development of genitourinary disorders such as vaginitis, bladder dysfunction, and urethral dysfunction [47, 48]. Other potential contributing factors include tobacco use, a higher number of sexual partners, and higher fertility rates in the UK [29, 46, 48‐51].

We discovered that prevalent diseases often serve as hub diseases in multimorbidity networks. We found that comorbidities covered by the hub diseases’ associated network account for over 68% and 55% frequency of comorbidities in the complete network for China and the UK, respectively. This finding highlights the potential importance of identifying hub diseases as a means of recognizing potential risk factors and underlying biological mechanisms for multimorbidity. Targeted surveillance and prevention of hub diseases could reduce the onset of associated comorbidities, improve healthcare utilization, and enable healthcare professionals to provide appropriate treatment plans [1]. This approach to care would shift from a single-condition treatment measurement to a patient-centered approach, allowing for comprehensive care and reducing the burden of polypharmacy. Policymakers can use these findings to establish more effective multimorbidity treatment guidelines, while patients can receive cost-effective treatment, and healthcare providers can enhance treatment efficiency and save medical resources [52, 53].

The main strength of our study is the important comparison of multimorbidity patterns in 14 ICD-10 disease chapters among middle-aged inpatients in China and the UK. However, several limitations still existed. First, we used undirected graphs based on baseline inpatient records, rather than directed graphs derived from inpatient cohort data. Our primary objective was to compare comorbidity patterns between two regions. However, conducting direct comparisons of temporal multimorbidity patterns between these regions posed challenges due to different observation periods. Second, our study, exclusively examining inpatients, may introduce sampling bias, limiting our understanding of multimorbidity. This hinders generalizability to outpatients with different patterns and factors. Third, the initial absolute number of diagnoses in different datasets which is related to the accessibility of different healthcare systems will affect the complexity of the multimorbidity network. Fourth, half of Chinese inpatients being blood donors may lead to underestimating disease prevalence due to the healthy donor effect, introducing sampling bias, and compromising the study’s representativeness for the general population, affecting its external validity. Fifth, the high prevalence of misdiagnosis and missed diagnosis in China may have underestimated comorbidity complexity. Sixth, the UK-Biobank population, being healthier and more health-literate than the general UK population, may underestimate disease prevalence and miss common comorbidity patterns, making it less representative of the broader population. Nevertheless, our conclusion remains that multimorbidity networks are more complex in Chinese inpatients than in those in the UK.

In conclusion, we identified higher multimorbidity prevalence and more diverse comorbidity patterns and complex multimorbidity networks in Chinese inpatients, compared to the UK inpatients. While circulatory diseases and endocrine/nutritional/metabolic disease-related comorbidities are common in both Chinese and UK inpatients, digestive and genitourinary diseases-related comorbidities are more specific in UK inpatients. Hub diseases’ associated network accounts for the majority of comorbidity counts in the complete network in both China and the UK. Identifying common comorbidity patterns and hub diseases can inform prevention strategies, thus enhancing patient-centered care, reducing healthcare burden, and providing valuable insights for policymakers, patients, and treatment guidelines in different regions.