Stroke is the second leading cause of disability and death worldwide. In China, ∼2.4 million new stroke cases and ∼1.1 million stroke-related deaths occurred in 2013 (Wu et al., 2019), and the numbers are expected to rise over the next few decades primarily due to population growth and aging. Survivors of stroke often present with poor physical function and impaired cognition, leading to significantly decreased quality of life (Davis et al., 2019; She et al., 2021). Approximately 70–80% of stroke survivors require rehabilitation and long-term care (Nichols-Larsen et al., 2005). Post-stroke physical and cognitive conditions have been associated with demographics (e.g., age and gender), stroke features (e.g., size, location, and type), walking capacity, and psychosocial factors (e.g., social support, depression, and balance self-efficacy) (Salbach et al., 2006; Yoon et al., 2017; Ilunga Tshiswaka et al., 2018). As post-stroke function deficits may increase the risk of readmission, mortality, and early death (Gaynor et al., 2018), exploring factors associated with poor functional status among survivors of patients with stroke is greatly warranted if we seek to achieve the overall goal of rehabilitation services.

Stroke survivors commonly have comorbid conditions, especially older stroke patients. Evidence suggests that a clinical stroke could occur in the absence of comorbid conditions in less than 6% of cases (Nelson et al., 2017). Multimorbidity, the co-occurrence of two or more chronic diseases in the same person, is sometimes used interchangeably with comorbidity, which is defined as the presence of at least one long-term condition alongside an index condition (Gallacher et al., 2019). The coexisting of multiple chronic conditions and the presence of comorbidity patterns may be due to the fact that these health conditions share common risk factors and pathophysiology (e.g., heart disease and stroke) or causal/precursor relationship (e.g., atrial fibrillation and stroke) (Schäfer et al., 2010; Gallacher et al., 2019). Previously, community-based studies indicated that the burden and patterns of multimorbidity were associated with impaired physical functioning, poorer quality of life, and more frequent use of health care services (Ryan et al., 2015; She et al., 2019). However, there is a dearth of studies that have focused specifically on comorbidity patterns in the stroke population. We only identified a few studies that investigated the associations between comorbidity (mainly operationalized as a count of numbers of chronic health conditions or comorbidity index) and poor physical function among stroke patients, which reported mixed findings (Schmidt et al., 2014; Kabboord et al., 2016; Gallacher et al., 2019).

Thus, in this hospital-based cross-sectional study, we aimed to investigate the burden and pattern of chronic disease comorbidity among Chinese patients with first-ever ischemic stroke; and further to explore the associations between the number and patterns of comorbidity and physical and cognitive function outcomes among stroke patients.

In this hospital-based study, comorbidity was present in nine out of the ten patients with first-ever acute stroke. The greater number of comorbidities was associated with an increased likelihood of physical dependence and cognitive impairment. Furthermore, three patterns of comorbidity were identified among stroke patients, which generally showed significant positive associations with physical dependence and cognitive impairment. To the best of our knowledge, this is the first study in a large sample of Chinese stroke patients that investigates the burden and patterns of comorbidity as well as their associations with cognitive and physical functional outcomes, which provides a novel perspective to assess the health impacts of comorbidities on post-stroke functions.

The overall prevalence of comorbidity was generally comparable with that of the previous examination in stroke patients, which showed great variations across studies due to differences in methodology (e.g., sample characteristics and the number, definition, and measurement of morbidities) (Gallacher et al., 2014). Patients with two or more comorbidities were more likely to have sleep problems while less likely to be current smokers and drink alcohol in the past year than those having no or only one comorbidity. Stroke patients with more comorbidities may be more inclined to be recommended by their doctors to adopt a healthy lifestyle prior to the occurrence of clinical stroke. The vulnerability of sleep disorders in stroke patients with multiple comorbidities warrants attention and further investigation. Corroborating previous studies, female patients were more likely to have poor physical functional status following an acute stroke (Gargano and Reeves, 2007). In the present study, female patients were older, less educated, and had more comorbidities and higher prevalence of multimorbidity, which might contribute to worse physical functioning. This suggests that greater attention should be paid to female stroke survivors to properly manage comorbidities and physical dependence.

We further identified three patterns of comorbidity among the stroke patients (i.e., degenerative-cardiopulmonary, heart-gastrointestinal-psychiatric, and metabolic-kidney diseases) and assessed their relationships with functional outcomes. The first pattern was mainly characterized by degenerative diseases (e.g., joint diseases), heart failure, cancer, and respiratory diseases. Relatedly, a previous study of patients in the primary care setting in Spain identified a comorbidity pattern of psychogeriatric diseases, which covered geriatric diseases, heart failure, stroke, and neurocognitive diseases (Prados-Torres et al., 2012). Another observational study based on electronic health records also suggested that the pattern of degenerative diseases (e.g., arthropathy, cataract, osteoporosis, and hearing loss) was one of the most prevalent comorbidity patterns in Spanish patients with heart failure, possibly explained by the shared risk of aging and physical limitation (Gimeno-Miguel et al., 2019). Corroborating a prior study among the Chinese elderly population, cancer was clustered with degenerative diseases, reflecting the strong age dependence of these conditions (Gu et al., 2017). A community-based survey of older adults in China also identified the comorbidity pattern of cancer and pulmonary diseases and suggested that cancer tended to affect most frequently the respiratory tracts (Wang et al., 2017). While no prior studies have explored comorbidity patterns among stroke patients, future studies are warranted to confirm whether this comorbidity pattern remains across different populations and geographic regions.

The second pattern was represented by cardiovascular diseases, gastrointestinal diseases, and depression. The close associations between gastrointestinal diseases and affective disorders have been frequently reported in the general and clinical populations (Mayer et al., 2001). Acute life-threatening stressors and the central nervous system mechanisms play an important role in the development of gastrointestinal and psychiatric symptoms. It is worth noting that cardiovascular and gastrointestinal diseases as a separate pattern was not common in previous studies. However, the recently discovered contribution of gut-microbiota-derived molecules in the development of heart disease and its risk factors has significantly increased attention toward the connection between gut and heart diseases (Ahmadmehrabi and Tang, 2017). For instance, gastroesophageal reflux disease can lead to atrial fibrillation, in which multiple mechanisms may be involved in such as inflammation, autoimmunity, and exacerbated autonomic stimulation (Martins et al., 2015). Future research should focus on the underlying pathogenesis connecting these medical conditions, and the role of age and aging in the development of cardiovascular and gastrointestinal diseases.

Consistent with prior literature of studies among the community-dwelling elderly people (Wang et al., 2015), hypertension, diabetes, dyslipidemia, and obesity, the main components of metabolic syndrome, are established risk factors for cardiovascular diseases. This finding corroborates a prior systematic review that identified the major multimorbidity pattern of cardiovascular-metabolic diseases in the adult populations (Prados-Torres et al., 2014). Additionally, we found that kidney disease was clustered with metabolic factors and disorders. Extensive literature has indicated that metabolic syndrome and its individual components (e.g., obesity and diabetes) are associated with heightened risks of chronic kidney diseases (Kumar et al., 2013). For instance, it is known that chronic high blood pressure is a major cause of kidney disease, while chronic kidney disease is one of the most common causes of secondary hypertension (Freedman and Cohen, 2016). Patients with long-term hypertension (e.g., >5 years) were more likely to suffer from kidney disease with the small renal arteries of the glomerulus pathological changes (Mulè et al., 2008). The epidemiologic data also revealed that the prevalence of diabetic kidney disease increased with the growing epidemic of diabetes (Harjutsalo and Groop, 2014). Therefore, kidney disease should be recognized and prevented as an important complication of cardiovascular and metabolic diseases. Our study indicated that these metabolic diseases were among the most prevalent comorbidities among stroke patients. Metabolic syndromes are arguably prominent risk factors in the development of stroke and thus they are common comorbid diseases among patients with stroke.

Furthermore, we found that the number of comorbidities was associated with an increased likelihood of both physical dependence and cognitive impairment among stroke survivors, which is consistent with literature among the general older population (She et al., 2019). Notably, the associations between comorbidity and poor physical function were overall consistent when using the two different tools for assessment of post-stroke functional outcomes (i.e., BI and mRS), supporting the robustness of the findings. The results corroborate a previous study showing that comorbidity assessed using the Charlson comorbidity index was associated with physical dependence among stroke patients (Jiménez Caballero et al., 2013). Other studies also suggested that the presence of comorbidities such as heart disease and COPD were risk factors of cognitive impairment among stroke patients (Valkova and Peychinska, 2012).

Specifically, the three comorbidity patterns identified in our study showed generally significant associations with physical and cognitive functional outcomes. These results extended the findings from previous studies of comorbidity patterns and health outcomes among the general populations by disentangling the relationship between comorbidity patterns and functional status among stroke survivors. The heart-gastrointestinal-psychiatric disease and metabolic-kidney disease patterns showed relatively consistent associations with the three measurements of cognitive and physical functional outcomes. Similarly, prior studies indicated the associations between heart diseases and metabolic syndromes with various health outcomes (e.g., morbidity, functional decline, muscular weakness, and cognitive function) among stroke patients (Akbal et al., 2012; Li et al., 2016; Specogna et al., 2017). In contrast, the degenerative-cardiopulmonary pattern was associated with an increased likelihood of moderate-to-severe physical dependence assessed by BI but not by mRS. This may indicate the discrepancy of BI and mRS in monitoring the impact of degenerative-cardiopulmonary diseases on physical function in stroke patients. Prospective follow-up studies will help further clarify the longitudinal associations between comorbidity patterns and post-stroke functional status as well as the concordance between functional outcome parameters in patients with stroke.

Our hospital-based study covered a broad range of chronic conditions in a large sample of stroke patients that were defined by integrating information from face-to-face interviews, clinical examinations, and instrumental and laboratory tests. However, our study also has limitations. First, the cross-sectional nature of the study design does not allow causal inference of the observed associations and mediations, and the findings might be subject to selective survival bias. Thus, caution is needed when interpreting the findings. Second, the study participants from the two local general hospitals might not be representative of the stroke patient population in China, which should be kept in mind when generalizing our findings to a broad patient population. Third, although factor analysis has been most frequently used in the literature to explore comorbidity patterns (Ng et al., 2018), the results may vary with the definition, type, number, and prevalence of included chronic diseases as well as participants’ sociodemographic characteristics. For instance, some common heart diseases (i.e., heart failure, coronary heart disease, and arrhythmia) did not cluster into a single group, as indicated in our study. Therefore, the interpretation of findings should be incorporated with pathophysiological and clinical features of the chronic conditions. Fourth, the prevalence of arthritis might have been underestimated because the misdiagnosis and underdiagnosis of arthritis was fairly common in China, particularly in primary care settings (Tian et al., 2021). Fifth, functional outcomes were assessed within 2 weeks after hospitalization. The findings may be relevant to the functional status of stroke patients in the acute phase and may have implications for early rehabilitation intervention. Future studies that assess cognitive and physical functioning of patients during the period of a few months post-stroke are warranted to confirm the associations between comorbidity and functional outcomes. Finally, we were not able to explore the potential influences of stroke characteristics (e.g., severity, size, and location) on the associations between comorbidities and functional outcomes due to lack of detailed CT or MRI data.

Our study indicates that comorbidity is highly prevalent among Chinese stroke patients and that chronic conditions are clustered in certain patterns (e.g., patterns of degenerative-cardiopulmonary, heart- gastrointestinal-psychiatric, and metabolic-kidney diseases). Furthermore, the burden and patterns of comorbidity are associated with both poor physical and cognitive function in patients with acute ischemic stroke. These findings may have implications for the proper management of comorbidity among stroke patients in order to maintain and improve post-stroke physical and cognitive functioning outcomes but warrant further investigation in longitudinal studies. Assessments of comorbidity should therefore be routinely included in stroke research and clinical practice.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the study protocols from the Ethics Committee at the Jining No. 1 People’s Hospital, Shandong (No. 2015B006). The patients/participants provided their written informed consent to participate in this study.

RS, ZY, YH, ZZ, YD, JD, BB, and CQ: conception and design of the study. ZY, YH, ZZ, and BB: execution. RS: statistical analysis. RS and CQ: writing the first draft of the manuscript. DV, JL, and CQ: supervision. All authors revised the manuscript.