BACKGROUND: Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults. METHODS: We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality. RESULTS: Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease. CONCLUSION Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.
Aged ; Arthritis, Rheumatoid ; Asians ; China/epidemiology* ; Humans ; Hypertension ; Middle Aged ; Multimorbidity

Objective:To describe the prevalence of multimorbidity and its secular trend, and to explore the common patterns of multimorbidity in Chinese adults.Methods:A total of 25 033 participants who attended the second resurvey of China Kadoorie Biobank (CKB) were included in the study. We used data collected both at baseline (2004-2008) and at resurvey (2013-2014). A total of 13 chronic conditions were included, defined by self-reported, physical examination, and blood sample testing. Multimorbidity was defined as co-existence of two or more chronic conditions. Patterns of multimorbidity were explored using hierarchical cluster analysis.Results:The mean age of participants was (51.5±10.1) years at baseline and (59.5±10.2) years at second resurvey. The prevalence of multimorbidity increased from 33.5% to 58.1% over (8.0±0.8) years of follow-up. The average number of chronic conditions per person increased from 1.15 to 1.82 and all participants increased 0.42 conditions per 5 years on average. Participants who were older, less educated or lived in urban areas had a higher prevalence of multimorbidity and a higher increase in the number of chronic conditions. The increase in the number of chronic conditions was also higher among smokers and heavy alcohol drinkers. The most common multimorbidity pattern in the present population consisted of obesity, hypertension, diabetes, stroke, and heart disease.Conclusions:The prevalence of multimorbidity in Chinese adults is increasing rapidly due to ageing population. Populations of different sociodemographic background and lifestyle habits may have different prevalence of multimorbidity and changes in rates over time.

Objective:To compare the consistency of frailty status measured by Fried phenotype and frailty index composed of different numbers of deficits, and their prospective associations with risk of mortality.Methods:Data of 23 615 participants from the second resurvey of the China Kadoore Biobank (CKB) was used. Fried phenotype was constructed using five phenotypes, and frailty indexes (FI) were constructed using 28 and 40 deficits, respectively. We calculated the Weighted Kappa coefficient to compare the consistency of three measures in the classification of frailty status. Cox regression was performed to analyze the association of frailty status with risk of mortality.Results:The frailty prevalence calculated by Fried phenotype, FI-28, and FI-40 were 5.4%, 7.9%, and 4.0%, respectively. The Kappa coefficients of Fried phenotype with FI-28 and FI-40 were 0.357 and 0.408, respectively. The Kappa coefficients of FI-28 and FI-40 was 0.712. During an average of (3.9±0.5) years of follow-up, 755 participants died. When Fried phenotype was used, compared with the robust participants, the prefrail and frail participants had increased risk of mortality, the multivariable-adjusted HRs were 1.60 (95% CI: 1.32-1.94) and 2.90 (95% CI: 2.25-3.73), respectively. When FI-28 was used, the corresponding HRs were 1.71 (95% CI: 1.39-2.11) and 2.52 (95% CI:1.95-3.27) for prefrail and frail participants, and when FI-40 was used, the corresponding HRs were 1.98 (95% CI:1.60-2.44) and 3.71 (95% CI: 2.80-4.91). The association of frailty status with mortality differed in different age groups, with the association stronger in younger adults than in older adults. Conclusion:Fried phenotype and frailty index constituted with different numbers of deficits showed good consistency; which can be used to well predict the risk of mortality.

Objective:To evaluate the transitions of frailty status and related factors influencing its worsening in middle-aged and elderly adults.Methods:Data was obtained from the Beijing MJ Health Screening Center. A total of 13 689 participants who attended health checkups at least twice during 2008-2019 and had more than three years' intervals during these two health checkups were included in the study. The frailty index comprising 28 variables was used to measure frailty status. Frailty was defined as frailty index ≥0.25, and prefrailty was defined as frailty index >0.10 and <0.25. Logistic regression analysis was performed to investigate the association of socio-demographic factors and lifestyle characteristics with the worsening of frailty status, stratified by frailty status at the first health checkup.Results:The mean age at the first and last health checkups were (42.3±9.2) and (47.9±9.3) years, respectively. The mean interval during these two health checkups was (5.7±1.9) years. At the first health checkup, the prevalence of frailty and prefrailty were 2.5% and 50.3%, respectively. While at the last health checkup, the prevalence of frailty and prefrailty rose to 3.9% and 55.4%. Of all participants, 67.3% remained in the same frailty state, 21.2% worsening, and 12.5% improving. In robust participants at the first health checkup, older age, female, low education level, smoking cessation, daily smoking, being general obesity measured by BMI or central obesity measured by WHR showed an increased the risk of worsening frailty status. However, in prefrail participants at the first health checkup, older age, female, general, or central obesity presented as risk factors for worsening frailty status.Conclusion:Modifiable factors such as low education level, smoking, and obesity may increase the risk of worsening frailty status.

Biological age (BA) can be used to measure the aging process of individuals and make up for the deficiency that chronological age cannot explain the discrepancy of health status among individuals at same chronological age. In recent years, multiple measurements of BA based on clinical or phenotypic, molecular biological, or compound indicators have emerged. In the paper, we summarize some common measurements of BA and compare their validities.

[Abstract] Objective:To explore the clinical significance of multiple serumcytokines in early diagnosis and progression assessment of gastric adenocarcinoma. Methods: Peripheral blood samples of 85 healthy subjects (healthy control group) and 81 patients with pathologically confirmed gastric adenocarcinoma (gastric cancer group) were collected from November 2017 to February 2018 at Shanxi Cancer Hospital. Serum levels of 17 cytokines (including IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-15, IL-17A, TNF-α, TNF-β, GM-CSF, G-CSF, IFN-γ, IP-10, MCP-1 andVEGF-A) were measured byAimPlex multiplex assay technology.Their diagnostic values were analyzed by receiver operating characteristic (ROC) curve. Results: Serum levels of IL-10, IL-8, IL-6, IP-10, MCP-1, VEGF-Aand IL-12p70 were significantly higher in gastric cancer patients than those in healthy controls (all P<0.01). There were significantly increasedlevelsofIL-8,IL-6and VEGF-Ain advanced-stage gastriccancer(stageI/II)groupoverearly-stage gastric cancer (stage III/IV) group (all P<0.01).AUC (areas under the curve) of IL-8, IL-6, IL-10, IP-10, MCP-1, IL-12p70 and VEGF-Afor distinguishing early-stage gastric cancer patientsfromhealthy controls was0.98,0.92,0.89,0.84,0.76,0.74 and 0.58, respectively. The diagnostic sensitivity of IL-8, IL-6 and IL-10 was 97.4%, 89.5% and 97.4%, respectively, and the specificity was 87.1%, 85.9%and 77.6%, respectively.TheAUCof IL-8, IL-6 andVEGF-Afor distinguishing advanced-stage gastric cancer patients from early-stage gastric cancer patients was 0.82, 0.72 and 0.69, respectively. Thediagnosticsensitivity of IL-8, IL-6 and VEGF-A was 83.7%, 60.5% and 41.9%, respectively, and the specificity was71.1%,76.3%and 92.1%, respectively. Conclusion: ThecombineddetectionofserumIL-8,IL-6andIL-10 may be a potential approach for early screening of gastric adenocarcinoma, which canalsobeusedtoassessthe progression of gastric adenocarcinoma.

Objective To investigate the expressions of Th17 lymphocytes and interleukin-17 (IL-17) in peripheral blood of patients with non-small cell lung cancer (NSCLC) and its clinical significance. Methods Sixty patients with primary and untreated NSCLC were enrolled and designed as experimental group, at the same time, 60 healthy volunteers were collected as control group. Flow cytometry (FCM) was used to detect the level of Th17 lymphocytes. Enzyme linked immunosorbent assay (ELISA) was used for detecting the level of IL-17. The relationship between the expression levels of Th17 and IL-17 in peripheral blood and clinicopathological features was compared between the two groups. Results The peripheral blood levels of Th17 lymphocytes and IL-17 in the experimental group [(1.7±1.2) ％, (8.3±2.5) pg/ml] were higher than those in the control group [(0.9 ±0.6) ％, (5.4 ±1.2) pg/ml] (P< 0.05). The peripheral blood expression of Th17 lymphocytes and IL-17 in patients with smoking history [(1.8±1.2) ％, (8.8±3.7) pg/ml] were higher than those in patients without smoking history [(1.6±1.2)％, (8.0±2.2) pg/ml], and the peripheral blood expression of Th17 lymphocytes and IL-17 were higher in patients with squamous-cell carcinoma [(1.8 ±1.2) ％, (9.4 ±4.7) pg/ml] than those in patients with adenocarcinoma [(1.6±1.1) ％, (7.3±3.9) pg/ml], furthermore, they were also higher in patients with stage Ⅲ-Ⅳ than those in patients with stage Ⅰ-Ⅱ (P < 0.05). Conclusion Th17 lymphocytes and IL-17 play certain roles in the occurrence and progression of NSCLC.

Objective To detect the expression levels of serum ITAC, Fractalkine, IL-8, IL-17A, IL-7 and TNF-α in patients with gastric cancer, and to explore correlation among them, as well as their association with different clinical characteristics.Methods The levels of the 6 kinds of cytokines in serum of 46 gastric cancer patients (gastric cancer group) and 30 healthy people (healthy control group) were detected.Results Compared with those in healthy control group, the levels of serum ITAC, Fractalkine, IL-8, IL-17A, IL-7 and TNF-α in gastric cancer group were significantly increased [22.26 (32.83) pg/ml vs 11.95 (9.99) pg/ml, P =0.001;62.21 (82.23) pg/ml vs 26.47 (50.87) pg/ml, P =0.050;4.50 (10.38) pg/ml vs 2.06 (3.17) pg/ml, P =0.002;0.83 (2.01) pg/ml vs 0.21 (0.85) pg/ml, P=0.013;3.46 (1.90) pg/ml vs 2.11 (1.48) pg/ml, P=0.001;1.21 (1.13) pg/ml vs 0.79 (0.37) pg/ml, P ＜ 0.001].There were correlations between cytokines (all P ＜ 0.05).The level of serum cytokines was no significant difference between gastric cancer patients with lymph node metastasis and those without lymph node metastasis (P ＞ 0.05).Conclusions The high level of serum ITAC, Fractalkine, IL-8, IL-17A, IL-7 or TNF-α may be related to the occurrence and development of gastric cancer.High level of serum IL-8 may be a marker of poor prognosis of gastric cancer, and interaction between the various cytokines also has a certain association with tumorigenesis.

Objective To detect the expression levels of multiple serum chemokines including IFN-inducible T cell chemoattractant (ITAC),Fractalkine,macrophage inflammatory protein (MIP)-3α,IL-8,MIP-lα,MIP-1β in patients with lung cancer and explore their association with the clinical characteristics of lung cancer as well as the correlations among these chemokines.Methods Forty newly diagnosed patients with lung cancer and thirty healthy controls were enrolled for detection of the serum levels of 6 kinds of chemokines by Luminex technology.The correlations of clinical characteristics of lung cancer with these chemokines and the correlations among these chemokines were analyzed by SPSS 17.0 software.Results The serum levels [M (QR)] of IL-8,Fractalkine and MIP-3α in patients with lung cancer were 5.16 (4.74),128.45 (141.89),10.31 (8.88) respectively,and 2.01 (0.95),61.46 (74.81),8.08 (5.87) respectively in control group,with significant differences (Z =-4.783,P ＜0.001;Z =-4.046,P ＜0.001;Z =-3.105,P =0.002).The expression of MIP-1β in lung adenocarcinoma was significantly higher than that in squamous carcinoma [18.32 (12.27) vs.13.72 (7.31),Z =-2.212,P =0.027],and of ITAC in squamous carcinoma was significantly higher than that in small cell lung cancer [24.51 (22.48) vs.9.28 (4.85),Z =-2.460,P =0.014].The expressions of MIP-3α and Fractalkine were positively correlated in the two groups (r =0.619,P＜0.001;r=0.766,P＜0.001).Conclusion The expressions of IL-8,Fractalkine and MIP-3α increase significantly in lung cancer patients,and they are may play important roles in metastatic lung cancer.

Objective To investigation the expressions of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and its receptors in non-small cell lung cancer (NSCLC) and their clinical significances.Methods The serum expression levels of TRAIL in 79 cases of NSCLC and 80 cases of normal subjects were detected by enzyme-linked immunosorbent assay (ELISA).The expressions of TRAIL-R2 and TRAIL-R4 in 42 cases of NSCLC and matched normal tissues were detected by immunohistochemistry.The relationships among TRAIL,TRAIL-R2,TRAIL-R4 and clinicopathologic features of NSCLC were analyzed.Results The expression of TRAIL in NSCLC patients was lower than that in normal human [(994.3 ±293.0)ng/ml vs.(1 141.7 ±266.1)ng/ml,t =3.29,P =0.00].The expression of TRAIL was closely correlated with clinical stage (F =2.28,P =0.00) and differentiated degree (t =5.76,P =0.00).The positive expression rate of TRAIL-R2 in NSCLC was 73.8％ (31/42),significantly lower than that in the normal tissue 100.0％ (42/42) (x2 =3.88,P =0.05).The expression of TRAIL-R2 was closely correlated with clinical stage (x2 =27.89,P=0.00) and differentiated degree (x:=9.50,P =0.00).The positive expression rate of TRAIL-R4 in NSCLC was 81.0％ (34/42),significantly higher than that in the normal tissue 50.0％ (21/42) (x2 =7.34,P =0.01).The expression of TRAIL-R4 was also closely correlated with clinical stage (x2 =17.82,P =0.00) and differentiated degree (x2 =4.47,P =0.03).There was a negative correlation between the expression of TRAIL-R2 and TRAIL-R4 in NSCLC (r =-0.67,P=0.01).Conclusion The decrease of TRAIL and TRAIL-R2 and increase of TRAIL-R4 expression may promote the occurrence and development of NSCLC,and they may provide targets for clinical treatment of NSCLC.