Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province

ObjectivesThe characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases.MethodsThis study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30–79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities.ResultsThe overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20–1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19–3.19) and 28.19 (95% CI = 14.85–53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22–15.31).ConclusionThe prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions

Associations between circulating proteins and cardiometabolic diseases: a systematic review and meta-analysis of observational and Mendelian randomisation studies

Background: Integration of large proteomics and genetic data in population-based studies can provide insights into discovery of novel biomarkers and potential therapeutic targets for cardiometabolic diseases (CMD). We aimed to synthesise existing evidence on the observational and genetic associations between circulating proteins and CMD. Methods: PubMed, Embase and Web of Science were searched until July 2023 for potentially relevant prospective observational and Mendelian randomisation (MR) studies investigating associations between circulating proteins and CMD, including coronary heart disease, stroke, type 2 diabetes, heart failure, atrial fibrillation and atherosclerosis. Two investigators independently extracted study characteristics using a standard form and pooled data using random effects models. Results: 50 observational, 25 MR and 10 studies performing both analyses were included, involving 26 414 160 non-overlapping participants. Meta-analysis of observational studies revealed 560 proteins associated with CMD, of which 133 proteins were associated with ≥2 CMDs (ie, pleiotropic). There were 245 potentially causal protein biomarkers identified in MR pooled results, involving 23 pleiotropic proteins. IL6RA and MMP12 were each causally associated with seven diseases. 22 protein-disease pairs showed directionally concordant associations in observational and MR pooled estimates. Addition of protein biomarkers to traditional clinical models modestly improved the accuracy of predicting incident CMD, with the highest improvement for heart failure (ΔC-index ~0.2). Of the 245 potentially causal proteins (291 protein-disease pairs), 3 pairs were validated by evidence of drug development from existing drug databases, 288 pairs lacked evidence of drug development and 66 proteins were drug targets approved for other indications. Conclusions: Combined analyses of observational and genetic studies revealed the potential causal role of several proteins in the aetiology of CMD. Novel protein biomarkers are promising targets for drug development and risk stratification. PROSPERO registration number: CRD42022350327

Impacts of solid fuel use versus smoking on life expectancy at age 30 years in the rural and urban Chinese population: a prospective cohort study

Background: The impact of solid fuel use on life expectancy (LE) in less-developed countries remains unclear. We aimed to evaluate the potential impact of household solid fuel use on LE in the rural and urban Chinese population, with the effect of smoking as a reference. Methods: We used data from China Kadoorie Biobank (CKB) of 484,915 participants aged 30–79 free of coronary heart disease, stroke, or cancer at baseline. Analyses were performed separately for solid fuel use for cooking, solid fuel use for heating, and smoking, with participants exposed to the other two sources excluded. Solid fuels refer to coal and wood, and clean fuels refer to electricity, gas, and central heating. We used a flexible parametric Royston-Parmar model to estimate hazard ratios of all-cause mortality and predict LE at age 30. Findings: Totally, 185,077, 95,228, and 230,995 participants were included in cooking-, heating-, and smoking-related analyses, respectively. During a median follow-up of approximately 12.1 years, 12,725, 7,531, and 18,878 deaths were recorded in the respective analysis. Compared with clean fuel users who reported cooking with ventilation, participants who used solid fuels with ventilation and without ventilation had a difference in LE (95% confidence interval [CI]) at age 30 of −1.72 (−2.88, −0.57) and −2.62 (−4.16, −1.05) years for men and −1.33 (−1.85, −0.81) and −1.35 (−2.02, −0.67) years for women, respectively. The difference in LE (95% CI) for heating was −2.23 (−3.51, −0.95) years for men and −1.28 (−2.08, −0.48) years for women. In rural men, the LE reduction (95% CI) related to solid fuel use for cooking (−2.55; −4.51, −0.58) or heating (−3.26; −6.09, 0.44) was more than that related to smoking (−1.71; −2.54, −0.89). Conversely, in urban men, the LE reduction (95% CI) related to smoking (−3.06; −3.56, −2.56) was more than that related to solid fuel use for cooking (−1.28; −2.61, 0.05) and heating (−1.90; −3.16, −0.65). Similar results were observed in women but with a smaller magnitude. Interpretation: In this Chinese population, the harm to LE from household use of solid fuels was greater than that from smoking in rural residents. Conversely, the negative impact of smoking was greater than solid fuel use in urban residents. Our findings highlight the complexity and diversity of the factors affecting LE in less-developed populations

A wide landscape of morbidity and mortality risk associated with marital status in 0.5 million Chinese men and women: a prospective cohort study

Background: A comprehensive depiction of long-term health impacts of marital status is lacking. Methods: Sex-stratified phenome-wide association analyses (PheWAS) of marital status (living with vs. without a spouse) were performed using baseline (2004–2008) and follow-up information (ICD10-coded events till Dec 31, 2017) from the China Kadoorie Biobank (CKB). We estimated adjusted hazard ratios (aHRs) to evaluate the associations of marital status with morbidity risks of phenome-wide significant diseases or sex-specific top-10 death causes in China documented in 2017. Additionally, the association between marital status and mortality risks among participants with major chronic diseases at baseline was assessed. Findings: During up to 11.1 years of the median follow-up period, 1,946,380 incident health events were recorded among 210,202 men and 302,521 women aged 30–79. Marital status was found to have phenome-wide significant associations with thirteen diseases among men (p < 9.92 × 10−5) and nine diseases among women (p < 9.33 × 10−5), respectively. After adjusting for all disease-specific covariates in the final model, participants living without a spouse showed increased risks of schizophrenia, schizotypal and delusional disorders (aHR [95% CI]: 2.55, [1.83–3.56] for men; 1.49, [1.13–1.97] for women) compared with their counterparts. Additional higher risks in overall mental and behavioural disorder (1.31, 1.13–1.53), cardiovascular disease (1.07, 1.04–1.10) and cancer (1.06, 1.00–1.12) were only observed among men without a spouse, whereas women living without a spouse were at lower risks of developing genitourinary diseases (0.89, 0.85–0.93) and injury & poisoning (0.93, 0.88–0.97). Among 282,810 participants with major chronic diseases at baseline, 39,166 deaths were recorded. Increased mortality risks for those without a spouse were observed in 12 of 21 diseases among male patients and one of 23 among female patients. For patients with any self-reported disease at baseline, compared with those living with a spouse, the aHRs (95% CIs) of mortality risk were 1.29 (1.24–1.34) and 1.04 (1.00–1.07) among men and women without a spouse (pinteraction<0.0001), respectively. Interpretation: Long-term associations of marital status with morbidity and mortality risks are diverse among middle-aged Chinese adults, and the adverse impacts due to living without a spouse are more profound among men. Marital status may be an influential factor for health needs. Funding: The National Natural Science Foundation of China, the Kadoorie Charitable Foundation, the National Key R&D Program of China, the Chinese Ministry of Science and Technology, and the UK Wellcome Trust

Temporal change in multimorbidity prevalence, clustering patterns, and the association with mortality: findings from the China Kadoorie Biobank study in Jiangsu Province

Objectives: The characteristics of multimorbidity in the Chinese population are currently unclear. We aimed to determine the temporal change in multimorbidity prevalence, clustering patterns, and the association of multimorbidity with mortality from all causes and four major chronic diseases. Methods: This study analyzed data from the China Kadoorie Biobank study performed in Wuzhong District, Jiangsu Province. A total of 53,269 participants aged 30–79 years were recruited between 2004 and 2008. New diagnoses of 15 chronic diseases and death events were collected during the mean follow-up of 10.9 years. Yule's Q cluster analysis method was used to determine the clustering patterns of multimorbidity. A Cox proportional hazards model was used to estimate the associations of multimorbidity with mortalities. Results: The overall multimorbidity prevalence rate was 21.1% at baseline and 27.7% at the end of follow-up. Multimorbidity increased more rapidly during the follow-up in individuals who had a higher risk at baseline. Three main multimorbidity patterns were identified: (i) cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), (ii) respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), and (iii) mental, kidney and arthritis multimorbidity (neurasthenia, psychiatric disorders, chronic kidney disease, and rheumatoid arthritis). There were 3,433 deaths during the follow-up. The mortality risk increased by 24% with each additional disease [hazard ratio (HR) = 1.24, 95% confidence interval (CI) = 1.20–1.29]. Compared with those without multimorbidity at baseline, both cardiometabolic multimorbidity and respiratory multimorbidity were associated with increased mortality from all causes and four major chronic diseases. Cardiometabolic multimorbidity was additionally associated with mortality from cardiovascular diseases and diabetes, with HRs of 2.64 (95% CI = 2.19–3.19) and 28.19 (95% CI = 14.85–53.51), respectively. Respiratory multimorbidity was associated with respiratory disease mortality, with an HR of 9.76 (95% CI = 6.22–15.31). Conclusion: The prevalence of multimorbidity has increased substantially over the past decade. This study has revealed that cardiometabolic multimorbidity and respiratory multimorbidity have significantly increased mortality rates. These findings indicate the need to consider high-risk populations and to provide local evidence for intervention strategies and health management in economically developed regions

Healthy lifestyle and life expectancy free of major chronic diseases at age 40 in Chinese population: a prospective cohort study

Background: A healthy lifestyle has been associated with a longer life expectancy (LE). However, whether it also helps achieve gains in LE free of major non-communicable diseases (NCDs) and its share of total LE in Chinese adults remains unknown. Methods: We used data from China Kadoorie Biobank (CKB) of 451,233 adults aged 30-79 free of heart disease, stroke, cancer, chronic obstructive pulmonary disease (COPD), and asthma at baseline. Low-risk lifestyle factors included never smoking or quitting for reasons other than illness, no excessive alcohol use, being physically active, healthy eating habits, and healthy body shape. We built multistate life tables for individuals with different risk levels of lifestyle factors to calculate LE with and without diseases (cardiovascular diseases [CVDs], cancer, chronic respiratory diseases [CRDs, including COPD and asthma]) at age 40. For life table calculation, we used prevalence of lifestyle factors, transition rates, and hazard ratios (HRs) for three transitions (disease-free to disease onset, disease-free to death, and presence of disease to all-cause mortality). Findings: During a median follow-up of 11.1 years, we documented 111,002 new CVD cases, 24,635 cancer cases, 12,506 CRD cases, and 34,740 deaths. The adjusted HRs (95% confidence intervals [CIs]) of men adopting all five versus 0-1 low-risk factors was 0.56 (0.50, 0.63), 0.40 (0.20, 0.80), and 0.64 (0.50, 0.83) for baseline to disease, baseline to death, and disease to death, respectively; the corresponding values for women were 0.69 (0.64, 0.75), 0.57 (0.34, 0.94), and 0.57 (0.47, 0.69). The LE free of the three NCDs (95%CI) at age 40 for individuals with 0-1 low-risk factor was on average 23.9 (23.2, 24.6) years for men and 24.2 (23.5, 24.9) years for women. For individuals adopting all five low-risk factors, it was 30.2 (28.8, 31.6) years for men and 28.4 (27.2, 29.6) years for women, with an increase of 6.3 (5.1, 7.5) years (men) and 4.2 (3.6, 5.4) years (women). Correspondingly, the proportion of LE free of the three NCDs to total LE increased from 73.1% to 76.3% for men and from 67.6% to 68.4% for women. Interpretation: Our findings suggest that promoting healthy lifestyles through public health interventions could be associated with increased LE free of major NCDs and 'relative compression of morbidity' in the Chinese population

Associations of traditional cardiovascular risk factors with 15-year blood pressure change and trajectories in Chinese adults: a prospective cohort study

Objective: How traditional cardiovascular disease (CVD) risk factors are related to long-term blood pressure change (BPC) or trajectories remain unclear. We aimed to examine the independent associations of these factors with 15-year BPC and trajectories in Chinese adults. Methods: We included 15 985 participants who had attended three surveys, including 2004–2008 baseline survey, and 2013–2014 and 2020–2021 resurveys, over 15 years in the China Kadoorie Biobank (CKB). We measured systolic and diastolic blood pressure (SBP and DBP), height, weight, and waist circumference (WC). We asked about the sociodemographic characteristics and lifestyle factors, including smoking, alcohol drinking, intake of fresh vegetables, fruits, and red meat, and physical activity, using a structured questionnaire. We calculated standard deviation (SD), cumulative blood pressure (cumBP), coefficient of variation (CV), and average real variability (ARV) as long-term BPC proxies. We identified blood pressure trajectories using the latent class growth model. Results: Most baseline sociodemographic and lifestyle characteristics were associated with cumBP. After adjusting for other characteristics, the cumSBP (mmHg × year) increased by 116.9 [95% confidence interval (CI): 111.0, 122.7] for every 10 years of age. The differences of cumSBP in heavy drinkers of ≥60 g pure alcohol per day and former drinkers were 86.7 (60.7, 112.6) and 48.9 (23.1, 74.8) compared with less than weekly drinkers. The cumSBP in participants who ate red meat less than weekly was 29.4 (12.0, 46.8) higher than those who ate red meat daily. The corresponding differences of cumSBP were 127.8 (120.7, 134.9) and 70.2 (65.0, 75.3) for BMI per 5 kg/m2 and WC per 10 cm. Most of the findings of other BPC measures by baseline characteristics were similar to the cumBP, but the differences between groups were somewhat weaker. Alcohol drinking was associated with several high-risk trajectories of SBP and DBP. Both BMI and WC were independently associated with all high-risk blood pressure trajectories. Conclusions: Several traditional CVD risk factors were associated with unfavorable long-term BPC or blood pressure trajectories in Chinese adults

Reproductive factors and risk of lung cancer among 300,000 Chinese female never-smokers: evidence from the China Kadoorie Biobank study

Background Lung cancer is the leading cause of cancer mortality among Chinese females despite the low smoking prevalence among this population. This study assessed the roles of reproductive factors in lung cancer development among Chinese female never-smokers. Methods The prospective China Kadoorie Biobank (CKB) recruited over 0.5 million Chinese adults (0.3 million females) from 10 geographical areas in China in 2004–2008 when information on socio-demographic/lifestyle/environmental factors, physical measurements, medical history, and reproductive history collected through interviewer-administered questionnaires. Cox proportional hazard regression was used to estimate adjusted hazard ratios (HRs) of lung cancer by reproductive factors. Subgroup analyses by menopausal status, birth year, and geographical region were performed. Results During a median follow-up of 11 years, 2,284 incident lung cancers occurred among 282,558 female never-smokers. Ever oral contraceptive use was associated with a higher risk of lung cancer (HR = 1.16, 95% CI: 1.02–1.33) with a significant increasing trend associated with longer duration of use (p-trend = 0.03). Longer average breastfeeding duration per child was associated with a decreased risk (0.86, 0.78–0.95) for > 12 months compared with those who breastfed for 7–12 months. No statistically significant association was detected between other reproductive factors and lung cancer risk. Conclusion Oral contraceptive use was associated with an increased risk of lung cancer in Chinese female never-smokers. Further studies are needed to assess lung cancer risk related to different types of oral contraceptives in similar populations

Association between health insurance cost-sharing and choice of hospital tier for cardiovascular diseases in China: a prospective cohort study

Background: Hospitals in China are classified into tiers (1, 2 or 3), with the largest (tier 3) having more equipment and specialist staff. Differential health insurance cost-sharing by hospital tier (lower deductibles and higher reimbursement rates in lower tiers) was introduced to reduce overcrowding in higher tier hospitals, promote use of lower tier hospitals, and limit escalating healthcare costs. However, little is known about the effects of differential cost-sharing in health insurance schemes on choice of hospital tiers. Methods: In a 9-year follow-up of a prospective study of 0.5 M adults from 10 areas in China, we examined the associations between differential health insurance cost-sharing and choice of hospital tiers for patients with a first hospitalisation for stroke or ischaemic heart disease (IHD) in 2009–2017. Analyses were performed separately in urban areas (stroke: n = 20,302; IHD: n = 19,283) and rural areas (stroke: n = 21,130; IHD: n = 17,890), using conditional logit models and adjusting for individual socioeconomic and health characteristics. Findings: About 64–68% of stroke and IHD cases in urban areas and 27–29% in rural areas chose tier 3 hospitals. In urban areas, higher reimbursement rates in each tier and lower tier 3 deductibles were associated with a greater likelihood of choosing their respective hospital tiers. In rural areas, the effects of cost-sharing were modest, suggesting a greater contribution of other factors. Higher socioeconomic status and greater disease severity were associated with a greater likelihood of seeking care in higher tier hospitals in urban and rural areas. Interpretation: Patient choice of hospital tiers for treatment of stroke and IHD in China was influenced by differential cost-sharing in urban areas, but not in rural areas. Further strategies are required to incentivise appropriate health seeking behaviour and promote more efficient hospital use. Funding: Wellcome Trust, Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, China Ministry of Science and Technology, and National Natural Science Foundation of China

Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank

Background: Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population. Methods: Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training (n = 28,490) and testing sets (n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21–I23 and fatal I20–I25) and soft CAD (all fatal or nonfatal I20–I25) were analyzed separately. Results: In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19–1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (–0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4–6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model. Conclusions: In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little to no improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction