BACKGROUND: Whether adherence to a healthy lifestyle is associated with a lower risk of developing pneumonia and a better long-term prognosis remains unclear. This study aimed to investigate associations of individual and combined lifestyle factors (LFs) with the incidence risk and long-term prognosis of pneumonia hospitalization. METHODS: Using data from the China Kadoorie Biobank study, we used the multistate models to investigate the role of five high-risk LFs, including smoking, excessive alcohol drinking, unhealthy dietary habits, physical inactivity, and unhealthy body shape, alone or in combination in the transitions from a generally healthy state at baseline to pneumonia hospitalization or cardiovascular disease (CVD, regarded as a reference outcome), and subsequently to mortality. RESULTS: Most of the five high-risk LFs were associated with increased risks of transitions from baseline to pneumonia and from pneumonia to death, but with different risk estimates. The greater the number of high-risk LFs, the higher the risk of developing pneumonia and long-term mortality risk after pneumonia, with the strength of associations comparable to that of LFs and CVD. Compared to participants with 0-1 high-risk LF, the adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for transitions from baseline to pneumonia and from pneumonia to death in those with five high-risk LFs were 1.43 (1.28-1.60) and 1.98 (1.61-2.42), respectively. Correspondingly, the respective HRs (95% CIs) for transitions from baseline to CVD and from CVD to death were 2.00 (1.89-2.11) and 1.44 (1.30-1.59), respectively. The risk estimates changed slightly when further adjusting for the presence of major chronic diseases. CONCLUSION In this Chinese population, unhealthy LFs were associated with an increased incidence and long-term mortality risk of pneumonia.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Cardiovascular Diseases/etiology* ; China/epidemiology* ; Life Style ; Pneumonia/etiology* ; Prognosis ; Risk Factors ; Smoking

BACKGROUND: Prospective evidence on how offspring number influences morbidity and mortality remains limited. This study investigated the associations between number of offspring and morbidity and mortality risks among 0.5 million Chinese adults. METHODS: By using data from the China Kadoorie Biobank (CKB; n = 512,723, an approximately 12-year follow-up), sex-stratified phenome-wide association study (PheWAS) analyses were conducted to investigate associations between offspring number (without vs . with offspring; more than one vs . one offspring) and risks of ICD10-coded morbidity and mortality. Sex-specific adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs) were estimated by Cox proportional-hazards models. RESULTS: Among 210,129 men and 302,284 women aged 30-79 years, 1,338,837 incident events were recorded. PheWAS results revealed that offspring number was associated with disease risks across multiple systems. Cox models showed that childless men ( vs . one offspring) had higher risks for nine of 36 diseases, while childless women for five of 37. Each additional offspring was associated with reduced risks of mental and behavioral disorders in men (aHR [95% CI] = 0.93 [0.87-0.98]) and both mental and behavioral disorders (aHR [95% CI] = 0.93 [0.89-0.97]) and breast cancer (aHR [95% CI] = 0.82 [0.78-0.86]) in women. However, each additional offspring was associated with a 4% increase in the risk of cholelithiasis and cholecystitis in women (aHR [95% CI] = 1.04 [1.02-1.07]). Among 282,630 patients, 44,533 deaths were documented. Childless patients had higher mortality risk in both men (aHR [95% CI] = 1.37 [1.28-1.47]) and women (aHR [95% CI] = 1.27 [1.15-1.41]). For men, each additional offspring reduced mortality by 4% (aHR [95% CI] = 0.96 [0.95-0.98]), while for women, the lowest risk was observed among those with three to four offspring ( Pnonlinear <0.0001). CONCLUSIONS Offspring number is closely linked to morbidity and mortality risks. Further research is warranted to verify our findings and clarify the underlying mechanisms involved.
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; China/epidemiology* ; Morbidity ; Proportional Hazards Models ; Prospective Studies ; Risk Factors ; Family Characteristics ; Mortality ; East Asian People

Objective:To explore the relationship between BMI and levels of plasma amino acids and acylcarnitines in Chinese adults.Methods:Based on 2 182 individuals with targeted mass spectrometry metabolomic measurements from the first resurvey of the China Kadoorie Biobank, we assessed the linear and nonlinear associations between BMI and plasma levels of 20 amino acids and 40 acylcarnitines using linear regression models and restricted cubic spline models, and identified BMI-related metabolic pathways. We conducted one-sample Mendelian randomization (MR) with BMI genetic risk scores as the instrumental variable further to explore the potential causal relationships between BMI and 20 amino acids and 40 acylcarnitines, and tested for horizontal pleiotropy using the MR-Egger method.Results:Observational analyses found that BMI was associated with increased plasma levels of 3 branched-chain amino acids (isoleucine, leucine, and valine), 2 aromatic amino acids (phenylalanine and tyrosine), 3 other amino acids (cysteine, glutamate, lysine), and 7 acylcarnitines (C3, C4, C5, C10, C10:1, C14, and C16), and with decreased circulating levels of asparagine, serine, and glycine. Pathway analysis identified 7 BMI-related amino acids metabolic pathways (false discovery rate corrected all P<0.05), including branched-chain amino acids and aromatic amino acids biosynthesis, glutathione metabolism, etc. BMI showed a nonlinear relationship with leucine, valine, and threonine, and a linear relationship with other amino acids and acylcarnitines. One-sample MR analyses revealed that BMI was associated with elevated levels of tyrosine and 4 acylcarnitines [C5-DC(C6-OH), C5-M-DC, C12-DC, and C14], with tyrosine and acylcarnitine C14 positively correlated with BMI in both observational [the β values (95% CIs) were 0.057 (0.044-0.070) and 0.018 (0.005-0.032), respectively] and One-sample MR analyses [the β values (95% CIs) were 0.102 (0.035-0.169) and 0.104 (0.036-0.173), respectively]. The MR analyses of the current study satisfied the 3 core assumptions of instrumental variable. Conclusions:BMI was associated with circulating 11 amino acids and 7 acylcarnitines in Chinese adults, involving several pathways such as branched-chain amino acid and aromatic amino acid metabolism, fatty acid metabolism, and oxidative stress. There may be a causal relationship between BMI and tyrosine and acylcarnitine C14.

Tuberculosis, caused by Mycobacterium tuberculosis, is an infectious disease that most often affects the lungs. China is still among the high-burden tuberculosis countries in the world. Although the estimated incidence of tuberculosis in China has declined in recent years, the declining rate is slow. It still faces major issues such as a slower rate of decline, a widening gap between estimated and notified incidence, higher risk among middle-aged and older adults, a high number of cases among agriculture and related workers, and a heavier disease burden in the country's western regions. In addition, latent tuberculosis infection, drug-resistant tuberculosis, tuberculosis coinfection with HIV, and extrapulmonary tuberculosis have also exacerbated the disease burden of tuberculosis to some extent. This paper reviewed the epidemic characteristics of tuberculosis, the epidemiological triad, three links and two factors in the transmission process, the disease burden, and other aspects to provide a reference for formulating prevention and control strategies on tuberculosis.

Epidemiology and medical statistics are essential courses for undergraduate students majoring in clinical medicine. By studying the two courses, they can obtain the core skills for their future clinical practice. High-level medical schools both at home and abroad have accumulated successful experiences in curriculum, teaching methods and teaching models of the two disciplines. These colleges have also carried out the exploration of the curriculum reform centering on "organ systems integration". This paper summarizes the current status of epidemiology and medical statistics teaching and curriculum integration in representative medical schools both at home and abroad, and puts forward suggestions for deepening teaching reform and optimizing the curriculum system to provide reference for the integration of epidemiology and medical statistics curriculums for undergraduate students majoring in clinical medicine in China.

Biological age (BA) is a marker to accurately assess aging, facilitating the prediction of age-related diseases and promoting healthy aging. In recent years, first- and second-generation organ-system-specific BA has been developed using chronological age (CA) or aging-related outcomes (mortality) as training phenotypes and data from questionnaires, physical examinations, clinical biochemistry, imaging, and multi-omics to investigate the specificity of organ systems aging. Here, we review the methodologies for constructing BA, current efforts to assess organ system-specific BA, and related genome-wide association studies (GWAS). Previous studies predominantly used the first-generation BA method, using CA as training phenotypes. Organ-system-specific BA can accurately predict the disease risk of corresponding organ systems. We propose the development of organ system-specific BA through second-generation BA models and conducting GWAS and Mendelian randomization studies to explore organ system-specific aging processes, which will provide a theoretical foundation for the clinical application of organ system-specific BA.

Metabonomics is a life science research that uses high-throughput omics technology to identify and quantify all metabolites and has been widely used to examine the etiology of cardiometabolic diseases in recent years. As a significant component of systemic epidemiology, metabolomics provides insights into disease etiology from the perspective of metabolic changes. Research questions of metabolomics include assessing the associations of metabolites with cardiometabolic diseases, discovering novel biomarkers, and constructing risk prediction models. This article reviews the applications of metabolomics in the etiological research on type 2 diabetes, cardiovascular disease, hypertension, and subclinical atherosclerosis, as well as recent advance and future perspectives.

BACKGROUND: Severe liver disease (SLD), including cirrhosis and liver cancer, constitutes a major disease burden in China. We aimed to examine the association of genetic and healthy lifestyle factors with the incidence and prognosis of SLD. METHODS: The study population included 504,009 participants from the prospective China Kadoorie Biobank aged 30-79 years. The individuals were from 10 diverse areas in China without a history of cancer or liver disease at baseline. Cox regression was used to estimate adjusted hazard ratios (HRs) for incident SLD and death after SLD diagnosis associated with healthy lifestyle factors (smoking, alcohol, physical activity, and central adiposity). Additionally, the contribution of genetic risk for hepatitis B virus (HBV, assessed by genetic variants in major histocompatibility complex, class II, DP/DQ [ HLA - DP / DQ ] genes) was also estimated. RESULTS: Compared with those with 0-1 healthy lifestyle factor, participants with 2, 3, and 4 factors had 12% (HR 0.88 [95% confidence interval [CI] 0.85, 0.92]), 26% (HR 0.74 [95%CI: 0.69, 0.79]), and 44% (HR 0.56 [95%CI: 0.48, 0.65]) lower risks of SLD, respectively. Inverse associations were observed among participants with both low and high genetic risks (HR per 1-point increase 0.83 [95%CI: 0.74, 0.94] and 0.91 [95%CI: 0.82, 1.02], respectively; Pinteraction = 0.51), although with a non-significant trend among those with a high genetic risk. Inverse associations were also observed between healthy lifestyle factors and liver biomarkers regardless of the genetic risk. Despite the limited power, healthy lifestyle factors were associated with a lower risk of death after incident SLD among participants with a low genetic risk (HR 0.59 [95%CI: 0.37, 0.96]). CONCLUSIONS Lifestyle modification may be beneficial in terms of lowering the risk of SLD regardless of the genetic risk. Moreover, it is also important for improving the prognosis of SLD in individuals with a low genetic risk. Future studies are warranted to examine the impact of healthy lifestyles on SLD prognosis, particularly among individuals with a high genetic risk.
Humans ; Prospective Studies ; Incidence ; East Asian People ; Healthy Lifestyle ; Risk Factors ; Liver Neoplasms ; Prognosis ; China/epidemiology*

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 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.
Male ; Humans ; Female ; Coronary Artery Disease/genetics* ; Biological Specimen Banks ; East Asian People ; Risk Assessment/methods* ; Genetic Predisposition to Disease/genetics* ; Risk Factors ; Genome-Wide Association Study