Cohort Profile: the China Multi-Ethnic Cohort (CMEC) study

Non-communicable diseases (NCDs), such as cardiovascular disease, cancer, chronic respiratory disease and diabetes, have become leading causes of death worldwide.1,2 It is estimated that 63% of all global deaths are due to NCDs,3 with an increasing contribution from low- and middle-income countries. The prevalence and incidence of NCDs are not evenly distributed between and within countries because of variations in environment, lifestyle, socio-economic position, genetic factors and access to health care services.4,5 China has been facing a growing burden of NCDs with strong regional variation.6 Most primary data on the prevalence of and risk factors for NCDs come from Central and Eastern China,7,8 with a mix of ethnicity, socio-economic status, geography, and dietary, behavioural and lifestyle factors that is very different compared to Western China. Ethnicity in particular is increasingly seen as an important risk factor for NCDs throughout the world.9 Ethnic minority groups are known to have different outcomes for cancer,10 diabetes,11 cardiovascular diseases9 and respiratory diseases12 compared with ethnic majority groups. China, with its 55 different ethnic minority groups, represents the largest ethnic minority population in the world (114 million in 2010).13 However, remarkably little is known about ethnic variation in the prevalence, incidence and/or risk factors for NCDs in China. One national cross-sectional study suggested that Tibetans had a significantly lower prevalence of diabetes than the majority Han population.14 Another national cross-sectional study found large ethnic differences in haemoglobin distribution and anaemia prevalence.15 To our knowledge, these are the only studies examining national ethnic variation in NCDs in China. China’s Southwest region is home to the 56 ethnic groups living in China.13 Ethnicity not only represents genetic diversity but also characterizes strong local identities for work and daily life, such as the Tibetan people in rural areas who usually live a nomadic life. Many ethnic minorities live in remote areas, speak different dialects and share some unique dietary habits, e.g. Tibetan people favouring butter tea16 or the Miao people’s diet rich in sour soup (fermented acidic liquid).17 Although substantial efforts have been made to improve the socio-economic status of ethnic minorities,18 they still tend to be much poorer than their Han counterparts. Many ethnic minorities live in distinct geographical environments and climates. Tibetans, for example, live in the Tibetan Plateau with low barometric pressure, which could cause high-altitude hypoxia or decreased oxygen levels.19 In contrast, >100 million Han people live in the low-altitude Sichuan Basin and are exposed to severe air pollution. To address the urgent need for data on the prevalence of, risk factors for and associated conditions of NCDs across various ethnicities in resource-constrained settings, the China Multi-Ethnic Cohort (CMEC) study was launched in 2017. This cohort study is supported by the National Key Research & Development Program of China. The CMEC aims to involve 100 000 middle-aged adults in five provinces of Southwest China. The recruitment started in May 2018 and was completed in September 2019. The study is based on a standardized survey approach and multiple stringent quality control (QC) measures. Such steps are essential, considering not only the substantial research gap but also that the study of NCDs across multiple ethnicities is likely to reveal important and potentially novel avoidable causes, which may inform disease prevention programmes in other populations worldwide. The CMEC was established in five provinces of Southwest China (Figure 1) and the baseline survey was conducted between May 2018 and September 2019. Given a full consideration of China’s ethnic characteristics, population size and NCD patterns, we aimed to include participants from the Tibetan, Yi, Miao, Bai, Bouyei and Dong ethnic groups. In addition, to compare those ethnic minorities with the majority of people in China, the Han ethnic population was also recruited into our cohort. A multistage, stratified cluster sampling method was used to obtain samples from community-based populations. In the first stage, one to two minority settlements for each ethnic group were selected as our study sites. To achieve better representation of variation with regard to geography and development state, settlements from high plateaus, basins, rural areas and highly air-polluted regions were given special consideration. In the second stage, 1–8 communities (depending on the size of communities) in each settlement were selected by the local Centres for Disease Control and Prevention (CDCs), taking into account migration status, local health conditions and, most importantly, ethnic structure. In the final stage, participants who met our inclusion criteria were invited to participate in our studies in consideration of both sex ratio and age ratio. The estimated population response rate was ∼60% (60–90% in rural areas and 40–60% in urban areas). Spatial distribution of baseline populations Spatial distribution of baseline populations The inclusion criteria included (i) age 30–79 years on the day of the investigation (except for Tibetan populations, whose inclusion criterion for age was 18–79 years, given the shorter life expectancy in this population); (ii) permanent residents, capability of completing baseline surveys and availability to complete follow-up studies; and (iii) complete questionnaire interviews, physical examinations and blood tests. The exclusion criteria were as follows: (i) inability to provide a unique national identification card; (ii) severe physical or mental diseases (e.g. schizophrenia and bipolar disorder); and (iii) refusal to comply with the requirements of the study. Overall, a total of 99 556 participants were enrolled in our cohort including 55 443 Han, 12 730 Tibetan, 6283 Yi, 5559 Miao, 6310 Bai, 5992 Bouyei and 7239 Dong ethnic people. All of the participants signed an informed consent form prior to data collection. Ethical approval was received from the Sichuan University Medical Ethical Review Board (K2016038). The follow-up stage will be conducted in both passive and active modes. In passive mode, we will conduct follow-up via linkage to the electronic records of disease and death registries, mainly relying on the National Electronic Disease Surveillance System (NEDSS) and the National Health Insurance (NHI) claim databases. Through annual data linkage with these established electronic disease registries, various health outcomes of the study participants will be obtained. The diagnoses of these conditions are based on well-accepted international standards. In China, the underlying and contributing causes of death are coded according to the 10th version of the International Statistical Classification of Diseases (ICD-10).20 All deaths during follow-up will be checked regularly for cause-specific mortality through the death certificates reported to the regional CDCs and the death registries. In active mode, all surviving study participants will be invited to resurvey every 3–5 years. We will re-estimate the status of risk exposure and document the incidence of multiple diseases (e.g. cancer, stroke, heart attack, diabetes mellitus, hypertension) using the same measurements as in the baseline survey (see more details in the following section). We aim to minimize the expected rate of loss to less than an estimated 8% in the next round of follow-up. Table 1 summarizes the measurements collected from the CMEC baseline survey, which consisted of an electronic questionnaire with face-to-face interviews, medical examinations and clinical laboratory tests. In addition, we collected biological specimens, including blood, saliva and stool, which were stored for further use. In addition to the individual-level data for each participant, we also collected regional-level data for each investigation site. More details on these measurements are described below. Summary of measurements at the baseline survey in the China Multi-Ethnic Cohort study 5 for male 8 for female Liver, gallbladder, spleen, pancreas, kidney. Uterus, ovaries and fallopian tubes (additional for female participants). 5 for male 8 for female Liver, gallbladder, spleen, pancreas, kidney. Uterus, ovaries and fallopian tubes (additional for female participants). Includes common food items and ethnic group-specific food items. Only available for high-altitude areas. Summary of measurements at the baseline survey in the China Multi-Ethnic Cohort study 5 for male 8 for female Liver, gallbladder, spleen, pancreas, kidney. Uterus, ovaries and fallopian tubes (additional for female participants). 5 for male 8 for female Liver, gallbladder, spleen, pancreas, kidney. Uterus, ovaries and fallopian tubes (additional for female participants). Includes common food items and ethnic group-specific food items. Only available for high-altitude areas. The CMEC baseline survey was conducted through the collaborative efforts of multiple agencies, including academic institutions, CDCs, local clinical centres, Third-Party Medical Laboratories (TPMLs) and local governments. Each agency has a clear role in the process of the investigation. Typically, the local government began the CMEC publicity campaigns a few weeks before the formal investigation. Meanwhile, the residents were fully informed of the benefits and requirements of participating in the CMEC study. Then, residents who were willing to participate made an appointment with the local clinical centre. The clinic visit for each participant typically took 90–120 min. The average daily recruitment rate was 70–80 participants per site. The main content of our questionnaire referred to the study of the China Kadoorie Biobank as the prototype.21 Major modifications were made in sections regarding physical activity, habitual diet and psychological conditions to fully capture the unique features of the different ethnic minority groups. We used a tablet computer with a self-developed application (CMEC App) to collect the questionnaire information (see more details in Table 1). The information was collected by a face-to-face interview implemented by well-trained interviewers who were typically local college students with medical backgrounds. For a skilled interviewer, an average of 30–45 min was often required to complete a questionnaire. The whole interview was audio recorded, and we documented the duration spent on each question. For data QC, on the same day of data collection, the data quality inspectors, who were chosen from excellent interviewers, drew random samples of questionnaires to assess their data quality by listening to the audio records. The sampling scheme was built on our computer system and could ensure that each interviewer was sampled at least once. Questionnaires that were classified as unqualified were excluded from the final analysis. We conducted medical examinations mainly using the resources and personnel at local clinical centres. We implemented standardized training for the doctors and nurses before the investigation. For those testing devices that the local clinical centres were rarely equipped with, we provided uniform devices for each site and trained the local staff to operate those devices, including bone mineral density densitometers (OSTEOKJ3000) and peak expiratory flowmeters (KOKA PEF-3). Particularly, for Tibet and high-altitude areas in Sichuan and Yunnan, qualified physicians used the chronic high-altitude disease scale, which consists of seven questions or symptoms for assessing chronic high-altitude disease and its severity. The CDCs took the main responsibility for field QC, guided by a handbook and serval forms to monitor key risk points. The main measures of QC included checking whether the measurement instruments were in good condition, inspecting whether the measurement was in accordance with standard operating procedures (SOPs) and randomly sampling participants to re-test their results. All participants provided blood and urine samples on-site at the time of the baseline survey. Venous blood samples, collected after overnight fasting (at least 8 h), were used for clinical laboratory testing, including routine blood tests, fasting blood glucose, lipid levels and hepatic function. (Table 1). Mid-stream urine was collected for routine urine testing. A total of 4000 saliva and 1000 stool samples were collected from Tibetans and Han individuals residing in Sichuan Province for multi-omics analysis, such as the microbiome and systemic metabolism. All the samples were centralized in a biobank located at the West China School of Public Health, Sichuan University and stored at −80°C in cryogenic refrigerators. Computer systems for sample entry, access and temperature monitoring were developed and have been applied. Blind panels of samples were periodically sent to the TPMLs for QC testing. Batches of controls were simultaneously put into the biobanking facility with samples and taken out for testing at regular intervals as a storage QC procedure. All of the above measurements were stored and managed in electronic form by a self-developed computer system, with the central server located at the West China School of Public Health, Sichuan University. Different datasets were linked by the unique participant’s ID. A visualized data organization schematic can be seen in Figure 2. Schematic graph of the data collection and computer system Schematic graph of the data collection and computer system In addition to data storage and management, our computer system also had some built-in functions to help with data cleaning based on electronic data. The whole process can be divided into two parts: detection and verification. In the detection part, we checked for duplication, completeness, outliers and logic errors via predesigned algorithms. Once suspicious data errors were detected, we ran a further verification process by listening to the audio recordings, looking up examination reports or calling back the participants. Then, the data were revised, and the whole correction process was recorded by our computer system. Table 2 shows the baseline characteristics of the participants. There were more women than men across the different ethnicities. The proportions of women ranged from 54.4% in the Han population in Basin (Chongqing, Chengdu) to 70.4% in the Bai population in the high plateau (Yunnan). Although we observed a similar age distribution and marital status across participants of different ethnicities, significant disparities were found in terms of highest education completed. For instance, 71.4% of Tibetans in Aba reported no formal schooling, whereas this number was as low as 10.7% among the Han in Basin. The proportions of participants who never smoked (91.3%) or drank alcohol (93.1%) were relatively high among Tibetans in Aba compared with other populations in our study. Additionally, we noted variations regarding some lifestyle variables within an ethnic group, e.g. the proportion that never consumed tea was 32.3% for Tibetans in Aba and 8.1% for Tibetans in Lhasa. Baseline characteristics of the participants in the China Multi-Ethnic Cohort Difficulty initiating or maintaining sleepn Difficulty initiating or maintaining sleepn The inclusion criteria for age was 30–79 years on the day of investigation (except for the Tibetan population in whose inclusion criteria for age was 18–79 is as a total of >100 smoked to is as for of alcohol is as on an average of per in the of alcohol is as on an average of per in the of tea is as on an average of per in the of tea is as on an average of per in the physical physical activity, physical activity, physical and physical is as per in the physical is as per in the A diet is as an average daily A high diet is as an average daily of is as an average of per in the Difficulty initiating or maintaining is as at least per in the is as at least per in the is as at least 1 day per in the is as at least per in the Baseline characteristics of the participants in the China Multi-Ethnic Cohort Difficulty initiating or maintaining sleepn Difficulty initiating or maintaining sleepn The inclusion criteria for age was 30–79 years on the day of investigation (except for the Tibetan population in whose inclusion criteria for age was 18–79 is as a total of >100 smoked to is as for of alcohol is as on an average of per in the of alcohol is as on an average of per in the of tea is as on an average of per in the of tea is as on an average of per in the physical physical activity, physical activity, physical and physical is as per in the physical is as per in the A diet is as an average daily A high diet is as an average daily of is as an average of per in the Difficulty initiating or maintaining is as at least per in the is as at least per in the is as at least 1 day per in the is as at least per in the Table the characteristics of the medical The was between in Miao and in Tibetans from Lhasa. The was between in the Han population in the high plateau and in Tibetans from The proportion of who had blood was low in Tibetans, and the proportion who had blood was low in Basin Han In terms of bone was in Aba Tibetans compared with other populations. examination for participants in the China Multi-Ethnic Cohort and were for each participant and the are based on the average of the examination for participants in the China Multi-Ethnic Cohort and were for each participant and the are based on the average of the Table the characteristics of the participants at The fasting blood was significantly low in Tibetans from and Tibetans from Aba The haemoglobin was between and across different ethnicities. regard to the highest was among the Han ethnic group in the high plateau whereas the was found among Tibetans in the high plateau of characteristics of participants in the China Multi-Ethnic Cohort standard fasting blood total blood blood total characteristics of participants in the China Multi-Ethnic Cohort standard fasting blood total blood blood total Figure the prevalence of which the disease among different ethnic groups. The highest prevalence of was observed in the Bai and ethnic groups in the high whereas the was reported in Tibetans from Aba was among the Han ethnic group in Basin heart disease, substantial was The most group was Tibetans from whereas the least group was their rural Tibetans from Aba Overall, was not with the highest in the Bouyei ethnic group in of some selected diseases among the participants in different ethnic groups. prevalence of all chronic may of some selected diseases among the participants in different ethnic groups. prevalence of all chronic may This study has some we on data for some such as lifestyle which may we excluded populations of 30–79 years (except for the Tibetan populations in which were also which may have information on life the above our study is to our knowledge, this is the first cohort study on ethnic minority groups in China. to the substantial in terms of and development among the ethnic minority groups, as as their distinct and and the based on our cohort study have the to not only to the of on the prevalence and risk factors of NCDs but also reveal novel that may as a to other global populations. our study groups of urban and rural residents, plateau and populations living in highly and air areas and those in remote areas. This one to conduct studies of the of various on people’s health outcomes from different For instance, Tibetan populations in rural areas live a nomadic life, which is not by their urban in One will be to significant disparities of lifestyle within the same ethnic our baseline survey collected and For instance, in addition to and we also collected biological and medical examinations and clinical laboratory for every our study is by the National Key Research and Development the research in China, this study is supported by the different levels of CDCs and local clinic centres. field and electronic medical records can be and may improve the data quality and minimize the loss of participants at follow-up. follow-up information will be through annual data linkage to electronic records of disease and death registries, as as every 3–5 years. This follow-up and of both and various have been implemented at every to ensure the quality of the data. To the of the CMEC we from all the the is not to be because of some However, in our study the at by The China Multi-Ethnic Cohort (CMEC) is a study to address the urgent need for NCDs prevalence, risk factors and associated conditions in resource-constrained for ethnic minorities in China. A total of 99 556 participants 30–79 years populations include those from the Tibetan, Yi, Miao, Bai, Dong and Han ethnic groups in Southwest China were recruited between May 2018 and September 2019. All surviving study participants will be invited for every 3–5 years with questionnaires to risk and disease the status of study participants will be through linkage with established electronic disease The CMEC baseline survey collected data with an electronic questionnaire and face-to-face interviews, medical examinations and clinical laboratory tests. we collected biological specimens, including blood, saliva and stool, for In addition to the individual-level we also collected regional-level data for each investigation site. are to the This work was supported by the National Key Program of China The most important is to all the participants in the as as to all the interviewers and of the survey in each of the study and We also and for their of the