Yufang Bi1, Limin Wang2, Yu Xu1, Yong Jiang2, Jiang He3, Mei Zhang2, Maigeng Zhou2, Yichong Li2, Min Xu1, Jieli Lu1, Tiange Wang1, Lin Ding1, Meng Dai1, Di Zhang1, Chung-Shiuan Chen3, Shenghan Lai4, Weiqing Wang5, Linhong Wang6, Guang Ning7. 1. State Key Laboratory of Medical Genomics, and National Clinical Research Center for Metabolic Diseases, Rui-Jin Hospital affiliated with Shanghai Jiao-Tong University School of Medicine, Shanghai, China. 2. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. 3. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA. 4. Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA. 5. State Key Laboratory of Medical Genomics, and National Clinical Research Center for Metabolic Diseases, Rui-Jin Hospital affiliated with Shanghai Jiao-Tong University School of Medicine, Shanghai, China. Electronic address: wqingw@hotmail.com. 6. National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China. Electronic address: linhong@chinawch.org.cn. 7. State Key Laboratory of Medical Genomics, and National Clinical Research Center for Metabolic Diseases, Rui-Jin Hospital affiliated with Shanghai Jiao-Tong University School of Medicine, Shanghai, China. Electronic address: gning@sibs.ac.cn.
Abstract
BACKGROUND: Little is known about the cardiometabolic health of internal migrant workers in China. We aimed to examine the prevalence of diabetes-related cardiometabolic risk factors in this large, but little-studied population. METHODS: We did this national surveillance study within the Chinese Center for Disease Control and Prevention's National Disease Surveillance Point System, which includes a nationally representative sample of 170 study sites in all 31 provinces, autonomous regions, and municipalities in mainland China. We used a stratified multistage cluster sampling design to select a nationally representative sample of 48,704 Chinese internal migrant workers aged 18-59 years in 2012. We defined migrant workers as individuals whose residence at the time of the study differed from their permanent residence in the government household registration system. Medical history, information about lifestyle risk factors, and clinical measurements were collected from study participants at workplaces or local health centres by trained staff. Overnight fasting blood samples were collected in the morning and oral glucose tolerance tests were done in accordance with a standard protocol. All calculations were weighted to represent the overall Chinese migrant worker population aged 18-59 years by assigning each participant a weight coefficient. Weight coefficients were derived from the 2012 China population census data for migrant population according to the distributions of industry sector, age, and sex. FINDINGS: Among Chinese migrant workers aged 18-59 years, the weighted prevalence estimates were 26·8% (95% CI 26·4-27·3) for overweight, 4·7% (4·5-5·0) for obesity, 29·4% (28·9-29·9) for central obesity, 30·5% (30·0-31·0) for prediabetes, 5·1% (4·9-5·3) for diabetes, 16·3% (15·9-16·7) for hypertension, 34·5% (34·0-35·0) for dyslipidaemia, and 18·6% (18·2-19·0) for metabolic syndrome. 9·0% (8·7-9·3) of Chinese migrant workers had none of the following cardiometabolic risk factors, including current cigarette smoking, low fruit and vegetable intake, low physical activity, obesity or central obesity, diabetes, hypertension, and dyslipidaemia, 26·7% (26·2-27·2) had one, 30·2% (29·7-30·7) had two, 19·6% (19·1-20·0) had three, 9·9% (9·6-10·3) had four, 3·7% (3·5-3·9) had five, 0·8% (0·8-0·9) had six, and 0·1% (0·1-0·1) had seven. The proportions of individuals with three or more risk factors were 44·6% (43·9-45·3) in men and 20·2% (19·6-20·9) in women. Most metabolic risk factors were significantly less prevalent in migrant workers than in the general population in China (all p<0·001), although in women, the proportion with central obesity was similar (p=0·50), and in men, the proportion with metabolic syndrome was similar (p=0·07), and overweight (p<0·0001), obesity (p=0·0008), and central obesity (p<0·0001) were more prevalent in male migrant workers. INTERPRETATION: Compared with the general population in China, most cardiometabolic risk factors were less prevalent in migrant workers. However, overweight, obesity and central obesity were more prevalent in male migrant workers than among men in the general population. Cardiometabolic risk profiles for migrant workers are not optimal and effective national interventions that can reach this special population are needed. FUNDING: Chinese Ministry of Finance, Ministry of Health, and Ministry of Science and Technology.
BACKGROUND: Little is known about the cardiometabolic health of internal migrant workers in China. We aimed to examine the prevalence of diabetes-related cardiometabolic risk factors in this large, but little-studied population. METHODS: We did this national surveillance study within the Chinese Center for Disease Control and Prevention's National Disease Surveillance Point System, which includes a nationally representative sample of 170 study sites in all 31 provinces, autonomous regions, and municipalities in mainland China. We used a stratified multistage cluster sampling design to select a nationally representative sample of 48,704 Chinese internal migrant workers aged 18-59 years in 2012. We defined migrant workers as individuals whose residence at the time of the study differed from their permanent residence in the government household registration system. Medical history, information about lifestyle risk factors, and clinical measurements were collected from study participants at workplaces or local health centres by trained staff. Overnight fasting blood samples were collected in the morning and oral glucose tolerance tests were done in accordance with a standard protocol. All calculations were weighted to represent the overall Chinese migrant worker population aged 18-59 years by assigning each participant a weight coefficient. Weight coefficients were derived from the 2012 China population census data for migrant population according to the distributions of industry sector, age, and sex. FINDINGS: Among Chinese migrant workers aged 18-59 years, the weighted prevalence estimates were 26·8% (95% CI 26·4-27·3) for overweight, 4·7% (4·5-5·0) for obesity, 29·4% (28·9-29·9) for central obesity, 30·5% (30·0-31·0) for prediabetes, 5·1% (4·9-5·3) for diabetes, 16·3% (15·9-16·7) for hypertension, 34·5% (34·0-35·0) for dyslipidaemia, and 18·6% (18·2-19·0) for metabolic syndrome. 9·0% (8·7-9·3) of Chinese migrant workers had none of the following cardiometabolic risk factors, including current cigarette smoking, low fruit and vegetable intake, low physical activity, obesity or central obesity, diabetes, hypertension, and dyslipidaemia, 26·7% (26·2-27·2) had one, 30·2% (29·7-30·7) had two, 19·6% (19·1-20·0) had three, 9·9% (9·6-10·3) had four, 3·7% (3·5-3·9) had five, 0·8% (0·8-0·9) had six, and 0·1% (0·1-0·1) had seven. The proportions of individuals with three or more risk factors were 44·6% (43·9-45·3) in men and 20·2% (19·6-20·9) in women. Most metabolic risk factors were significantly less prevalent in migrant workers than in the general population in China (all p<0·001), although in women, the proportion with central obesity was similar (p=0·50), and in men, the proportion with metabolic syndrome was similar (p=0·07), and overweight (p<0·0001), obesity (p=0·0008), and central obesity (p<0·0001) were more prevalent in male migrant workers. INTERPRETATION: Compared with the general population in China, most cardiometabolic risk factors were less prevalent in migrant workers. However, overweight, obesity and central obesity were more prevalent in male migrant workers than among men in the general population. Cardiometabolic risk profiles for migrant workers are not optimal and effective national interventions that can reach this special population are needed. FUNDING: Chinese Ministry of Finance, Ministry of Health, and Ministry of Science and Technology.
Authors: Charles M Yarborough; Stacy Brethauer; Wayne N Burton; Raymond J Fabius; Pamela Hymel; Shanu Kothari; Robert F Kushner; John Magaña Morton; Kathryn Mueller; Nicolaas P Pronk; Mitchell S Roslin; David B Sarwer; Brian Svazas; Jeffrey S Harris; Garrett I Ash; Jamie T Stark; Marianne Dreger; Julie Ording Journal: J Occup Environ Med Date: 2018-01 Impact factor: 2.162