A Study on the Prevalence Trend of Overweight and Obesity among Adults Aged 20 and above in Shanxi Province from 2010 to 2018

Background Overweight, obesity, and central obesity have become significant public health issues globally, affecting the well-being of residents. Analyzing the prevalence trends of overweight, obesity, and central obesity among residents in Shanxi Province can provide valuable scientific insights for the prevention and control of related diseases. Objective To analyze the prevalence and trends of overweight, obesity, and central obesity among adults aged 20 and above in Shanxi Province between 2010 and 2018. Methods The survey data of adults aged 20 and above in Shanxi Province were collected during four rounds of the China Chronic Disease Surveillance project from August 2010 to November 2018 (in 2010, 2013, 2015, and 2018) to calculate the rates of overweight, obesity, and central obesity among adults aged 20 and above in different years, and analyze the prevalence trends of overweight, obesity and central obesity for different characteristics of the study subjects. Results From 2010 to 2018, the overall crude rates and age- and gender-standardized rates of overweight among adults aged 20 and above in Shanxi Province ranged from 37.7% to 40.1% and 36.1% to 39.6%, respectively, with no significant upward trend (Z=0.005, 2.413; P=0.942, 0.120). The overall standardized obesity rate, overall crude rate of central obesity and the standardized rate central of obesity increased from 17.2%, 53.8%, and 52.4% in 2010 to 20.0%, 61.6%, and 60.2% in 2018, respectively (Z=8.100, 10.994, 12.218; P<0.05). From 2010 to 2018, there was no significant trends in the comparison of the overall crude overweight rate and the standardized overweight rate among adults aged 20 years and above by age, gender and region (P>0.05) ; the standardized overweight rate for males was higher than that for females (χ2=4.259, P<0.05), while the standardized obesity rate was lower than that for females (χ2=13.724, P<0.001) in 2013; no statistically significant differences between genders were observed at other time points (P>0.05) ; the overall obesity rate, male obesity rate, and both male and female central obesity rates in the age group of 20-39 years old showed an upward trend during the 8-year period (P<0.05). From 2010 to 2018, the standardized rates of overweight, obesity, and central obesity among urban residents were overall higher than those among rural residents (P<0.05). Specifically, significant differences were observed in the standardized overweight rates in 2013 and 2015, the standardized obesity rates in 2010 and 2015, and the standardized central obesity rates in 2015 and 2018 (P<0.05). The results of the Joinpoint regression analysis revealed that, from 2010 to 2018, the age-standardized overweight rate among females in Shanxi Province exhibited a decreasing trend (APC=-0.57, P<0.05), while the age-standardized obesity rate among males showed an increasing trend (APC=2.72, P<0.05). The standardized rates of overweight, obesity, and central obesity among urban and rural residents remained relatively stable over the 8-year period (P>0.05). There was also no significant difference in the trends of these rates between different genders and regions (P>0.05) . Conclusion From 2010 to 2018, the overweight rate among residents aged 20 and above in Shanxi Province remained stable, while the overall trends for obesity and central obesity rates showed an increasing trend. The prevention and control of obesity and central obesity should focus on the population aged 20-39 years to slow down the growth rate. For residents aged 40 and above, as well as urban residents, targeted prevention strategies should be implemented, so as to control the prevalence of overweight, obesity, and central obesity

Diabetes mellitus early warning and factor analysis using ensemble Bayesian networks with SMOTE-ENN and Boruta

Abstract Diabetes mellitus (DM) has become the third chronic non-infectious disease affecting patients after tumor, cardiovascular and cerebrovascular diseases, becoming one of the major public health issues worldwide. Detection of early warning risk factors for DM is key to the prevention of DM, which has been the focus of some previous studies. Therefore, from the perspective of residents' self-management and prevention, this study constructed Bayesian networks (BNs) combining feature screening and multiple resampling techniques for DM monitoring data with a class imbalance in Shanxi Province, China, to detect risk factors in chronic disease monitoring programs and predict the risk of DM. First, univariate analysis and Boruta feature selection algorithm were employed to conduct the preliminary screening of all included risk factors. Then, three resampling techniques, SMOTE, Borderline-SMOTE (BL-SMOTE) and SMOTE-ENN, were adopted to deal with data imbalance. Finally, BNs developed by three algorithms (Tabu, Hill-climbing and MMHC) were constructed using the processed data to find the warning factors that strongly correlate with DM. The results showed that the accuracy of DM classification is significantly improved by the BNs constructed by processed data. In particular, the BNs combined with the SMOTE-ENN resampling improved the most, and the BNs constructed by the Tabu algorithm obtained the best classification performance compared with the hill-climbing and MMHC algorithms. The best-performing joint Boruta-SMOTE-ENN-Tabu model showed that the risk factors of DM included family history, age, central obesity, hyperlipidemia, salt reduction, occupation, heart rate, and BMI

Exome sequencing identifies a novel mutation of the GDI1 gene in a Chinese non-syndromic X-linked intellectual disability family

Abstract X-linked intellectual disability (XLID) has been associated with various genes. Diagnosis of XLID, especially for non-syndromic ones (NS-XLID), is often hampered by the heterogeneity of this disease. Here we report the case of a Chinese family in which three males suffer from intellectual disability (ID). The three patients shared the same phenotype: no typical clinical manifestation other than IQ score ≤ 70. For a genetic diagnosis for this family we carried out whole exome sequencing on the proband, and validated 16 variants of interest in the genomic DNA of all the family members. A missense mutation (c.710G > T), which mapped to exon 6 of the Rab GDP-Dissociation Inhibitor 1 (GDI1) gene, was found segregating with the ID phenotype, and this mutation changes the 237th position in the guanosine diphosphate dissociation inhibitor (GDI) protein from glycine to valine (p. Gly237Val). Through molecular dynamics simulations we found that this substitution results in a conformational change of GDI, possibly affecting the Rab-binding capacity of this protein. In conclusion, our study identified a novel GDI1 mutation that is possibly NS-XLID causative, and showed that whole exome sequencing provides advantages for detecting novel ID-associated variants and can greatly facilitate the genetic diagnosis of the disease

Exploring relationship between social inequality and adaptations to climate change: evidence from urban household surveys in the Yangtze River delta, China

This research enhances our understanding of the complex relationship between climate change, social inequality, and adaption, in urban areas. It is novel, being the first research in this area to be based on a conceptual econometric framework within which multiple stages are explicitly developed, and for which empirical evidence is gathered. We use this approach to examine the role of material, social status, and power inequality in influencing spontaneous adaptation choices in urban settings of China’s Yangtze River delta. This framework differentiates two vital stages in adaptation decision making at the household level which allows us to examine, first, how social inequality shapes the severity of climate impact and, second, how social inequality interacts with this experience to influence responses to these impacts. We pilot this approach in selected metropolitan areas of Shanghai and Nanjing. Our results show that all dimensions of social inequality are significantly associated with experiences of climate change and adaptation choice. Application of our conceptual framework provides policymakers and planners with a new and useful tool that can be used to formulate better policy measures that either enable the disadvantaged to adapt in situ or provide these groups with real opportunities and capacities to migrate.Yan Tan, Xuchun Liu, Graeme Hug