R. Wang

BACKGROUND: The epidemiology and effects of functional constipation (FC) on Chinese people remain unclear. AIM: To investigate the epidemiology of FC and its distinction from constipation-predominant irritable bowel syndrome (IBS-C) in China. METHODS: A cross-sectional survey was conducted in a representative adult Chinese population (n = 16,078), which was selected from five regions using randomised, stratified, multistage sampling methodology. All respondents completed the modified Rome II questionnaire; 20% were asked to complete the 36-item Short Form (SF-36) and the Epworth Sleepiness Scale (ESS). RESULTS: Overall, 948 respondents (6%) had FC and FC was more prevalent in women than in men (8% vs. 4%, P < 0.001). Straining and hard stools were the two most frequent symptoms. FC was associated significantly with dyspepsia and abdominal bloating. All SF-36 domain scores were lower for respondents with FC than for those without. The prevalence of clinically meaningful daytime sleepiness was significantly higher in respondents with FC than in those without (22% vs. 14%, P = 0.003). Respondents with FC were more likely to strain, but less likely to have a feeling of incomplete emptying after a bowel movement than those with IBS-C. Respondents with IBS-C experienced similar demographics, quality of life and daytime sleepiness to those with FC. CONCLUSIONS: The prevalence of FC in China is substantially lower than that in Western countries. FC has negative effects on quality of life and daytime sleepiness. The demographics and burden of illness are similar between FC and IBS-C, although the clinical symptoms are somewhat different.

Aliment Pharmacol Ther 2010; 32: 562–572 Summary Background Dyspepsia and irritable bowel syndrome (IBS) are common in Western populations. Aim To determine the epidemiology of dyspepsia and IBS in China. Methods A representative sample of 18 000 adults from five regions of China were asked to complete the modified Rome II questionnaire; 20% were asked to complete the 36‐item Short Form Health Survey (SF‐36). Participants from Shanghai were invited to provide blood samples and undergo oesophagogastroduodenoscopy. Odds ratios (ORs) and 95% confidence intervals (CIs) were determined using a multivariate logistic regression model. Results The survey was completed by 16 091 individuals (response rate: 89.4%). Overall, 387 participants (2.4%) had dyspepsia and 735 (4.6%) had IBS. All SF‐36 dimension scores were at least five points lower in individuals with than without dyspepsia or IBS ( P ≤ 0.001). In Shanghai, 1030 (32.7%) of the 3153 respondents agreed to endoscopy; neither dyspepsia nor IBS was found to be associated with reflux oesophagitis, peptic ulcer disease or Helicobacter pylori infection. Conclusions Prevalence estimates for dyspepsia and IBS in China are lower than in Western populations. In China, dyspepsia or IBS symptoms are generally not associated with underlying organic disease.

BACKGROUND: To investigate the relationship between obesity and health-related quality of life (HRQL) in a randomly selected Chinese sample. METHODS: A total of 3600 residents aged 18-80 years were sampled in five cities of China using a randomized stratified multiple-stage sampling method to receive the interview, with a self-completed questionnaire to collect demographic information, and the Mandarin version of Short Form 36 Health Survey questionnaire (SF-36) to assess HRQL, followed by height and weight measurements for calculating body mass index (BMI). Cross-sectional association between BMI and HRQL was analysed. RESULTS: Among the 3207 participants (mean age 42 years) suitable for analysis, BMI differed by age and gender. Based on the international or the Asian BMI categories, in women, meaningful impairments were seen between obese and normal weight participants in four physical health scales, and only one scale of the four mental health scales--vitality scale was affected by obesity; in men, impairments by obesity were not found in all of the eight SF-36 scales, and better HRQL in two mental health scales were observed in obese participants compared to normal weight ones; after adjusting related variables, several physical but not mental health scales were found impaired by obesity. CONCLUSION: Obesity impaired physical but not mental health, and the impairments varied between genders. Public health agencies and government should emphasize the impairments of obesity on physical health.

The load characteristics of the park have strong fluctuation and nonlinearity due to the comprehensive power supply capacity, weather and holidays. This paper proposes a data-driven short-term load forecasting model, taking into account meteorological and temporal features of industrial parks, that takes into account time dependence. In the process of prediction, we build a convolutional neural network based on PyTorch framework, which combines short term memory network and autoregressive model. We construct a convolutional neural network based on PyTorch framework, a combination of short-term memory network and autoregressive model, in order to forecast. By unifying the benefits of CNN and LSTM, CNN-LSTM can extract features, seize long-term dependencies, and minimize overfitting. Therefore, we first extract both spatial and time series features by combining CNN-LSTM networks. Feature extraction modules, such as the CNN convolution layer and pooling layer, are employed to acquire data features. Temporal correlation properties of data can be mined through Long Short-Term Memory (LSTM) networks. Nonlinear time series prediction is achieved by employing Autoregressive Integrated Moving Average (ARIMA) to extract periodic and trend factors from the time series data. Finally, the prediction results are obtained according to the inverse error combined weights. Based on the load data of an industrial park in Liaoning Province, this paper carries out simulation experiments. The CNN-LSTM-ARIMA model has been demonstrated to be a successful means of enhancing the accuracy of load forecasting in industrial parks, when compared to LSTM and CNN-LSTM models. The practical engineering application of the prediction model holds a certain worth.