Development and evaluation of a simple and effective prediction approach for identifying those at high risk of dyslipidemia in rural adult residents.

BACKGROUND: Dyslipidemia is an extremely prevalent but preventable risk factor for cardiovascular disease. However, many dyslipidemia patients remain undetected in resource limited settings. The study was performed to develop and evaluate a simple and effective prediction approach without biochemical parameters to identify those at high risk of dyslipidemia in rural adult population. METHODS: Demographic, dietary and lifestyle, and anthropometric data were collected by a cross-sectional survey from 8,914 participants living in rural areas aged 35-78 years. There were 6,686 participants randomly selected into a training group for constructing the artificial neural network (ANN) and logistic regression (LR) prediction models. The remaining 2,228 participants were assigned to a validation group for performance comparisons of ANN and LR models. The predictors of dyslipidemia risk were identified from the training group using multivariate logistic regression analysis. Predictive performance was evaluated by receiver operating characteristic (ROC) curve. RESULTS: Some risk factors were significantly associated with dyslipidemia, including age, gender, educational level, smoking, high-fat diet, vegetable and fruit intake, family history, physical activity, and central obesity. For the ANN model, the sensitivity, specificity, positive and negative likelihood ratio, positive and negative predictive values were 90.41%, 76.66%, 3.87, 0.13, 76.33%, and 90.58%, respectively, while LR model were only 57.37%, 70.91%, 1.97, 0.60, 62.09%, and 66.73%, respectively. The area under the ROC cure (AUC) value of the ANN model was 0.86±0.01, showing more accurate overall performance than traditional LR model (AUC = 0.68±0.01, P<0.001). CONCLUSION: The ANN model is a simple and effective prediction approach to identify those at high risk of dyslipidemia, and it can be used to screen undiagnosed dyslipidemia patients in rural adult population. Further work is planned to confirm these results by incorporating multi-center and longer follow-up data.

[Multiple correspondence analysis on multiple metabolic abnormalities and family history in adults].

OBJECTIVE: To investigate the relationship between phenomenon of aggregation on multiple metabolic abnormalities and their family history. METHODS: A random cluster sampling was carried out to study the phenomenon of multiple metabolic abnormalities among the adult inhabitants in a county of Henan province. Questionnaire, physical examination and biochemical tests were admitted. Multiple correspondence analyses were used to explore the aggregation of multiple metabolic abnormalities among objects including hyperlipidemia, diabetes, coronary heart disease etc. Corresponding relationships between objects and their parents on multiple metabolic abnormalities were also analyzed. RESULTS: In total, 3901 people were investigated including 1428 (36.6%) males and 2473 (63.4%) females. The mean age of them was 32.8±6.3. Data showed that the Cronbach's α were 0.547 and 0.387 while Eigen values were 1.971 and 1.535 in two dimensions, regarding the correspondence analysis on their parents' multiple metabolic abnormalities. Cronbach's α levels were 0.598 and 0.457 together with Eigen values as 2.263 and 1.743 in two dimensions on the correspondence analysis of the objects' and their parents' multiple metabolic abnormalities. Results from Multiple correspondence analysis diagrams showed that there was an aggregation of variety metabolic abnormalities in both objects and their parents but not between objects and their parents or between fathers and mothers, though χ2 test showed a weak correlation between some of the categories. The ranges of contingency coefficients between metabolic abnormalities were 0.04 to 0.11, 0.04 to 0.08 and 0.04 to 0.11 between parents, objects and fathers, objects and mothers, respectively. When compared with simple obesity, the central obesity aggregated appeared more obviously with other metabolic abnormalities. CONCLUSION: Both objects and their parents showed an aggregation of variety metabolic abnormalities. Aggregation of central obesity showed more obvious on other metabolic abnormalities than the simple obesity. Family histories of metabolic abnormalities played a moderate role in the generations suffering from multiple metabolic abnormalities.

[Multilevel regression analysis on region cluster and risk factors of hypertension in the Chinese adult population].

OBJECTIVE: To analyze the region cluster and risk factors of hypertension in the Chinese adult population and to explore the application of multilevel regression model in the risk factors of hypertension. METHODS: Multi-stage random sampling technique was used to choose 15,540 individuals aged 35-74 years from 10 regions in China. Two-level logistic regression models were fitted under MLwiN 2.02 software. RESULTS: The region cluster of hypertension existed and variance portion coefficient was 3.1%. After adjusting for the age and gender, overall obese people (BMI> or =28 kg/m2) were 4.50 (95% CI: 4.00-5.06) times, overweight people (BMI=24-27.9 kg/m2) were 2.26 (95% CI: 2.07-2.46) times more likely to be hypertensive as compared with those of normal BMI (18.5-23.9 kg/m2), and those centrally obesive people (Waist circumference > or =85 cm in male or 80 cm in female) were 2.62 (95% CI: 2.42-2.83) times more likely to be hypertensive as compared with those of normal WC. The age-and gender-adjusted odds ratios (ORs) of triglyceride (TG), serum total cholesterol (TC), glucose, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and drinking alcohol were 2.10 (95% CI: 1.89-2.33), 2.08 (95% CI: 1.84-2.35), 1.85 (95% CI: 1.60-2.14), 1.58 (95% CI: 1.38-1.81), 1.49 (95% CI: 1.32-1.69) and 1.15 (95% CI: 1.05-1.27), respectively. CONCLUSION: The prevalence of hypertension was not only affected by individual risk factors, such as obesity, drinking alcohol, abnormal glucose and serum lipids profile, but also affected by the geographic environment where people resided in. Population-and risk factors targeted strategies, proved a promising way to reduce individual risk of hypertension in the primary prevention of hypertension.

[Secular trend of nosocomial pneumonia in an university hospital in Zhengzhou].

OBJECTIVE: To investigate the secular trend of infection rate, risk factor exposure rates for nosocomial pneumonia (NP), and to evaluate the nosocomial infection surveillance and control programs efficacy in an university hospital from 1993 to 2000. METHODS: All 126 665 hospitalized patients from 1993 to 2000 were studied for NP. The independent risk factors for NP were analyzed by using case-control study method and logistic regression technique. The time-specific rates for NP and risk factor exposure were calculated annually. RESULTS: The infection rates for NP were decreased by 50% from 1.20% in 1993 to 0.60% in 2000. The logistic regression analysis showed that the independent risk factors for NP were immunosuppressive therapy (OR = 2.72), chemotherapy (OR = 2.17), cancer (OR = 1.45), chronic obstructive pulmonary disease (COPD, OR = 1.88), ICU (OR = 3.18), coma (OR = 3.26), tracheotomy (OR = 14.95), hemodialysis (OR = 5.12), bone or lumbar puncture (OR = 1.82). The time-trends for exposure rates of COPD and bone or lumbar puncture were slightly decreased, however those for the others and the synthetic risk factors were not changed significantly. CONCLUSION: The infection rates for NP were significantly decreased in the case of no change for exposure rates of risk factors for NP, this suggests that the nosocomial infection surveillance and control programs were effective for lowering infection rate for NP in this hospital.