Background: There is evidence that body mass index (BMI) is closely related to hyperlipidemia. This study aimed to estimate the cross-sectional relationship between Body Mass Index (BMI) and hyperlipidemia. Methods: We recruited 21,435 subjects (aged 18–79 years and residing in Jilin province, China) using the multistage stratified cluster random sampling method. Subjects were interviewed with a standardized questionnaire and physically examined. We analyzed the cross-sectional relationship between BMI and hyperlipidemia. Results: The prevalence of hyperlipidemia was 51.09% (52.04% in male and 50.21% in female). The prevalence of overweight and obesity was 31.89% and 6.23%, respectively. Our study showed that underweight (OR = 0.499, 95% CI: 0.426–0.585), overweight (OR = 2.587, 95% CI: 2.428–2.756), and obesity (OR = 3.614, 95% CI: 3.183–4.104) were significantly associated with hyperlipidemia (p < 0.001) in the age- and sex-adjusted logistic regression. After further adjusting for age, gender, region, district, ethnicity, education, marital status, main occupation, monthly family income per capita, smoking, drinking, exercise, central obesity, waist and hip, underweight (OR = 0.729, 95% CI: 0.616–0.864), overweight (OR = 1.651, 95% CI: 1.520–1.793), and obesity (OR = 1.714, 95% CI: 1.457–2.017) were independently associated with hyperlipidemia (p < 0.001). The restricted cubic spline model illustrated a nonlinear dose-response relationship between levels of BMI and the prevalence of hyperlipidemia (P_nonlinearity < 0.001). Conclusion: Our study demonstrated that the continuous variance of BMI was significantly associated with the prevalence of hyperlipidemia.

This study examined the frequency of mobile phone dependence in Chinese university students and explored its association with social support and impulsivity. Altogether, 909 university students were consecutively recruited from a large university in China. Mobile phone use, mobile phone dependence, impulsivity, and social support were measured with standardized instruments. The frequency of possible mobile phone use and mobile phone dependence was 78.3% and 7.4%, respectively. Multinomial logistic regression analyses revealed that compared with no mobile phone dependence, possible mobile phone dependence was significantly associated with being male (p = 0.04, OR = 0.7, 95% CI: 0.4–0.98), excessive mobile phone use (p < 0.001, OR = 1.2, 95% CI: 1.09–1.2), and impulsivity (p < 0.001, OR = 1.05, 95% CI: 1.03–1.06), while mobile phone dependence was associated with length of weekly phone use (p = 0.01, OR = 2.5, 95% CI: 1.2–5.0), excessive mobile phone use (p < 0.001, OR = 1.3, 95% CI: 1.2–1.4), and impulsivity (p < 0.001, OR = 1.08, 95% CI: 1.05–1.1). The frequency of possible mobile phone dependence and mobile phone dependence was high in this sample of Chinese university students. A significant positive association with impulsivity was found, but not with social support.

Background: Prehypertension is a category between normotension and hypertension that is becoming increasingly common in China. However, limited data are available on the prevalence and correlates of prehypertension in northeastern China. Methods: A cross-sectional study using stratified, clustered multistage, and random sampling methods was performed on 17,584 participants. Results: The prevalence of prehypertension and hypertension was 36.0% and 30.8% in northeastern China, respectively. As age increased, the prevalence of prehypertension in males declined (p-trend < 0.001), in parallel to an increase in the prevalence of hypertension (p-trend < 0.001). The prevalence of hypertension for females increased as age increased (p-trend < 0.001). Logistic regression analysis showed that age, gender, location, drinking, Body Mass Index (BMI), abdominal obesity, hypertriglyceridemia, and hypercholesterolemia correlated with prehypertension and hypertension (p-trend < 0.05). Conclusions: This study revealed a high prevalence of prehypertension and hypertension in an adult population of northeastern China and some correlates of prehypertension and hypertension.