Chunlei Han

Bio: Chunlei Han is an academic researcher from Binzhou University. The author has contributed to research in topics: Medicine & China. The author has an hindex of 2, co-authored 6 publications receiving 10 citations. Previous affiliations of Chunlei Han include Monash University.

The risk of shoulder pain after laparoscopic surgery for infertility is higher in thin patients.

Abstract: Postlaparoscopic shoulder pain (PLSP) is a common clinical problem that needs to be addressed by medical professionals who are currently perform laparoscopic surgeries. The purpose of this study was to determine the perioperative clinical factors and demographic characteristics associated with PLSP. A prospective observational study was performed with 442 inpatients undergoing laparoscopic surgery for infertility. The pain visual analogue scale was used as the measuring instrument. To identify the predictors of PLSP, we performed multivariate conditional logistic regression. PLSP was correlated with body mass index (BMI, odds ratio = 0.815). The incidence of shoulder pain and more severe shoulder pain in patients with a lower BMI was significantly higher than it was in patients with a higher BMI, and BMI was significantly negatively correlated with PLSP. Most of the patients (95%) began to experience shoulder pain on the first postoperative day, and it rarely occurred on the day of surgery. Patients with lower BMI presented a higher risk of reporting shoulder pain on the first postoperative day. We should identify high-risk patients in advance and make specific treatment plans according to the characteristics of their symptoms.

The impact of temperature on mortality in Tianjin, China : a case-crossover design with a distributed lag non-linear model

Abstract: Background There has been increasing interest in assessing the impacts of temperature on mortality. However, few studies have used a case–crossover design to examine non-linear and distributed lag effects of temperature on mortality. Additionally, little evidence is available on the temperature-mortality relationship in China, or what temperature measure is the best predictor of mortality. Objectives To use a distributed lag non-linear model (DLNM) as a part of case–crossover design. To examine the non-linear and distributed lag effects of temperature on mortality in Tianjin, China. To explore which temperature measure is the best predictor of mortality; Methods: The DLNM was applied to a case¬−crossover design to assess the non-linear and delayed effects of temperatures (maximum, mean and minimum) on deaths (non-accidental, cardiopulmonary, cardiovascular and respiratory). Results A U-shaped relationship was consistently found between temperature and mortality. Cold effects (significantly increased mortality associated with low temperatures) were delayed by 3 days, and persisted for 10 days. Hot effects (significantly increased mortality associated with high temperatures) were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. Conclusions In Tianjin, extreme cold and hot temperatures increased the risk of mortality. Results suggest that the effects of cold last longer than the effects of heat. It is possible to combine the case−crossover design with DLNMs. This allows the case−crossover design to flexibly estimate the non-linear and delayed effects of temperature (or air pollution) whilst controlling for season.

Global climate change and human health: pathways and possible solutions

Abstract: Global warming has been changing the planet’s climate pattern, leading to increasing frequency, intensity and duration of extreme weather events and natural disasters. These climate-changing events affect various health outcomes adversely through complicated pathways. This paper reviews the main signs of climate change so far, e.g., suboptimal ambient temperature, sea-level rise and other conditions, and depicts the interactive pathways between different climate-changing events such as suboptimal temperature, wildfires, and floods with a broad range of health outcomes. Meanwhile, the modifying effect of socioeconomic, demographic and environmental factors on the pathways is summarised, such that the youth, elderly, females, poor and those living in coastal regions are particularly susceptible to climate change. Although Earth as a whole is expected to suffer from climate change, this review article discusses some potential benefits for certain regions, e.g., a more liveable environment and sufficient food supply. Finally, we summarise certain mitigation and adaptation strategies against climate change and how these strategies may benefit human health in other ways. This review article provides a comprehensive and concise introduction of the pathways between climate change and human health and possible solutions, which may map directions for future research.

Exposure to PM 2.5 and Obesity Prevalence in the Greater Mexico City Area.

Abstract: Exposure to PM2.5 has been associated with the prevalence of obesity. In the Greater Mexico City Area (GMCA), both are ranked among the highest in the world. Our aim was to analyze this association in children, adolescents, and adults in the GMCA. We used data from the 2006 and 2012 Mexican National Surveys of Health and Nutrition (ENSANUT). Participants’ past-year exposure to ambient PM2.5 was assessed using land use terms and satellite-derived aerosol optical depth estimates; weight and height were measured. We used survey-adjusted logistic regression models to estimate the odds ratios (ORs) of obesity (vs. normal-overweight) for every 10 µg/m3 increase in annual PM2.5 exposure for children, adolescents, and adults. Using a meta-analysis approach, we estimated the overall odds of obesity. We analyzed data representing 19.3 million and 20.9 million GMCA individuals from ENSANUT 2006 and 2012, respectively. The overall pooled estimate between PM2.5 exposure and obesity was OR = 1.96 (95% CI: 1.21, 3.18). For adolescents, a 10 µg/m3 increase in PM2.5 was associated with an OR of 3.53 (95% CI: 1.45, 8.58) and 3.79 (95% CI: 1.40, 10.24) in 2006 and 2012, respectively. More studies such as this are recommended in Latin American cities with similar air pollution and obesity conditions.