DESIGN: Health efficiency analysis using data envelopment analysis (DEA) and stochastic frontier approach analysis.
SETTING: Health systems in China and ASEAN countries.
METHODS: DEA-Malmquist model and SFA model were used to analyse the health system efficiency among China and ASEAN countries, and the Tobit regression model was employed to analyse the factors affecting the efficiency of health system among these countries.
RESULTS: In 2020, the average technical efficiency, pure technical efficiency and scale efficiency of China and 10 ASEAN countries' health systems were 0.700, 1 and 0.701, respectively. The average total factor productivity (TFP) index of the health systems in 11 countries from 2015 to 2020 was 0.962, with a decrease of 1.4%, among which the average technical efficiency index was 1.016, and the average technical progress efficiency index was 0.947. In the past 6 years, the TFP index of the health system in Malaysia was higher than 1, while the TFP index of other countries was lower than 1. The cost efficiency among China and ASEAN countries was relatively high and stable. The per capita gross domestic product (current US$) and the urban population have significant effects on the efficiency of health systems.
CONCLUSIONS: Health systems inefficiency is existing in China and the majority ASEAN countries. However, the lower/middle-income countries outperformed high-income countries. Technical efficiency is the key to improve the TFP of health systems. It is suggested that China and ASEAN countries should enhance scale efficiency, accelerate technological progress and strengthen regional health cooperation according to their respective situations.
MATERIALS AND METHODS: Comprehensive information on lablab was gathered from databases including Web of Science, Science Direct, Google Scholar, Springer, PubMed, CNKI, Wanfang, and ancient materia medica.
RESULTS: Lablab, a member of the lentil family, thrives in warm and humid climates, and is distributed across tropical and subtropical regions worldwide. Traditionally, lablab is used to treat various ailments, such as spleen and stomach weakness, loss of appetite, and diarrhea. Phytochemical analyses reveal that lablab is a rich source of triterpenoid saponins, glucosides, volatile components, polysaccharides, and amino acids. Lablab extracts exhibit diverse biological activities, including hypolipidemic, hypoglycemic, immunomodulatory, antioxidant, hepatoprotective, antitumoral, antiviral properties, and more. Besides its medicinal applications, lablab is extensively used in the food industry due to its high nutrient content. Additionally, the quality of lablab can be regulated by determining the levels of key chemical components pivotal to its medicinal effects, ensuring the herb's overall quality.
CONCLUSION: Lablab is a promising medicinal and edible plant ingredient with diverse pharmacological effects, making it a valuable ingredient for food, pharmaceuticals, and animal husbandry. However, it has inherent toxicity if not properly prepared. Additionally, some traditional uses and pharmacological activities lack scientific validation due to incomplete methods, unclear results, and insufficient clinical data. Thus, further in vivo and in vitro studies on its pharmacology, pharmacokinetics, and toxicology, along with clinical efficacy evaluations, are needed to ensure lablab's safety and effectiveness. As an important traditional Chinese medicine, lablab deserves more attention.
METHODS: The study included healthy controls (HCs; n=40) and individuals with BD (n=33). Participants listened to audio stimuli representing low- and high-EE environments while cortical hemodynamic activity was recorded using functional near-infrared spectroscopy (fNIRS). Hemodynamic activation and functional connectivity were examined in the left ventrolateral prefrontal cortex (vlPFC), left superior temporal gyrus (STG), and medial prefrontal cortex (mPFC)-regions implicated in emotion processing and regulation.
RESULTS: Both groups showed significantly greater hemodynamic activation in the left vlPFC and left STG, together with greater nodal efficiency within the left vlPFC-STG network, under the high-EE condition than under the low-EE condition (p<0.05), with no significant between-group differences in these EE-related changes. In contrast, individuals with BD showed significantly reduced mPFC modulation relative to baseline and lower mPFC nodal efficiency than HCs (p<0.05). Within the BD group, mPFC nodal efficiency was significantly lower under the high-EE condition than under the low-EE condition (p<0.05).
CONCLUSION: The findings indicate region- and context-specific differences in cortical hemodynamic responses and functional coupling in individuals with BD during EE processing. These fNIRS-derived measures may serve as candidate features for further investigation in larger and independent studies, including computational models aimed at characterizing cortical responses associated with BD.