Background: Community-based health insurance (CBHI) schemes are increasingly implemented in low-income settings. These schemes limit the coverage they offer both by the types of care considered, and by applying thresh...Background: Community-based health insurance (CBHI) schemes are increasingly implemented in low-income settings. These schemes limit the coverage they offer both by the types of care considered, and by applying thresholds and/or caps to costs reimbursed. The consequences of these thresholds and/or caps on insurance coverage have hitherto been usually ignored, for lack of data on the distributions of healthcare costs or understanding of their impact on effective coverage levels. This article describes a theoretical model to obtain the distributions even without data collection in the field, and demonstrates the quantitative impact of thresholds and/or caps on claim reimbursements. Methods: This model applies to applications on healthcare expenditures in low-income settings, following research methods examined in the Western world. We looked at hospitalizations and tests;we compared the simulated distributions to empirical data obtained through 11 household surveys conducted between 2008 and 2010 in rural locations (9 in India and 2 in Nepal). Results: We found that the shape of the distributions was very similar in all locations for both benefits, and could be represented by a model based on a lognormal distribution. The agreement between theoretical and empirical results was satisfactory (mostly within 10% difference). Conclusions: The model makes it possible to simulate the expected performance of the CBHI (represented by the percentage of costs or bills covered). The aim is to match costs with local levels of willingness-to-pay for health insurance. This model makes it possible to determine at the stage of package-design the optimal levels of thresholds and/or caps for each benefit-type included.展开更多
Introduction: Working in a noisy environment is a risk for employee hearing health. Standard threshold shift (STS) can be used as a screening method to detect early indications of hearing deterioration. Objective: To ...Introduction: Working in a noisy environment is a risk for employee hearing health. Standard threshold shift (STS) can be used as a screening method to detect early indications of hearing deterioration. Objective: To investigate health effects related to STS in motor compressor workers. Methods: A cross sectional study of 464 motor compressor workers was conducted including hearing health examination by audiometer, and noise level in the workplace was monitored. Workers who reported having hobbies relating to noise, e.g. gun shooting, or a personal history of disease relating to the ear were excluded. The relationship between health effects and workers with STS was studied. Results: There were more men 81.90% (aged range 31-40 years old) than women working for the company. The average continuous noise level in the workplace was 84.14 ± 5.21 dB(A). The study showed that working at the factory for more than 14 years (OR= 3.84, 95%CI 1.54-9.56) and being exposed to noise at least 8 hours a day (OR = 2.12, 95%CI = 1.02-4.40) effected to STS. Workers with STS showed significant communication difficulties (OR = 1.89, 95%CI = 1.03-3.49) and stress/nausea more than workers without STS (OR = 1.54, 95%CI = 0.90-2.65) although not statistically significant. Conclusions: Workers exposed to continuous noise in the motor compressor industry are at risk of STS. Duration of exposure to noise is a key factor in respect of harm to hearing health. STS could be used as a tool to screen workers who have hearing health problems.展开更多
目的在不使用骨密度的情况下探讨无锡地区相对健康绝经后女性最佳FRAX^(■)干预阈值,旨在不浪费过多资源的前提下有效地识别出患有骨质疏松症(osteoporosis,OP)的潜在人群。方法将在作者医院随机招募的符合纳排标准的124名50岁以上健康...目的在不使用骨密度的情况下探讨无锡地区相对健康绝经后女性最佳FRAX^(■)干预阈值,旨在不浪费过多资源的前提下有效地识别出患有骨质疏松症(osteoporosis,OP)的潜在人群。方法将在作者医院随机招募的符合纳排标准的124名50岁以上健康绝经后女性作为研究对象,以65岁为分界年龄分为50~65岁组(n=86)和>65岁组(n=38)。收集受试者年龄、体质量指数(body mass index,BMI)、既往骨质疏松性骨折史、慢性病史等个人信息。使用FRAX^(■)软件得出受试者髋部骨折的概率(probability of hip fractures,PHF)、主要骨质疏松性骨折概率(probability of major osteoporotic fractures,PMOF),以骨密度T值是否小于-2.5为状态变量,不输入骨密度T值的PHF、PMOF为检验变量,运用受试者工作特征(receiver operating characteristic,ROC)曲线及曲线下面积(area under the curve,AUC)分析其临床筛选OP的效能,确定无锡地区相对健康绝经后中老年女性最佳干预阈值。结果50~65岁组OP患者39人(45.35%),>65岁组OP患者23人(60.53%)。ROC曲线分析结果显示,50~65岁组PHF AUC为0.771,灵敏度为0.718,特异度为0.681,最佳阈值为0.7%;PMOF AUC为0.748,灵敏度为0.667,特异度为0.723,最佳阈值为3.4%。>65岁组受试者PHF AUC为0.554,灵敏度为0.783,特异度为0.400;PMOF AUC为0.546,灵敏度为0.826,特异度为0.400,>65岁组PHF、PMOFAUC接近0.5,说明预测的准确性较低。按照《原发性骨质疏松症诊疗指南》推荐PHF、PMOF阈值划分骨折风险,50~65岁组全为骨折低风险人群,>65岁组30人为低风险、8人为高风险人群,此结果低估了本研究患者的骨折风险。结论推荐PHF为0.7%、PMOF为3.4%为无锡地区50~65岁健康绝经后女性FRAX^(■)干预阈值,大于该阈值者建议进行骨密度检测,适当给予治疗措施;对于无锡地区65岁以上健康绝经后女性建议直接进行骨密度检测。展开更多
Obesity is one of the greatest public health challenges of the 21st century. Overweight and obesity drastically increase a person’s risk of developing chronic non-communicable diseases (NCDs), including cardiovascula...Obesity is one of the greatest public health challenges of the 21st century. Overweight and obesity drastically increase a person’s risk of developing chronic non-communicable diseases (NCDs), including cardiovascular disease, cancer and diabetes. Furthermore, obesity is already responsible for 2% -8% of health costs and 10% -13% of deaths in several industrialized countries. Lifestyle modifications involving changes in exercise, diet and psychological support are effective in reducing the incidence of overweight. Moreover, positive effects of physical activity (PA) for weight loss and prevention of weight regain are well documented. It was recognized that health benefits regarding both psychological and physiological aspects, such as improving cardiorespiratory and muscular fitness and/or decreasing depression symptoms, can be obtained from numerous activities. Public health institutions (American College of Sports Medicine, World Health Organization) provide recommendations for PA (volume, frequency, intensity and type of exercise) to achieve positive effects, at all ages and for many diseases and disorders situations. Although exercise under guidelines can be safely performed by obese subjects, several questions still need to be fully answered. In facts, the exercise program should be tailored according to an individual’s habitual physical activity, physical function, health status, exercise responses, and stated goals. Thus, this review analyzes the intensity of PA parameters. In the last years, research has been focused on the individualization of the right intensity in which different types of subjects’ condition must undergo to achieve the health goals. Aerobic exercise has been commonly used to reach weight loss goal. Prescription of aerobic exercise in clinical practice is frequently based on the percentage of maximum heart rate (%HRmax), heart rate reserve (%HRreserve), rating of perceived exertion (RPE), maximal oxygen consumption (%VO2max) and for unhealthy subjects, peak oxygen consumption (%VO2peak). It has been shown that unhealthy subjects, such as individuals affected by diabetes, obesity and cardiovascular diseases have a reduced maximal aerobic exercise capacity. For instance, using the formula based on percentage of HRmax or VO2max, it could be prescribed heavy exercises, which would result not appropriated and fully functional for the specific individual goal. To avoid this problem, another approach to individualize aerobic exercise could be to consider the gas exchange parameters such us aerobic gas exchange threshold (AerTGE). AerTGE corresponds to the first increase in blood lactate during incremental exercise. This review offers an overview of the different methods to assess exercise intensity, considering the different subjects health characteristics, in order to choose the right methods to achieve the health goals in obese and overweight subjects.展开更多
文摘Background: Community-based health insurance (CBHI) schemes are increasingly implemented in low-income settings. These schemes limit the coverage they offer both by the types of care considered, and by applying thresholds and/or caps to costs reimbursed. The consequences of these thresholds and/or caps on insurance coverage have hitherto been usually ignored, for lack of data on the distributions of healthcare costs or understanding of their impact on effective coverage levels. This article describes a theoretical model to obtain the distributions even without data collection in the field, and demonstrates the quantitative impact of thresholds and/or caps on claim reimbursements. Methods: This model applies to applications on healthcare expenditures in low-income settings, following research methods examined in the Western world. We looked at hospitalizations and tests;we compared the simulated distributions to empirical data obtained through 11 household surveys conducted between 2008 and 2010 in rural locations (9 in India and 2 in Nepal). Results: We found that the shape of the distributions was very similar in all locations for both benefits, and could be represented by a model based on a lognormal distribution. The agreement between theoretical and empirical results was satisfactory (mostly within 10% difference). Conclusions: The model makes it possible to simulate the expected performance of the CBHI (represented by the percentage of costs or bills covered). The aim is to match costs with local levels of willingness-to-pay for health insurance. This model makes it possible to determine at the stage of package-design the optimal levels of thresholds and/or caps for each benefit-type included.
文摘Introduction: Working in a noisy environment is a risk for employee hearing health. Standard threshold shift (STS) can be used as a screening method to detect early indications of hearing deterioration. Objective: To investigate health effects related to STS in motor compressor workers. Methods: A cross sectional study of 464 motor compressor workers was conducted including hearing health examination by audiometer, and noise level in the workplace was monitored. Workers who reported having hobbies relating to noise, e.g. gun shooting, or a personal history of disease relating to the ear were excluded. The relationship between health effects and workers with STS was studied. Results: There were more men 81.90% (aged range 31-40 years old) than women working for the company. The average continuous noise level in the workplace was 84.14 ± 5.21 dB(A). The study showed that working at the factory for more than 14 years (OR= 3.84, 95%CI 1.54-9.56) and being exposed to noise at least 8 hours a day (OR = 2.12, 95%CI = 1.02-4.40) effected to STS. Workers with STS showed significant communication difficulties (OR = 1.89, 95%CI = 1.03-3.49) and stress/nausea more than workers without STS (OR = 1.54, 95%CI = 0.90-2.65) although not statistically significant. Conclusions: Workers exposed to continuous noise in the motor compressor industry are at risk of STS. Duration of exposure to noise is a key factor in respect of harm to hearing health. STS could be used as a tool to screen workers who have hearing health problems.
文摘目的在不使用骨密度的情况下探讨无锡地区相对健康绝经后女性最佳FRAX^(■)干预阈值,旨在不浪费过多资源的前提下有效地识别出患有骨质疏松症(osteoporosis,OP)的潜在人群。方法将在作者医院随机招募的符合纳排标准的124名50岁以上健康绝经后女性作为研究对象,以65岁为分界年龄分为50~65岁组(n=86)和>65岁组(n=38)。收集受试者年龄、体质量指数(body mass index,BMI)、既往骨质疏松性骨折史、慢性病史等个人信息。使用FRAX^(■)软件得出受试者髋部骨折的概率(probability of hip fractures,PHF)、主要骨质疏松性骨折概率(probability of major osteoporotic fractures,PMOF),以骨密度T值是否小于-2.5为状态变量,不输入骨密度T值的PHF、PMOF为检验变量,运用受试者工作特征(receiver operating characteristic,ROC)曲线及曲线下面积(area under the curve,AUC)分析其临床筛选OP的效能,确定无锡地区相对健康绝经后中老年女性最佳干预阈值。结果50~65岁组OP患者39人(45.35%),>65岁组OP患者23人(60.53%)。ROC曲线分析结果显示,50~65岁组PHF AUC为0.771,灵敏度为0.718,特异度为0.681,最佳阈值为0.7%;PMOF AUC为0.748,灵敏度为0.667,特异度为0.723,最佳阈值为3.4%。>65岁组受试者PHF AUC为0.554,灵敏度为0.783,特异度为0.400;PMOF AUC为0.546,灵敏度为0.826,特异度为0.400,>65岁组PHF、PMOFAUC接近0.5,说明预测的准确性较低。按照《原发性骨质疏松症诊疗指南》推荐PHF、PMOF阈值划分骨折风险,50~65岁组全为骨折低风险人群,>65岁组30人为低风险、8人为高风险人群,此结果低估了本研究患者的骨折风险。结论推荐PHF为0.7%、PMOF为3.4%为无锡地区50~65岁健康绝经后女性FRAX^(■)干预阈值,大于该阈值者建议进行骨密度检测,适当给予治疗措施;对于无锡地区65岁以上健康绝经后女性建议直接进行骨密度检测。
文摘Obesity is one of the greatest public health challenges of the 21st century. Overweight and obesity drastically increase a person’s risk of developing chronic non-communicable diseases (NCDs), including cardiovascular disease, cancer and diabetes. Furthermore, obesity is already responsible for 2% -8% of health costs and 10% -13% of deaths in several industrialized countries. Lifestyle modifications involving changes in exercise, diet and psychological support are effective in reducing the incidence of overweight. Moreover, positive effects of physical activity (PA) for weight loss and prevention of weight regain are well documented. It was recognized that health benefits regarding both psychological and physiological aspects, such as improving cardiorespiratory and muscular fitness and/or decreasing depression symptoms, can be obtained from numerous activities. Public health institutions (American College of Sports Medicine, World Health Organization) provide recommendations for PA (volume, frequency, intensity and type of exercise) to achieve positive effects, at all ages and for many diseases and disorders situations. Although exercise under guidelines can be safely performed by obese subjects, several questions still need to be fully answered. In facts, the exercise program should be tailored according to an individual’s habitual physical activity, physical function, health status, exercise responses, and stated goals. Thus, this review analyzes the intensity of PA parameters. In the last years, research has been focused on the individualization of the right intensity in which different types of subjects’ condition must undergo to achieve the health goals. Aerobic exercise has been commonly used to reach weight loss goal. Prescription of aerobic exercise in clinical practice is frequently based on the percentage of maximum heart rate (%HRmax), heart rate reserve (%HRreserve), rating of perceived exertion (RPE), maximal oxygen consumption (%VO2max) and for unhealthy subjects, peak oxygen consumption (%VO2peak). It has been shown that unhealthy subjects, such as individuals affected by diabetes, obesity and cardiovascular diseases have a reduced maximal aerobic exercise capacity. For instance, using the formula based on percentage of HRmax or VO2max, it could be prescribed heavy exercises, which would result not appropriated and fully functional for the specific individual goal. To avoid this problem, another approach to individualize aerobic exercise could be to consider the gas exchange parameters such us aerobic gas exchange threshold (AerTGE). AerTGE corresponds to the first increase in blood lactate during incremental exercise. This review offers an overview of the different methods to assess exercise intensity, considering the different subjects health characteristics, in order to choose the right methods to achieve the health goals in obese and overweight subjects.
