Measuring health and economic wellbeing in the Sustainable Development Goals era: development of a poverty-free life expectancy metric and estimates for 90 countries

Addressing the Knowledge Deficit in Hospital Bed Planning and Defining an Optimum Region for the Number of Different Types of Hospital Beds in an Effective Health Care System

Based upon 30-years of research by the author, a new approach to hospital bed planning and international benchmarking is proposed. The number of hospital beds per 1000 people is commonly used to compare international bed numbers. This method is flawed because it does not consider population age structure or the effect of nearness-to-death on hospital utilization. Deaths are also serving as a proxy for wider bed demand arising from undetected outbreaks of 3000 species of human pathogens. To remedy this problem, a new approach to bed modeling has been developed that plots beds per 1000 deaths against deaths per 1000 population. Lines of equivalence can be drawn on the plot to delineate countries with a higher or lower bed supply. This method is extended to attempt to define the optimum region for bed supply in an effective health care system. England is used as an example of a health system descending into operational chaos due to too few beds and manpower. The former Soviet bloc countries represent a health system overly dependent on hospital beds. Several countries also show evidence of overutilization of hospital beds. The new method is used to define a potential range for bed supply and manpower where the most effective health systems currently reside. The method is applied to total curative beds, medical beds, psychiatric beds, critical care, geriatric care, etc., and can also be used to compare different types of healthcare staff, i.e., nurses, physicians, and surgeons. Issues surrounding the optimum hospital size and the optimum average occupancy will also be discussed. The role of poor policy in the English NHS is used to show how the NHS has been led into a bed crisis. The method is also extended beyond international benchmarking to illustrate how it can be applied at a local or regional level in the process of long-term bed planning. Issues regarding the volatility in hospital admissions are also addressed to explain the need for surge capacity and why an adequate average bed occupancy margin is required for an optimally functioning hospital.

Associations Between Gender Gaps in Life Expectancy, Air Pollution, and Urbanization: A Global Assessment With Bayesian Spatiotemporal Modeling

Objectives: It's evident that women have a longer life expectancy than men. This study investigates the spatiotemporal trends of gender gaps in life expectancy (GGLE). It demonstrates the spatiotemporal difference of the influence factors of population-weighted air pollution (pwPM_2.5) and urbanization on GGLE. Methods: Panel data on GGLE and influencing factors from 134 countries from 1960 to 2018 are collected. The Bayesian spatiotemporal model is performed. Results: The results show an obvious spatial heterogeneity worldwide with a continuously increasing trend of GGLE. Bayesian spatiotemporal regression reveals a significant positive relationship between pwPM_2.5, urbanization, and GGLE with the spatial random effects. Further, the regression coefficients present obvious geographic disparities across space worldwide. Conclusion: In sum, social-economic development and air quality improvement should be considered comprehensively in global policy to make a fair chance for both genders to maximize their health gains.

Applying logistic LASSO regression for the diagnosis of atypical Crohn's disease

In countries with a high incidence of tuberculosis, the typical clinical features of Crohn's disease (CD) may be covered up after tuberculosis infection, and the identification of atypical Crohn's disease and intestinal tuberculosis (ITB) is still a dilemma for clinicians. Least absolute shrinkage and selection operator (LASSO) regression has been applied to select variables in disease diagnosis. However, its value in discriminating ITB and atypical Crohn's disease remains unknown. A total of 400 patients were enrolled from January 2014 to January 2019 in second Xiangya hospital Central South University.Among them, 57 indicators including clinical manifestations, laboratory results, endoscopic findings, computed tomography enterography features were collected for further analysis. R software version 3.6.1 (glmnet package) was used to perform the LASSO logistic regression analysis. SPSS 20.0 was used to perform Pearson chi-square test and binary logistic regression analysis. In the variable selection step, LASSO regression and Pearson chi-square test were applied to select the most valuable variables as candidates for further logistic regression analysis. Secondly, variables identified from step 1 were applied to construct binary logistic regression analysis. Receiver operating characteristic (ROC) curve analysis was performed on these models to assess the ability and the optimal cutoff value for diagnosis. The area under the ROC curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy rate, together with their 95% confidence and intervals (CIs) were calculated. MedCalc software (Version 16.8) was applied to analyze the ROC curves of models. 332 patients were eventually enrolled to build a binary logistic regression model to discriminate CD (including comprehensive CD and tuberculosis infected CD) and ITB. However, we did not get a satisfactory diagnostic value via applying the binary logistic regression model of comprehensive CD and ITB to predict tuberculosis infected CD and ITB (accuracy rate:79.2%VS 65.1%). Therefore, we further established a binary logistic regression model to discriminate atypical CD from ITB, based on Pearsonchi-square test (model1) and LASSO regression (model 2). Model 1 showed 89.9% specificity, 65.9% sensitivity, 88.5% PPV, 68.9% NPV, 76.9% diagnostic accuracy, and an AUC value of 0.811, and model 2 showed 80.6% specificity, 84.4% sensitivity, 82.3% PPV, 82.9% NPV, 82.6% diagnostic accuracy, and an AUC value of 0.887. The comparison of AUCs between model1 and model2 was statistically different (P < 0.05). Tuberculosis infection increases the difficulty of discriminating CD from ITB. LASSO regression showed a more efficient ability than Pearson chi-square test based logistic regression on differential diagnosing atypical CD and ITB.

Poverty and health-related quality of life: a cross-sectional study in rural China

BACKGROUND

The association between poverty and health has been widely assessed. However, whether the association between poverty and health-related quality of life (HRQOL) holds among different groups is unknown. This study aimed to 1) assess the association between poverty and HRQOL among rural residents in China and 2) examine whether the association holds among different populations, thereby supporting policy-making and implementation.

METHODS

A multistage, stratified, random household survey was conducted with self-administered questionnaires. Matched samples were generated by the censored exact matching method to reduce selection bias between the poverty and comparison groups. We applied Tobit and ordinal logit regression models to evaluate the association between poverty and HRQOL measured by the EQ-5D-3 L among different groups.

RESULTS

The health utility score of the poverty group was 6.1% lower than that of comparison group (95% CI = - 0.085, - 0.037), with anxiety/depression being most common (95% CI = 1.220, 1.791). The association between poverty and HRQOL was significantly stronger among residents from central China, males, people who were middle-aged, elderly, highly educated, married, or widowed, those living far from healthcare facilities, and those without chronic disease. Male and highly educated subjects reported worse mobility, self-care, usual activities, pain/discomfort and anxiety/depression dimensions than the other respondents. Middle-aged (95% CI = 1.692, 2.851) and married respondents (95% CI = 1.692, 2.509) and respondents with chronic diseases (95% CI = 1.770, 2.849) were most affected in the anxiety/depression.

CONCLUSIONS

The HRQOL of individuals living in poverty is lower than that of the general population, and the mental health dimension is most affected by poverty among respondents who are middle-aged or married and respondents with chronic diseases. The identification of populations that are more affected by poverty is critical to improve their HRQOL. Various associations have indicated the need for integrated policies and specific decision-making.

Public health law coverage in support of the health-related sustainable development goals (SDGs) among 33 Western Pacific countries

Background

A resilient health system is inevitable in attaining the health-related Sustainable Development Goals (SDGs). One way of strengthening health systems is improving the coverage of public health laws for better health governance. The aim of this study is to describe the public health law situation in the Western Pacific Region and analyse the association of public health law coverage with health-related SDGs statistics.

Methods

A total of 33 Western Pacific countries were selected and analysed using a multi-group ecological study design. Public health law coverage was measured from April 2013 to October 2016 based on the public health law coverage module in the ‘Tool to Assess Health Law’ developed by the WHO Western Pacific Regional Office and Asian Institute for Bioethics and Health Law of Yonsei University. The health-related SDGs status were examined using health statistics data from World Health Statistics 2017 and 2018 by WHO and SDGs index scores of previous research.

Results

Countries with high public health law coverage were Vietnam, Republic of Korea, Hong Kong, and Singapore. Low coverage countries were mainly Pacific Island countries. High public health law coverage issues were health care organisation, communicable diseases, and substance abuse, whereas those of low coverage were human reproduction, family health, and oral health. Public health law coverage was associated with health-related SDGs statistics such as life expectancy at birth (r = 0.47, p = 0.03), health life expectancy at birth (r = 0.47, p = 0.04), health-related SDGs index (r = 0.43, p = 0.05). Among the SDG 3 indicators, maternal mortality ratio (r = − 0.53, p = 0.01), neonatal mortality rate (r = − 0.44, p = 0.02), new HIV infections (r = 0.78, p = 0.04), total alcohol consumption (r = 0.45, p = 0.02), adolescent birth rate (r = − 0.40, p = 0.04), UHC service coverage index (r = 0.50, p = 0.02), and IHR average core capacity score (r = 0.54, p = 0.004) were statistically meaningful. However, there was no association of public health law coverage with health statistics in other SDGs.

Conclusions

This study proved the importance of public health law in supporting the attainment of health-related SDGs. These results should be used as the basis for review and action at country level in improving public health law for better health systems, consequently achieving health-related SDGs.