Willingness and influencing factors of old-age care mode selection among middle-aged and older adults in Henan Province, China.

BACKGROUND: The choice of old-age care methods or places plays an important role in improving the quality of life and well-being of older adults. This study aimed to analyze the choices of various old-age care modes (OCMs) among middle-aged and older adults (MOA) aged 40 years and older in Henan Province, China, and to explore the influence of personal health status, perspectives on old-age (POA) and external support received on their choices. METHODS: This study analyzed the data from the previous survey which included 911 MOA. The mean comparison method was used to analyze the evaluation of MOA prior to selecting OCMs, and the effect of individual characteristics, external support received, and personal health status on the choice of OCM for MOA was assessed by Logistic regression (LR) and Concentration Index. The Mediation Effect Model was used to explore effect manner and scope of MOA' POA in their choice of OCM. RESULTS: The overall scores for MOA on the choice of the home-based, community-family, retirement village, nursing homes OCM were 4.06 ± 0.81, 3.70 ± 0.88, 3.72 ± 0.90, 3.49 ± 0.97, respectively. The LR model indicated that education level, number of children, relationship between family members and the relationship with neighbors affected the choice of OCM for MOA (P < 0.05). Difference in OCM selection was relatively the largest based on the individual's POA (Concentration index = -0.0895 ~ -0.0606), and it was shown to play a mediating role in other factors influencing the choice of OCM for MOA (Mediation effect = -0.002 ~ 0.013). CONCLUSIONS: The evaluation of MOA on choosing a non-home OCM was generally, and the number of children and external support received were shown to have a relatively substantial impact on the choice of OCM among MOA, however, their power was affected by MOA' POA. Policy makers could encourage the MOA' selection of non-home OCM by improving the relationship among MOA persons while positively transforming their POA.

Current state, equality level and trends of self-rated health among old adults with intact physical condition.

BACKGROUND: Self-rated health among old adults (SHOA) indicates individuals' subjective assessments and evaluations of their overall health based on objective physical circumstances. The purpose of this study was to analyze the current state and influencing factors of the subjective perception-based self-rated health (SH) by qualifying selected older adults with similar objective physical conditions, as well as to explore the equality and changing trends of SHOA based on influencing factors. METHODS: This study designed a cross-sectional study, conducted in three provinces in east, central and west China, and included 1,153 older adults (> = 60 years) with intact physical condition (IPC). The current state of SHOA and its influencing factors were analyzed using mean comparisons and Logistic regression (LR) models. The equality level and trend of SHOA's effect on health literacy, health habits, and access to health care were determined using the Lorenz curve, Gini coefficient, and Vector Autoregression (VAR) model. RESULTS: The mean SHOA with IPC was 74.37 ± 13.22. Findings from LR modeling indicated that SHOA with IPC was mainly influenced by age and communication methods (P < 0.05). It was also observed that the total Gini coefficient of the allocation of SHOA with IPC based on communication methods was equal to 0.0188, and the VAR results showed that the total effect of change in SHOA on health literacy among older adults was negative and its duration of the effect exceeded 50. CONCLUSIONS: The SHOA with IPC was shown to be better and was primarily influenced by age and communication methods. The observed effect of SHOA on health literacy was negative and lasting. To improve SHOA with IPC even further, policymakers could consider promoting the use of modern and convenient communication methods (such as smartphones) through training and purchasing subsidies, as well as focusing on increasing sustained attention and promoting health literacy and behavior among older adults with improved SH.

A study on the equity of self-rated health of older adults at the family level.

BACKGROUND: The self-rated health of older adults (SHOA) plays an important role in enhancing their medical service utilization and quality of life. However, the determinants and magnitude variations in SHOA at the family level (SHOAFL) remain unknown. The purpose of this study was to assess the status and equitable level of SHOAFL in China, as well as to analyze the influencing factors and the precise nature and scope of their impacts. METHODS: This study analyzed the data from the "Chinese residents' health service needs survey in the New Era", and included a total of 1413 families with older adults. The status and influencing factors of SHOAFL were analyzed using mean comparison and Logistic regression (LR) models. The Concentration Index method was used to explore the equity of the distribution of SHOAFL. The relationship between differences in personal characteristics among family members and differences in SHOA was determined by the method of Coupling Coordination Degree (CCD). RESULTS: The total score of SHOAFL was 66.36 ± 15.47, and LR results revealed that the factors with a significant impact on SHOAFL were number of people living in family, distance to the nearest medical service institution, travel time to the nearest medical service institution, annual family income, yearly family medical and health expenditures, average age, and residence (all P < 0.05). The Concentration index of SHOAFL ranged from -0.0315 to 0.0560. CCD of the differences between SHOA and medical insurance and smoking status were 0.9534 and 0.7132, respectively. CONCLUSION: The SHOAFL was found to be generally but more inclined towards urban families with high incomes and a short time to medical service institution. The observed disparities in SHOA among family members were mostly attributable to differences in health insurance and pre-retirement occupations. The status and equality of SHOAFL may be improved if policymakers prioritize making services more accessible to older rural residents with low incomes. Concurrently, reducing the existing discrepancy in health insurance coverage between older couples may also enhance their health.

A study on the current state and equity level of the health promotion service demands among older adults in China.

BACKGROUND: Meeting the demands of older adults for health promotion services (DOAHPS) is essential for maintaining their health and enhancing their quality of life. The purpose of this study was to construct a model for evaluating DOAHPS to quantitatively evaluate the current state and equity level of DOAHPS in China, as well as to explore the main factors affecting DOAHPS' current state and equity level. METHODS: This study analyzed the DOAHPS data from the "Survey on Chinese Residents' Health Service Demands in the New Era", which included 1542 older adults aged 65 and older. Relationships between evaluation indicators of DOAHPS were explored using Structural Equation Modeling (SEM). The Weighted TOPSIS method and Logistic regression (LR) were used to analyze the current state and factors impacting DOAHPS. The equity level of DOAHPS' allocation among different older adult groups and its influencing factors were determined using the Rank Sum Ratio (RSR) method and T Theil index. RESULTS: The evaluation score for DOAHPS was 42.57 ± 1.51. Health status, health literacy and behavior were positively correlated with DOAHPS (r = 0.40, 0.38; P < 0.05). The LR results revealed that the most significant determinants of DOAHPS were sex, residence, education level and pre-retirement occupation (all P < 0.05). The number of older adults with very poor, poor, general, high and very high level health promotion service demands accounted for 2.27%, 28.60%, 53.05%, 15.43% and 0.65%, respectively. The total T Theil index of DOAHPS was 2.7433*10-4, and the intra-group difference contribution rate exceeded 72%. CONCLUSIONS: Compared to the maximum level, the total DOAHPS level was found to be moderate, although the demands of urban seniors with higher levels of education may be substantially greater. The observed inequities in the allocation of DOAHPS were primarily related to differences in education level and pre-retirement occupation within group. To better address health promotion services for older adults, policymakers could target older males with low education who reside in rural regions.

A study on the current state and equity level of social participation ability among older adults in Henan Province, China.

BACKGROUND: The social participation ability among older adults (SPAOA) plays an important role in enhancing their quality of life and utilization of medical services. This study aimed to evaluate the current state and equity level of SPAOA in Henan Province, China, as well as explore the factors associated with the current state and equity level of SPAOA. METHODS: This study analyzed data from the "2019 Henan Provincial Older Adults Ability Assessment Survey", which included 4,593 older people (over 60 years old). The relationships among the SPAOA indicators were explored using the Structural Equation Model (SEM). The Dynamic Material Element Analysis (DMA) and Logistic Regression (LR) were used to examine the current state of SPAOA and its associated factors. The equity level of SPAOA and its correlated factors were determined using the concentration index and T Theil index. RESULTS: SPAOA received an overall score of 91.89 ± 9.83. Daily living, perception ability and mental state were positively correlated with SPAOA (r = 0.13, 0.83, 0.11, all P < 0.05). Results of LR indicated that the most significant predictors of SPAOA were age, education level, pre-retirement occupation, and income (all P < 0.05). The concentration index of SPAOA based on age and income were -0.0058 and 0.0096, respectively. SPAOA had a total T Theil index of 0.030-0.031, and the contribution rate of the difference within the group was greater than 94%. CONCLUSIONS: While the overall level of SPAOA has been demonstrated to be outstanding, persons with a higher educational level and income are likely to benefit the most. The observed unequal distribution of SPAOA is primarily related to disparities in age or income within the group. To better serve older adults and improve their position and equity in terms of social participation ability, policymakers could emphasize older males with little income who live in urban areas, as well as unhealthy older females who live in rural residences.

Prediction of low Apgar score at five minutes following labor induction intervention in vaginal deliveries: machine learning approach for imbalanced data at a tertiary hospital in North Tanzania.

BACKGROUND: Prediction of low Apgar score for vaginal deliveries following labor induction intervention is critical for improving neonatal health outcomes. We set out to investigate important attributes and train popular machine learning (ML) algorithms to correctly classify neonates with a low Apgar scores from an imbalanced learning perspective. METHODS: We analyzed 7716 induced vaginal deliveries from the electronic birth registry of the Kilimanjaro Christian Medical Centre (KCMC). 733 (9.5%) of which constituted of low (< 7) Apgar score neonates. The 'extra-tree classifier' was used to assess features' importance. We used Area Under Curve (AUC), recall, precision, F-score, Matthews Correlation Coefficient (MCC), balanced accuracy (BA), bookmaker informedness (BM), and markedness (MK) to evaluate the performance of the selected six (6) machine learning classifiers. To address class imbalances, we examined three widely used resampling techniques: the Synthetic Minority Oversampling Technique (SMOTE) and Random Oversampling Examples (ROS) and Random undersampling techniques (RUS). We applied Decision Curve Analysis (DCA) to evaluate the net benefit of the selected classifiers. RESULTS: Birth weight, maternal age, and gestational age were found to be important predictors for the low Apgar score following induced vaginal delivery. SMOTE, ROS and and RUS techniques were more effective at improving "recalls" among other metrics in all the models under investigation. A slight improvement was observed in the F1 score, BA, and BM. DCA revealed potential benefits of applying Boosting method for predicting low Apgar scores among the tested models. CONCLUSION: There is an opportunity for more algorithms to be tested to come up with theoretical guidance on more effective rebalancing techniques suitable for this particular imbalanced ratio. Future research should prioritize a debate on which performance indicators to look up to when dealing with imbalanced or skewed data.

The Impact of Health Insurance Policy on the Fertility Intention of Rural Floating Population in China: Empirical Evidence from Cross-Sectional Data.

Declining total fertility rates pose a severe challenge to the economy, society, culture, and politics of any region. Low fertility rates among China's rural floating population with strong fertility are aggravating these challenges. Previous research has confirmed the relationships between health insurance and fertility intention. However, it is still unclear whether the existing association is favorable or not. Moreover, the majority of existing studies in China employ data from either urban or rural populations, whereas evidence from rural floating populations remains scarce. Based on the "China Migrants Dynamic Survey (CMDS)" in 2016, the current study used the logistic regression model to explore the impact of health insurance policy on the fertility intention of the rural floating population in China. Propensity Score Matching (PSM) was used to address potential selection bias. Three important findings were observed: Firstly, participating in the Basic Medical Insurance System (BMISUR) significantly improved rural floating populations' fertility intentions in China. Secondly, the association between age and the fertility intention of the floating population was "inverted u-shaped" with the highest fertility intention among those aged 25 to 34. There was also a positive correlation between personal income and fertility intention, and it was found between local housing purchase, formal employment, the co-residents scale, and the fertility intention in the rural floating population in China. Interprovincial mobility was positively associated with the fertility intention among rural migrants. Thirdly, the impact of health insurance policies on the fertility intention of the rural migrant population varies by gender, age, and inflow areas. The aforementioned findings can guide the Chinese government in its efforts to improve the fertility intention of the rural floating population, reform the social security system with a focus on "targets", and implement differentiated welfare policies aimed at promoting the equalization of basic public services, thereby contributing to China's population structure and long-term development.

The degree of equity and coupling coordination of staff in primary medical and health care institutions in China 2013-2019.

BACKGROUND: Primary medical and health care facilities are the first lines of defense for the health of population. This study aims to evaluate the current state and trend of equity and coupling coordination degree (CCD) of staff in primary medical and health care institutions (SPMHCI) based on the quantity and living standards of citizens in China 2013-2019. The research findings are expected to serve as a guideline for the allocation of SPMHCI. METHODS: The data used in this study including the quantity and living standards of citizens, as well as the number of SPMHCI in 31 provincial administrative regions of China, were obtained from the China Statistical Yearbook and the China Health Statistics Yearbook. The equity and CCD for SPMHCI were analyzed by using the Gini coefficient and the CCD model, and the Grey forecasting model GM (1, 1) (GM) was used to predict the equity and CCD from 2020 to 2022. RESULTS: Between 2013 and 2019, the number of SPMHCI increased from 3.17 million to 3.50 million, and the population-based Gini coefficient declined from 0.0704 to 0.0513. In urban and rural areas, the Gini coefficients decreased from 0.1185 and 0.0737 to 0.1025 and 0.0611, respectively. The CCD between SPMHCI and citizens' living standards (CLS) changed from 0.5691, 0.5813, 0.5818 to 0.5650, 0.5634, 0.6088 at national, urban, and rural levels, respectively. The forecasting results of GM revealed that at the national, urban and rural levels from 2020 to 2022, the Gini coefficient would rise at a rate of - 13.53, - 5.77%, and - 6.10%, respectively, while the CCD would grow at a rate of - 0.89, 1.06, and 0.87%, respectively. CONCLUSIONS: In China, the number of SPMHCI has increased significantly, with an equitable allocation based on the population. The interaction between SPMHCI and CLS is sufficient, but the degree of mutual promotion is moderate. The government could optimize SPMHCI and improve the chronic disease management services to improve CLS and to ensure the continued operation of primary medical and health care institutions in urban areas.

Combining Resampling Strategies and Ensemble Machine Learning Methods to Enhance Prediction of Neonates with a Low Apgar Score After Induction of Labor in Northern Tanzania.

OBJECTIVE: The goal of this study was to establish the most efficient boosting method in predicting neonatal low Apgar scores following labor induction intervention and to assess whether resampling strategies would improve the predictive performance of the selected boosting algorithms. METHODS: A total of 7716 singleton births delivered from 2000 to 2015 were analyzed. Cesarean deliveries following labor induction, deliveries with abnormal presentation, and deliveries with missing Apgar score or delivery mode information were excluded. We examined the effect of resampling approaches or data preprocessing on predicting low Apgar scores, specifically the synthetic minority oversampling technique (SMOTE), borderline-SMOTE, and the random undersampling (RUS) technique. Sensitivity, specificity, precision, area under receiver operating curve (AUROC), F-score, positive predicted values (PPV), negative predicted values (NPV) and accuracy of the three (3) boosting-based ensemble methods were used to evaluate their discriminative ability. The ensemble learning models tested include adoptive boosting (AdaBoost), gradient boosting (GB) and extreme gradient boosting method (XGBoost). RESULTS: The prevalence of low (<7) Apgar scores was 9.5% (n = 733). The prediction models performed nearly similar in their baseline mode. Following the application of resampling techniques, borderline-SMOTE significantly improved the predictive performance of all the boosting-based ensemble methods under observation in terms of sensitivity, F1-score, AUROC and PPV. CONCLUSION: Policymakers, healthcare informaticians and neonatologists should consider implementing data preprocessing strategies when predicting a neonatal outcome with imbalanced data to enhance efficiency. The process may be more effective when borderline-SMOTE technique is deployed on the selected ensemble classifiers. However, future research may focus on testing additional resampling techniques, performing feature engineering, variable selection and optimizing further the ensemble learning hyperparameters.

The situation and influencing factors of outpatient satisfaction in large hospitals: Evidence from Henan province, China.

BACKGROUND: The level of outpatient satisfaction plays a significant role in improving the quality and utilization of healthcare services. Patient satisfaction gives providers insights into various aspects of services including the effectiveness of care and level of empathy. This study aimed to evaluate the level of patient satisfaction in the outpatient department and to explore its influencing factors in large hospitals (accommodating over 1000 beds) of Henan province, China. METHODS: We analyzed data from Henan Large Hospitals Patient Satisfaction Survey conducted in the year 2018 and included 630 outpatients. Structural Equation Model (SEM) was used to explore the relationship among evaluation indicators of outpatient satisfaction levels. We used Dynamic Matter-Element Analysis (DMA) to evaluate the status of outpatient satisfaction. Binary Logistic Regression (BLR) was adopted to estimate the impact of personal characteristics towards outpatient satisfaction. RESULTS: The overall score for outpatient satisfaction in large hospitals was 66.28±14.73. The mean outpatient satisfaction scores for normal-large, medium-large, and extra-large hospitals were 63.33±12.12, 70.11±16.10, 65.41±14.67, respectively, and were significantly different (F = 11.953, P < 0.001). Waiting time, doctor-patient communication, professional services, and accessibility for treatment information were shown to have directly positive correlations with outpatient satisfaction (r = 0.42, 0.47, 0.55, 0.46, all P < 0.05). Results from BLR analysis revealed that patients' age and frequency of hospital visits were the main characteristics influencing outpatient satisfaction (P < 0.05). CONCLUSIONS: The outpatient satisfaction of large hospitals is moderately low. Hospital managers could shorten the waiting time for outpatients and improve the access to treatment information to improve the satisfaction of outpatients. It is also necessary to enhance service provision for outpatients under the age of 18 as well as the first-time patients.

The scale and structure of government financial investment in traditional medicine based on optimal efficiency: evidence from public traditional Chinese medicine hospitals (PTHs) of Henan province, China.

BACKGROUND: Traditional medicine has been widely used to address relatively common illnesses. In this regard, Chinese government has been continually topping up its investments on public Traditional Chinese Medicine hospitals (PTHs) in recent years. This study aimed to assess the optimal scales and structure of the investments in Henan province by analyzing the contribution of Government Financial Investment (GFI) to the efficiency and revenue growth of PTHs as well as recommending proper investment strategies for implementation to policy-makers. METHODS: This study was a panel data study, conducted in Henan Province, China. By collecting 143 PTHs' operational data from the year 2005 to 2017, Barro Economic Growth (BEG) model, Stochastic Frontier Analysis (SFA) and Vector Autoregressive (VAR) model were used to assess the efficiency and PTHs revenue. RESULTS: The study observed the positive contribution of GFI to PTHs' revenue growth (average MPG = 2.84), indicating that the GFI had not reached the required optimal level of "Barro Law". In order to maximize the input-output efficiency, the scales of GFI on Grade III, Grade II A, Grade II B PTHs need to be increased by - 5.96, 4.88 and 11.51%, respectively. The third year following the first investment may be a more essential period for conducting an effective GFI evaluation in Henan Province. CONCLUSIONS: GFI on PTHs usually has a long-term impact on PTHs. Governments can adjust its GFI policy so as to maximize the input-output efficiency.