Forecasting Weekly Influenza Outpatient Visits Using a Two-Dimensional Hierarchical Decision Tree Scheme

[[abstract]]Influenza is a serious public health issue, as it can cause acute suffering and even death, social disruption, and economic loss. Effective forecasting of influenza outpatient visits is beneficial to anticipate and prevent medical resource shortages. This study uses regional data on influenza outpatient visits to propose a two-dimensional hierarchical decision tree scheme for forecasting influenza outpatient visits. The Taiwan weekly influenza outpatient visit data were collected from the national infectious disease statistics system and used for an empirical example. The 788 data points start in the first week of 2005 and end in the second week of 2020. The empirical results revealed that the proposed forecasting scheme outperformed five competing models and was able to forecast one to four weeks of anticipated influenza outpatient visits. The scheme may be an effective and promising alternative for forecasting one to four steps (weeks) ahead of nationwide influenza outpatient visits in Taiwan. Our results also suggest that, for forecasting nationwide influenza outpatient visits in Taiwan, one- and two-time lag information and regional information from the Taipei, North, and South regions are significant.[[notice]]補正完

Associations of lower-limb muscle strength performance with static and dynamic balance control among older adults in Taiwan

BackgroundAging is an inevitable process of life development. These physical changes can cause a decline in the functional adaptability and health status of older adult individuals.AimsThe purpose of this study was to investigate the association of lower-limb muscle strength performance with static and dynamic balance control among older adults in Taiwan.MethodsWe conducted a cross-sectional study and reviewed data derived from the National Physical Fitness Survey in Taiwan 2015–2016. A total of 20,846 Taiwanese older adult individuals aged 65 years old or older were recruited as study participants. Demographic characteristics, anthropometric assessments, lifestyle habits, and health-related physical fitness measurements from this dataset were analyzed using the chi-square test, one-way analysis of variance, and linear regression analysis. Lower-limb muscle strength performance was classified into 4 groups based on quartile (Quartile 1 [Q1], Quartile 2 [Q2], Quartile 3 [Q3], and Quartile 4 [Q4]) values.ResultsIncreased lower-limb muscle strength levels were significantly associated with static balance in men (Q2: β = 2.539, p < 0.0001; Q3: β = 4.590, p < 0.0001; Q4: β = 7.700, p < 0.0001) and women (Q2: β = 2.022, p < 0.0001; Q3: β = 4.179, p < 0.0001; Q4: β = 6.920, p < 0.0001) after adjusting for potential confounders. In addition, we observed that increased lower-limb muscle strength levels were significantly associated with dynamic balance in men (Q2: β = −1.661, p < 0.0001; Q3: β = −2.434, p < 0.0001; Q4: β = −3.091, p < 0.0001) and women (Q2: β = −1.660, p < 0.0001; Q3: β = −2.548, p < 0.0001; Q4: β = −3.196, p < 0.0001) after adjusting for potential confounders.ConclusionLower-limb muscle strength was the most important factor, as it was an improved method for static and dynamic balance control in both genders

A Hybrid Machine Learning Scheme to Analyze the Risk Factors of Breast Cancer Outcome in Patients with Diabetes Mellitus

Along with the worldwide trend of rapidly aging populations, diabetes mellitus and its comprehensive complications have become major public health issues. Considerable evidence suggests patients with diabetes mellitus have a higher risk of breast cancer. However, the relationships between the complications of diabetes mellitus and occurrence of breast cancer have not been well characterized. Despite the higher risk of breast cancer among patients with diabetes mellitus, patients with breast cancer constitute only a relatively small proportion of the diabetes mellitus data, leading to an imbalanced data set. This study proposes a hybrid machine learning scheme to cope with imbalanced data in the analysis of risk factors of breast cancer in patients with diabetes mellitus. The scheme combines the undersampling based on the clustering algorithm, the k-means algorithm, and the extreme gradient boosting algorithm. The results identify that occlusion stroke, diabetes with peripheral circulatory disorders, peripheral angiopathy in diseases classified elsewhere, and other forms of chronic ischemic heart disease are risk factors. This study provides an application of advanced methods in health care and shows the epidemiologic and informatics value of the proposed hybrid machine learning scheme

Cluster analysis of medical service resources at district hospitals in Taiwan, 2007–2011

Background: A vast amount of the annual/national budget has been spent on the National Health Insurance program in Taiwan. However, the market for district hospitals has become increasingly competitive, and district hospitals are under pressure to optimize the use of health service resources. Therefore, we employed a clustering method to explore variations in input and output service volumes, and investigate resource allocation and health care service efficiency in district hospitals. Methods: Descriptive and cluster analyses were conducted to examine the district hospitals included in the Ministry of Health and Welfare database during 2007–2011. Results: The results, according to the types of hospital ownership, suggested that the number of public hospitals has decreased and that of private hospitals increased; the largest increase in the number of district hospitals occurred when Taichung City was merged into Taichung County. The descriptive statistics from 2007 to 2011 indicated that 43% and 36.4% of the hospitals had 501–800 occupied beds and 101–200 physicians, respectively, and > 401 medical staff members. However, the number of outpatients and discharged patients exceeded 6001 and 90,001, respectively. In addition, the highest percentage of hospitals (43.9%) had 30,001–60,000 emergency department patients. In 2010, the number of patients varied widely, and the analysis of variance cluster results were nonsignificant (p > 0.05). Conclusion: District hospitals belonging to low-throughput and low-performance groups were encouraged to improve resource utilization for enhancing health care service efficiency

The Effects of Daily Sleep Condition on Performances of Physical Fitness among Taiwanese Adults: A Cross-Sectional Study

Physical fitness is a powerful indicator of health. Sleep condition plays an essential role in maintaining quality of life and is an important marker that predicts physical fitness. This study aimed to determine the relationship between sleep conditions (sleep quality, sleep duration, bedtime) and multiple physical fitness indicators (body mass index (BMI), flexibility, abdominal muscle strength and endurance, cardiopulmonary endurance) in a well-characterized population of Taiwanese adults aged 23 to 65. The applied data were obtained from the National Physical Fitness Examination Survey 2014 conducted in Taiwan. We assessed the association of the sleep conditions with physical fitness performances in Taiwanese adults by using the multivariate adaptive regression spline (MARS) method with a total of 69,559 samples. The results show that sleep duration, sleep quality, and bedtime were statistically significant influence factors on physical fitness performances with different degrees. Gender was an important factor that affects the effects of daily sleep conditions on performances of physical fitness. Sleep duration was the most important factor as it was simultaneously correlated with BMI, sit-ups, and sit-and-reach indicators in both genders. Bedtime and sleep quality were only associated with sit-ups performance in both genders

Poor Physical Fitness Performance as a Predictor of General Adiposity in Taiwanese Adults

The purpose of the present study was to investigate the association between different levels of health-related physical fitness measurements and obesity status in Taiwanese adults. A cross-sectional study was conducted by reviewing the National Physical Fitness Survey in Taiwan (HPFSIT) database. Responses from 60,056 participants, aged 23–64 years from the database were collected in the present study. Data from a standardized structured questionnaire and health-related physical fitness tests were analyzed. The quartiles of each physical fitness measurement were used for unconditional logistic regression analyses. Our results indicated clear trends in the association between cardiorespiratory fitness and overweight/obesity. Overweight and obesity were associated with a 10% to 60% increased risk of low levels of cardiorespiratory fitness in men and a 10% to almost 30% increased risk in women. However, the association between muscle strength/endurance and obesity status as well as flexibility and obesity status needs further investigation