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This study used an efficient data mining algorithm, called DCIP (the data cutting and inner product method), to explore association rules between the lifestyles of factory workers in Taiwan and the metabolic syndrome. A total of 1,216 workers in four companies completed a lifestyle questionnaire. Results of the questionnaire survey were integrated into the workers' health examination reports to form an attribute database of the metabolic syndrome. Among the association rules derived by DCIP, 80% of those on the list of the top 15 highest support counts are corroborated by medical literature or by healthcare professionals. These findings prove that data mining is a valid and effective research method, and that larger sample sizes will likely produce more accurate associations connecting the metabolic syndrome to specific lifestyles. The rules already verified can serve as a reference guide for the health management of factory workers. The remaining 20%, while still lacking hard evidence, provide fertile ground for future research. [ABSTRACT FROM AUTHOR]

Currently, interpretation of health examination reports relies primarily on the physician's own experience. If health screening data could be integrated with outpatient medical records to uncover correlations between disease and abnormal test results, the physician could benefit from having additional reference resources for medical examination report interpretation and clinic diagnosis. This study used the medical database of a regional hospital in Taiwan to illustrate how association rules can be found between abnormal health examination results and outpatient illnesses. The rules can help to build up a disease-prevention knowledge database that assists healthcare providers in follow-up treatment and prevention. Furthermore, this study proposes a new algorithm, the data cutting and sorting method, or DCSM, in place of the traditional Apriori algorithm. DCSM significantly improves the mining performance of Apriori by reducing the time to scan health examination and outpatient medical records, both of which are databases of immense sizes. [ABSTRACT FROM AUTHOR]

Background: The standardized mortality rate of type 2 diabetes is higher in Taiwan than that in other developed countries. In Taiwan, the diabetes mortality rate in Chiayi County is the highest nationwide. Purpose: This study was designed to explore the health status (to measure six physiological indicators), the health-related behaviors, and the associated factors among type 2 diabetes sufferers living in rural communities. Methods: Researchers used a cross-sectional, correlation design and conducted the study at nine local health districts in Chiayi County, Taiwan. A total of 387 participants previously diagnosed with type 2 diabetes were randomly selected and invited to join in the program. Results: Fifty-nine percent of participants were women; their mean age was 68.7 years, and their mean duration with diabetes was 7.9 years. Most were treated at local health centers and took oral medications (90.7%). More than 40% did not exercise regularly and 33.9% did not practice diet control. Results found a higher percentage of abnormal health indicators in terms of participant body mass index, waist circumference, HbA1C, and peripheral neurovascular function. After controlling for potential confounding factors, researchers found smaller waist circumference, participating in community support groups, better foot self-care capability, and frequent exercise to be associated with better health indicators. Diabetes duration, lower education, and being of mate gender were found to be negatively associated with health status. Conclusions/Implications for Practice: This study found that rural residents with diabetes do not adequately control their diabetes and exhibit inadequate health-related behavior. Joining community support groups, increasing exercise frequencies, and improving foot self-care capabilities should be employed in nursing strategies and health policies for diabetes control--especially for those who have less formal education or are male. [ABSTRACT FROM AUTHOR]

This study was based on the analysis of isotopic compositions of hydrogen and oxygen in samples from precipitation, groundwater and stream water. In addition, parts of groundwater samples were dated by carbon-14 and tritium. These data are integrated to provide other views of the hydrologic cycle in the Hsinchu-Miaoli groundwater district. The groundwater district is principally composed of Pleistocene and Holocene aquifers. The Pleistocene aquifers are highly deformed by folding and faults into small sub-districts with areas of only tens of square kilometers. These aquifers are exclusively recharged by local precipitation. The Holocene aquifers cover narrow creek valleys, only tens of meters in thickness. The local meteoric water line (LMWL), constructed from rainfall samples in the Hsinchu Science Park, is described by the equation δD=8.02δ18O+10.16, which agrees with the global meteoric water line. In addition, the precipitation isotopic compositions can be categorized into two distinct end members: typhoon type and monsoon type. The groundwater isotopic compositions are perfectly located on an LMWL and can be considered a mixture of precipitations. Based on the mass balance of isotopic compositions of oxygen and hydrogen, infiltration is more active in the rainy season with depleted isotopic compositions. The amount of infiltration during May–September is roughly estimated to comprise at least 55% of the whole year’s recharge. The isotopic compositions of stream water are expressed by a regression equation: δD=7.61δ18O+9.62, which is similar to the LMWL. Although precipitation isotopic compositions are depleted during summer time, the isotopic compositions contrarily show an enriched trend in the upstream area. This is explained by the opposite altitude effect on isotopic compositions for typhoon-related precipitations. [ABSTRACT FROM AUTHOR]

To compare the practicality, reliability, validity, and responsiveness of the timed up and go (TUG), one-leg stand (OLS), functional reach (FR), and Tinetti balance (TB) performance measures in people aged 65 and older. A prospective study. Shin-Sher Township of Taichung County, west-central Taiwan. Twelve hundred community-dwelling older people. During an initial assessment at their residences, participants were interviewed for demographics, cognition, fall history, use of a walking aid, and activities of daily living (ADLs), in addition to completing the four balance tests. Falls were ascertained by telephone every 3 months for a 1-year follow-up; the four balance measures and ADLs were also reassessed at the end of the follow-up year. Of the four balance measures, the OLS had the lowest participation rate, and participation of people who were cognitively impaired had fallen in the previous year, used a walking aid, or suffered from an ADL disability was lower than for their counterparts. The time to complete the tests ranged from 58 seconds for OLS, to 160 seconds for the TB. All four balance measures exhibited excellent test-retest reliability and discriminant validity but poor responsiveness to fall status. The TB showed better discriminant, convergent, and predictive validities and responsiveness to ADL changes than the other three tests. According to psychometric properties, the most suitable performance measure for evaluating balance in community-dwelling older people was the TB, followed by the TUG. [ABSTRACT FROM AUTHOR]

Currently, interpretation of health examination reports relies primarily on the physician's own experience. If health screening data could be integrated with outpatient medical records to uncover correlations between disease and abnormal test results, the physician could benefit from having additional reference resources for medical examination report interpretation and clinic diagnosis. This study used the medical database of a regional hospital in Taiwan to illustrate how association rules can be found between abnormal health examination results and outpatient illnesses. The rules can help to build up a disease-prevention knowledge database that assists healthcare providers in follow-up treatment and prevention. Furthermore, this study proposes a new algorithm, the data cutting and sorting method, or DCSM, in place of the traditional Apriori algorithm. DCSM significantly improves the mining performance of Apriori by reducing the time to scan health examination and outpatient medical records, both of which are databases of immense sizes.