Search

Background: Observation and feedback are core strategies of hand hygiene (HH) improvement. Direct overt observation is currently the gold standard method. Observation bias, also known as the Hawthorne effect, is a major disadvantage of this method. Our aim was to examine the variation of the Hawthorne effect on HH observation in different healthcare groups and settings., Methods: A prospective cohort study was performed in a tertiary teaching hospital during a 15-month period. Up to 38 overt observers (82% nurses) and 93 covert observers (81% medical students) participated in HH observation. The HH events observed overtly were matched for occupation, department, observation time, and location with those observed covertly. The data of matched pairs were then analysed to detect possible Hawthorne effects on different variables., Results: A total of 31,522 HH opportunities were observed (4581 overtly, 26,941 covertly). There were 3047 matched pairs after 1:1 matching of overt and covert observations. The overall HH compliance was higher with overt observation than with covert observation (78% vs. 55%, p < 0.001). The Hawthorne effect was nearly three times larger in nurses (30 percentage points) than in physicians (11 percentage points) and was significantly greater in outpatient clinics (41 percentage points) than in intensive care units (11 percentage points). The magnitude of the Hawthorne effect varied among healthcare worker occupations and observation locations (p values both < 0.001) but not among departments, observation times, or HH indications., Conclusions: Heterogeneity in the Hawthorne effect may influence the interpretation of overt observations and prevent the correct identification of target populations with poor HH compliance. Therefore, directly observed HH compliance may not be an adequate performance indicator for infection control.

Objective: This study examined the distribution of perceived workplace justice and examined the modifying effects of gender, age and enterprise size on the associations between workplace justice and poor health., Methods: A total of 9,636 male and 7,406 female employees from a national survey conducted in 2007 in Taiwan were studied. A self-administered questionnaire was used to assess workplace justice (9 items), psychosocial work conditions, self-rated health and burnout status., Results: A clear gradient was observed across employment grades, with employees of lower grades reporting lower workplace justice. Government employees were found to have higher levels of workplace justice than those in private sectors, and among those in private sectors, female employees in larger enterprises were found to have significantly lower workplace justice. Multivariate regression analyses showed that employees with workplace justice in the lowest tertile had increased scores in work-related burnout (11.0 and 12.8 points in men and women, respectively) and increased risks for poor self-rated health (OR = 2.5, 2.6) as compared to those with workplace justice in the highest tertile. The associations were stronger in younger groups than in older groups, and in female employees of larger enterprises than those of smaller enterprises., Conclusion: Employees with lower socioeconomic position and female employees in larger enterprises might be more likely to be exposed to work practices that give rise to the sense of injustice. The underlying mechanisms for the observed stronger associations between lower workplace justice and poor health in younger groups and in workers of larger enterprises deserve further investigation.

A deeper understanding of extreme hot weather are needed in cities sensitive to heat effects, an investigation was done in the tropical town of Kaohsiung in Taiwan. Its 11 districts were divided into three climatic classes varying from high urban heat, low levels of green space and lack of proximity to water bodies to low urban heat, adequate green space and proximity to water bodies. Daily data on natural mortality, meteorological variables, and pollutants from May-October 1999-2008 were analysed using generalised additive models for the time-series data. Subgroup analyses were conducted, stratifying decedents according to the level of planning activity required in order to mitigate adverse heat effects in their residential areas, classifying districts as "level 1" for those requiring a high level of mitigation action; "level 2" for those requiring some action; and "level 3" for those that need only preserve existing conditions. Stratified analyses showed that mortality increases per 1 °C rise on average, either on the same day or in the previous 4 days (lags 0-4), were associated with 2.8%, 2.3% and -1.3% for level 1, 2 and 3 districts, respectively. The slope describing the association between temperature and mortality was higher above 29.0 °C resulting in corresponding increases of 4.2%, 5.0% and 0.3% per per 1 °C rise in temperature, respectively. Other meteorological variables were not significantly associated with mortality. It is concluded that hot season mortality in Kaohsiung is only sensitive to heat effects in districts classified as having unfavourably climatic conditions and requiring mitigation efforts in city planning. Urban planning measures designed to improve climatic conditions could reduce excess mortality resulting from extreme hot weather.

Background: Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared., Methods: The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests., Results: In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?

The objectives of this study were to (1) examine the relationship between total trihalomethanes (TTHM) levels in public water supplies and risk of esophageal cancer occurrence and (2) determine whether calcium (Ca) and magnesium (Mg) levels in drinking water modify the effects of TTHM on risk to develop esophageal cancer. A matched case-control study was used to investigate the relationship between the risk of death attributed to esophageal cancer and exposure to TTHM in drinking water in 53 municipalities in Taiwan. All esophageal cancer deaths in the 53 municipalities from 2006 through 2010 were obtained from the Bureau of Vital Statistics of the Taiwan Provincial Department of Health. Controls were deaths from other causes and were pair-matched to the cancer cases by gender, year of birth, and year of death. Each matched control was selected randomly from the set of possible controls for each cancer case. Data on TTHM levels in drinking water were collected from Taiwan Environmental Protection Administration. Information on the levels of Ca and Mg in drinking water was obtained from the Taiwan Water Supply Corporation. The municipality of residence for cancer cases and controls was presumed to be the source of the subject's TTHM, Ca, and Mg exposure via drinking water. Relative to individuals whose TTHM exposure level <4.9 ppb, the adjusted odds ratio (OR) with 95% confidence interval (CI) for esophageal cancer was 1.02 (0.84-1.23) for individuals who resided in municipalities served by drinking water with a TTHM exposure ≥4.9 ppb. There was evidence of an interaction between drinking-water TTHM levels and low Ca and Mg intake. Our findings showed that the correlation between TTHM exposure and risk of esophageal cancer development was influenced by Ca and Mg levels in drinking water. This is the first study to report effect modification by Ca and Mg intake from drinking water on the correlation between TTHM exposure and risk of esophageal cancer occurrence. Increased knowledge of the interaction between Ca, Mg, and TTHM in reducing risk of esophageal cancer development will aid in public policymaking and standard setting for drinking water.

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

Recent studies showed that air pollution is a risk factor for hospitalization for myocardial infarction (MI). However, there is limited evidence to suggest which subpopulations are at higher risk for MI arising from air pollution. This study was undertaken to examine the modifying effects of specific secondary cardiovascular diagnosis (including hypertension, diabetes, congestive heart failure, and arrhythmias) on the relationship between hospital admissions for MI and exposure to ambient air pollutants. Hospital admissions for MI and ambient air pollution data for Taipei were obtained for the period 1999-2009. The relative risk of hospital admissions for MI was estimated using a case-crossover approach. None of the secondary diagnosis examined showed significant evidence of effect modification. It would appear that the correlation between air pollutant exposure and MI occurrence is not affected by predisposing factors present in other cardiovascular diseases.

The objective of this study was to explore whether calcium (Ca) levels in drinking water modified the effects of nitrate on colon cancer risk. A matched case-control study was used to investigate the relationship between the risk of death from colon cancer and exposure to nitrate in drinking water in Taiwan. All colon cancer deaths of Taiwan residents from 2003 through 2007 were obtained from the Bureau of Vital Statistics of the Taiwan Provincial Department of Health. Controls were deaths from other causes and were pair-matched to the cases by gender, year of birth and year of death. Information on the levels of nitrate-nitrogen (NO(3)-N) and Ca in drinking water have been collected from Taiwan Water Supply Corporation (TWSC). The municipality of residence for cases and controls was assumed to be the source of the subject's NO(3)-N and Ca exposure via drinking water. We observed evidence of an interaction between drinking water NO(3)-N and Ca intake via drinking water. This is the first study to report effect modification by Ca intake from drinking water on the association between NO(3)-N exposure and risk of colon cancer mortality.

Background: Job satisfaction and quality of life among home care workers who serve simultaneously as informal carers for their own family members have seldom been explored. This study examined how this dual role influences job satisfaction and quality of life by comparing these dual carers with home care workers who do not provide informal care. The study also explored whether the factors related to job satisfaction and quality of life between these two groups were different., Method: Standardized self-administered questionnaires (Job Satisfaction Survey, the World Health Organization Quality of Life (WHOQOL) scales and various social demographic questions) were administered to the two groups of home care workers in Taiwan from March to April 2009. A total of 1,641 home care workers working in 119 non-government organizations sponsored by 23 local authorities completed and returned the questionnaires., Results: The two groups did not differ in individual characteristics, work characteristics or job satisfaction. Analysis results indicate that the lowest mean scores for all home care workers were the domains of promotion and pay within their job satisfaction and the domain of environment within their quality of life., Conclusions: Multiple regression analysis revealed a significant effect of unpaid caregiving in terms of quality of life but not in terms of job satisfaction. Moreover, job satisfaction and quality of life among home care workers were significantly determined by both their work conditions (e.g. travelling time, salary and length of work experience) and personal variables (e.g. age, family income and family support).

Family studies to identify disease-related genes frequently collect only families with multiple cases. It is often desirable to determine if risk factors that are known to influence disease risk in the general population also play a role in the study families. If so, these factors should be incorporated into the genetic analysis to control for confounding. Pfeiffer et al. [2001 Biometrika 88: 933-948] proposed a variance components or random effects model to account for common familial effects and for different genetic correlations among family members. After adjusting for ascertainment, they found maximum likelihood estimates of the measured exposure effects. Although it is appealing that this model accounts for genetic correlations as well as for the ascertainment of families, in order to perform an analysis one needs to specify the distribution of random genetic effects. The current work investigates the robustness of the proposed model with respect to various misspecifications of genetic random effects in simulations. When the true underlying genetic mechanism is polygenic with a small dominant component, or Mendelian with low allele frequency and penetrance, the effects of misspecification on the estimation of fixed effects in the model are negligible. The model is applied to data from a family study on nasopharyngeal carcinoma in Taiwan., (Copyright 2003 Wiley-Liss, Inc.)