What Are the Sources of Exposure to Eight Frequently Used Phthalic Acid Esters in Europeans?

Phthalic acid esters (phthalates) are used as plasticizers in numerous consumer products, commodities, and building materials. Consequently, phthalates are found in human residential and occupational environments in high concentrations, both in air and in dust. Phthalates are also ubiquitous food and environmental contaminants. An increasing number of studies sampling human urine reveal the ubiquitous phthalate exposure of consumers in industrialized countries. At the same time, recent toxicological studies have demonstrated the potential of the most important phthalates to disturb the human hormonal system and human sexual development and reproduction. Additionally, phthalates are suspected to trigger asthma and dermal diseases in children. To find the important sources of phthalates in Europeans, a scenario-based approach is applied here. Scenarios representing realistic exposure situations are generated to calculate the age-specific range in daily consumer exposure to eight phthalates. The scenarios demonstrate that exposure of infant and adult consumers is caused by different sources in many cases. Infant consumers experience significantly higher daily exposure to phthalates in relation to their body weight than older consumers. The use of consumer products and different indoor sources dominate the exposure to dimethyl, diethyl, benzylbutyl, diisononyl, and diisodecyl phthalates, whereas food has a major influence on the exposure to diisobutyl, dibutyl, and di-2-ethylhexyl phthalates. The scenario-based approach chosen in the present study provides a link between the knowledge on emission sources of phthalates and the concentrations of phthalate metabolites found in human urine.     

Changes in the association between job decision latitude and work engagement at different levels of work experience: A 10-year longitudinal study

ABSTRACT

This study set out to explore the effects of accumulating work experience on the association between job decision latitude and its interaction with job demands and work engagement. Our ten-year longitudinal study followed 333 junior physicians in postgraduate training at baseline. We used self-report measures in four assessment waves, and we conducted path analyses to investigate linear and curvilinear regression effects. Results show that high job decision latitude was associated with high work engagement at all levels of work experience, with strongest associations at baseline and after ten years. Only for novices did job decision latitude buffer the negative association between job demands and work engagement. At the stage of high work experience, low levels of job decision latitude were weakly associated with work engagement, whereas with higher levels of job decision latitude, the positive association seemed to strengthen. Our findings indicate that job decision latitude is a key job resource at all stages of work experience, with stronger effects among novices and experts. Organisations’ work design efforts should include job decision latitude to promote work engagement across employees’ different career stages, with consideration to job entrants and experts in order to tailor specific work design solutions.     

Isotonic Window Estimators of the Baseline Hazard Function in Cox's Regression Model Under Order Restriction

The regression model suggested by Cox (1972) has been widely used in survival analysis with censored observations. We propose isotonic window estimators for a monotone baseline hazard function in the Cox regression model. We prove that these estimators are asymptotically normal. The simulati on results presented in the article suggest that the proposed estimator performs better than several existing estimators in the literature     

Health Service Utilization and Expenditure of the Elderly in China

Using data from the China Health and Retirement Longitudinal Survey, we employed counterfactual propensity score matching to examine the association between income and health service utilization and expenditure of the elderly in China. The results demonstrated that income did not differentiate whether the poor elderly in China visited a doctor when suffering an illness, but their expenditure on medical treatment was significantly associated with income. Subgroup analysis further indicated that the medical demands of female, older, and rural elderly were more likely to be reduced by their income compared with their counterparts.     

The Role of Social Contact in the Experience of Discrimination: Implications for Subjective Health Among Marriage Migrant Women in South Korea

Several studies have found that various social contexts could serve a protective role for minorities facing discrimination. One of these contexts is frequency of social contact, which is known to be positively associated with health outcomes. The purpose of this study was to examine the frequency of social contact with various social groups as a protective factor against the negative association between perceived discrimination and subjective health. Using data from the 2009 Korean National Survey of Multicultural Families, a total of 27,083 marriage migrant women were analyzed via hierarchical multiple regression. After controlling for socio‐demographic factors and Korean proficiency, the experience of discrimination was found to be significantly associated with lower levels of subjective health (B = ?0.22; P < 0.001). More frequent meetings with one's family of origin (B = 0.02; P < 0.01) and in‐laws (B = 0.06; P < 0.001) were associated with higher levels of subjective health, while more frequent meetings with neighbors were negatively associated (B = ?0.02; P < 0.001). More frequent contact with one's family of origin (B = 0.03; P < 0.05), rather than with other groups, such as friends from their country of origin, in‐laws, and neighbors, seemed to reduce the negative influence of discrimination on subjective health.     

Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates

We present a new algorithm for boosting generalized additive models for location, scale and shape (GAMLSS) that allows to incorporate stability selection, an increasingly popular way to obtain stable sets of covariates while controlling the per-family error rate. The model is fitted repeatedly to subsampled data, and variables with high selection frequencies are extracted. To apply stability selection to boosted GAMLSS, we develop a new “noncyclical” fitting algorithm that incorporates an additional selection step of the best-fitting distribution parameter in each iteration. This new algorithm has the additional advantage that optimizing the tuning parameters of boosting is reduced from a multi-dimensional to a one-dimensional problem with vastly decreased complexity. The performance of the novel algorithm is evaluated in an extensive simulation study. We apply this new algorithm to a study to estimate abundance of common eider in Massachusetts, USA, featuring excess zeros, overdispersion, nonlinearity and spatiotemporal structures. Eider abundance is estimated via boosted GAMLSS, allowing both mean and overdispersion to be regressed on covariates. Stability selection is used to obtain a sparse set of stable predictors.     

Supporting familial and community care for children: legislative reform and implementation challenges in South Africa

This article critically evaluates important legislative reforms in South Africa, which, at the height of the AIDS pandemic, are intended to reduce the need for removing children from their families or communities. In a textual analysis of the 2005 Children's Act and the 2006 Children's Act Amendment Bill, the shift in focus from individual interventions to a developmental approach incorporating prevention and early intervention is explained. New family service and alternative care orders such as partial care, shared care, cluster care and support for child-headed households are described. Although these creative solutions have considerable potential, there are gaps in the legislation that require supplementary wording. Drawing on the work of researchers and commentators, it is also shown that an inappropriate approach towards implementation has commenced, which harms rather than assists children. Recommendations are made for improving implementation that may be of relevance to other countries faced with similar challenges.     

SIDE EFFECTS OF CAMPAIGN FINANCE REFORM

Because campaign finance reform is usually motivated by the concern that existing legislation cannot effectively prevent campaign contributions to “buy favors,” this article assumes that contributions influence political decisions. But, given that it is also widely recognized that interest groups achieve influence by providing political decision makers with policy relevant information, we also assume that lobbies engage in non‐negligible informational lobbying. We focus on a single political decision to be taken and offer a simple model in which the optimal influence strategy is a mixture of both lobbying instruments. Our main result is to show that campaign finance reform may have important side effects: It may deter informational lobbying so that less policy relevant information is available and as a result political decisions become less efficient. (JEL: C72, D72)     

Generalized Tukey-type distributions with application to financial and teletraffic data

Constructing skew and heavy-tailed distributions by transforming a standard normal variable goes back to Tukey (Exploratory data analysis. Addison-Wesley, Reading, 1977) and was extended and formalized by Hoaglin (In: Data analysis for tables, trends, and shapes. Wiley, New York, 1983) and Martinez and Iglewicz (Commun Statist Theory Methods 13(3):353–369, 1984). Applications of Tukey’s GH distribution family—which are composed by a skewness transformation G and a kurtosis transformation H—can be found, for instance, in financial, environmental or medical statistics. Recently, alternative transformations emerged in the literature. Rayner and MacGillivray (Statist Comput 12:57–75, 2002b) discuss the GK distributions, where Tukey’s H-transformation is replaced by another kurtosis transformation K. Similarly, Fischer and Klein (All Stat Arch, 88(1):35–50, 2004) advocate the J-transformation which also produces heavy tails but—in contrast to Tukey’s H-transformation—still guarantees the existence of all moments. Within this work we present a very general kurtosis transformation which nests H-, K-and an approximation to the J-transformation and, hence, permits to discriminate between them. Applications to financial and teletraffic data are given.