Clinical Capital and the Risk of Maternal Labor and Delivery Complications: Hospital Scheduling,Timing, and Cohort Turnover Effects

The establishment of interventions to maximize maternal health requires the identification of modifiable risk factors. Toward the identification of modifiable hospital‐based factors, we analyze over 2 million births from 2005 to 2010 in Texas, employing a series of quasi‐experimental tests involving hourly, daily, and monthly circumstances where medical service quality (or clinical capital) is known to vary exogenously. Motivated by a clinician's choice model, we investigate whether maternal delivery complications (1) vary by work shift, (2) increase by the hours worked within shifts, (3) increase on weekends and holidays when hospitals are typically understaffed, and (4) are higher in July when a new cohort of residents enter teaching hospitals. We find consistent evidence of a sizable statistical relationship between deliveries during nonstandard schedules and negative patient outcomes. Delivery complications are higher during night shifts (OR = 1.21, 95% CI: 1.18–1.25), and on weekends (OR = 1.09, 95% CI: 1.04–1.14) and holidays (OR = 1.29, 95% CI: 1.04–1.60), when hospitals are understaffed and less experienced doctors are more likely to work. Within shifts, we show deterioration of occupational performance per additional hour worked (OR = 1.02, 95% CI: 1.01–1.02). We observe substantial additional risk at teaching hospitals in July (OR = 1.28, 95% CI: 1.14–1.43), reflecting a cohort‐turnover effect. All results are robust to the exclusion of noninduced births and intuitively falsified with analyses of chromosomal disorders. Results from our multiple‐test strategy indicate that hospitals can meaningfully attenuate harm to maternal health through strategic scheduling of staff.     

Poverty affects access to regular source of primary care among the general population in Hong Kong

A territory‐wide two‐stage stratified random sample of 2,282 community‐dwelling Hong Kong adults were surveyed between 2014 and 2015 to investigate the association between poverty and regular source of primary care utilization. Poverty was operationalized by income‐poverty and deprivation. About 94% of our sample reported having regular source of primary care (Western and/or Chinese medical practitioner) and about 69% among them were in private sector. Multivariable logistic regression showed that people who were income‐poor and deprived were less likely to have regular source of primary care (income‐poor: OR = 0.523, p = .027; deprived: OR = 0.488, p = .007) and visit private primary care doctors (income‐poor: OR = 0.445, deprived: OR = 0.222, both p < .0001). Those who had chronic diseases were more likely to have regular source of primary care (multimorbid: OR = 10.709, p < .0001), but less likely to access care in the private sector (one chronic disease: OR = 0.690, p = .019; multimorbid: OR = 0.374, p < .0001) than those without. Further, being older and less skilled were significantly associated with less likelihood of visiting a private doctor. Path analysis showed that the number of chronic diseases had significant indirect effect on having regular source of primary care with being income‐poor and deprived as the mediators (β = ?.0183, p = .0016). Therefore, despite a public health‐care system that aims to deny no one from adequate health care for lack of means, regular source of primary care in Hong Kong is found to be pro‐rich. Future policies should tackle the problem of health‐care inequalities to meet the needs of the underprivileged.     

Talking about Integration: The Voices of Syrian Refugees Taking Part in Introduction Programmes for Integration into Swedish Society

The significant increase in the number of refugees entering the European Union and the low employment rates among them remain pressing issues across Europe. While previous research has mainly focused on refugee integration prospects from the policymakers’ point of view, we shift the analytical focus to how refugees perceive the introduction programme experience, examining the case of Syrian refugees to Sweden. Drawing upon semi‐structured interviews with Syrian refugees, our results suggest that the quality of language training, the complexity of the validation process for educational qualifications and the lengthy administrative procedures are perceived as important barriers hindering the access of refugees to the Swedish labour market. These barriers are differently perceived, especially by those with differing levels of education. This highlights the utility of an intersectional approach, and the continued need to explore the diversity of migrant experiences when assessing integration policies and programmes.     

On the use of priors in goodness‐of‐fit tests

Priors are introduced into goodness‐of‐fit tests, both for unknown parameters in the tested distribution and on the alternative density. Neyman–Pearson theory leads to the test with the highest expected power. To make the test practical, we seek priors that make it likely a priori that the power will be larger than the level of the test but not too close to one. As a result, priors are sample size dependent. We explore this procedure in particular for priors that are defined via a Gaussian process approximation for the logarithm of the alternative density. In the case of testing for the uniform distribution, we show that the optimal test is of the U‐statistic type and establish limiting distributions for the optimal test statistic, both under the null hypothesis and averaged over the alternative hypotheses. The optimal test statistic is shown to be of the Cramér–von Mises type for specific choices of the Gaussian process involved. The methodology when parameters in the tested distribution are unknown is discussed and illustrated in the case of testing for the von Mises distribution. The Canadian Journal of Statistics 47: 560–579; 2019 © 2019 Statistical Society of Canada     

The social work services in screening process of compulsory treatment interventions in addicts in Iran: A content analysis study

Compulsory treatment has had a detrimental impact on drug abuse treatment policies and programs in Iran. Physicians are currently required to conduct initial treatment screening. Social workers are a part of the treatment team but have no authority to initiate a compulsory drug treatment plan. For this reason, the present article investigates social work service participation in the process of compulsory drug treatment. The study methodology is content analysis. Nine social workers participated in seven focus group discussions. Overall, 110 codes were extracted from the sessions and were categorized into five main themes: interview and initial assessment; referral; investigation of ineligibility criteria; report to judicial authority; and follow‐up and advocacy. The results of this research suggest amending executive bylaws based on a social work approach to the screening process for compulsory drug treatment.     

A Novel Approach to Chemical Mixture Risk Assessment—Linking Data from Population‐Based Epidemiology and Experimental Animal Tests

Humans are continuously exposed to chemicals with suspected or proven endocrine disrupting chemicals (EDCs). Risk management of EDCs presents a major unmet challenge because the available data for adverse health effects are generated by examining one compound at a time, whereas real‐life exposures are to mixtures of chemicals. In this work, we integrate epidemiological and experimental evidence toward a whole mixture strategy for risk assessment. To illustrate, we conduct the following four steps in a case study: (1) identification of single EDCs (“bad actors”)—measured in prenatal blood/urine in the SELMA study—that are associated with a shorter anogenital distance (AGD) in baby boys; (2) definition and construction of a “typical” mixture consisting of the “bad actors” identified in Step 1; (3) experimentally testing this mixture in an in vivo animal model to estimate a dose–response relationship and determine a point of departure (i.e., reference dose [RfD]) associated with an adverse health outcome; and (4) use a statistical measure of “sufficient similarity” to compare the experimental RfD (from Step 3) to the exposure measured in the human population and generate a “similar mixture risk indicator” (SMRI). The objective of this exercise is to generate a proof of concept for the systematic integration of epidemiological and experimental evidence with mixture risk assessment strategies. Using a whole mixture approach, we could find a higher rate of pregnant women under risk (13%) when comparing with the data from more traditional models of additivity (3%), or a compound‐by‐compound strategy (1.6%).     

Optimization of the Aflatoxin Monitoring Costs along the Maize Supply Chain

An optimization model was used to gain insight into cost‐effective monitoring plans for aflatoxins along the maize supply chain. The model was based on a typical Dutch maize chain, with maize grown in the Black Sea region, and transported by ship to the Netherlands for use as an ingredient in compound feed for dairy cattle. Six different scenarios, with different aflatoxin concentrations at harvest and possible aflatoxin production during transport, were used. By minimizing the costs and using parameters such as the concentration, the variance of the sampling plan, and the monitoring and replacement costs, the model optimized the control points (CPs; e.g., after harvest, before or after transport by sea ship), the number of batches sampled at the CP, and the number of samples per batch. This optimization approach led to an end‐of‐chain aflatoxin concentration below the predetermined limit. The model showed that, when postharvest aflatoxin production was not possible, it was most cost‐effective to collect samples from all batches and replace contaminated batches directly after the harvest, since the replacement costs were the lowest at the origin of the chain. When there was aflatoxin production during storage, it was most cost‐effective to collect samples and replace contaminated batches after storage and transport to avoid the duplicate before and after monitoring and replacement costs. Further along the chain a contaminated batch is detected, the more stakeholders are involved, the more expensive the replacement costs and possible recall costs become.     

On the accuracy in high‐dimensional linear models and its application to genomic selection

Genomic selection is today a hot topic in genetics. It consists in predicting breeding values of selection candidates, using the large number of genetic markers now available owing to the recent progress in molecular biology. One of the most popular methods chosen by geneticists is ridge regression. We focus on some predictive aspects of ridge regression and present theoretical results regarding the accuracy criteria, that is, the correlation between predicted value and true value. We show the influence of singular values, the regularization parameter, and the projection of the signal on the space spanned by the rows of the design matrix. Asymptotic results in a high‐dimensional framework are given; in particular, we prove that the convergence to optimal accuracy highly depends on a weighted projection of the signal on each subspace. We discuss on how to improve the prediction. Last, illustrations on simulated and real data are proposed.