Relationship between sleeping on the night shift and recovery from work among nursing workers - the influence of domestic work

P>Aim. This paper is a report of a study on the association between sleep patterns during work nights and recovery from work among nursing workers, considering domestic work hours. Background. Several hospitals allow nursing workers to sleep during the night shift, but this is rarely evaluated from the workers` health perspective. The need for recovery from work concept can be useful for testing the impact of night work on sleep. Recovery is not a problem if workers have enough time to recover between periods of work. Therefore, domestic work would be likely to interfere in the recovery process. Methods. This cross-sectional study was carried out at three hospitals in 2005-2006, through a comprehensive questionnaire. All nursing teams engaged in assistance to patients were invited to participate. Analyses included female night workers with no incidence of insomnia. Participants (n = 396) were classified into those who did not sleep during night shifts, those who slept for up to 2 hours and those who slept for 2-3 hours. Results. Binomial logistic regression analysis showed that sleeping on the job for 2-3 hours during night shifts is related to a better recovery from work provided the workers do not undergo long domestic work hours. Conclusions. Being allowed to sleep at work during night shifts seemed to contribute to, but was not enough to guarantee, a good recovery from work in the studied population. Recommendations to deal with sleep-deprivation among night workers should consider the complexity of gender roles on the recovery process.

A gender approach to work ability and its relationship to professional and domestic work hours among nursing personnel

The association between working hours and work ability was examined in a cross-sectional study of male (N = 156) and female (N = 1092) nurses in three public hospitals. Working hours were considered in terms of their professional and domestic hours per week and their combined impact; total work load. Logistic regression analysis showed a significant association between total work load and inadequate work ability index (WAI) for females only. Females reported a higher proportion of inadequate WAI, fewer professional work hours but longer domestic work hours. There were no significant differences in total work load by gender. The combination of professional and domestic work hours in females seemed to best explain their lower work ability. The findings suggest that investigations into female well-being need to consider their total work load. Our male sample may have lacked sufficient power to detect a relationship between working hours and work ability. (c) 2008 Elsevier Ltd. All rights reserved.

Work and Excessive Sleepiness among Brazilian Evening High School Students Effects on Days Off

Previous studies have revealed that students who work and study build up sleep deficits during the workweek, which can trigger a sleep rebound during days off. The objective of this study was to investigate the impact of working/non-working on sleepiness during days off among high school students. The study population, aged 14-21 years, attended evening classes in Sao Paulo, Brazil. For the study, the students completed questionnaires on living conditions, health, and work; wore actigraphs; and completed the Karolinska Sleepiness Scale (KSS). To predict sleepiness, a logistic regression analysis was performed. Excessive sleepiness was observed on the first day off among working students. Results suggest that working is a significant predictor for sleepiness and that two shifts of daily systematic activities, study and work, might lead to excessive daytime sleepiness on the first day off. Further, this observed excessive sleepiness may reflect the sleep debt accumulated during the workweek.

Environmental conditions and rodent infestation in Campo Limpo district, Sao Paulo municipality, Brazil

Rodents are involved in the transmission to human beings of several diseases, including liptospirosis, which shows high lethality rates in Sao Paulo municipality. Despite this, few studies have assessed the relationship existing between urban environmental conditions and building rodent infestation. With the purpose of clarifying this relationship, an analysis has been conducted in order to quantify the influence of environmental factors upon rodent infestation on a low-income district. Diagnosis of the environmental situation has been performed to evaluate the frequency according to which harborage, food and access sources occur, and a survey on infestation rates in 2175 dwellings in the area studied. The logistic regression analysis showed that among the environmental variables, the one that showed the closest association with rodent infestation was access; followed by harborage, and food. It was concluded that poor socioeconomic and environmental conditions in the area propitiate the occurrence of high rodent infestation rates.

Use of a predictive model for food insecurity estimates in Brazil

In 2004 the National Household Survey (Pesquisa Nacional par Amostras de Domicilios - PNAD) estimated the prevalence of food and nutrition insecurity in Brazil. However, PNAD data cannot be disaggregated at the municipal level. The objective of this study was to build a statistical model to predict severe food insecurity for Brazilian municipalities based on the PNAD dataset. Exclusion criteria were: incomplete food security data (19.30%); informants younger than 18 years old (0.07%); collective households (0.05%); households headed by indigenous persons (0.19%). The modeling was carried out in three stages, beginning with the selection of variables related to food insecurity using univariate logistic regression. The variables chosen to construct the municipal estimates were selected from those included in PNAD as well as the 2000 Census. Multivariate logistic regression was then initiated, removing the non-significant variables with odds ratios adjusted by multiple logistic regression. The Wald Test was applied to check the significance of the coefficients in the logistic equation. The final model included the variables: per capita income; years of schooling; race and gender of the household head; urban or rural residence; access to public water supply; presence of children; total number of household inhabitants and state of residence. The adequacy of the model was tested using the Hosmer-Lemeshow test (p=0.561) and ROC curve (area=0.823). Tests indicated that the model has strong predictive power and can be used to determine household food insecurity in Brazilian municipalities, suggesting that similar predictive models may be useful tools in other Latin American countries.

Is bird incidence in Atlantic forest fragments influenced by landscape patterns at multiple scales?

The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales. Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex pattern-process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise the accuracy of species incidence models.

Multicenter Analysis of Glucocerebrosidase Mutations in Parkinson`s Disease

Background Recent studies indicate an increased frequency of mutations in the gene encoding glucocerebrosidase (GBA), a deficiency of which causes Gaucher`s disease, among patients with Parkinson`s disease. We aimed to ascertain the frequency of GBA mutations in an ethnically diverse group of patients with Parkinson`s disease. Methods Sixteen centers participated in our international, collaborative study: five from the Americas, six from Europe, two from Israel, and three from Asia. Each center genotyped a standard DNA panel to permit comparison of the genotyping results across centers. Genotypes and phenotypic data from a total of 5691 patients with Parkinson`s disease (780 Ashkenazi Jews) and 4898 controls (387 Ashkenazi Jews) were analyzed, with multivariate logistic-regression models and the Mantel-Haenszel procedure used to estimate odds ratios across centers. Results All 16 centers could detect two GBA mutations, L444P and N370S. Among Ashkenazi Jewish subjects, either mutation was found in 15% of patients and 3% of controls, and among non-Ashkenazi Jewish subjects, either mutation was found in 3% of patients and less than 1% of controls. GBA was fully sequenced for 1883 non-Ashkenazi Jewish patients, and mutations were identified in 7%, showing that limited mutation screening can miss half the mutant alleles. The odds ratio for any GBA mutation in patients versus controls was 5.43 across centers. As compared with patients who did not carry a GBA mutation, those with a GBA mutation presented earlier with the disease, were more likely to have affected relatives, and were more likely to have atypical clinical manifestations. Conclusions Data collected from 16 centers demonstrate that there is a strong association between GBA mutations and Parkinson`s disease.

Some factors associated with dental caries in the primary dentition of children with Down syndrome

Aim It is well reported in the scientific literature that there is a high level of periodontal disease and lower caries prevalence in Down Syndrome (DS) individuals, when compared with age-matched non DS individuals. This study was conducted to investigate the process of dental caries in DS children. Materials and methods In this study the following parameters were considered: oral hygiene habits, levels of Streptococcus mutans (SM) and Lactobacillus spp. (LB), Modified Gingival Index (MGI), and Simplified Oral Hygiene Index (OHI-S). A case group with DS children (n=69) and a control group of non DS children (n=69) were formed to perform this study Dental caries severity was determined using the DMFT index. Samples of non-stimulated saliva were collected to determine the Lactobacillus spp levels. For SM levels, MSB agar plates were used. Results The findings revealed that the case group attended, dental check-ups more frequently brushed their teeth more times per day, flossed less, and also more frequently had SM levels classified as ""high count"". The MGI was higher and the OHI-S was lower than the control group (p<0.001). Conclusion No significant differences were found between the DMFT indexes of children from the two groups (p=0.345). The logistic regression analysis showed that in the case group, age, MGI, and SM count were positively related to dental caries (p<0.05).

Naturally Acquired Antibodies to Plasmodium vivax Duffy Binding Protein (DBP) in Rural Brazilian Amazon

Duffy binding protein (DBP), a leading malaria vaccine candidate, plays a critical role ill Plasmodium vivax erythrocyte invasion. Sixty-eight of 366 (18.6%) subjects had IgG anti-DBP antibodies by enzyme-linked immunosorbent assay (ELISA) in a community-based cross-sectional survey ill the Brazilian Amazon Basin. Despite Continuous exposure to low-level malaria transmission, the overall seroprevalence decreased to 9.0% when the Population was reexamined 12 months later. Antibodies from 16 of 50 (360%) Subjects who were ELISA-positive at the baseline were able to inhibit erythrocyte binding to at least one of two DBP variants tested. Most (13 of 16) of these subjects still had inhibitory antibodies when reevaluated 12 months later. Cumulative exposure to malaria was the strongest predictor of DBP seropositivity identified by Multiple logistic regression models in this population. The poor antibody recognition of DBP elicited by natural exposure to P. vivax in Amazonian populations represents a challenge to be addressed by vaccine development strategies.

Human toxocariasis in rural Brazilian Amazonia: Seroprevalence, risk factors, and spatial distribution

This population-based cross-sectional study of 403 rural settlers in Brazilian Amazonia revealed an overall rate of IgG seropositivity to Toxocara canis excretory-secretory larval antigen of 26.8% (95% confidence interval [CI], 22.5-31.4%). Multilevel logistic regression analysis identified current infection with hookworm (odds ratio [OR], 2.32; 95% CI, 1.11-4.86) and residence in the most recently occupied sectors of the settlement (OR, 1.81.; 95%CI, 1.3-2.52) as significant risk factors for Toxocara seropositivity; age > 14 years (OR, 0.46; 95% CI, 0.28-0.73) and the presence of cats in the household (OR, 0.57; 95% CI, 0.32-1.02) appeared to be protective. Two significant high-prevalence clusters were detected in the area, together comprising 38.9% of the seropositive subjects; households in the clusters had slightly lower socioeconomic status and were less likely to have cats as pets. The obstacles for controlling human toxocariasis in this and other tropical rural settings are discussed.

Malaria on the Amazonian frontier: Transmission dynamics, risk factors, spatial distribution, and prospects for control

Little follow-up data on malaria transmission in communities originating from frontier settlements in Amazonia are available. Here we describe a cohort study in a frontier settlement in Acre, Brazil, where 509 subjects contributed 489.7 person-years of follow-up. The association between malaria morbidity during the follow-up and individual, household, and spatial covariates was explored with mixed-effects logistic regression models and spatial analysis. Incidence rates for Plasmodium vivax and Plasmodium falciparum malaria were 30.0/100 and 16.3/100 person-years at risk, respectively. Malaria morbidity was strongly associated with land clearing and farming, and decreased after five years of residence in the area, suggesting that clinical immunity develops among subjects exposed to low malaria endemicity. Significant spatial clustering of malaria was observed in the areas of most recent occupation, indicating that the continuous influx of nonimmune settlers to forest-fringe areas perpetuates the cycle of environmental change and colonization that favors malaria transmission in rural Amazonia.

A Community-based Survey of Human Toxoplasmosis in Rural Amazonia: Seroprevalence, Seroconversion Rate, and Associated Risk Factors

IgG antibodies to Toxoplasma gondii were detected in, March-April 2004, in 65.8% (95% confidence interval, 60.8-70.8%) of 342 systematically sampled subjects 5-90 years of age (87.5% of the eligible) living in a rural settlement in Amazonia, with a seroconversion rate of 9% over I year of follow-up of 99 seronegative subjects. Multiple logistic regression analysis identified age as the only significant independent predictor of seropositivity at the baseline. Each additional year of age increases the odds of being seropositive by 6%, and 76.8% of the subjects are expected to be seropositive at 30 years of age. A single high-prevalence spatial cluster, comprising 11.9% of the seropositive subjects, was detected in the area; households in the cluster were less likely to have dogs as pets and their heads had a lower education level, when compared with households located outside the cluster. The challenges for preventing human toxoplasmosis in tropical rural settings are discussed.

Age-Dependent Acquisition of Protective Immunity to Malaria in Riverine Populations of the Amazon Basin of Brazil

Five community-based cross-sectional surveys of malaria morbidity and associated risk factors in remote riverine populations in northwestern Brazil showed average parasite rates of 4.2% (thick-smear microscopy) and 14.4% (polymerase chain reaction [PCR]) in the overall population, with a spleen rate of 13.9% among children 2-9 years of age. Plasmodium vivax was 2.8 times more prevalent than P. falciparum, with rare instances of P. malariae and mixed-species infections confirmed by PCR; 9.6% of asymptomatic subjects had parasitemias detected by PCR. Low-grade parasitemia detected by PCR only was a risk factor for anemia, after controlling for age and other covariates. Although clinical and subclinical infections occurred in all age groups, the risk of infection and disease decreased significantly with increasing age, after adjustment for several covariates in multilevel logistic regression models. These findings suggest that the continuous exposure to hypo- or mesoendemic malaria may induce significant anti-parasite and anti-disease immunity in native Amazonians.

Poly-bagging predictors for classification modelling for credit scoring

Credit scoring modelling comprises one of the leading formal tools for supporting the granting of credit. Its core objective consists of the generation of a score by means of which potential clients can be listed in the order of the probability of default. A critical factor is whether a credit scoring model is accurate enough in order to provide correct classification of the client as a good or bad payer. In this context the concept of bootstraping aggregating (bagging) arises. The basic idea is to generate multiple classifiers by obtaining the predicted values from the fitted models to several replicated datasets and then combining them into a single predictive classification in order to improve the classification accuracy. In this paper we propose a new bagging-type variant procedure, which we call poly-bagging, consisting of combining predictors over a succession of resamplings. The study is derived by credit scoring modelling. The proposed poly-bagging procedure was applied to some different artificial datasets and to a real granting of credit dataset up to three successions of resamplings. We observed better classification accuracy for the two-bagged and the three-bagged models for all considered setups. These results lead to a strong indication that the poly-bagging approach may promote improvement on the modelling performance measures, while keeping a flexible and straightforward bagging-type structure easy to implement. (C) 2011 Elsevier Ltd. All rights reserved.

Comparing diagnostic tests with missing data

When missing data occur in studies designed to compare the accuracy of diagnostic tests, a common, though naive, practice is to base the comparison of sensitivity, specificity, as well as of positive and negative predictive values on some subset of the data that fits into methods implemented in standard statistical packages. Such methods are usually valid only under the strong missing completely at random (MCAR) assumption and may generate biased and less precise estimates. We review some models that use the dependence structure of the completely observed cases to incorporate the information of the partially categorized observations into the analysis and show how they may be fitted via a two-stage hybrid process involving maximum likelihood in the first stage and weighted least squares in the second. We indicate how computational subroutines written in R may be used to fit the proposed models and illustrate the different analysis strategies with observational data collected to compare the accuracy of three distinct non-invasive diagnostic methods for endometriosis. The results indicate that even when the MCAR assumption is plausible, the naive partial analyses should be avoided.