Mental health and educational difficulties in children in contact with Children's Social Services

The British Child Mental Health Survey 1999 collected data from 10 438 children aged 5–15 years, selected at random from the child benefit register. At 2 and 3 years, all those with a psychiatric disorder and a random third without were followed up with further detailed interviews about the services contacted if parents reported service contact or if parents expressed concern about their child's mental health at baseline and follow‐up, but reported no service use. We compared children in contact with Children's Social Services with children in contact with Child and Adolescent Mental Health Services (CAMHS) or no services. The children in contact with Children's Social Services had a high level of psychopathology and considerable educational difficulties. Despite this, they often had no contact with CAMHS or access to provision for special educational needs. It also became clear that parents were often using Children's Social Services as a first‐line service, i.e. a way of trying to access help. The results provide us with an interesting insight into the level of need of those children in contact with Children's Social Services and we hope to stimulate discussion about how liaison between all the services children access can better provide for their needs.     

Relative effect sizes for measures of risk

Effect sizes are an important component of experimental design, data analysis, and interpretation of statistical results. In some situations, an effect size of clinical or practical importance may be unknown to the researcher. In other situations, the researcher may be interested in comparing observed effect sizes to known standards to quantify clinical importance. In these cases, the notion of relative effect sizes (small, medium, large) can be useful as benchmarks. Although there is generally an extensive literature on relative effect sizes for continuous data, little of this research has focused on relative effect sizes for measures of risk that are common in epidemiological or biomedical studies. The aim of this paper, therefore, is to extend existing relative effect sizes to the relative risk, odds ratio, hazard ratio, rate ratio, and Mantel–Haenszel odds ratio for related samples. In most scenarios with equal group allocation, effect sizes of 1.22, 1.86, and 3.00 can be taken as small, medium, and large, respectively. The odds ratio for a non rare event is a notable exception and modified relative effect sizes are 1.32, 2.38, and 4.70 in that situation.     

The internalising and externalising problems of adolescents in Croatia: Socio‐demographic and family victimisation factors

This study assessed Croatian adolescents' problems in relation to socio‐demographic characteristics and experienced family violence in early and late adolescence. A national representative sample of 1,780 Croatian students (45.3% males) in two age groups representing early (M = 13.20; SD = 0.42) and late adolescence (M = 18.14; SD = 0.38) participated. The questionnaire included the Youth Self‐Report, modified version of ISPCAN Child Abuse Screening Tool – Children's Version, and socio‐demographic data. Results show that internalising problems were more present in female adolescents, in adolescents who perceived family financial hardship and in those whose biological parents did not live together. More externalising problems were reported in late adolescence by students who were living in large cities and whose families had either low, or above‐average, financial status. Adolescents who have experienced family violence were at higher risk of developing internalising and/or externalising problems.     

Spatial pattern analysis of the incidence of aster yellows disease in lettuce

The degree of aggregation of lettuce plants infected by aster yellows phytoplasma (AYP) was investigated in 12 fields from three experiments. Position of diseased and healthy plants was mapped in a 6–9×12-m section of each field; for most analyses, fields were divided into 10-plant quadrats. Mean disease incidence (p) ranged from 0.01 to 0.30. The frequency of diseased plants was described by the beta-binomial distribution, with an index of aggregation (θ) ranging from 0 to 0.17, positively correlated withp, and generally increasing over time within a field. Distance-class analysis revealed a core-cluster size of only a few plants. However, spatial autocorrelations ofp between quadrats were not significant, indicating that the scale of spatial pattern was small, generally less than 10 plants. An overall measure of aggregation was given by the slope parameter of the binary form of the power law, in which the log of the calculated variance is regressed on the log of the theoretical variance for a binomial distribution. The slope was 1.18 and significantly different from 1. Results for this “simple-interest” disease are interpreted in relation to the persistent transmission of AYP by its aster leafhopper vector.     

Risk groups for parasuicide – a survey of unselected people who attempt suicide treated in hospital

A registration survey of parasuicide patients seeking hospital care in a defined catchment area was conducted over 24 months (1989-1990). In 1989, 475 individuals registered as residents in the catchment area were given care on 541 occasions, and in 1990, 382 individuals received care on 426 occasions as as a result of parasuicide. The parasuicide rates for the overall population in the catchment area were estimated by means of demographic variables. Parasuicide rates were highest among women 25-39 years old and among men 30-39 years old, i.e., in older age groups than previous studies (from the 1970s) have shown. Parasuicide rates are 3 times as high for single men as for married men and twice as high for single women as for married women. Among single men and women, divorcé(e)s show the highest parasuicide rates, especially in the 15-34 age group. The number of parasuicides among women decreased significantly between 1989 and 1990, which had the effect of evening out the female: male parasuicide ratio (1.28:1). Moreover, for the first time it becomes clear that the Finnish citizens in Sweden, both men and women, show a high risk for parasuicide compared with the Swedish population. These results focus attention on deficient psychic and social wellbeing of Finns in Sweden.     

A Probabilistic Transmission Dynamic Model to Assess Indoor Airborne Infection Risks

The purpose of this article is to quantify the public health risk associated with inhalation of indoor airborne infection based on a probabilistic transmission dynamic modeling approach. We used the Wells-Riley mathematical model to estimate (1) the CO2 exposure concentrations in indoor environments where cases of inhalation airborne infection occurred based on reported epidemiological data and epidemic curves for influenza and severe acute respiratory syndrome (SARS), (2) the basic reproductive number, R0 (i.e., expected number of secondary cases on the introduction of a single infected individual in a completely susceptible population) and its variability in a shared indoor airspace, and (3) the risk for infection in various scenarios of exposure in a susceptible population for a range of R0. We also employ a standard susceptible-infectious-recovered (SIR) structure to relate Wells-Riley model derived R0 to a transmission parameter to implicate the relationships between indoor carbon dioxide concentration and contact rate. We estimate that a single case of SARS will infect 2.6 secondary cases on average in a population from nosocomial transmission, whereas less than 1 secondary infection was generated per case among school children. We also obtained an estimate of the basic reproductive number for influenza in a commercial airliner: the median value is 10.4. We suggest that improving the building air cleaning rate to lower the critical rebreathed fraction of indoor air can decrease transmission rate. Here, we show that virulence of the organism factors, infectious quantum generation rates (quanta/s by an infected person), and host factors determine the risk for inhalation of indoor airborne infection.     

Estimation from current-status data in continuous time

The nonparametric maximum likelihood estimator for current-status data has been known for at least 40 years, but only recently have the mathematical-statistical properties been clarified. This note provides a case study in the important and often studied context of estimating age-specific immunization intensities from a seroprevalence survey. Fully parametric and spline-based alternatives (also based on continuous-time models) are given. The basic reproduction number R ₀ exemplifies estimation of a functional. The limitations implied by the necessarily rather restrictive epidemiological assumptions are briefly discussed.     

A Risk Assessment for Occupational Acrylonitrile Exposure Using Epidemiology Data

The extensive data from the Blair et al.((1)) epidemiology study of occupational acrylonitrile exposure among 25460 workers in eight plants in the United States provide an excellent opportunity to update quantitative risk assessments for this widely used commodity chemical. We employ the semiparametric Cox relative risk (RR) regression model with a cumulative exposure metric to model cause-specific mortality from lung cancer and all other causes. The separately estimated cause-specific cumulative hazards are then combined to provide an overall estimate of age-specific mortality risk. Age-specific estimates of the additional risk of lung cancer mortality associated with several plausible occupational exposure scenarios are obtained. For age 70, these estimates are all markedly lower than those generated with the cancer potency estimate provided in the USEPA acrylonitrile risk assessment.((2)) This result is consistent with the failure of recent occupational studies to confirm elevated lung cancer mortality among acrylonitrile-exposed workers as was originally reported by O'Berg,((3)) and it calls attention to the importance of using high-quality epidemiology data in the risk assessment process.