Stillbirths among offspring of male radiation workers at Sellafield nuclear reprocessing plant.

BACKGROUND: Ionising radiation is a known mutagen, but few studies have examined transgenerational effects of paternal exposure in human beings. The workforce at the Sellafield nuclear reprocessing plant in the county of Cumbria, UK, is the most highly exposed workforce in western Europe and North America. This study, which is part of a larger programme of work investigating the health of the children of the Sellafield workforce, set out to find whether there was evidence of an association between stillbirth risk and paternal exposure to ionising radiation. METHODS: We collected details from birth registration documents for all singleton 248,097 livebirths and 3715 stillbirths in the county of Cumbria 1950-89. Within this cohort the 130 stillbirths and 9078 livebirths to partners of male radiation workers employed at Sellafield were identified. Logistic regression was used to analyse the relation between stillbirth risk and father's preconceptional radiation exposure, with adjustment for social class, year of birth, father's age, and birth order. FINDINGS: A significant positive association was found between the risk of a baby being stillborn and the father's total exposure to external ionising radiation before conception (adjusted odds ratio per 100 mSv 1.24 [95% CI 1.04-1.45], p=0.009). The risk was higher for stillbirths with congenital anomaly and was highest for the nine stillbirths with neural-tube defects. The statistical models predicted that, were the association to be interpreted as causal, between 0 and 31.9 of the 130 stillbirths to the workforce may be attributable to father's radiation exposure. INTERPRETATION: The findings of an increased risk of stillbirth with increasing paternal occupational exposure to external radiation are qualitatively consistent with those from animal models, though the risk estimate is higher. Although we cannot exclude the possibility of an unmeasured risk factor for stillbirth, confounded with paternal preconceptional irradiation, extensive checks confirmed that the statistical models were a good fit to the data and there was not statistical evidence of unmeasured factors.

Meta-analysis by random effect modelling in generalized linear models.

The meta-analysis of multi-centre trials can be based on either fixed or random effect models. This paper argues for the general use of random effect models, and illustrates the value of non-parametric maximum likelihood (NPML) analysis of such trials. The same general approach unifies administrative 'league table' analyses in epidemiological and other studies. Several examples of the NPML analysis are given, including a 70-centre trial.

Detailed modelling of caffeine metabolism and examination of the CYP1A2 gene: lack of a polymorphism in CYP1A2 in Caucasians.

The cytochrome P450 CYP1A2 is important in the metabolism of both drugs and procarcinogens such as heterocyclic amines. We aimed to clarify the existence of a phenotypic polymorphism and explore the molecular basis of such a polymorphism. Ninety-two non-smoking individuals underwent caffeine phenotyping. The distribution of the 1,7-dimethylxanthine + 1,7-dimethyluracil/caffeine (17U + 17X/137X) ratio and log-transformed data were determined. Probit plots were constructed and the distribution fitted using maximum likelihood method. The CYP1A2 gene, including upstream regulatory regions, was examined for sequence polymorphisms using the single-strand conformation polymorphism technique in 19 individuals and by complete DNA sequencing in two individuals from the extremes of the distribution. We found a similar range (1.45-18.65) and median (6.7) for the 17U + 17X/137X ratio to that found in previous studies of non-smoking Caucasians and no effect of sex. The 17U + 17X/137X ratio gave a normal distribution when log-transformed. Maximum likelihood analysis showed that the log-normal and bimodal distributions had similar deviances but the log-normal distribution was favoured because it has fewer parameters. There was no evidence for significant DNA sequence differences between fast and slow metabolizers, although some differences from published sequences including a silent polymorhpism in exon 7 which were unlikely to be of functional significance were found. We therefore conclude that CYP1A2 does not show functionally significant polymorphism but that the wide interindividual variation in activity may be due to environmental factors.

Ambulatory blood pressure in schoolchildren.

OBJECTIVE: To define the range and variability of ambulatory blood pressure in normal schoolchildren. DESIGN: Prospective study. METHODS: Resting blood pressure of 1121 schoolchildren from Newcastle upon Tyne was recorded. An ambulatory blood pressure device, which uses both auscultatory (Korotkoff) and oscillometric methods of blood pressure measurement, was then put in place for 24 hours. RESULTS: The day was divided into three time periods: school, home, and night time. Normal centiles for blood pressure for each of these time periods were obtained and many daytime readings were outside reported normal resting levels. The normal variation of blood pressure was quantified by comparing each of these time periods with the resting readings. Resting systolic blood pressure did not predict 24 hour mean systolic blood pressure. CONCLUSIONS: The availability of normal ambulatory blood pressure data on the level and variation of blood pressure in children may facilitate the early identification of hypertension in this age group.

A general maximum likelihood analysis of variance components in generalized linear models.

This paper describes an EM algorithm for nonparametric maximum likelihood (ML) estimation in generalized linear models with variance component structure. The algorithm provides an alternative analysis to approximate MQL and PQL analyses (McGilchrist and Aisbett, 1991, Biometrical Journal 33, 131-141; Breslow and Clayton, 1993; Journal of the American Statistical Association 88, 9-25; McGilchrist, 1994, Journal of the Royal Statistical Society, Series B 56, 61-69; Goldstein, 1995, Multilevel Statistical Models) and to GEE analyses (Liang and Zeger, 1986, Biometrika 73, 13-22). The algorithm, first given by Hinde and Wood (1987, in Longitudinal Data Analysis, 110-126), is a generalization of that for random effect models for overdispersion in generalized linear models, described in Aitkin (1996, Statistics and Computing 6, 251-262). The algorithm is initially derived as a form of Gaussian quadrature assuming a normal mixing distribution, but with only slight variation it can be used for a completely unknown mixing distribution, giving a straightforward method for the fully nonparametric ML estimation of this distribution. This is of value because the ML estimates of the GLM parameters can be sensitive to the specification of a parametric form for the mixing distribution. The nonparametric analysis can be extended straightforwardly to general random parameter models, with full NPML estimation of the joint distribution of the random parameters. This can produce substantial computational saving compared with full numerical integration over a specified parametric distribution for the random parameters. A simple method is described for obtaining correct standard errors for parameter estimates when using the EM algorithm. Several examples are discussed involving simple variance component and longitudinal models, and small-area estimation.

A method of fitting the gravity model based on the Poisson distribution.

"In this paper, [the authors] suggest an alternative method for fitting the gravity model. In this method, the interaction variable is treated as the outcome of a discrete probability process, whose mean is a function of the size and distance variables. This treatment seems appropriate when the dependent variable represents a count of the number of items (people, vehicles, shipments) moving from one place to another. It would seem to have special advantages where there are some pairs of places between which few items move. The argument will be illustrated with reference to data on the numbers of migrants moving in 1970-1971 between pairs of the 126 labor market areas defined for Great Britain...."

Structural analysis of the ridge count data of Australian Europeans using multivariate analysis.

Multivariate analyses are used to study the structural patterns of ridge counts of fingers. There is a significant difference between the ridge counts of two hands, chiefly due to the first and fourth fingers. There is asymmetry in the covariance matrix of the ridge counts. The correlations between fingers are significant and the decrease in correlation with increasing distance between fingers is not significant.