A study of all 77 995 live births and 1234 stillbirths to mothers living in West Cumbria from 1950 to 1989 found no significant increase in stillbirth risk with distance of mother's residence from the first or second nearest maternity services, after allowing for year of birth, father's social class, and birth order. (Arch Dis Child Fetal Neonatal Ed 2000;82:F167-F168)

Stone's isotonic regression method for analysing count data to estimate disease risk in relation to a point source of environmental pollution is now routinely used. This paper develops the corresponding procedure for case-control data consisting of the locations of individual cases with controls with associated covariate information. In this setting, the generalized likelihood ratio statistic to test the null hypothesis of constant risk against the alternative that risk is a monotone non-increasing function of distance from the point source is intractable. An approximate Monte Carlo test is described, extending an exact test proposed by Bithell for the situation in which there are no covariates. Interval estimates of risk as a function of distance from the point source are constructed by simulation of the sampling distribution of the isotonic regression estimator. The methodology is illustrated by two applications: one to the relative risk of larynx cancers and lung cancers near a now-disused industrial incinerator; the other to the risk of asthma in children in relation to distance of residence from the nearest main road.

Objective-To derive a predictive model for national prescribing behaviour in terms of basic morbidity and demographic factors.Design-24 demographic, morbidity, and practice factors were entered into a multiple regression analysis to determine the net ingredient cost per patient.Setting-The 90 family health service authorities in England for 1989.Results-For net ingredient cost per patient only two demographic factors (numbers of pensioners and the mobility of the registered population measured by list inflation) and two morbidity related factors (standardised morAality ratios and numbers of prepayment certificates issued) significantly contributed to a multiple regression model. This model explained 81% of the variation in net ingredient cost per registered patient between family health services authorities. The model also enabled a weighting factor of 4-6 (95% confidence interval 3-2 to 6.7) to be derived for the net ingredient cost for elderly patients (compared with the existing prescribing unit factor of 3).Conclusions-The model shows that variations in prescribing costs essentially reflect demand. It also suggests that the current prescribing unit value of 3 for patients aged 65 or more underestimates the extra costs ofprescribing for elderly patients.

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Objective-To examine differences in prescribing between dispensing and non-dispensing practices.Setting-The 108 practices covered by Lincolnshire Family Health Services Authority.Design-Analysis of prescribing data for 1990-1 from PD2 reports from the Prescription Pricing Authority in relation to data on practice characteristics obtained from Lincolnshire Family Health Services Authority; and aggregated level 3 prescribing and cost information (PACT data) for 10 selected drugs from the Prescription Pricing Authority to examine amounts prescribed.Main outcome measures-Prescribing cost per patient, items per patient, and cost per item in dispensing and non-dispensing practices.Results-Dispensing practices had higher prescribing costs per patient than non-dispensing practices. This difference held for non-dispensing patients within dispensing practices. Structural features failed to explain the differences in prescribing cost, except for the higher numbers of elderly patients in dispensing practices (which explained 13% of the difference) and the number of partners (5%). The main determinant of the difference was the lower use ofgeneric drugs in dispensing practices (84%). Dispensing patients were prescribed lower quantities ofdrugs on average for each item.Conclusions-Dispensing practices could reduce their prescribing expenditure to that of nondispensing practices by increasing their prescribing of generic drugs. The shorter prescribing intervals for dispensing patients may be due to dispensing fees being related to the number ofprescribed items.