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Subjects aged 1 6 6 4 years (592; 258 men and 334 women), randomly selected from the population of Northern Ireland, kept a 7 d weighed record of all food and drink consumed. Social, personal and anthropometric data were also collected. From the weighed records food consumption was described in terms of forty-one food groups. Using principal components analysis, four distinct dietary patterns were generated which were identified as a traditional diet, a cosmopolitan diet, a convenience diet and a 'meat and two veg ' diet. These dietary patterns were then correlated with sociocultural, lifestyle and anthropometric variables. It is clear that dietary behaviour is influenced by a number of inter-related sociocultural demographics and that identifiable population groups in Northern lreland have different dietary behaviours.

This article examines the role of the confidence interval (CI) in statistical inference and its advantages over conventional hypothesis testing, particularly when data are applied in the context of clinical practice. A CI provides a range of population values with which a sample statistic is consistent at a given level of confidence (usually 95%). Conventional hypothesis testing serves to either reject or retain a null hypothesis. A CI, while also functioning as a hypothesis test, provides additional information on the variability of an observed sample statistic (ie, its precision) and on its probable relationship to the value of this statistic in the population from which the sample was drawn (ie, its accuracy). Thus, the CI focuses attention on the magnitude and the probability of a treatment or other effect. It thereby assists in determining the clinical usefulness and importance of, as well as the statistical significance of, findings. The CI is appropriate for both parametric and nonparametric analyses and for both individual studies and aggregated data in meta-analyses. It is recommended that, when inferential statistical analysis is performed, CIs should accompany point estimates and conventional hypothesis tests wherever possible.

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