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P. Bundred1, D. Kitchiner2, I. Buchan3. 1Department of Primary Care, University of Liverpool; 2Department of Cardiology, Alder Hey Children’s Hospital; 3Department of Epidemiology, Manchester University

Introduction: As the obesity epidemic increases the early identification of at risk children will become important so that they can be included in weight reduction programmes as these are developed.

Aims: To examine routinely collected data on height and weight in order to develop simple low cost screening programmes for children at risk of overweight and obesity.

Methods: Sequential height and weight measurements taken at child health clinics were used to examine the weight trajectory in 5245 Wirral preschool children from the 1997, 1998, and 1999 birth cohorts. Data were collected at 6 weeks, 9 months, and 3 years. Overweight (BMI>85th centile) and obesity (BMI>95th centile) were used as the end point of the study. Ethical approval was obtained from the Wirral ethics committee.

Results: Children who showed a rapid increase in weight between 6 weeks and 9 months (SDS weight gain>1) were more at risk of overweight and obesity at 3 years than those who had normal weight gain (p<0.0001). Children who were above the 50th centile weigh for age at 6 weeks were more at risk of overweight and obesity at 3 years than those who were below the 50th centile (p<0.0001). Finally, children who were over the 85th centile weight for age at 6 weeks were at higher risk of being overweight and obese at 3 years than those below the 85th centile but above the 50th centile (p<0.0001). From these results it was possible to develop 3 simple screening scenarios that could be used to identify a high proportion of at risk children before their first birthday.

Conclusions: The early identification of children at risk of developing obesity will be important in containing the obesity epidemic. Routinely collected child health data can be used to do this at low cost.


R. Naidoo, G. P. Phillipps, S. Smallwood, D. H. Newsom. Department of Community Paediatrics, Brent Primary Care Trust, 116 Chaplin Road, Wembley, Middlesex HA0 4UZ

Aim: To display MMR immunisation data using Geographic Information System (GIS) software and observe variations in MMR coverage over time.

Methods: Details of children age 18–36 months who have received MMR immunisation in 1995, 1998, 2001, and the half year (up to June) 2003 were collected from the Community Information System database of Brent Primary Care Trust. Using the child’s date of birth and postcode, co-ordinates were generated and plotted using GIS computer software (MapInfo, version 7.0, 2002, Mapinfo Corporation, USA). The cumulative data are expressed as percentages and represented by thematic maps displaying spatial differences in MMR uptake. Data from 2003 were displayed to view differences in uptake across the borough and were compared with previous years.

Results: From the 2003 thematic map of MMR uptake in Brent, it can be seen that MMR uptake varies widely across the borough, with an overall average of 74% and lowest uptake in the south east (64%). The level of detail includes proximity to specific GP practices and is much more refined than previously used tables. The variation in MMR uptake over time is demonstrated in maps from 1995, 1998, and 2001. The south east of Brent had the highest uptake in 1995 (80%), but this region now has the lowest immunisation rate (64%).

Conclusions: GIS maps uptake of MMR immunisation with great precision. GIS helps identify trouble spots and monitors changes over time. GIS mapping has improved our immunisation service, directing us as to where to place health promotion meetings and will aid further research into this difficult issue.


D. Manning1, B. Brewster1, P. Bundred2, I. Buchan3. 1Neonatal Unit, Wirral Hospital; 2Department of Primary Care, University of Liverpool; 3School of Epidemiology and Health Sciences, University of Manchester

Introduction: While social deprivation is associated with increased perinatal and neonatal mortality, little is known of its influence on neonatal morbidity. The aim of this study was to determine whether deprivation is associated with increased need for neonatal unit admission.

Method: Review of the numbers of admissions, and indications for admission, to the neonatal unit in a large English district general hospital between 1990 and 2002. Socioeconomic status was determined using the mother’s postcode at delivery, from which the Townsend deprivation index was calculated. Admission frequency was calculated for each quartile of the Townsend index, and frequencies in each quartile were compared using the χ2 test for trend.

Results: There was a linear increase in admission rate with increasing deprivation, from 6.1% in the least deprived, to 11.2% in the most deprived, quartile (p<0.0001). Deprivation was associated with significantly increased admissions for delivery <34 weeks gestation (p<0.0001), delayed onset of respiration (p 0.004), respiratory distress (p<0.0001), congenital anomalies (p<0.0001), hypoglycaemia (p 0.0008), neonatal abstinence syndrome (p<0.0001), and infection (p 0.006). There was no significant association between deprivation and admissions for jaundice (p 0.72) and feeding problems (p 0.1).

Conclusion: Social deprivation is significantly associated with neonatal morbidity, and therefore with the need for neonatal admission. Our study provides further evidence that health inequalities are exacerbated by deprivation.

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