THE DISCRIMINATORY POWER OF GEODEMOGRAPHICS TO INFORM HEALTH PROMOTION STRATEGIES Applied to breast screening

Transcription

1 THE DISCRIMINATORY POWER OF GEODEMOGRAPHICS TO INFORM HEALTH PROMOTION STRATEGIES Applied to breast screening CE JONES, P MATEOS, PA LONGLEY, R WEBBER Centre for Advanced Spatial Analysis 17 th September 2004

2 Contents Aim What are we trying to achieve? Introduction Why is this research needed? Study Area Where is the study being carried out? Background What are geodemographics? Design & Method What did we do? Results What did we find? Conclusion

3 Aims Understand the characteristics of women who did not respond to breast screening invites To describe the patterns across different neighbourhoods Demonstrate the use of geodemographic and geographic analysis

4 Introduction NHS Breast Screening Programme established 1988 coverage rate greater than 70%, women aged between 50 and 70 (current age cohort) Breast Screening Programme: Coverage of Women aged 53 to 64 by PCT Coverage (%) London North Central London Barnet Camden Enfield Haringey Islington Breast Screening Programme: coverage of women aged 53 to 64 for North Central London PCT s Source: last viewed 17 th May 2005

5 Study Area North Central London Borough of Camden Population: 210,800 people (mid 2003 pop estimates) Ethnicity: White: 74% Asian: 10% Black 8% Chinese & Other: 4% Mixed: 4%

6 Geodemographics Small area measures Social, economic, demographic & lifestyle characteristics Applied at the unit postcode Classify UK~1.6million postcodes: 61 types 11 groups

7 Geodemographic Groups in Camden Metro Multiculture Global Connections

8 Design - Analysing the data Unit postcode file Camden Geodemographic classification INPUTS Non responders List eligible women PROCESSES Geodemographic file of non responders Geodemographic file of eligible women List of General Practices Index of non - responders Country/Ethnicity/ Language classification General Practice analysis of non-responders OUTPUTS Postcode analysis of non-responders Postcode analysis of non-responders & ethnicity

9 Method creating a geodemographic index 1 Woman who did not respond to screening invites 2 NW4 6TF Non responder s postcode used as identifier 3 A B C D E F G H I J K Append Geodemographic code according to non responder s postcode 4 Number of each non-responders totalled for each geodemographic type Index created using number of eligible women as denominator Analysis of geodemographic index values

10 Results Index of non-responders Mosaic Group Num of registered patients aged 50 to 65 Num of Non- Responders in Camden Performance Rate Response Index 95% Confidence Interval A % B % D % E % F % I % J % %

11 Results: Likely lifestyle of non-responders Lifestyle Group Lifestyle Type Group Correlation T-Statistic Newspapers Sunday Post Hobbies Bingo Home Ownership Public rented Social grade E Lowest level of subsistence

12 Results : Non-responders across Camden Density low Meduim High

13 Results: GP practices Index of likelihood of nonresponse for GP practices Likelihood of being admitted to hospital with Breast Cancer

14 Results: Neighbourhood type & ethnicity Number of People 'British' F 28% I 1% J 0% A 34% A B D E F Mosaic Group E 36% B D 0% 1% I J 'Muslim: Bangladeshi' J I A 1% 0% 4% B 0% D 3% F 73% E 19% A B D E F I J

15 Results: Neighbourhood type & ethnicity Most Affluent Least Affluent

16 Limitations of the study Different dataset was used to create the denominator values of all eligible women Assumption that all non responders did not attend any screening

17 Conclusions The application of geodemographic techniques to routine data enhances : ability to understand the contextual & compositional variables of women not attending breast screening Mapping highlights the extent of the differences in uptake rates for different neighbourhoods Provide understanding of population differences: to inform strategic planning & delivery within Public Health.