The influence of socio-economic deprivation on rates of major lower limb amputation secondary to peripheral arterial disease.
OBJECTIVE
To investigate a hypothesised link between socio-economic deprivation and rates of major lower limb amputation within the catchment of a district general hospital in the United Kingdom.


METHODS
An analysis of a demographic database collated using patients identified by the OPCS codes for lower limb amputations.


METHODS
All patients undergoing a lower limb amputation as a result of peripheral vascular disease, as identified by ICD-10 code, between January 2003 and January 2009 were included in the study.


METHODS
A case-control study was undertaken, comparing the Index of Multiple Deprivation 2007 (IMD) scores of major lower limb amputees, to those of the catchment population. Multivariate analysis was not undertaken.


RESULTS
A total of 327 patients underwent 445 lower limb amputations during the 6-year period. A comparative plot of cumulative frequency of IMD score in the catchment and amputation groups indicates greater numbers of major amputations in more deprived postcodes (P=0.004). The catchment population was further divided into population-matched deprivation quintiles. A significant increase in the number of amputations occurred in the two most deprived quintiles (OR (95%CI)=1.654 (1.121-2.440), P=0.011)


CONCLUSIONS
This study indicates a positive association between increasing social deprivation and rates of lower limb amputation. If the most deprived quintiles are combined, this increase in amputation rates is approximately 65%. This inequity should be further investigated, and consideration given to targeted care within areas of greater social deprivation.
Ferguson
H J M
HJ
Core Surgical Trainee, West Midlands Deanery, Russell's Hall Hospital, Pensnett Road, Dudley DY1 2HQ, UK. fergusonh@doctors.org.uk
Nightingale
P
P
Pathak
R
R
Jayatunga
A P
AP
D000671:Amputation, Surgical / Q000706:statistics & numerical data*; D000674:Amputees / Q000706:statistics & numerical data*; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D004739:England / Q000453:epidemiology; D006767:Hospitals, District / Q000706:statistics & numerical data; D006769:Hospitals, General / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D035002:Lower Extremity / Q000098:blood supply*; D016017:Odds Ratio; D010342:Patient Acceptance of Health Care; D016491:Peripheral Vascular Diseases / Q000453:epidemiology / Q000523:psychology / Q000601:surgery*; D011177:Postal Service; D011204:Poverty Areas; D012111:Residence Characteristics / Q000706:statistics & numerical data; D018570:Risk Assessment; D012307:Risk Factors; D012923:Social Class; D012959:Socioeconomic Factors