The effect of participant nonresponse on HIV prevalence estimates in a population-based survey in two informal settlements in Nairobi city

Population Health Metrics

Research

Alex C Ezeh¹  Eliya Zulu¹  Abdhalah K Ziraba²  Vincent Okoth³  Mwau Matilu³  Samoel Khamadi³  John Kebaso⁴  Nyovani J Madise⁵ 

[1] African Population and Health Research Center, Shelter Afrique Centre, 2nd Floor, Longonot Road, Upper Hill, 10787, 00100, Nairobi, Kenya;African Population and Health Research Center, Shelter Afrique Centre, 2nd Floor, Longonot Road, Upper Hill, 10787, 00100, Nairobi, Kenya;Department of Epidemiology and Population Health, Centre for Population Studies, London School of Hygiene and Tropical Medicine, 49-51 Bedford Square, WC1B 3DP, London, UK;Kenya Medical Research Institute (KEMRI), 54840, 00200, Nairobi, Kenya;Loma Linda University, School of Public Health, 24951 North Circle Drive, Nichol Hall 1410, 92350, Loma Linda, California, USA;University of Southampton, School of Social Sciences, SO17 1BJ, Southampton, UK;

关键词: Informal Settlement;    Wealth Status;    Demographic Surveillance System;    Mobility Index;    Nonresponse Rate;   

DOI  :  10.1186/1478-7954-8-22

 received in 2009-07-29, accepted in 2010-07-22,  发布年份 2010

来源: Springer

【 摘 要 】

BackgroundParticipant nonresponse in an HIV serosurvey can affect estimates of HIV prevalence. Nonresponse can arise from a participant's refusal to provide a blood sample or the failure to trace a sampled individual. In a serosurvey conducted by the African Population and Health Research Center and Kenya Medical Research Centre in the slums of Nairobi, 43% of sampled individuals did not provide a blood sample. This paper describes selective participation in the serosurvey and estimates bias in HIV prevalence figures.MethodsThe paper uses data derived from an HIV serosurvey nested in an on-going demographic surveillance system. Nonresponse was assessed using logistic regression and multiple imputation methods to impute missing data for HIV status using a set of common variables available for all sampled participants.ResultsAge, residence, high mobility, wealth, and ethnicity were independent predictors of a sampled individual not being contacted. Individuals aged 30-34 years, females, individuals from the Kikuyu and Kamba ethnicity, married participants, and residents of Viwandani were all less likely to accept HIV testing when contacted. Although men were less likely to be contacted, those found were more willing to be tested compared to females. The overall observed HIV prevalence was overestimated by 2%. The observed prevalence for male participants was underestimated by about 1% and that for females was overestimated by 3%. These differences were small and did not affect the overall estimate substantially as the observed estimates fell within the confidence limits of the corrected prevalence estimate.ConclusionsNonresponse in the HIV serosurvey in the two informal settlements was high, however, the effect on overall prevalence estimate was minimal.

【 授权许可】

CC BY   
© Ziraba et al; licensee BioMed Central Ltd. 2010