Demographic

EFFECT OF NONRESPONSE ON THESDHS HIV PREVALENCE RESULTSAppendix DAs was seen earlier in Chapter 14 of this report, not all eligible SDHS respondents participated inthe HIV testing component. The potential for bias associated with this nonparticipation is a concern sincerespondents who refused to be tested or were absent at the time of testing may bias the results if theircharacteristics or behaviours may be different from those who consented to provide a blood sample. Toaddress these concerns, it has become standard procedure in DHS surveys with an HIV testing componentto conduct an analysis of those who are not tested in order to look for potential biases 1 .Table D.1 summarizes the results of the nonresponse analysis that was conducted for the 2006-07SDHS. The table shows the observed HIV rates for women, men, and the total sample and the rates forthese groups following an adjustment for nonresponse. Overall, the adjustment for nonresponse raises theHIV prevalence by about 0.1 percentage points above the observed level (from 25.9 percent to 26.0percent). For women, the adjusted prevalence is 31.0 percent compared with the observed level of 31.1percent. For men, the effect of the adjustment is slightly bigger, adding about 0.6 percentage points to theobserved rate of 19.7 percent. The differences between the observed and adjusted rates were not found tobe statistically significant.Table D.1 Observed and adjusted HIV prevalence among women and menPercentage HIV positive among women and men age 15-49 who were tested for HIV, by observedand adjusted prevalence and 95% confidence intervals, Swaziland 2006-07SexObserved HIV prevalenceAdjusted HIV prevalencePrevalence 95% confidence interval Prevalence 95% confidence interval(R) R-2SE R+2SE (R) R-2SE R+2SEWomen 31.1 29.8 32.5 31.0 29.8 32.2Men 19.7 18.4 21.0 20.3 19.3 21.4Total 25.9 24.9 26.8 26.0 25.2 26.81 The analysis predicted HIV prevalence among the two non-responder groups based on multivariate models of HIVfor those who were tested, using a common set of predictor variables. A logistic regression model is used tocalculate predicted HIV prevalence separately for the “not-interviewed, not-tested” and “interviewed, not-tested”groups. Predictions for the “not-interviewed, not-tested” group are based on a limited set of variables from thehousehold questionnaire including age, education, wealth index, residence, and geographic region. Predictions forthe “interviewed, not-tested” group additionally account for several individual socio-demographic and behavioralcharacteristics of the respondents, as collected in the survey including marital union, childbirth in last five years(women only), occupation, media exposure, religion, circumcision (men only), STI or STI symptom in last 12months, cigarette smoking/tobacco use, age at first sex, number of lifetime sex partners, number of sex partners inlast 12 months, non-spousal sex in last 12 months, condom use at last sex in last 12 months, paid for sex (for men),participation in household decision-making (women only), number of times slept away in last 12 months (menonly), away for more than one month in last 12 months (men only), number of years living in current place ofresidence, knowledge of HIV prevention methods (ABC), attitude toward people living with HIV/AIDS, woman’sability to negotiate for safer sex, medical injection (women only), alcohol use at last sex in last 12 months, andpreviously tested for HIV. Analysis for total prevalence used variables that commonly available for both women andmen.Appendix D | 325