Tanzania HIV/AIDS and Malaria Indicator Survey ... - Measure DHS

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INFANT AND CHILD MORTALITY 1010.1 INTRODUCTIONThis chapter analyses information on mortality levels, trends and differentials in neonatal,postnatal, infant, child and under-five mortality. Traditionally, the source of information for mortalitydata is the Population and Housing Censuses and the Tanzania Demographic and Health Surveys(TDHS). This is the first attempt to include a mortality component in the HIV/AIDS indicator survey.However, the methods and procedures applied are the same as those used in the TDHS. This providesan opportunity to link HIV/AIDS and malaria episodes with childhood mortality.Tanzania is among the countries with a high burden of disease caused by HIV/AIDS andmalaria. For many years, malaria has been a major cause of morbidity and mortality, particularlyamong children under age five. Furthermore, HIV/AIDS is increasingly seen among children underfive. To address these two problems, both the Government of Tanzania and Zanzibar, through theirMinistry of Health and Social Welfare, initiated a number of interventions that are currently beingimplemented. The aim is to scale down the prevalence of both malaria and HIV/AIDS in the country.The 2007-08 THMIS provides information that can be used to assess the impact of interventions onthe population. Various stakeholders are interested to know the outcome of their programmes.Funding for interventions mainly comes from the two governments and the development partners.The data for child mortality estimation were obtained from the Individual Questionnairewhich was administered to women age 15-49. In the survey, women were asked to provide theircomplete birth history. Each woman was asked to list all of her children who were born alive, startingwith the first birth. For each child, information was collected on the name, whether the child wassingle or twins, sex, month and year of birth, and survivorship. For each living child, the current agewas reported. For dead children, the age at death was reported.Because the primary cause of death varies with children’s age, the mortality rates presentedare age-specific. They are defined as follows:Neonatal mortality (NN): the probability of dying within the first month of lifePostneonatal mortality (PNN): the difference between infant and neonatal mortalityInfant mortality ( 1 q 0 ): the probability of dying before the first birthdayChild mortality ( 4 q 1 ): the probability of dying between the first and fifth birthdayUnder-five mortality ( 5 q 0 ): the probability of dying between birth and the fifth birthdayAll rates are expressed per 1,000 live births, except for child mortality, which is expressed per1,000 children surviving to twelve months of age.10.1.1 Levels and Trends in Infant and Child MortalityNeonatal, postneonatal, infant, child, and under-five mortality rates for three successive fiveyearperiods before the survey are shown in Table 10.1. The infant mortality rate for the most recentperiod (2004-2009) is 58 deaths per 1,000 live births. This is a decline from 68 deaths per 1,000 livebirths in the 2004-05 TDHS. The child mortality rate is 36 deaths per 1,000 live births, lower thaninfant mortality rate, implying that the main factors contributing to under-five mortality are neonataland postneonatal mortality. The under-five mortality rate for 2004-2008 is 91 per 1,000 live births,which is an improvement from the 2004-05 TDHS results (112 deaths per 1,000 live births).Infant and Child Mortality | 127
Table 10.1 Early childhood mortality ratesNeonatal, postneonatal, infant, child, and under-five mortality rates for five-year periods precedingthe survey, Tanzania HMIS 2007-08Years precedingthe surveyApproximatecalendar yearsNeonatalmortality(NN)Postneonatalmortality 1(PNN)Infantmortality( 1 q 0 )Childmortality( 4 q 1 )Under-fivemortality( 5 q 0 )0-4 2004-08 29 29 58 36 915-9 1999-2003 36 53 89 51 13610-14 1994-98 40 49 89 57 1411Computed as the difference between the infant and neonatal mortality ratesFigure 10.1 shows a recent and rapid decline in infant mortality and under-five mortalityrates. The infant mortality rate declined from 89 deaths per 1,000 live births in 1999-2003 to 58deaths per 1,000 live births in 2004-2008. Over the same period, under-five mortality declined from136 to 91 deaths per 1,000 live births.Figure 10.1 Early Childhood Mortality Rates1411361008989918060404036495329 2958575136200NeonatalmortalityPostneonatalmortality160 Per 1,000 live births 1994-1998 1999-2003 2004-2008140120InfantmortalityChildmortalityUnder-fivemortalityMortality rates10.2 SOCIO-ECONOMIC DIFFERENTIALS IN CHILD MORTALITYTable 10.2 presents socio-economic differentials in childhood mortality for the ten-yearperiod preceding the survey (1998-2007). The longer period was used to have a sufficient number ofbirths to study mortality differentials across population subgroups.In most cases, childhood mortality is higher among children living in rural areas than those inurban areas. Contrary to expectation, infant mortality in urban areas is higher than in rural areas (79and 70 deaths per 1,000 live births, respectively). The opposite pattern is expected because urbanareas typically have better health services, education, and living conditions than rural areas. Thedifference is a result of the higher neonatal mortality in urban areas than in rural areas. The reversedpattern may be associated with higher HIV/AIDS prevalence in urban than in rural areas. Under-fivemortality in rural areas is slightly higher than in urban areas. This can be attributed to significantlyhigher child mortality in rural areas than in urban areas. Across zones, infant mortality ranges between54 in Zanzibar and 103 deaths per 1,000 live births in the Eastern Zone.128 | Infant and Child Mortality
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TanzaniaHIV/AIDS and MalariaIndicat
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The 2007-08 Tanzania HIV/AIDS and M
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3.5 Access to Mass Media ..........
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12.2 Orphans and Vulnerable Childre
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Table 4.3Table 4.4Table 4.5Table 4.
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Figure 9.2 HIV Prevlence by Region/
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FOREWORDThis report presents the ma
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SUMMARY OF FINDINGSThe 2007-08 Tanz
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HIV prevalence among youth (women a
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xxii | Map of Tanzania
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1.2 NATIONAL POLICY ON HIV/AIDSIn r
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To assess levels and trends in know
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1.8 FIELDWORKData collection was ca
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Table 1.1 Results of the household
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Figure 2.1 presents a graphic pictu
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Table 2.3.1 Educational attainment
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Educational attainment is higher in
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2.5.1 Energy SourcesTable 2.5 prese
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The most common items are agricultu
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The 2007-08 THMIS included aquestio
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Table 3.1—ContinuedBackgroundchar
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Education is positively related to
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Table 3.3.2 Employment status: MenP
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Table 3.4.1 Exposure to mass media:
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3.6 CURRENT MARITAL STATUSMarriage
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Polygyny also varies by household w
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Four in ten women age 20-49 marry b
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There is a positive relationship be
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FERTILITY AND REPRODUCTIVE HEALTH 4
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Table 4.2 Fertility by background c
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infertility, 1 or the inability to
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4.3 ADOLESCENT FERTILITYAdolescent
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Table 4.7 Antenatal carePercent dis
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Table 4.8 Place of antenatal carePe
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Table 5.1 Knowledge of AIDSPercenta
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The use of condoms as an effective
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Table 5.3.2 Comprehensive knowledge
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more education) and those in the fo
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Table 5.5.1 Exposure to HIV educati
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5.6 KNOWLEDGE AND ATTITUDE CONCERNI
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Table 5.6.2 Knowledge and attitudes
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Table 6.1.1 Accepting attitudes tow
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Stigma is also found to vary with l
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6.3 ATTITUDES OF ADULTS TOWARDS EDU
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HIV/AIDS-RELATED BEHAVIOUR 77.1 INT
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Table 7.2.1 Recent sexual activity:
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Page 102 and 103: Table 7.3.2 Multiple sexual partner
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Page 106 and 107: Table 7.5.1 Coverage of prior HIV t
Page 108 and 109: Figure 7.2 Prior HIV Testing by Edu
Page 110 and 111: 7.7 PREVALENCE OF SEXUALLY TRANSMIT
Page 112 and 113: Figure 7.3 Prevalence of STIs and S
Page 114: Table 7.8 Prevalence of medical inj
Page 117 and 118: Table 8.1 Comprehensive knowledge a
Page 119 and 120: Table 8.2 Age at first sexual inter
Page 121 and 122: Never-married women and men age 15-
Page 123 and 124: Figure 8.3 Condom Use at Premarital
Page 125 and 126: Table 8.5.2 Higher-risk sexual inte
Page 127 and 128: Table 8.6 Age-mixing in sexual rela
Page 129 and 130: 8.9 HIV TESTING AMONG YOUNG PEOPLEK
Page 132 and 133: HIV PREVALENCE 99.1 INTRODUCTIONPri
Page 134 and 135: Table 9.1 Coverage of HIV testing b
Page 136 and 137: Table 9.1—ContinuedBackgroundchar
Page 138 and 139: Table 9.3 HIV prevalence by ageAmon
Page 140 and 141: There are large variations in HIV p
Page 142 and 143: Table 9.5 shows that men who are cu
Page 144 and 145: Women who said they had higher-risk
Page 146 and 147: Table 9.8 shows data on HIV prevale
Page 148 and 149: Table 9.11 HIV prevalence by male c
Page 152 and 153: As expected, the level of infant an
Page 154: category (1.41) is 41 percent highe
Page 157 and 158: 11.1 OWNERSHIP AND USE OF MOSQUITO
Page 159 and 160: carrying mosquitoes. Much of the fi
Page 161 and 162: 11.2 USE OF ANTIMALARIAL DRUGS DURI
Page 163 and 164: 11.3 TREATMENT OF CHILDREN WITH FEV
Page 165 and 166: 11.4.1 Type and Timing of Antimalar
Page 167 and 168: 11.4.2 Availability of Drug at Home
Page 169 and 170: 11.6 SOURCE OF MOSQUITO NETSUntil l
Page 171 and 172: In spite of steady increases in ITN
Page 174 and 175: ORPHANS AND VULNERABLE CHILDREN 12P
Page 176 and 177: 12.2 ORPHANS AND VULNERABLE CHILDRE
Page 178 and 179: 12.3.1 School Attendance by Survivo
Page 180 and 181: While there are no differences in p
Page 182 and 183: Table 12.7 Widows dispossessed of p
Page 184 and 185: Table 12.9 External support for orp
Page 186 and 187: REFERENCESAgot, K.E., J.O. Ndinya-A
Page 188 and 189: SAMPLE IMPLEMENTATIONAPPENDIX AAppe
Page 190 and 191: Table A.2 Sample implementation: Me
Page 192 and 193: Table A.4 Coverage of HIV testing a
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Table B.4 Sampling errors for Rural
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Table B.6 Sampling errors for Mainl
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Table B.8 Sampling errors for Mainl
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Table B.10 Sampling errors for Zanz
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Table B.12 Sampling errors for Nort
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Table B.14 Sampling errors for Sout
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Table B.16 Sampling errors for East
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Table B.18 Sampling errors for Dodo
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Table B.20 Sampling errors for Kili
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Table B.22 Sampling errors for Moro
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Table B.24 Sampling errors for Dar
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Table B.26 Sampling errors for Mtwa
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Table B.28 Sampling errors for Irin
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Table B.30 Sampling errors for Sing
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Table B.32 Sampling errors for Rukw
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Table B.34 Sampling errors for Shin
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Table B.36 Sampling errors for Mwan
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Table B.38 Sampling errors for Many
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Table B.40 Sampling errors for Pemb
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216 | Appendix B
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Joyce MbambaYulitha MwakasoleRemigi
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QUESTIONNAIRESAppendix DAppendix D
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HOUSEHOLD SCHEDULEIntroduction and
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IF AGE 0-17 YEARSIF AGE 5 YEARS OR
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IF AGE 0-17 YEARSLINE SICK CARE SUR
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HOUSEHOLD CHARACTERISTICSNO. QUESTI
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NO. QUESTIONS AND FILTERS CODING CA
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SUPPORT FOR SICK PEOPLENO. QUESTION
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NO.QUESTIONS AND FILTERSSUPPORT FOR
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NO.QUESTIONS AND FILTERSCODING CATE
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CHILD 4 CHILD 5 CHILD 6502 LINE NUM
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515 CHECK 509:NUMBER OF CHILDREN WI
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UNITED REPUBLIC OF TANZANIATANZANIA
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213 214 215 216217 218219 220221222
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LAST BIRTH NEXT-TO-LAST BIRTH SECON
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LASTSEXUAL PARTNERSECOND-TO-LASTSEX
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SECTION 7 - HIV TESTTHIS PAGE TO BE
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