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

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As expected, the level of infant and child mortality is highest among women with noeducation, decreasing with higher levels of education. For example, infant mortality is 85 deaths per1,000 live births for mothers with no education and 64 deaths per 1,000 live births for mothers withsecondary or higher education.Table 10.2 shows that mortality level is associated with wealth quintile. For instance, underfivemortality is 129 deaths per 1,000 live births for children in households in the lowest quintile and101 deaths per 1,000 live births for children in households in the highest quintile.Table 10.2 Early childhood mortality rates by socioe-conomic characteristicsNeonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year periodpreceding the survey, by background characteristic, Tanzania HMIS 2007-08BackgroundcharacteristicNeonatalmortality(NN)Postneonatalmortality 1(PNN)Infantmortality( 1 q 0 )Childmortality( 4 q 1 )Under-fivemortality( 5 q 0 )ResidenceUrban 46 33 79 34 110Rural 29 41 70 45 112Mainland/ZanzibarMainland 32 40 72 43 112Mainland – Urban 47 34 81 35 113Dar es Salaam City 70 42 112 43 150Other Urban 39 31 70 32 99Mainland – Rural 29 42 70 45 112Zanzibar 31 23 54 26 79Unguja 36 19 55 18 72Pemba 23 29 52 39 89ZoneWestern 17 45 63 31 92Northern 29 33 63 31 92Central 43 35 78 54 128Southern Highlands 36 39 75 50 121Lake 23 45 68 56 120Eastern 58 45 103 46 145Southern 44 31 75 34 107Zanzibar 31 23 54 26 79Mother's educationNo education 33 51 85 49 129Primary incomplete 26 45 71 42 110Primary complete 33 34 67 42 106Secondary + 32 31 64 15 78Wealth quintileLowest 31 51 82 51 129Second 32 37 69 43 110Middle 26 41 67 47 111Fourth 32 36 68 37 103Highest 41 32 73 30 1011Computed as the difference between the infant and neonatal mortality rates10.3 DEMOGRAPHIC DIFFERENTIALS IN CHILDHOOD MORTALITYTable 10.3 presents differentials in childhood mortality by demographic characteristics ofmother and child. In general, during childhood, male mortality is higher than female mortality. Forexample, infant mortality for boys is 74 deaths per 1,000 live births compared with 70 deaths per1,000 live births for girls, and boys are more likely than girls to die during the neonatal period. On theother hand, girls are more likely to die during the postnatal period than boys.Infant and Child Mortality | 129
Mother’s age at birth is associated with childhood mortality in a U-shaped pattern. Childrenborn to young mothers (under 20 years) and old mothers (age 40-49) have relatively higher infantmortality than children born to mothers in the middle age groups. Shorter birth intervals are associatedwith higher mortality. The under-five mortality rate for children born less than two years after thepreceding birth is 159 per 1,000 live births compared with 77 deaths per 1,000 live births amongchildren born four or more years after their preceding sibling.Table 10.3 Early childhood mortality rates by demographic characteristicsNeonatal, postneonatal, infant, child, and under-five mortality rates for the 10-year periodpreceding the survey, by demographic characteristics, Tanzania HMIS 2007-08DemographiccharacteristicNeonatalmortality(NN)Postneonatalmortality 1(PNN)Infantmortality( 1 q 0 )Childmortality( 4 q 1 )Under-fivemortality( 5 q 0 )Child's sexMale 36 38 74 39 110Female 28 42 70 46 112Mother's age at birth
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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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Figure 7.1 Recent Sexual Intercours
Page 102 and 103: Table 7.3.2 Multiple sexual partner
Page 104 and 105: Table 7.4 Payment for sexual interc
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 150 and 151: INFANT AND CHILD MORTALITY 1010.1 I
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
Page 194: Table A.6 Coverage of HIV testing a
Page 197 and 198: where h represents the stratum whic
Page 199 and 200: Table B.2 Sampling errors for Natio
Page 201 and 202: 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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