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Malimu demography

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  • *INTRODUCTION TO DEMOGRAPHY

    MALIMU, PhDDept of Epidemiology/Biostatistics,School of Public Health and Social Sciences,Muhimbili University of Health and Allied Sciences.

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    OBJECTIVESTo understand basic concepts of demographyTo understand common vital statisticsTo understand sources of vital eventsAble to calculate and interpret common indices in public health

    *Within the presentation, I will talk on what we know about birth defects in general and the background information from Africa with respect to birth defects. We shall discuss challenges of studying birth defects with respect to sources and analyses of data.

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    OUTLINE OF THE PRESENTATIONIntroduction and some definitionsSources of dataCommon indices used in public health

    *Within the presentation, I will talk on what we know about birth defects in general and the background information from Africa with respect to birth defects. We shall discuss challenges of studying birth defects with respect to sources and analyses of data.

  • *DemographyScience of human populationFormal demographySize (number)Distribution (geographical)Structure (age and sex)Change (decline or increase)

  • *Extended meaning of demography Ethnic characteristicsRace, nationality, mother tongue, etcSocial characteristicsMarital, pace of birth, literacy, education Economic characteristicsEmployment, occupation,, industry, income, etc

  • *Vital statistics The most common are: (1) Births (Natality) (2) Deaths (Mortality) (3) Marriages (Nuptiality) (4) Movements (Migrations)

  • *Demographic equationIn order to project population in futurePt = Po + (B D) +( I O)P = NI NM

    *Embarking on preventive and control measures of birth defects, we need first to understand the magnitude and pattern of the problem. We need to know the system of data collection, modes of analyses and monitoring tools.

  • *Use of demographyUnderstand magnitude

    Understand the pattern (trend)

    Understand causes (etiology)/ risk factors

    Utulization of health care services

    *Embarking on preventive and control measures of birth defects, we need first to understand the magnitude and pattern of the problem. We need to know the system of data collection, modes of analyses and monitoring tools.

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    Consequences for lack of statisticsUnknown number of population at riskUnknown number of casesUnknown risk factorsPoor planning

    *The direct consequences for lack of health-related information in Africa and other developing countries include unknown number of births and unknown number of infants with a particular birth defect. Ultimately, it will never be easy to control the problem of birth defects.

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    Sources of vital statisticsCensusVital registrationSample surveys

    *There are substantial studies of birth defects in industrialized counties ranging from descriptive to analytical, across different spectrum of settings. In Africa very little is known about the magnitude, distribution and risk factors for birth defects. This discrepancy is not only on birth defects but may be also for other different types of morbidities. Studies that exist are based on hospital delivery registers where birth rates and prevalences of birth defects are only estimated. It is unlikely to capture most of births using hospital data. Although use of antenatal services is rising (currently over 60%), most of deliveries (60-80%) occur at home. Failure to capture all births through hospital delivery registers, means under-reporting of number and types of birth defects.

  • *CensusSystematic routine of counting subjectsProduce record of individual at a particular timeOutcome: size and structure

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  • *CensusCovers ALL subjectsA single point figure (cross-sectional)LegalWithin or between census comparison (numbers, %)

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  • *Enumeration methodsDe facto (in fact present)De jurePeople who live there or have the right to be there

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  • *Census100% coverage Not helpful for health programs when population characteristics change rapidly.Projections usedDetailed questions on fertility and mortality.

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  • *Vital registrationEvents during a particular time interval (year)Dynamic informationEvents are affected by numbers at risk, used to calculate ratesPossible to compare levels

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  • *Vital registration Common in industrialized countries Less developed countries, incomplete Simple and few questions

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  • *Vital registrationExamples: death, birth or marriage certificatesWeaknesses:IncompleteSelectivePractically unreliable

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  • *E.g. Birth registration

  • *Sample surveys Study a small part of populationLess costlyQuicker

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  • *Sample surveys DetailedChances of errorsExamples: DHS, HIV/AIDS Surveillance

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    Sources of morbidity dataAdmission registers, these can be: Institutional-based (Hospitals)Community-based (surveillance, environmental safety)Example: Cancer, accident

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

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    Sources of morbidity dataClinical recordsIndicate history of illness For example, laboratory records

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

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    Sources of morbidity dataHospital discharge summariesFound in Health isntitutionsHMIS

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

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    Sources of morbidity dataDisease surveillance and screening programsScreening and investigations for epidemicsRecords show prevalence (symptoms and non-)

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

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    Sources of morbidity dataSources outside health facilitiesMCHEDPEPIMental Health ProgrammeOral, Dental and Eye care CentresNutritional programmes

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

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    Sources of mortality dataDeath certificateDisease control programsCensusSpecial surveys

    *I may broadly categorize available studies on birth defects from Africa in four categories: Studies on birth defects seeking to determine the prevalence or incidence, case-control studies, genetic studies that may or may not be case-control in design and others.

  • *FERTILITYNumber of live births the woman has ever hadFertile = woman had at least one childOpp: infertility (childless)Physiological ability to bear children (fecundity)Opp: sterilityPhysiological ability to conceive (in a menstrual cycle) = fecundability

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  • *Measures of fertilityCrude Birth Rate (CBR) Not a rate but ratio CBR=Live births/year x 1000

    Total population

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  • *Measures of fertility2002 Tanzania Population and Household Census:Total births = 1,191,084Total population = 34,443,603CBR = 34.6 births per 1000 population

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  • *Measures of fertilityCBR is simple to calculateRequires few dataEasy to understandUsed for crude RNIRNI = CBR - CDR

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  • *Measures of fertilityGeneral Fertility Rate (GFR) Acceptable rate GFR=LB (year) x 1000

    Mid year WRA Refined fertility measure

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  • *Measures of fertilityRanges between 50 and 3002002 PHC:Total births = 1,191,084WRA = 8,245,388GFT = 144.5 per 1000 WRA.

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  • *Total Fertility Rate (TFR)

    Based on specific F-rates Hypothetical measures Reproductive experience

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  • *Total Fertility Rate (TFR)

    Average number of children per womanIn their reproductive lifeGiven that she survives to age 50Given that current age specific fertility rates would still be applicable during all these 35 years

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  • *ExampleTable 12.1 Age-Specific Fertility Rates (ASFR): Tanzania, TDHS, 1996.

    Age groupsNumber of womenBirthsASFR per 100015-1920-2425-2930-3435-3940-4445-491729169414151135 896 670 581233440361246150 58 24135260255217167 87 42

  • *Calculation of TFRTFR = c(ASFR): c = age interval

    = 1.163 x 5 = 5.815

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  • *Interpretation of TFROn average, each woman would have 6 children IF she survives through her reproductive life AND ASFRs do not change

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  • *Gross Reproduction Rate (GRR)GRR similar to TFRConsiders ONLY female live born babies

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  • *Gross Reproduction Rate (GRR)Average number of DAUGHTERS a woman would have if she survives up to her 50th birthday and experiences the given females ASFRsGRR=1 (able to reproduce)GRR=2 (population doubling)

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  • *Example: GRRTable 12.1 Age-Specific Fertility Rates (ASFR): Tanzania, TDHS, 1996.

    Age groupsNumber of womenFemale BirthsFemale ASFR per 100015-1920-2425-2930-3435-3940-44