Morbidity In Kenya

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d e t e r m in a n t s o f m a t e r n a l m o r t a l it y a n dMORBIDITY IN KENYAuwn'cp Tv n r W4IR0B/\BY\KIAGE, PAULa iS T S E 8I8 f U *THE d e g r e e Off—A C C E P T O * * *D "VND A COPY MAY BE A C E DTHESIS SUBMITTED TO THE POPULATION STUDIES AND RESEARCH INSTITUTEIN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTEROF ARTS IN POPULATION STUDIES OF THE UNIVERSITY OF NAIROBI.1999" ’ ' m i r o t m u n r o N t *

DECLARATIONThis thesis is my original work and has not been presented elsewhere for theaward of a degree in any other University.Candidate:PaulSignature:This thesis has been submitted for examination with our approval as UniversitySupervisors.Supervisor:Dr. Boniface K' OyugiSignature:Supervisor:Prof. Zibeon MuganziSignature:Population Studies and Research InstituteUniversity of NairobiP.O. Box 30197NAIROBI

ACKNOWLEDGEMENTI owe special thanks to the University of Nairobi for the scholarship offeredto me to pursue a graduate programme leading to a Master of Arts degree inPopulation Studies at the Population Studies and Research Institute.This study was undertaken with significant input from many people andinstitutions. IFRA - Nairobi provided grants for this study. I am grateful to IFRA forits financial support which contributed to the success of this project.Special thanks go to my supervisors Dr. Boniface K'Oyugi and ProfessorZibeon Muganzi for their thorough supervision which culminated into thecompletion of this work. Without their substantive intellectual support, particularlyDr. K'Oyugi who not only encouraged me to work on the project but also managedto find time out of his busy schedule to work with me on the Kenya MaternalMortality Baseline Survey data bank until such a time when I was able to handlethe data on my own, the work would have remained at the proposal stage. I willalways strive to emulate him.I am also indebted to the Director of the Population Studies and ResearchInstitute, Professor A.B.C. Ocholla - Ayayo and the entire staff of the Institute fortheir contribution in one way or another to the current state of this thesis.I also wish to extend my sincere thanks to my colleagues particularly TomOwuor and Peter Otieno fortheir help and co-operation throughout the entire periodI worked on this project.Last but not least, to my parents the late Mzee Kiage and Mama Yucabeth,I express most gratitude for their patience and great assistance I received duringthe long period of my study.ii

DEDICATIONThis thesis is dedicated to my father, the late Mzee Kiage "Ongujo" whoselflessly sacrificed to sell his hard earned livestock to finance my education.ii

TABLE OF CONTENTDECLARATION.ACKNOWLEDGEMENT . .DEDICATION. .ABSTRACT .viCHAPTER ONEINTRODUCTION .1.1General Introduction.1.2Problem Statem ent. .1.3Objectives .1.3.1 General O b je c tiv e :.1.4Justification Of The S tu d y.1.5Background Information .1.5.1 Geography .1.5.2 Demographic S itu a tio n .1.5.3 Health Services in Kenya.1.6Scope and Limitation .CHAPTER TWOLITERATURE REVIEW . .2.12.22.32.42.4.12.4.2A Preview of Maternal Mortality in The World .Maternal Mortality and Morbidity in Developed Countries . . .Maternal Mortality and Morbidity in Developing Countries . .Maternal Mortality and Morbidity in K enya.Incidence of Maternal Mortality in K e nya.Causes of Maternal Mortality in Kenya .CHAPTER THREECONCEPTUAL FRAMEWORK, DATA SOURCE AND METHODOLOGY3.1Conceptual Fram ew ork.3.1.2 McCarthy and Maine (1992) Analytical Fram ework.3.2Conceptual Hypotheses .3.3Operational Hypotheses . . . .3.4Operational D e fin itio n s.3.4.1 Death : .3.4.2 Distant Determinants .3.4.3 Socio-economic Factors .3.5Demographic F a c to rs .3.6Socio-Economic Factors .3.7Data Sources .3.7.1 Primary Data Source.3.7.2 Other Sources of Data on Maternal Mortality .3.7.3 Hospital Data . .3.8Methods Of Data Analysis .3.8.1 Descriptive Statistics . 353535363737

3.8.2 Cross Tabulations .3.8.3 Logistic Regression .CHAPTER FOURREGIONAL MATERNAL MORTALITY .6.55.6.645Introduction .45Distribution of Maternal Deaths . 46Maternal Mortality Differentials .49Maternal Mortality By Demographic F actors.49Maternal Mortality By Socio-economic Factors:53Maternal Mortality By Social Factors. 56Summary of the Cross Tabulations Results on Maternal Mortality . . . 58Regional Maternal Morbidity Differentials in Kenya .59A naem ia.60Differentials in Anaemic Morbidity By Demographic F a c to rs .62Differentials in Maternal Morbidity By Social F a c to rs .65Differentials in Maternal Morbidity By Socio-Economic Factors . . . .66Differentials in Maternal Mortality By Anaemic M o rb id ity .68Pregnancy Complications .69Pregnancy complications By Social Factors .71Pregnancy Complications By Socio-Economic Factors .72Differentials in Pregnancy Complications By Maternal D e a th s . 73CHAPTER FIVEDETERMINANTS OF MATERNAL MORTALITY ANDKENYA: .5.13739MORBIDITYIN75Definition of Dummy Variables in The Logistic Regression modelUsed .75Demographic V ariables. 75A g e .75Marital Status .76Parity .77Social F a c to rs .77E ducation.77Province of Residence .77Socio-economic Factors . . . .78Ante-natal Clinic A ttendance.78Postnatal Clinic Attendance . 78Logistic Regression R esults.78Limitations of Stepwise Regression.79Discussion of R e su lts.82Effects of Province of Residence on Maternal M o rta lity .82The Effects of Age on Maternal Mortality .83The Effects of Ante-natal Clinic Attendance on Maternal Mortality . 85The Effects of Parity on Maternal mortality .86The Effects of Education on Maternal Mortality .87The Effects of Marital Status on Maternal M o rta lity .89IV

CHAPTER SIXSUMMARY, CONCLUSIONS AND RECOMMENDATIONS6.16.26.36.46.5. 90Introduction .90Summary Of Findings.91Conclusions .94Recommendations to Policy Makers . 96Areas for Further Research . 98REFERENCES.APPENDIX.v99108

Table 4.1:TableTableTableTable4.2:4.3:4.4:4.5:Table 4.6:Table 4.7:Table 4.8:Table 4.9 eTable4.17:4.18:4.19:4.20:4.21:4.22:4.23:Table 4.24:Table 4.25:Table 5.1:LIST OF TABLESDistribution of Maternal Deaths admitted by variousBackground Characteristics:.48Distribution of Maternal Mortality By Age of the Mother . . .50Distribution of Maternal Mortality By P a rity .52Distribution of Maternal Mortality By Marital S ta tu s .53Distribution ofMaternal Deaths By Regular Attendance ofA n te na ta l.54Distribution of Maternal Deaths By Parity 2 AttendingPostnatal C lin ic .55Distribution of Maternal Mortality By Educational Level: . . . .56National Distribution of Maternal Deaths By Province ofResidence .58Distribution of Women Diagnosed With Specific MaternalMorbidity Type: .60Distribution of Anaemia Cases By A g e . 62Distribution of Anaemia cases By P a r ity .63Distribution ofAnaemia by Marital S ta tu s .64Distribution ofAnaemic Cases By Educational L e v e l.65Distribution ofanaemia cases By Provinces .66Distribution ofAnaemia By Ante-natal Clinic Attendance . . . . 67Distribution of Anaemia By Parity 2 Attending PostnatalClinic .67Distribution ofAnaemia By Maternal Mortality: .68Distribution ofPregnancy complications By A g e : .69Distribution ofPregnancy Complications By P a rity:.70Pregnancy complications By Marital Status: .70Pregnancy ComplicationsBy Education .71Pregnancy complications By Province: .72Pregnancy Complications By Regular Attendance of Ante-natalC a r e .72Pregnancy Complications By Parity 2 attending PostnatalClinic .73Distribution of PregnancyComplications By Maternal Deaths:74Logistic Regression Estimates on the Determinants of MaternalMortality and the selected Independent Variables.81LIST OF FIGURESFigure'1 :Figure 2 :Conceptual M o d e l. 29Operational M o d e l. 30VVI

ABSTRACTThe study attempts to examine the demographic, socio-economic and socialdeterminants of maternal mortality and morbidity in Kenya using hospital basedinformation of the Kenya Maternal Mortality Survey of 1994. In an attempt todetermine the crucial factors that influence maternal mortality and morbidity inKenya, the study analyzed 66,080 cases drawn from 19 district and provincialhospitals covered by the survey. The hospital information was collected using pre designed forms of three types. The first form was used to extract information fromfiles of each woman admitted to the pregnancy ward. The basic informationincluded age, parity, marital status, educational level attained, ante-natal andpostnatal clinic attendance, medical history on the survival status of the patient atthe time of discharge, and the cause of death if applicable. The second form wasused to collect a summary information from the maternity and gynaecology wardson the number of admissions, the number of deliveries by method and the numberof maternal deaths.Lastly, the third form was a designed questionnaireadministered to hospital personnel pertaining to major maternal mortality causes,ante-natal and postnatal services as well as referrals from traditional birthattendants admitted to the hospitals. The hospital-based maternal mortalitystatistics suffered selectivity bias in reflecting national level of maternal mortality,particularly in areas where women did not routinely give birth in the hospitals.The data obtained was analyzed by the use of descriptive statistical methodsinvolving the performance of percentages, frequencies, cross tabulation and logisticregression through SPSS / PC computer program.VII

The primary finding of the study indicated that mothers age, parity,educational level attained, ante-natal and postnatal clinic attendance and provinceof residence were significant determinants of maternal mortality and morbidity inKenya. The results further revealed that maternal deaths was highest amongwomen of older reproductive ages (40 years) and those of parity 7 . Withregard to maternal level of education on maternal mortality, there was a noteddecrease in maternal deaths with an increase in level of education attained with asecondary level of education exhibiting the lowest maternal mortality incidence.Lastly the wide disparities in maternal mortality across the provinces with Nyanzaand Coast Provinces experiencing higher maternal mortality incidence Eastern, RiftValley and Central Provinces.Based on these findings, a number of relevant recommendations to policymakers and areas of further research are suggested. In order to reduce maternalmortality, an intensive campaign has to be carried out by the government throughthe Ministry of Education to promote women education especially to higher levels(secondary ), expand provision of primary health care particularly the coverage ofante-natal and postnatal services to women equitably across all provinces. Furtherstudies should be done to find out why some provinces exhibit higher maternalmortality than others and to establish whether the regional disparities across theprovinces noted by hospital data also exist in the household / community basedsurvey. Lastly, research should be done to assess the impact of HIV/AIDSprevalence on maternal mortality and morbidity given the close association betweenthe AIDS pandemic and reproductive health.VIII

CHAPTER ONEINTRODUCTION1.1 - General IntroductionThe World Health Organization estimates that at least 585,000 women dieeach year as a result of complications of pregnancy or child birth (Rinehart andKols,1992). The majority of these deaths occur in the developing world, estimatedat 1,025 deaths per 100,000 live births in some African countries (Boerma,1 987).The increasing maternal mortality and morbidity rates in the world wheretremendous achievements in medicine has been realised continue to be a majorworry for African governments (Rosenfield and Maine, 1985). As African womentry to fight for equal rights, maternal deaths still remain a big problem in a continentwhere high fertility and mortality rates reign supreme.In 1987, the Kenya Government hosted the launch of the International SafeMotherhood Initiative and endorsed the Plan of Action to reduce maternal mortalityand morbidity. The Safe Motherhood Initiative focused international attention onthe problem of maternal mortality.A decade after the launching of SafeMotherhood Initiative, it has become increasingly clear that strategies to savemother's lives have been less successful than the child survival programme (Maineand McNamara 1987, Royston and Armstrong, 1989).The complexity of theissues and the broad range of factors that have been taken into account have madeinterventions with specific target, difficult to design. The provision of adequatehealth services to prevent maternal mortality and morbidity is constrained by lackof infrastructure,equipment and trained medical personnel that hampersdevelopment in general, and thus adverse maternal outcomes are inextricably tied1

to difficult economic conditions that characterise many parts of the developingworld, Kenya included (Obermeyer, 1993:354-365).The Kenya Maternal Mortality Baseline Survey (1994) indicated that regionalmaternal mortality differentials characterise Kenya's provinces as do the disparitiesin fertility and in infant and child mortality. Thus, the high maternal mortality inCoast, Nyanza and parts of Western Kenya contrasts sharply with exceptionallylow rates in Central and parts of Eastern Provinces attest to this fact. Accordingto this report (KMMBS, 1994), Kwale, South Nyanza (Homa-Bay, Migori) and Busiadistricts reflect a less stage in the demographic transition and have much poorermaternal health regimes hence they deserve special attention.1.2 - PROBLEM STATEMENTA maternal death is defined as the death of a woman while pregnant orwithin 42 days (6 weeks) of a termination of a pregnancy, irrespective of theduration and site of pregnancy, from any cause related to or aggravated bypregnancy or its management but not from accidental or incidental cause (WHO,1993). Maternal mortality has long been a neglected topic of research and asrecently as 1985, maternal mortality in developing countries was referred to as"a neglected tragedy" (Rosenfield and Maine,1985). In Kenya, the precise numberof these silent and neglected tragedies that occur to women in their prime life (1 549 years) cannot be determined and the estimates are alarming. Over 4,300 die ofmaternal deaths and over half-a-million women encounter obstetric complicationsyearly (Ministry of Health, 1997). At this rate, a great many Kenyans are affectedby these tragedies through the loss or disablement of a wife, a daughter, sister -2

indeed a mother.Although the national estimate for maternal mortality ratio of 365 deaths per100,000 live births (KMMBS, 1994) appears low by comparison with the figuresfrom other sub-saharan countries, the same report indicates that regional maternalmortality differentials characterize Kenya's provinces from the highest maternalmortality ratio of 2221.7 per 100,000 births in Kwale to the lowest ratio of 18.8per 100,000 births for Nyeri district. South Nyanza ( the current Migori, HomaBay, Suba and Rachuonyo) districts are ranked second, with maternal mortalityratio of 1072.9 per 100,000 births (KMMBS, 1994:42). Thus South Nyanza(Homa-Bay, Suba, Rachuonyo and Migori) districts reflect a less stage in thedemographic transition because of their much poorer health regimes and hencedeserves special attention (KMMBS, 1994).Maternal mortality rate in Kenya as in any other part of Africa is exceedinglyhigh. In Kenya the family formation patterns are influenced by cultural and socialvalues which place a high premium on fertility. Marriage is universal and earlymarriage is almost the rule. Girls are often married by the time of menarche (1 5years).Pregnancy and childbirth often occur within two years of marriage.Polygamy is widely practised and acceptable among many Kenyans. Fecundity andhigh parity (7 ) are regarded as great attributes and blessings. The high rates ofchildhood mortality in Kenya over 97 per 1000 births, (NCPD, 1993) cause parentsto overinsure against the anticipated child losses. As a consequence, the earlymarriage for women in Kenya is followed by three decades of unregulatedsuccession of pregnancies, childbirth and lactation. But each pregnancy entails arisk of injury to the life or health of the mother. It is against this background that3

the study seeks to investigate the socio-econom ic, dem ographic and socialdeterminants of maternal m ortality and m orbidity in Kenya.1.3 - OBJECTIVES1.3.1 - General Objective:The main objective of this study is to establish the determinants of maternalmortality and morbidity in Kenya.The specific objectives of the study are:1)To determine socio-economic correlates of maternal morbidity and mortalitydifferentials in Kenya.2)To establish the socio-demographic determinants of maternal morbidity andmortality rates in Kenya.3)To identify demographic factors underlying the maternal morbidity andmortality in Kenya.1.4 - JUSTIFICATION OF THE STUDYA woman in Kenya has 1 in 43 chance of dying of pregnancy-related causesduring her reproductive life. About 194,000 experience life-threatening conditionsand over half-a-million women suffer complications related not to a disease - buta natural event - pregnancy (M.O.H, 1997). The death of such a mother seriouslyaffects the survivalof her children and particularly the index child.In a highfertility population such as Kenya, the number of children orphaned by maternaldeath is indeed high. For some of these, their mother would have been the headof the household and death leaves them destitute. Beyond the immediate loss oflife, maternal mortality also exerts a devastating effect on the family. Frequently,4

the study seeks to investigate the socio-econom ic, demographic and socialdeterminants of maternal m ortality and m orbidity in Kenya.1.3 - OBJECTIVES1.3.1 - General Objective:The main objective of this study is to establish the determinants of maternalmortality and morbidity in Kenya.The specific objectives of the study are:1)To determine socio-economic correlates of maternal morbidity and mortalitydifferentials in Kenya.2)to establish the socio-demographic determinants of maternal morbidity andmortality rates in Kenya.3)To identify demographic factors underlying the maternal morbidity andmortality in Kenya.1.4 - JUSTIFICATION OF THE STUDYA woman in Kenya has 1 in 43 chance of dying of pregnancy-related causesduring her reproductive life. About 194,000 experience life-threatening conditionsand over half-a-million women suffer complications related not to a disease - buta natural event - pregnancy (M.O.H, 1997). The death of such a mother seriouslyaffects the survivalof her children and particularly the index child.In a highfertility population such as Kenya, the number of children orphaned by maternaldeath is indeed high. For some of these, their mother would have been the headof the household and death leaves them destitute. Beyond the immediate loss oflife, maternal mortality also exerts a devastating effect on the family. Frequently,4

infant and maternal deaths occur simultaneously. Prevention of maternal deathscan, in many cases, also save the life of a child perhaps several children (Beverlyand Sullivan, 1987). The fate of surviving children is not documented, but thelikelihood that they will receive optimal care and health protection is probablydiminished.Emphasis on maternal mortality prevention thus complements thegrowing concern about infant and childhood mortality (KMMBS, 1994).Since adequate information on the determinants of maternal mortality andmorbidity are still lacking in developing countries, the study intends to fill the gapleft by the earlier survey (KMMBS, 1994) which was a baseline survey to assessmainly the magnitude and pattern of maternal mortality in Kenya. A comprehensiveknowledge on the explanations of determinants of maternal mortality and morbiditywill be essential for planning successful maternal and child health programmes inthe country.1.5 - Background Information1.5.1 - GeographyKenya covers an area of 582,000 sq kilometres. It borders Ethiopia in thenorth, Sudan in the northwest, Uganda on the west, Tanzania in the south andSomalia in the east. It has 400 kilometres of Indian Ocean Shoreline. Lyingbetween 3 degrees north and 5 degrees south latitude and between 34 and 41degrees east longitude , it is entirely within the equatorial zone. The country isalmost bisected by the equator.The country falls into two distinct regions, i.e. lowland and highland (upland)Kenya. This distinction affects the climate patterns of human settlement and5

agricultural activities. Kenya has an unusually diversified physical environment:savannah, tropical, equatorial volcanic and tectonic. Approximately 80% ofKenya's land is arid and semi-arid and only 20% is arable. A large part of the aridand semi-arid zones have been set aside for wildlife conservation.Kenya is divided into 8 provinces, which are subdivided into districts. In allthere are about 68 districts, 26 of which were recently delineated.1.5.2 - Demographic SituationPopulation distribution in Kenya is influenced by factors among them thephysical, historical, pattern of economic development and policies pertaining to landsettlement. The average population density was approximately 37 persons in 1989.With only 17.5% of Kenya's land suitable for cultivation, population density varyconsiderably. Population densities for areas with large proportions of arable landsuch as Western, Central and Nyanza provinces reached 230 persons per squarekilometre while in the dry North Eastern Province the average density was only 3persons per sq. kilometre in 1989.On the basis of census statistics, Kenya's population increased from 5.4million in 1948 to 1 5.3 million in 1979 and to 21.4 million in 1989 (CBS,1994) andwas estimated at 27.5 million by mid-1995 assuming moderate decline in fertilityand mortality rates that take into account the AIDS pandemic. A time seriesanalysis of census results indicate that Kenya's natural rate of increase acceleratedfrom 2.5% in 1948 to 3.0%, 3.3%, 3.8% in 1962, 1969 and 1979 respectively.The analysis also indicates that the country's rate of population growth declinedfrom 3.8% in 1979 to 3.3% in 1989 and was estimated at 3.0% in mid 1995.6

While the acceleration in the growth rate during the 1948-1 985 period was due toa combination of factors namely - high fertility levels and low contraceptive use,the decrease in mortality was attributed to improvements in the health and socio economic status; the decline in growth rate during the 1990-1995 period wasmainly due to fertility decline.The crude birth rate increased from 50 per thousand in 1948 to 52 perthousand in 1979. The high fertility rates in Kenya in the past four decades arenow on the rapid decline. The Total Fertility Rate (TFR) was 7.7 children perwoman in 1984. This declined to 6.7 in 1989, 5.4 in 1993 and declined to 4.7 in1998 (NCPD,1998). The reported drop in fertility rate has been observedthroughout the country although differentials still exists among Kenyan womenassociated with the area of residence and level of education. Although theexplanation for the past onset of demographic transition towards lower fertility iscomplex and requires a detailed analysis, the factors which have contributed to thedecline in fertility in Kenya have been mainly the increased use of contraceptionand increased age at marriage and women's educational status.Levels of mortality in Kenya have declined steadily during the four decadesprior to 1989. Crude death rate decreased from 17 per thousand in 1948 to 14 and12 per thousand in 1979 and 1989 respectively. Infant mortality declined from 184deaths

2.3 Maternal Mortality and Morbidity in Developing Countries . . 2.4 Maternal Mortality and Morbidity in Kenya. 2.4.1 Incidence of Maternal Mortality in Kenya. 2.4.2 Causes of Maternal Mortality in Kenya . CHAPTER THREE

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