BACKGROUND: Globally, perinatal mortality accounts for a large proportion of child deaths. Perinatal mortality rate (PNMR) is taken as an index of efficient obstetric care, and also serves as an indicator for the Millennium Development Goals (MDGs) 4 and 5, that is related to infant mortality rate and improving maternal health (Day, Monticelli, Barron, et al., 2010). In developed countries, perinatal mortality rate has shown a marked decrease over the past few years. This is mostly due to the changing patterns in reproductive health, improved socio-economic factors and quality of maternal and child care (World Health Organization, 2006). However, developing countries are still struggling to curb perinatal deaths. In South Africa, there has been a gradual decline in the PNMR in public health facilities from 38.6 in 2003/2004 to 31.0 per 1000 live births in 2008/2009. However, there has been a slight increase to 32.8 per 1000 live births in 2010/2011 (Day, Barron, Massyn, et al., 2012). In the Mpumalanga province, the PNMR has decreased slightly from 34.9 per 1000 live births in 2008/2009 to 33.2 per 1000 live births in 2010/2011. Carolina Hospital itself has a PNMR which is far too high at 43 per 1000 live births from January to June in 2008/2009. It is assumed that because the sub-district is underserved with primary health care facilities as well as having a poor attendance of antenatal care services by pregnant women, this has subsequently had a negative effect on perinatal care. However, this has never been formally assessed. AIM: The aim of the study was to describe the perinatal mortality and morbidity, and to identify the causes and avoidable factors of perinatal mortality and morbidity at Carolina Hospital for the period 1st April 2009 to 31st March 2011. METHODOLOGY: The setting for the study was the maternity unit of Carolina Hospital, a district hospital in the Gert Sibande district, Mpumalanga. It comprised of a retrospective record review of data from the maternity registers and the Perinatal Problem Identification Programme (PPIP); from the 1st April 2009 to the 31st March 2011. All the records of perinatal deaths (N=94) and admissions (N=35) of babies 7 days old and younger during the study period were included in the study and no sampling was done for these two groups of patients. For all other delivery records, systematic sampling was utilized by choosing every tenth record listed on the sampling frame. Data was extracted from the PPIP and maternity registers using data extraction sheets. Data was captured onto a Microsoft excel based spreadsheet, imported into and analyzed with EPI-Info software version 3.5.1 using descriptive and analytic statistics. Data was collected the number of perinatal deaths, admissions, total number of deliveries, neonatal and maternal profile, causes of perinatal mortality and morbidity and factors associated with perinatal mortality and morbidity RESULTS: During the period of the study there was a total of 1 604 deliveries with 94 perinatal deaths and 35 perinatal admissions. The perinatal mortality rate was 61.4 per 1000 live births with a stillbirth rate of 47 per live births; and an early neonatal death rate of 14.4 per 1000 live birth. Nine percent of the mothers were unbooked, and this accounted for 11.4% of perinatal morbidity and 17% of the mortality which occurred during the study period. Over a third (34%) of the perinates who died were born from HIV positive mothers; whilst more than halve (54.3%) of those perinates who were admitted during the perinatal period were born from HIV positive mothers. Over two thirds (63.2%) of the perinatal deaths were below 2500g while half (45.7%) of admissions were below this birth weight. Intrauterine death (40.4%) was the leading cause of perinatal mortality at Carolina Hospital for the two years of study. Over the two year study period, patient related factors were the highest avoidable factors given, accounting to 72.9% of the total while health care related avoidable factors accounted to 39.5% of the perinatal mortalities and morbidities. CONCLUSION: The study found that there was a high PNMR and high still birth rate at Carolina Hospital. The majority of the avoidable factors were patient related. The reasons for this included late booking, delay in seeking medical attention during labour, never initiating antenatal care, infrequent visits to the clinic, and inappropriate response to poor fetal movement. In order to achieve the Millennium Development Goal 4 more attention should be given to reducing perinatal deaths. These indicate a need to strengthen the quality of ANC rendered, especially in the primary health care facilities. RECOMMENDATIONS: There is a need to strengthen maternal and child health services in the maternity unit of Carolina Hospital, and in the surrounding clinics within the Albert Luthuli sub-district. Clinical governance should be strengthened within Carolina Hospital. There is also a need for maternal and child health specialist outreach services within the Gert Sibande district health as a whole.

Diss. (sammanfattning) Stockholm : Karol. inst. / Härtill 6 uppsatser.

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The subject of rickets is one to which I have given much thought during several years of an intimate experience in the management of the disease. I have been particularly impressed by its great prevalence amongst the more crowded districts and lower classes of our city population as compared with the less populous, but not necessarily less fortunately circumstanced country localities. I have likewise observed marked differences in physique between the parents of the city and those of the country; also the apparent contempt of the citizen parent for the health-giving influences of fresh air. Even more so have I noticed the crass ignorance exhibited in the choice of proper articles of diet for the rearing of children of tender years. Another striking factor is the appalling death-rate amongst young children from this disease and its protean consequences, a death-rate which, in this so called enlightened age, is not showing the diminution it should do: largely, in my opinion, owing to the invincible ignorance and obstinacy of the lower-class mother. She, in not a few instances, insists in bringing up her infant in the same faulty way as she herself was reared. In these cases the fussy grandmother is the bugbear of every family practitioner. "Children are not reared nowadays as they were in my time," she says. Granted; and it is well for the present-day pediatric prospects that usually they are not. The grandmother-empiric, when inclined to practice her domestic medicine with its nonsensical basis, is an everyday evil, and should be fought at every turn. There is too great a tendency on the part of some practitioners to agree with her for the sake of peace and popularity and recommendation: this fact, particularly in slum experience, I have from time to time observed. "Look at me," she commands the anxious mother, "I was reared on such and such a food or in this or that way, and what's good enough for your mother should be good enough for your bairn." Authority has spoken and nothing more can be said.

Introduction The fourth Millennium Development Goal (MDG) calls for a reduction in newborn mortality but newborn mortality is one of the world’s most neglected health problems. While there has been significant progress in reducing deaths among children under age five over the past decade, the proportion of under five mortality that occur in the neonatal period, an estimated 38% in 2000, is increasing. Therefore the Millennium Development Goal for child survival cannot be met without substantial reductions in neonatal mortality. It is therefore extremely important to make available the much needed epidemiological information regarding the time, place and causes of neonatal deaths which will enable greater attention to policies aimed at reducing levels of mortality and programme planning. Objectives The objective of this study was to investigate the relationship between neonatal mortality and place of delivery in Rufiji in rural Tanzania. The specific objectives were: 1.to measure and compare the neonatal mortality rates among neonates born in and outside health facilities, 2. to compare the maternal characteristics of those who deliver in and outside health facilities, 3. to compare cause-specific neonatal mortality among neonates born in and outside health facilities and 4.to measure the association between place of delivery and neonatal mortality. Methods Data from the Rufiji Demographic Surveillance System (RDSS), Tanzania, was used for the analysis. A total of 5124 live births and 166 neonatal deaths were recorded from 1st January, 2005 to 31st December, 2006. Place of delivery and place of death were categorized as either health facility or outside health facility. Neonatal mortality rates were calculated by dividing the number of neonatal deaths to the total number of live births and multiplied by 1000. Data on causes of death were collected using verbal autopsies. Cause specific mortality was determined by using physician coding according to a list of causes of death based on the 10th revision of International Classification of Diseases. Household characteristics and assets ownership of the mothers of the neonates were used to construct a wealth index as proposed by Filmer and Pritchett in 20011. The index was calculated using Principal Component Analysis (PCA) in Stata version 10 software. A chi-square (x2) test at 5% significant level was also used to compare the maternal characteristics by place of delivery and neonatal characteristics and place of delivery. Univariate and multivariate logistic regression models were also used to assess the association between neonatal mortality and place of delivery as well as between neonatal mortality and maternal risk factors, while adjusting for potential confounders. Results The highest number of neonatal deaths occurred during the first week of life 111(67%), the remainder occurred from the second week to the fourth weeks of life 55(33%). The overall neonatal mortality rate was 32/1000 live births. Neonatal mortality rate was higher in children born outside heath facilities 43/1000 live births compared with those born in health facilities 27/1000 live births. The two major causes of deaths in both health facility deliveries and outside health facility deliveries were birth injury or asphyxia n=29 (26%) and prematurity/low birth weight n=25 (22%). Mothers who delivered out-side a health facility were 1.6 times more likely to have experienced neonatal death [unadjusted OR=1.6, p-value = 0.002, 95% CI 1.2, 2.2] compared to mothers who delivered in health facility and this was statistically significant. After adjusting for maternal risk factors, mothers who delivered outside a health facility were 1.7 times more likely to have experienced neonatal death [adjusted OR=1.7, p-value = 0.002, 95% CI 1.2, 2.4] compared to mothers who delivered in a health facility and this was statistically significant. Maternal household socio-economic status and parity were the only other factors that were found to be statistically significantly associated with neonatal mortality in the multivariate analysis. For instance, least poor mothers were found to be 40% less likely to have experienced neonatal death [adjusted OR = 0.6, pvalue = 0.046, 95% CI 0.4, 1.1] compared to the poorest mothers and this was statistically significant. Less poor mothers were also found to be 50% less likely to experience neonatal mortality [adjusted OR =0.5, p-value = 0.002, 95% CI 0.3, 0.8] compared to the poorest mothers. Mothers who had parity of three to four (3-4) were found to be 40% less likely to have experienced neonatal death compared to mothers who had parity of one to two (1-2). Mothers who had parity of five (5) and above were also found to be 50% less likely to have experienced neonatal death compared to those who had parity of one to two (1-2). Conclusion Place of delivery has a very important role in neonatal survival in this rural setting. In order to reduce neonatal mortality, pregnant women should be encouraged and supported to give birth to their newborns in a health facility while discouraging deliveries that occurred outside health facility. Infrastructure, such as emergency transport, to facilitate health facility deliveries requires attention.

Background Disparities in health outcomes between the poor and the rich are increasingly attracting attention from researchers and policy-makers. However, policies aimed at reducing inequities need to be based on a sound assessment of the nature, magnitude and determinants of the problem, as policy decisions based on intuition are likely to be misguided. Objective The work investigates the relationship between household socio-economic status and under-five mortality at Rufiji DSS in year 2005. The specific objectives were; 1.To construct wealth and concentration indices for households with children under age five. 2. To measure health inequality by poorest / least poor mortality rate ratio and the use of concentration index 3. To determine significance in gradient of mortality rates across wealth index quintiles by a trend test (chi-square) 4. To assess the magnitude of association between socio-economic status of households and under-five mortality. Methods Data from Rufiji DSS, Tanzania was used for the analysis. Out of 11,189 children under five years of age from 7298 households, 251 died in the year 2005. These yielded a total of 9341.6 PYO in 2005 which was used in the analysis. Household wealth index was constructed by use of Principal Component Analysis (PCA), as a proxy measure of each household SES. From this index households were categorized into five quintiles (i.e., poorest, poorer, poor, less poor and least poor). Kaplan-Meier (K-M) survival estimates of incidence rates were used to estimate mortality rates per 1000 PYO for infants (0-1), children (1-4) and under-fives. Health inequality was measured by poorest to least poor mortality rate ratio and by computing mortality concentration indices. Trend test chi-square was used to determine significance in gradient of mortality rates across wealth index quintiles. Risk factors of child mortality were assessed by the use of Poisson regression taking into account potential confounders. Results The result indicates that the mortality rate was higher for infants (123.4 per 1000 PYO, 95% CI (104.3, 146.1)) than for children aged 1-4 years (17.3 per 1000 PYO, 95% CI (14.3, 20.9)). Under-five mortality was 26.9 per 1000 PYO (95% CI (23.7, 30.4)). The poorest to least poor ratio were 1.5, 3.8 and 2.4 for infants, children, and under-five year olds, respectively indicating that children in the poorest quintile were more likely to die as compared to those in the least poor household. Computed values for concentration indices were negative (infant C= -0.07, children C= -0.24 and under-five C= -0.16) indicating a disproportionate concentration of under-five mortality among the poor. The mortality rates trend test chi-square across wealth index quintiles were significant for both children (P<0.001) and under-five year old children (P<0.001) but not for infants (P=0.10). In univariate Poisson regression, children in the least poor households were shown to have a 58% significantly reduced risk of dying as compared to the poorest households [crude RR=0.42, P < 0.001, 95% CI (0.27 - 0.62)]. The effect of household socio-economic status attenuated after adjusting for maternal education, maternal age and occupation. Children in vi the least poor households had a 52% significantly reduced risk of dying as compared to the poorest households [adjusted RR=0.48, P = 0.002, 95% CI (0.30 - 0.80)]. Conclusion The study shows that household socio-economic inequality is associated with under-five mortality in Rufiji DSS in 2005 and that the survival advantage of under-five year old children is associated with maternal education. Reducing poverty and making essential health services more available to the poor are critical to improving overall childhood mortality in rural Tanzania.

A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand in partial fulfillment of the requirements for the degree of Master of Science in Medicine (Epidemiology and Biostatistics) Johannesburg, May 2014 / Objective: The objective is to estimate the magnitude and determinants of perinatal mortality in Agincourt, and determine whether there is a difference in perinatal mortality rate between South Africans and self-settled Mozambicans. Design: Case-control study of 134 cases and 136 controls using longitudinal data drawn from the Agincourt dataset for the period 1995-2000 Methods: All cases were matched against a random selection of 136 controls. Odds ratios were used to assess risk, with p-values for trend where necessary. Logistic regression was used to determine independent effects of significant risk factors. Limitations of the study: Probable under-reporting of stillbirths and early neonatal deaths. Results: The Agincourt perinatal mortality rate is estimated as 13.4 per 1000 births (95%CI, 11.23- 15.8) with an increasing trend from 1995-2000 (X2 for trend 19.487, p-value <0.001). Delivery by a nurse attendant is a protective factor but not independently so. Multivariate analysis indicates that babies of women who never attended antenatal clinic during the index pregnancy are at higher risk of perinatal death (OR= 7.55; 95%CI, 2.03-28.05) compared to others whose mothers attended antenatal clinic at least four times. Women with history of perinatal death are at a higher risk of experiencing it again, compared with those without (OR =13.68; 95%CI, 1.43-130.82). The difference in perinatal mortality rate for South Africans (13.3) and former Mozambican refugees (11.8) is not statistically significant (p-value = 0.522). Conclusion: Perinatal mortality is rising; key risk factors are non-attendance for antenatal care by mothers, and previous perinatal death. There is no significant difference in perinatal mortality rate between South Africans and self-settled Mozambicans in Agincourt.

Background: This study examines the association between place of delivery, delivery assistants and perinatal mortality in Nigeria. Previous studies have found these factors to be associated with the risk of perinatal mortality. This study therefore aims to determine the extent to which these two factors predict perinatal mortality in the Nigerian context as this information will be useful in informing health policy decisions and actions in so far as a desirable reduction in childhood mortality in Nigeria is concerned. Methods: This study uses cross sectional design through secondary analysis of the 2003 Nigerian Demographic and Health Survey (NDHS). The variables representing place of delivery and delivery assistants have been fitted into logistic regression models to determine their association with perinatal mortality. Several other known risk factors for perinatal mortality such as maternal education and birth weight, to mention a few, have also been investigated using the logistic regression analysis. Results: 5783 live singleton births were analyzed with 194 newborns dying within the first seven days of life giving an early neonatal mortality rate (ENMR) of 33.5 per 1000 and an estimated perinatal mortality rate (PNMR) of 72.4 per 1000 live births. The results also show that place of delivery [p=0.8777] and delivery assistants [p=0.3812] are not significantly associated with perinatal mortality even after disaggregating the analysis by rural and urban areas. However being small in size at birth [AOR= 2.13, CI=1.41 – 3.21], female [AOR=0.57, CI= 0.42 – 0.77] and having a mother who practiced traditional religion [AOR= 4.37, CI= 2.31 – 8.26], were all significantly associated with perinatal mortality. Conclusions: Place of delivery and delivery assistants are not good predictors of perinatal mortality in the Nigerian context. However various limitations of the study design used such as the issue of uncontrolled confounding may have affected the findings. Nonetheless, the increased risk of perinatal deaths in small babies and the decreased risk of death among female babies are consistent with other studies and have both been attributed elsewhere to biologic mechanisms.

Background: This study examines the socioeconomic and biodemographic determinants of infant, neonatal and post neonatal mortality in Egypt. It also tries to reach better understanding on the relative importance of these factors. Methods: Population-based cross-sectional secondary data analysis of the 2005 Egypt Demographic and Health Survey (EDHS). Cox’s proportional hazard models have been fitted to select the significant determinants of infant and post neonatal mortality, while logistic regression models were adopted for the neonatal period. Results: 13,851 live births were analyzed with 463 deaths before the first birthday; the total follow up time is 144,835 babymonths, giving an IMR of 32 per 10,000 baby-months. After adjusting for all socioeconomic and biodemographic factors, the analyses reveal strong association between infant mortality and biodemographic factors, while the only significant socioeconomic determinant is the mother’s education. Also it has been shown that mother’s education, child’s sex and place of delivery are time dependent covariates. Analyses of neonatal period indicate no association with any socioeconomic factor, while child’s sex and place of delivery are significant predictors. Exclusion of neonatal deaths shows that the risk of post neonatal mortality is inversely related to mother’s education, and not determined by sex of the child nor place of delivery. The risk of infant, neonatal and post neonatal death is consistently related to birth interval and birth size. Conclusions: Biodemographic characteristics represent the most substantial impacts on infant mortality. The only significant socioeconomic predictor (maternal education) has a modest impact, at best, on infant mortality, which appears at later stages of infancy period (namely post neonatal period); since the later proved to be a time varying covariate. Unlike neonatal period, analysis indicates lack of association between post neonatal mortality and child’s sex contradicting the biological knowledge, and supporting the hypothesis of gender discrimination and male sex preference.