The purpose of our study is to evaluate the role of several maternal factors that would contribute to low birth weight (LBW) and to what extend they would affect the birth weight. The main objectives is to look at the LBW incidence, risk factors and immediate perinatal outcomes from 2008-2009 in Zimbabwe and make a comparison with normal weight babies. In addition, it tries to illustrate any relationship between LBW and the several suspected contributing factors to immediate outcome (fetal condition on delivery).
Low birth weight (LBW) has been defined by the World Health Organization (WHO) as weight at birth less than 2 500 grams (5.5 pounds). This practical cut-off for international comparison is based on epidemiological observations that infants weighing less than 2 500 g are approximately 20 times more likely to die than heavier babies. A birth weight below 2 500 g contributes to a range of poor health outcomes and this is more common in developing than developed countries.
According to the 2002 census, Zimbabwe has 11.6 million people. Infant mortality rates (IMR) climbed from 53 to 81 deaths per 1000 from 1960 to 2008. Also 2/3 of childhood deaths occur during infancy, with more than a third taking place during the 1st month of life. Estimates of unemployment rate are around 85-90%. As of 2009, 1.2 million Zimbabweans live with HIV. By end of 2008 the health system had more or less collapsed. Three of Zimbabwe’s four major hospitals (Mpilo was the exception) had shut down, along with University of Zimbabwe’s Medical School.
Table of contents
1. PURPOSE OF THE STUDY
2. OBJECTIVES
3. ASSUMPTIONS
4. STUDY POPULATION
5. BACKGROUND
6. METHODOLOGY
7. LIMITATIONS
8. RESULTS
9. DISCUSSION
10. CONCLUSION
LITERATURE CITED
APPENDIX
1. PURPOSE OF THE STUDY
There are several factors which are associated with low birth weight (LBW). The purpose of our study is to evaluate the role of several maternal factors that would contribute to LBW and to what extend they would affect the birth weight. We also factored in the immediate outcome in relation to the birth weight and the various risk factors involved.
2. OBJECTIVES
1. To look at the LBW incidence, risk factors and immediate perinatal outcomes from 2008-2009 and make a comparison with normal weight babies.
2. To determine the effect of various maternal factors on LBW.
3. To illustrate any relationship between LBW and the several suspected contributing factors to immediate outcome (fetal condition on delivery).
4. To measure any association between LBW and other peri-partum conditions and to what extend perinatal outcome was affected by LBW.
5. To determine the trends and any differences in birth weights during the year of socio-economic and political turmoil and through the transition thereof (any difference between the 2008 and 2009 figures).
6. To identify and quantify risk factors for preterm (<37 gestation) and term LBW (>/= 37 gestation).
7. To illustrate any seasonal variation of birth weights through measurement of proportion of LBW to normal birth weights on a month-on-month basis.
3. ASSUMPTIONS
1. Unbooked pregnancies, age, parity, HIV status and whether on treatment or not, current and past obstetric history, and socio-economic status affect birth weights.
2. The more the confounding factors, the higher the risk and hence the lower the birth weight
3. Birth weights during a stressful period would be lower than during a phase of relative stability
4. Lower birth weights will lead to lower Apgar scores
5. Birth weight may affect delivery and mode of delivery
4. STUDY POPULATION
ZIMBABWE
According to the 2002 census, the country has 11.6 million people. Average annual population growth reached a peak of 3.5% in 1951-1961, and then dropped to 3% between 1982 & 1992 and to 1.1% between 1992 and 2002. 34
Blacks constitute about 99% of the population, whites, coloured and those of Asian descent contribute about 1% of Zimbabwe’s population.41% of the population is less than 15 years old. Those between the ages of 15 and 64 make up 55%, and 4% are 65 years old and above. Crude birth rate is 30.3/1000and crude death rate is 17.2/1000. 35
Life expectancy at birth has dramatically declined since 1990 from 60 to 37 in 2008, but has since risen to about 52years. Infant mortality rates (IMR) climbed from 53 to 81 deaths per 1000 during the same period. Current figures from Zimbabwe Demographic and Health Survey(DHS) 2010-11 states that IMR is 57, under 5 mortality rate is 84 and neonatal mortality rate is 31 per 1000 births. Also 2/3 of childhood deaths occur during infancy, with more than a third taking place during the 1st month of life 35. Estimates of unemployment rate are around85-90%. As of 2009, 1.2 million Zimbabweans live with HIV. By end 0f 2008 the health system had more or less collapsed. Three of Zimbabwe’s four major hospitals (Mpilo was the exception) had shut down, along with University of Zimbabwe’s Medical School. Due to hyperinflation, those hospitals still open were not able to obtain basic drugs, medicines, equipment and other utilities. The on-going political and socio-economic crisis also contributed to mass exodus of health professionals including doctors and midwives.
POLITICAL & SOCIO-ECONOMIC SITUATION(S)
Zimbabwe had been in rapid deterioration in terms of its economic and political situation from 1999 to 2008, resulting in untold human suffering. The largest burden was probably felt by women (especially expecting & nursing mothers) and children. After a widely condemned run-off election in June 2008, a power-sharing agreement was reached in September 2008 and only fully implemented in February 2009. Dollarization of the economy was effected during the first quarter of 2009. All these factors contributed to the sudden rise of much yearned social and economic stability.
MPILO CENTRALHOSPITAL – MATERNITY
The main hospital (including the maternity wing) was opened in 1954. The new maternity wing, which excludes post-natal ward (PNW) and antenatal clinic, was constructed with the assistance of the Japanese Government and opened in 1991. On average there are about 10 000 deliveries per year making it the 2nd largest maternity unit in Zimbabwe. Catchment area includes the western and some southern Bulawayo suburbs, Matabeleland North and southern Midlands provinces. The hospital is located to the west of the city centre, surrounded by the very poor high density suburbs of Mzilikazi, Nguboyenja, Makokoba and Barbourfields.
5. BACKGROUND
Low birthweight (LBW) has been defined by the World Health Organization (WHO) as weight at birth less than 2 500 grams (5.5 pounds). This practical cut-off for international comparison is based on epidemiological observations that infants weighing less than 2 500 g are approximately 20 times more likely to die than heavier babies. A birthweight below 2 500 g contributes to a range of poor health outcomes and this is more common in developing than developed countries.
The goal of reducing low birthweight incidence by at least one third between 2000 and 2010 is one of the major goals in ‘A World Fit for Children,’ the Declaration and Plan of Action adopted at the United Nations General Assembly Special Session on Children in 2002. The reduction of low birthweight also forms an important contribution to the Millennium Development Goal (MDG) for reducing child mortality. Activities towards the achievement of the MDGs will need to ensure a healthy start in life for children by making certain that women commence pregnancy healthy and well nourished, and go through pregnancy and childbirth safely. Low birthweight is therefore an important indicator for monitoring progress towards these internationally agreed-upon goals 41. Low birth weight may arise for different reasons, one related to gestational age and the other corresponding to births that are small for gestational age (SGA). The cohort of LBW is likely to reflect two effects; short gestational age (preterm delivery) and SGA. SGA usually arises from intra-uterine growth restriction (IUGR) 11. Preterm delivery is defined as delivery before 37 completed weeks of gestation. Small for gestational age infants are those whose weights are below the 10th percentile for their gestational age 27.
Many factors affect the duration of gestation and of fetal growth, and thus, the birthweight. They relate to the infant, the mother or the physical environment and play an important role in determining the infant’s birthweight and future health 42. The need to identify factors which contribute to LBW is essential to reduce infant mortality and morbidity. LBW by definition is birth weight less than 2500g. It can arise because of small for gestational age from intrauterine growth restriction or preterm delivery. LBW is a surrogate measure for the health of any community or nation. It is one of the strongest determinants of infant mortality and morbidity, thus it continues to be closely monitored. Birth weight is a powerful indicator of infant growth and survival. Infants born with LBW begin life immediately disadvantaged and face extremely poor survival rates. In poor developing countries it was approximated that every 10 seconds an infant dies from a disease or infection that can be attributed to LBW 1.Generally the risk of neonatal mortality for LBW infants is 25-30 times greater than for infants with birth weights of 2500g or greater, and it increases sharply as birth weight decreases 2 . The increase in survival rates of LBW infants leads to increasing health care costs due to extensive hospital stays. It is estimated that extremely LBW (ELBW) babies are up to six times as costly as normal weight babies. The concepts of preterm birth and small for gestational age differ in their pathogenesis but share many predisposing factors and as such, these phenomenon are often considered together.
Known factors for preterm delivery and fetal growth restriction which are associated with LBW include low maternal food intake, hard physical work during pregnancy and illness, especially infections 3, 16.Several studies suggest that cigarette smoking, genetic and environmental factors can cause LBW 4, short maternal stature, very young age, high parity, close birth spacing, and high C8 cell counts in HIV infections are all associated risk factors 5, 17. Risk of giving birth to a LBW baby increases with severity of HIV infection in pregnant women 6. High proportion of LBW are associated with the observations that women spend most of the day standing whilst looking after cattle or squatting during milking thus straining their bodies and possibly getting little time for resting 7, 18. Complications during delivery such as delivery such as placenta abruption and praevia have been directly associated with LBW 8. Poor maternal nutrition and diet around and during pregnancy adversely affect fetal and neonatal outcomes 9, 15. Other determinants of LBW include hypertension during pregnancy or pre-eclampsia 13 and previous LBW 41. Low birth weight in singleton term live births occur more frequently in women with one, two, three or more previous induced abortions, compared with women without any previous induced abortion of similar gravidity, 2.2% versus 1.5%, 2.4% versus 1.7%, and1.8% versus 1.6% respectively 37. In a population survey done in Ahmedabad, India; low maternal weight, poor obstetric history, lack of antenatal care, clinical anaemia and hypertension were significant independent risk factors for both term and preterm LBW. Short interpregnancy interval was associated with an increased risk of preterm LBW birth while primiparous women had increased risk of term LBW 38. Another study done in Islamabad showed that risk factors like maternal nutrition, young age of mothers, poverty, close birth spacing, hypertension and antepartum per vaginum bleeding during pregnancy have independent effect in causing low birth weight 39. At Harare Hospital the frequency of preterm delivery among live birth was 16.4%. Prior history of stillbirth or abortion was associated with preterm delivery. Nutritional factors, including drinking a local non-alcoholic beverage during pregnancy and mother’s increasing mid-arm circumference reduced the risk of preterm delivery. Conditions like malaria, eclampsia, anaemia, ante-partum haemorrhage, and placenta praevia were infrequent, but when present, were strongly associated with preterm delivery.
For the same gestational age, girls weigh less than boys, firstborn infants are lighter than subsequent infants, and twins weigh less than singletons. To a large extend the mother’s own fetal growth and her diet from birth to pregnancy, and thus, her body composition at conception also affects birthweight of her baby. Women of short stature, those living at high altitudes, and young mothers have smaller babies.41
LBW is estimated to be 16% worldwide (or some 20million infants per year), 19% in least developed countries and 7% in the developed world. LBW incidence is 31% in South Asia, 15% in Middle East and North Africa, 14% in Sub-Saharan Africa and 7% in East Asia and Pacific 12.
Despite decades of advances in reproductive medicine and large reductions in the rates of neonatal and infant mortality the incidence of LBW has not decreased . In the USA the rate of LBW births declined during the 1970s and early 80s. From a low of 6.7% in 1984, it increased to 8% in 2002 . Global incidence of LBW is around 17 % . In a literature review, de Onis et al (1998) found that IUGR babies are at increased risk of perinatal mortality and morbidity, i.e. sudden infant death syndrome (SIDS), poor cognitive development and neurological impairment, high blood pressure, obstructive lung disease, diabetes, high cholesterol concentration and renal damage in adulthood11. Such babies remain a burden on government expense in developed countries and a permanent problem for their families in developing countries.
Birth weight categories
LBW <2500g
Very LBW <1500g
Extremely LBW </=1000g
Incredibly LBW </=750g
Categories of maternal risk for LBW
1. Economic-poverty, unemployment, poor access to antenatal care(ANC), poor access to food
2. Cultural-behavioural-low education status, poor health care attitudes, no or inadequate ANC, cigarette/alcohol/drug abuse, age less than 16years or greater than 35years, single, short interpregnancy interval, lack of support groups(partner, family, church, community), stress(physical, psychological) 24, 33, poor weight gain during pregnancy, black race 25
3. Biological-Genetic-Medical-previous LBW 14, 26, mother low weight at birth, low weight for height, short stature, poor nutrition, chronic medical illness, inbreeding, intergenerational effect.
4. Reproductive-multiple gestation, preterm rapture of membranes, infections (systemic, amniotic, extra-amniotic, cervical) 25, pre-eclampsia/eclampsia, antepartum hemorrhage, parity (0 or >5), utero-cervical anomalies, fetal disease, anaemia or high hemoglobin, idiopathic premature labor, iatrogenic prematurity
INTRAUTERINE GROWTH RESTRICTION
LBW babies who are small for gestational age (SGA) are often designated as having fetal growth restriction. It is estimated that 3% of infants are growth restricted in the USA. SGA infants are those whose weights were below the 10th percentile for their gestational age (Battaglia & Lubchenco, 1967).IUGR accounts for 11% of the total babies in developing countries ranging from 2-21%, that is 6 times higher compared to developed countries 11.IUGR babies are at an increased risk of perinatal mortality and morbidity, i.e. sudden infant death syndrome (SIDS), poor cognitive development and neurologic impairment, cardiovascular disease, diabetes mellitus, high cholesterol concentrations and renal damage in adulthood 11.
Symmetrical growth restriction: -an early insult could result in a relative decrease in cell number and size e.g. chemical exposure, viral infection. Asymmetrical growth restriction: -might follow a late pregnancy insult such as placental insufficiency from hypertension.
Risk factors
-constitutionally small mothers 29
-poor maternal nutrition 30
-social deprivation 31
-maternal and fetal infections
-congenital malformations
-chromosomal aneuploidies
-drugs with teratogenic and fetal effects
-vascular disease, anaemia, renal disease
-chronic hypoxia, pre-gestational diabetes
-placental and cord abnormalities 28, 32, 36.
-antiphospholipid syndrome
-genetics
-multiple foetuses
PRETERM LBW
Preterm birth is any birth regardless of birth weight which occurs before 37 completed weeks of gestation. The lower gestational age limit for a preterm birth is 24 weeks of gestation or 500g according to WHO. In Zimbabwe and other resource-poor settings it’s from 28 weeks of gestation or 1000g. In the USA preterm delivery rate is about 12% and directly responsible for 75-90% of all neonatal deaths.
Reasons for preterm delivery
1. Delivery for maternal or fetal indications in which labor is induced or delivery via Caesarean section
2. Spontaneous, unexplained preterm labor with intact membranes
3. Idiopathic preterm premature rapture of membranes
4. Multiple gestations
Risk factors
-threatened miscarriages
-lifestyle factors e.g. cigarette smoking, inadequate maternal weight gain and use of illicit drugs 20.
-genetic factors 19.
-birth defect 21.
-interpregnancy interval less than 18 months and greater than 59 months 22.
-young or advanced maternal age, poverty short stature, vitamin C deficiency, strenuous working conditions 23.
6. METHODOLOGY
The study was a retrospective, descriptive matched control study of LBW. Data was collected from Maternal Delivery Registry. Captured data was for a 2-year period from 01 January 2008 to 31 December 2009.Low birth weight was defined as delivering an infant with birth weight of 500g to less than 2500g at birth. Controls were births with weight equal to or above 2500g. Multiple gestation deliveries were excluded from the study.
Several risk factors (antepartum variables) were looked into. Booking was defined as registering the pregnancy and attending antenatal clinic on at least three occasions. The cases that are booked at Mpilo hospital are usually medium to high risk pregnancies. Usually mothers booked with Mpilo deliver at the facility. In some instances women with no risk at all end up delivering at our hospital due to poor referral criteria from surrounding clinics among other reasons. A few women only come when already in labour, without having been referred and unbooked. Residence was subdivided into three categories; from the rural areas, from the poor suburbs immersing Mpilo and the other high suburbs of Bulawayo (western suburbs). It’s very rare to have pregnant women from the medium density suburbs, and virtually none from the affluent low density areas. Maternal age was subcategorized into teenagers, those between age 20 and 34 years, and finally mothers of age 35 years and above. For analysis gestational age was further grouped into babies less than 28 weeks of gestation, between 28 and less than 38 weeks of gestation, and the term babies at 38 weeks of gestation or more. Parity was also considered and then categorized into the primiparous, grand-multiparas (those at least para 5), and those in between. Bad obstetric history of preterm delivery, low birth weight, miscarriages and other factors was also analysed. If the mother also had adverse conditions like gestational hypertension, draining liquor and other conditions that was also looked into. Sex of the baby was also considered as a variable. With the devastating effects of HIV across all sections of our society, it was going to be foolhardy to ignore its contribution towards birth weight. Whether administration of anti-retroviral therapy (ART) and the type of ART regimen had an/any effect on newborn weight was measured.
Some of the perinatal outcomes examined other than birth weight included labour duration, estimated blood loss, state of perineum post-delivery and Apgar scores. Labour duration was further subdivided into 12 hours or less, between 12 and 24 hours, and duration of greater than 24 hours. Blood loss measurement has great intra-observer and inter-observer errors. Estimates of blood loss are by subjective visual inspection of perineum, swabs and linen pads. That was classed further to loss of less than 500ml, 500 to<1000ml and any loss greater than 1000ml. Perineal tears were graded into 1st, 2nd and 3rd degree tears. Unfortunately 4th degree tears were classified under 3rd degree ones. 1st degree is where only the vaginal epithelium and perineal skin are breached. If the perineal muscles are lacerated then it is 2nd degree. 3rd degree (plus 4th degree) is when the perineal body, anal sphincters and mucosa were torn.
SAMPLING AND STATISTICAL METHODS
The sample used for this study consisted of data imported from an Epi Info Mpilo Hospital database containing data for 2345 maternal patients into the Statistical Package for Social Sciences (SPSS) version 16.0 (see Appendix II).The research made extensive use of descriptive statistics, that is, the methodology for describing or summarising a set of data using tables, graphs and charts so as to spot any patterns in the data. Numerical measures such as the arithmetic mean, the standard deviation and proportions were derived. Statistical t-tests for the comparisons of proportion means were done based on normal birth weights as ‘the control’ and low birth weights as ‘the experiment’, probability values (p-values) were used to draw conclusions. Relationships among the risk factors and birth weight are explored using a multiple regression analysis.
ETHICS STATEMENT
This research made use of primary data that already has ethical documentation and did secondary analysis. The researcher was authorized to carry out secondary analysis on the Mpilo Central Hospital Maternal database captured in the Epi Info system which hides the identity of individual patients (see Appendix I). The data obtained was treated with strict confidentiality and the results are presented in ways that make specific identification by future researchers and users of this paper impossible.
7. LIMITATIONS
The audit would have been more powerful if the study had been for the 2008 to 2011 period. Any significant changes (improvement or deterioration) in outcomes would have possibly been more appreciable. Due to time and financial costs that was, unfortunately, not achievable. Other variables of importance like marital status, maternal hemoglobin levels, anthropometric measurements, number of antenatal visits, timing of first booking, level of education and employment status of both spouses are not recorded in the Delivery Register. Focusing solely on births at Mpilo Hospital may cause potential selection bias. Because this population is mostly high risk, there is a possibility of high incidence of iatrogenic preterm deliveries. Exclusion of twin deliveries may also underestimate rate of preterm delivery. Bias towards sampling deliveries from urban folk would naturally exclude the population that has lack of nutritious food, easy access to modern healthcare and good sanitation among several other disadvantages.
8. RESULTS
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Figure 1. Age of the mothers (Author’s own illustration/work)
The majority of mothers (73.3%) had ages of between 20 to 34 years. 17.8% were teenage mothers and 8.9% had advanced maternal age.
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Figure 2. Area of residence (Author’s own illustration/work)
About 91% of the women were from other high density areas in Bulawayo, 6.5% from very poor high density areas close to the hospital and 2.8% from rural areas
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Figure 3. Gestational Age (Author’s own illustration/work)
The majority of babies (50.5%) were born after 37 weeks of gestation, and almost 44% were preterm deliveries.
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Figure 4. Booking status of the mothers (Author’s own illustration/work)
About 51% of the mothers were booked for deliveries at their local clinics, whereas only 26.2% were booked at Mpilo. A relatively higher percentage (22.9%) was not booked at any health institution.
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Figure 5. Parity (Author’s own illustration/work)
45.5% of the women who delivered at Mpilo were nulliparas, 1.8% were grand-multiparas and a larger proportion (52.8%) had previously delivered up to 4 children
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Figure 6. Bad obstetric history (Author’s own illustration/work)
The majority of the women (83%) did not have a bad obstetric history. For those with the BOH, most common was others and miscarriages/abortions. Low birth weight had the least percentage of 0.1%.
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Figure 7. Presentation (Author’s own illustration/work)
A fairly large percentage of women had no current pregnancy complications (39.7%). Hypertension in pregnancy was seen in 11.6%. Those with draining liquor were 3.4%. 0.4% of women presented with twin gestation; those in whom multiple gestation was only observed at delivery were obviously not included. As expected at a tertiary referral hospital, the majority of women (60.3%) had pregnancy related complications.
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Figure 8. Mode of delivery (Author’s own illustration/work)
The most common mode of delivery was NVD (82%), followed by LSCS (17%) whilst the other modes had percentages less than 2%.
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Figure 9. Labour duration (Author’s own illustration/work)
The majority of labours (55.3%) were up to 12 hours in duration. A small proportion (7.4%) of labours lasted for more than 24hrs.
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Figure 10. Perineal Tears (Author’s own illustration/work)
37.7% of deliveries were complicated by first degree tears. Almost 1% had 2nd degree tears. A relatively acceptable figure 0.2% had 3rd degree perineal lacerations. A huge proportion had no perineal lacerations at all (61.2%).
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Figure 11. HIV Status of the mothers (Author’s own illustration/work)
An unacceptable proportion of women had their HIV status not known. Almost tallying with national figures, 17% of mothers were HIV positive.
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Figure 12. HIV treatment (Author’s own illustration/work)
Of those who were HIV positive, only 15% were on Highly Active Antiretroviral Therapy (HAART). 6% were on moderately efficacious regimen (MER). 60% were only given Nevirapine in labour. 19% were not given any form of ARV treatment.
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Figure 13. Estimated blood loss (Author’s own illustration/work)
90.7% by old definition didn’t have any postpartum hemorrhage. Of those who had postpartum hemorrhage, 2% had estimated blood loss of at least 1000ml.
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Figure 14. Outcome newborn (Author’s own illustration/work)
Of the sampled data, 88.3% of births were live. Macerated still births were 9.6% and 2.2% were fresh still births.
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Figure 15. Proportion of low birth weight babies (Author’s own illustration/work)
Compared to 2008, 2009 had smaller proportion of low birth weight babies to total birth, 10.0% and 7.3% respectively.
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Figure 16. Age of mother at birth (Author’s own illustration/work)
Teenage pregnancies contributed to 17.8% of the deliveries. 73.3% of the mothers were between the ages of 20 and 34yrs. Advanced maternal age (35yrs and older) saw a contribution of 8.9%.
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Figure 17. Area of residence (Author’s own illustration/work)
The 4 very poor high density suburbs surrounding Mpilo contributed to 6.5% of the deliveries, 2.8% were from the rural areas and possibly outside referrals and 90.8% were from the other high density suburbs of Bulawayo.
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Figure 18. Number of children had previously (Author’s own illustration/work)
45.5% of births were by nulliparas women, 1.8% were by grand-multipara mothers and the rest (52.8%) were from women who had previously up to 4 children.
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Figure 19. Booking Status (Author’s own illustration/work)
A fairly large proportion of women who gave birth at Mpilo Hospital had booked their pregnancies (77%), of which 26.2% had been registered at Mpilo antenatal clinic (ANC).
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Figure 20. Mode of delivery (Author’s own illustration/work)
81.1% of mothers spontaneously delivered vaginally, 16.7% did so via Caesarean section. Only 0.5% had operative assisted vaginal delivery (0.3% by forceps & 0.2% by Ventouse). 1.6%, spontaneously delivered vaginally, were classified as miscarriages as the estimated gestational age was less than 28 weeks of gestation.
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Figure 21. Estimated blood loss (Author’s own illustration/work)
9.3% of the women had postpartum hemorrhage; 2.0% had major obstetric hemorrhage.
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Figure 22. Apgar scores (Author’s own illustration/work)
Normal Apgar scores were observed in 76% of births.
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Figure 23. State of the placenta (Author’s own illustration/work)
98.9% of the placentae were delivered complete initially. The incomplete ones were 0.4% and 0.7% were ragged.
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Figure 24. Sex of the born child (Author’s own illustration/work)
The births were slightly biased towards boys (50.2%).
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Figure 25. Birth mass (Author’s own illustration/work)
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Figure 26. Gestational age and birth mass (Author’s own illustration/work)
For the low birth weight babies, 9% were less than 28 weeks of gestational but at least 500g. 62.2% of low birth weights were preterm according to Zimbabwean and some other low resource settings’ definition. Possible intra-uterine growth restriction contributed to 28.8% of the low birth weight deliveries.
A very small fraction of the normal birth weight babies were less than 28 weeks of gestation. 21.9% of deliveries between 28 and 37 weeks of gestation weighed at least 2 500g. So, 23.4% of those weighing at least 2 5000g were preterm deliveries.
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Figure 27. Bad obstetric history (Author’s own illustration/work)
Of the low birth weights; 0.1% had previous low birth weight, 1.9% had previous preterm delivery, 6.1% had a previous miscarriage(s) or abortion(s), 10.1% had some other form of bad obstetric history and 81.8% didn’t have past adverse obstetric event.
For those with birth weights of at least 2 500g; only 1% had previous preterm delivery, 0.1% had previous low birth weight, 4.6% had previous miscarriage(s) or abortion(s), those with other prior bad obstetric events were 10.4% and 83.9% had normal previous pregnancies.
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Figure 28. Labour duration (Author’s own illustration/work)
Babies less than 2 500g were more likely to be delivered by at most 12hrs, a higher proportion of babies weighing at least 2 500g were more likely to deliver longer than 12hrs than the smaller babies
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Figure 29. Perineal tears (Author’s own illustration/work)
Perineal tears were more likely with babies of weights of 2 500g or more.
47.5% of deliveries for normal birth weights ended up with 1st degree tears compared to 29.9% from low birth weights. 0.3% and 1.5% of low birth weights and normal births respectively, led to 2nd degree tears. Also 0.2% and 0.3% of low birth weights and birth weights of at least 2 500g respectively, resulted in obstetric anal sphincter injuries.
Smaller babies were more likely to result in a normal, intact perineum than bigger babies. 69.9% of low birth weight babies were more likely to be delivered without any damage to the perineum. Only about half (50.7%) of babies weighing at least 2 500g were likely not to tear mother’s perineum.
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Figure 30. HIV status of mother (Author’s own illustration/work)
A higher proportion of HIV mothers who had babies weighing at least 2 500g (57.5%) were HIV negative than those who had low birth weight (40.6%). The maternal HIV positive status rates, 15.7% and 18.3%, respectively were almost equal between low birth weight and normal birth weight babies. HIV status of mothers with low birth weights (43.7%) were more unlikely to be known than those of normal birth weights (24.2%).
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Figure 31. ART therapy (Author’s own illustration/work)
For mothers of those babies with weights below 2 500g; 16.9% were on Highly Active Antiretroviral therapy (HAART), 2.6% were on moderately efficacious regimen (MER), 59.0% on Nevirapine (NVP) and 21.5% not on any form of HIV treatment.
Babies weighing at least 2 500g, the mothers; 14.1% were taking HAART, 9.0% were on MER, 60.5% took NVP and some 16.4% were not taking any antiretroviral drugs.
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Figure 32. Outcome of newborn (Author’s own illustration/work)
97.5% of babies weighing at least 2 500g were live, 0.9% were fresh still births (FSB) and 1.6% were macerated still births (MSB).
Those babies with weights of less than 2 500g; 81.0% were alive at birth, 3.3% were FSB, 15.7% were macerated.
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Figure 34. Number of children born with low birth weights in 2008 and 2009 (Author’s own illustration/work)
There were much higher rates of low birth weights in 2008 than in 2009 with only the months of June, July and September showing some deviation.
The differences in the mean percentages of LBW between 2008 and 2009 were analysed using a Student T-Test. The mean percentage for 2008 was 11.4±4.0 and for 2009 was 9.6±2.1. The t test showed that there was no significant differences in the mean number of children born with LBW, between 2008 and 2009 (F= 1.966, p= 0.199).
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Figure 35. Number of children born >/=2500g in 2008 and 2009 (Author’s own illustration/work)
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Figure 36. Comparison of weights of children born in 2008 and 2009(Author’s own illustration/work)
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Figure 37. Weight of children and booking status (Author’s own illustration/work)
29.7% of the mothers with low birth weight babies were unbooked, compared with 13.5% of those who delivered normal weight babies. There was a significant difference between the weights of babies who had been born by mothers who had booked at a health centre and those babies whose mothers had not booked (F = 70.28; p< 0.0001). Those women who had booked their pregnancies had higher rates of normal weight babies (86.5% vs. 70.3%) irrespective of place of booking compared to women who had not booked.
Abbildung in dieser Leseprobe nicht enthalten
Figure 38. Area of residence and weight of babies (Author’s own illustration/work)
There were no significant birth weight differences between women from the rural areas and those from the high density suburbs (p = 0.625).
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Figure 39. Age of mothers and weight of babies (Author’s own illustration/work)
Teenagers had slightly higher proportions of low birth weight babies to normal birth weight conceptuses. No significant birth weight differences irrespective of mother’s age were observed (p > 0.05).
Abbildung in dieser Leseprobe nicht enthalten
Figure 40. Maternal antepartum complications (Author’s own illustration/work)
Women who had pregnancy related complications were more likely to have LBW babies than those who didn’t have any. Of mothers who delivered LBW babies; 12.8% had hypertension in pregnancy (PIH), 3.4% were draining, 51.4% had other complications and 31.8% didn’t have any adverse conditions. This is in comparison to women who delivered a baby with at least 2500g; 10.3% had PIH, 3.3% were draining, 36.5% had other complications and 49.7% had no any other conditions. Figures for twin gestations probably arose because of wrong clinical diagnosis before parturition.
Abbildung in dieser Leseprobe nicht enthalten
Figure 41. Apgar scores and weight of babies (Author’s own illustration/work)
Babies who had birth weights of 2 500g or more were more likely to have high Apgar scores than low birth weight babies (93.4% vs. 62.9%)
Abbildung in dieser Leseprobe nicht enthalten
Figure 42. Mode of delivery and weight of babies (Author’s own illustration/work)
The chi-square showed that mode of delivery and weight of a baby were not independent (p < 0.001). Compared to those babies delivered weighing at least 2 500g, low birth weight babies were slightly more likely to be delivered by Caesarean section (17.2% vs. 16.1%), marginally less likely to be spontaneously delivered vaginally (79.6% vs.82.9%) and significantly more likely to be a miscarriage.
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Figure 42. State of the placenta (Author’s own illustration/work)
For the normal birth weights; 99.6%, 0.1% & 0.3% of deliveries were accompanied by a complete, incomplete and ragged placenta respectively. As for the births of low weight babies; complete, incomplete and ragged placentae were seen in 98.3%, 0.6% & 1.1% respectively. So, delivery of a low birth weight baby was more likely to be associated with incomplete or ragged placenta (1.7% vs. 0.4%).
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Figure 43. Estimated blood loss during birth (Author’s own illustration/work)
Delivery of a low birth weight baby was accompanied by a very smaller chance of not having postpartum haemorrhage (91.4% vs. 90.0%). There was no significant difference in the amount of blood lost by mothers who gave birth to low birth weight babies and normal babies (p>0.05).
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Figure 44. Parity and weight of babies (Author’s own illustration/work)
Mothers who delivered low birth weight babies were proportionally more likely to be nulliparas and less likely to be multiparous compared to those who delivered normal weight babies. There was no difference among the grand-multiparas.
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Figure 45. Sex of child and weight (Author’s own illustration/work)
Proportionally, more female (51.2%) than male babies had low birth weight. Conversely male babies tended to be associated with birth weights of at least 2 500gthan females (51.7% vs. 48.3%).
Summary of Regression analysis
Regression analysis showed that gestational age, labour complications and Apgar score were the only variables with a significant association with the child’s weight. (All the other variables did not have a significant association with birth weight) The regression equation read off from the analysis is:
Child’s weight = 98.468 + 585.188 (gestational age) – 54.438 (Labour complications) + 604.017 (Apgar score). Nearly 43% of the variance in child’s weight is explained by gestational age, labour complications and Apgar score. The overall F=443.129 is highly significant, p<0.001, indicating that the three independent variables together provide a good association.
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9. DISCUSSION
Gestational age
The longer the gestational age the bigger the newborn baby. Such a trend is clearly outlined by the findings above. A huge number of babies weighing at least 2 500g were delivered after 37 completed gestation – 76.6%. As expected more of the LBW babies were delivered before 37 gestation – 71.2%.Using the analysis of variance, the F test was highly significant (F = 469.56; p < 0.0001) which showed that the means from the three gestational age groups were significantly different. The means show a trend with weight of child increasing from a mean of 1395g in children with a gestational age of less than 28 weeks, to 2094g in children with a gestational age of between 28 to 36 weeks and then to 2455g in children with ages of 37 weeks and above. Children with a gestation of 37 weeks and above, on average weighed 1484.56g more than children with less than 28 weeks, and 785.44g compared with children between 28 to 36 weeks. 1.5% of the normal birth weight deliveries were recorded as having estimated age of less than 28 weeks of gestation; this could be as a result of wrong calculation of dates in the absence of a dating scan.
Maternal prenatal psychosocial stress
The proportions of LBW were larger in 2008 compared to 2009, 10.0% versus 7.3% respectively, the difference did not reach statistical significance. According to Wadhwa PD and others, maternal prenatal stress factors are significantly associated with infant birth weight and with gestational age at birth, independent of biomedical risk.43Low birth weight and prematurity were significantly associated with objective major life events but not state anxiety. The occurrence of objective major life events in the third trimester may be important in precipitating preterm labour.47
Maternal age
Though, in our study there were proportionally more babies with low birthweight amongst teenage mothers and fewer of these amongst mothers in the age group 20 to 34 years, the differences were not statistically significant. There was also no major difference for mothers with advanced age, though women in that particular age range were more likely to deliver a LBW baby. In a study done in Tanzania, there was no significant association between LBW and maternal age of less than 20 years 44. According to Sawchuk LA, conception at a young age of less than 20 years leads to smaller babies, more so if it is premarital.46 In the US, the risk of LBW tends to increase more quickly with maternal age for black women than it does for white women.45 The interactions between maternal age and risk factors could reflect a ‘weathering’ effect of cumulative disadvantage as women age. The ‘weathering hypotheses was coined by Geronimus, who proposed that health ‘may begin to deteriorate in early adulthood as a physical consequence of cumulative socioeconomic disadvantage’. A similar view is promoted by the ‘life course approach’, which emphasizes the cumulative health impact of social, biological, and psychological processes from conception to death. Both the ‘life course approach’ and the ‘weathering hypotheses suggest that social inequalities cause premature ageing. According to these approaches, the accumulating burdens of poverty and discrimination compromise a woman’s health and chances of delivering a healthy infant, even before she conceives the pregnancy.45
Booking (ANC)
From the above analysis; unbooked women had proportionally more low birth weight babies. Booking was associated with a higher incidence of babies weighing at least 2 500g. From a study done in Nigeria, women who had antenatal care had heavier babies than unbooked mothers.48According to a cross-sectional analytical study done in Bangladesh, positive pregnancy outcome, such as birth-weight of baby, is directly related to antenatal care(ANC) visit of mother.49A Kenyan study done in 2007showed some mixed results50.
Bad obstetric history
For women who had previous delivery of a preterm baby the proportion of low birth weight babies was 1.9% compared to 1% for normal weight babies. Prior miscarriage was also associated with low birth weight in 6.1% of cases and birth weight of at least 2 500g in 4.6% of cases. A major risk factor for preterm labour is prior preterm delivery. According to Bloom and associates, the risk of recurrent preterm delivery for women whose first delivery was preterm was increased threefold compared with that of women whose neonate was born at term. Previous history of preterm delivery and miscarriages are known associated factors.55
Parity
Though the nulliparas women were more likely to deliver babies with low weight (46.9% vs. 44.0%) and women with between 1 and 4 previous deliveries were less likely to have low birth weight babies (51.3% vs. 54.2%), there was no statistical difference (P > 0.05). For the grand-multipara women the proportions (1.8%) were a dead heat. The effect of maternal age on different anthropometric and genetic markers has been a subject of great interest. Several studies relating the effect of mother’s age and parity on birth weight indicate that parity is the more important of the two.51
HIV Status and Treatment
Numerous studies from Sub-Saharan Africa have reported that HIV-infected pregnant mothers are at increased risk of delivering LBW infants, preterm delivery, and of intrauterine growth retardation.52Prevalence of LBW infants delivered by HIV and non HIV-infected pregnant mothers were 12.6% and 13.6% respectively in a study done in Thailand. There was no significant association between HIV infection and low birth weight. With the same study, LBW infants delivered from HIV- infected pregnant women with and without antiretroviral therapy were 9.9% and 13.6% respectively. Various types of antiretroviral (ARV) drugs including no ARV were significantly associated with LBW. The one who received highly active antiretroviral therapy (HAART) had 2.27 times higher risk of having LBW.53Published data, based on comprehensive population surveillance in the UK and including 4445 women receiving HAART, demonstrate a significantly increased risk of prematurity associated with HAART. This association, which remained after adjustment for HIV-related symptoms and CD4 cell count as a proxy for maternal health, is consistent with findings from other European cohorts. There was no detectable relationship between prematurity and duration of HAART exposure, although this may have been due to sample size. The association between HAART and other adverse pregnancy outcomes is unclear: an increased risk of fetal death and very low birthweight (1500 g) has been reported in some studies, but not in others.60An analysis from the above graphs will show that of those women who were negative for HIV, proportionally there were fewer low birth weights and more babies with weight of at least 2 500g as compared to those with unknown HIV status (40.6% vs. 43.7%) and (57.5% vs. 24.2%) respectively. Where the mother was HIV positive the baby was more likely to be of normal weight (18.3% vs. 15.7%). HIV positive mothers on HAART had a slightly increased risk of delivering low birth weight babies. Those on MER had higher chances of having a normal weight baby than LBW baby (9.o% vs. 2.6%). There wasn’t much proportional difference of birth weights for those on NVP. Mothers who were HIV positive but not on any form of anti-retroviral treatment had higher incidences of LBW than normal birth weight (21.5% vs. 16.4%).
Pregnancy Related (Antepartum) Complications
A prevailing hypothesis regarding the pathogenesis of preeclampsia is the ‘ischemic model.’ decreased uteroplacental perfusion is hypothesized to be the primary step and the point of convergence of diverse pathogenic processes in the development of preeclampsia. It is intuitive that reduced placental blood flow should result in decreased fetal growth, with an increased risk of intrauterine growth restriction and low birth weight. However epidemiological studies have not conclusively established an association between preeclampsia or gestational hypertension and poor fetal growth.54Preterm pre-labour ruptures of membranes (PPROM) complicate up to 2% of all pregnancies and are the cause of 40% of all preterm births.56 Women who had pregnancy related complications were more likely to have LBW babies than those who didn’t have any. Of mothers who delivered LBW babies; 12.8% had hypertension in pregnancy (PIH), 3.4% were draining, 51.4% had other complications and 31.8% didn’t have any adverse conditions. This is in comparison to women who delivered a baby with at least 2500g; 10.3% had PIH, 3.3% were draining, 36.5% had other complications and 49.7% had no any other conditions. This illustrates that LBW is accompanied by more complications of pregnancy.
Blood Loss
LBW delivery was slightly less likely, and insignificantly, to be accompanied by post-partum hemorrhage (8.6% vs. 10% incidence). There was no any study in literature that pertained to any relationship between postpartum blood loss and birth weight. It is known that birth weight of at least 4 000g is a risk for postpartum hemorrhage. Maternal anaemia often leads to both low birth weights and postpartum hemorrhage.
Mode of Delivery
Optimal route of delivery of preterm vertex neonates has been a controversial topic in the obstetric and neonatal community for decades, and continues to be debated. The value of Caesarean section in preterm labour is less clear. This has not been subjected to robust randomized controlled trial. In one study, overall Caesarean delivery rate for premature newborns was 32.2%. Only those weighing between 1000 – 1499g had a survival advantage associated with Caesarean section.57From the data we collected, though there were more LBW babies being delivered by Caesarean section than normal weight ones (17.2% vs. 16.1%) and less by spontaneous vaginal delivery (79.6% vs. 82.9%), there was no statistical difference (p > 0.05). Almost the same proportion of LBW and normal weight babies were delivered by assisted/operative vaginal delivery. A surprising incidence of 0.5% of deliveries of birth weights of at least 2 5000g recorded as miscarriage could be a result of wrong entries. 2.8% of LBW births were categorised as miscarriages because the estimated gestational age was less than 28 weeks.
Perineal Trauma
The only association between birth weight and risk of perineal trauma mentioned in literature was big babies. A retrospective study done in Austria showed that high birth weight had odds ratio (OR) 1.68 (1.18-2.41) of anal sphincter damage.58Our study showed no significant increased risk of obstetric anal sphincter injury. LBW delivery was less associated with any form of perineal tears. 1st and 2nd degree tears were more likely to be accompanied with birth weight of at least 2 500g than LBW (49.0% vs. 30.2%).
Gender
More female babies weighed less than 2 500g at birth than their male counterparts by proportion (51.2% vs. 48.8%). Conversely, for birth weights of at least 2 500g, male babies were more (51.7% vs. 48.3%). These differences were not significant (p > 0.05).
Demography
There were no significant birth weight differences between women from the rural areas and those from the high density suburbs. The relative importance of individual and area factors and their association with health has been a matter of debate for many decades, both generally and in the context of the outcome of pregnancy. In particular, there is growing interest in the US in the association between mothers' areas of residence and their babies' birth weights. Potential explanations for a relationship between areas and birth weights can be broadly categorised as either arising from stressors such as crime, racism and pollution, or the resources, such as social support or access to healthcare, available to residents in an area. These area effects have often been operationalised by a general measure of area deprivation.59
Neonatal Outcomes
As compared to babies weighing at least 2 500g, LBW babies had higher incidence of low Apgar scores (37.1% vs. 6.6%). They also had, proportionally, lower rates of scoring high Apgar scores (62.9% vs. 93.4%). The Pearson Chi-square was highly significant p< 0.0001, which suggests that weight of the child and Apgar scores supply, are not independent. Comparison of the observed and expected numbers shows that there were statistically significant more children with normal birth weights and high Apgar scores compared to more children with low birth weights and low Apgar scores.
State of Placenta
For the normal birth weights; 99.6%, 0.1% & 0.3% of deliveries were accompanied by a complete, incomplete and ragged placenta respectively. As for the births of low weight babies; complete, incomplete and ragged placentae were seen in 98.3%, 0.6% & 1.1% respectively. Hence, delivery of a low birth weight baby was more likely to be associated with incomplete or ragged placenta (1.7% vs. 0.4%).
10. CONCLUSION
This analysis demonstrates that preterm birth is a significant perinatal health problem associated with both maternal and fetal morbidity hence financial implications for health-care systems. Unfortunately, there are currently no effective diagnostic measures for preterm labour resulting in preterm birth, and no effective early interventions for prevention. Progress in medical care has contributed to improved survival among all but the most immature infants. The use of modern technology allows survival of many preterm neonates in developed countries, but such care is not widely available in developing countries. As this situation changes and countries develop and apply technologies that raise survival rates, the morbidity burden will increase. Thus, the development of strategies for improving access to effective care in developing countries must remain a top research and operational priority. Developing such strategies will depend on a better understanding of the etiology, risk factors neonatal outcomes of preterm birth and improved estimates of the incidence of preterm birth at the country level. Our analysis is a step forward in this direction. In conclusion, the well-known predictors of LBW and outcomes (hypertension, spontaneous delivery, HIV status and treatment mode, social class, primiparity, maternal age, Apgar scores, etc.) behave in the same manner in our population. We believe that more research is needed on effect of birthweight on peripartum blood loss and state of delivered placenta. Thus findings of this study emphasize the need for improving the quality and utilization of antenatal care, and prevention and proper management of risk factors like draining and hypertension.
ACKNOWLEDGEMENTS
My utmost gratitude to my supervisor and Head of Department, Mr S. Ngwenya for providing guidance from the time of choosing the topic up to the last word of the research. His approval of this particular work is highly appreciable. The mentorship and brotherly roles were second to none.
I also appreciate the input of Mr F. Chiwora; his many years of experience were indispensable. The statistical analysis by Dr P. Makoni was highly commendable; the task was daunting considering the data cleaning that was also needed.
The research wouldn’t have proceeded without the laborious work of looking for the delivery registers by the Mpilo Records staff, many thanks.
Probably the greatest honour is to every African woman who, if not labouring in the agricultural fields or her household, is in labour in a poorly equipped health facility. More so, her endurance was tested during our socio-economic and political crisis, and continues to be challenged to this day.
LITERATURE CITED
1. Villar J. &Belizan J. (1982). The relative contribution of prematurity and fetal growth retardation to LBW in developing and developed societies. American Journal of Obstetrics and Gynaecology 143, 793.
2. Podja J. and Kelly L. (2000) Administrative Committee on Coordination/ Sub-Committee on Nutrition. The UN Systems Forum for Nutrition. Nutrition Paper Policy # 8.
3. Klinberg C ; Oloni R; Oneko M; Sam N and Langeland N (2003) Neonatal morbidity and mortality in a Tanzanian tertiary care referral hospital. Annals Paediatrics 23, 293-299
4. Bang A.T., Bang R.A, Baitule S.B., Reddy M.H and Deshmukh M.D. (1999) Effect of home based neonatal care and management of sepsis on neonatal growth & mortality: field trial in India. Lancet 354, 1955-1961.
5. UNAIDS (1999) AIDS epidemic update. Geneva: UN Administrative Committee on Coordination/ Sub-Committee on Nutrition (2000). Nutrition Policy Paper # 18.
6. Dreyfuss M.L., Msamanga G.I., Spiegelman D., Hunter D.J., Urassa E.J.N., Hertzmark E. &Fanzi W.W. (2000) Determinants of LBW amongHIV infected pregnant women in Tanzania. American Journal of Clinical Nutrition 74, 814-826.
7. Tema T. (2006) Prevalence & determinants of LBW in Jima Zone, Southwest Ethiopia. East African Medical Journal 83, 366-371.
8. Colorado Department of Public Health 2000; weighing in on solution to the LBW in Colorado.
9. Kramer M.S., McLean F.H., Cason E.L and Usher R.H. (1982). Maternal nutrition and spontaneous preterm birth. American Journal of Epidemiology 136, 574-583.
10. UNICEF: LBW, Country, Regional and Global Estimates. http//www.unicef.org/publications. Accessed 21/08/12
11. de Onis M., Blossner M., Villar J. : Levels and patterns of IUGR in developing countries. European Journal of Clinical Nutrition (1998), 52 (Suppl 1): S5-15. PubMed Abstract.
12. UNDP: Infants with low birthweight. Accessed 20/08/12
13. Arias F &Tomich P (1982). Etiology and outcome of low birthweight and preterm infants. Obstet. Gynecol 60: 277-281.
14. Michielutte R, Ernest JM, Moore ML, Meis PJ, Sharp PC, Wells HB, and Buescher PA (1992). A comparison of risk assessment models for term and preterm low birthweight. Prev. Med. 21. 98-109
15. Kind K.L., Moore V.M. and Davies M.J. (2006) Diet around conception and during pregnancy – effects on fetal and neonatal outcomes. Reproductive Biomedical Online, 532-541.
16. Renquist R., Karjati S. and Kusis J.A (1994) Maternal Body Mass Index: the functional significancy during reproduction. European Journal of Clinical Nutrition 48; suppl 3556-3567.
17. Verma V. and Das K.B. (2000) Teenage primigravidae: a comparative study. Available at www.harvard.eu
18. Kinabo J. (1993) Seasonal variation of birthweight distribution in Morogoro Tanzania. East African Medical Journal 70, 752-755.
19. Anum EA, Springel EH, Shriver MD & Strauss JF (2010) Genetic Contributions to Disparities in Preterm Birth. BMC Public Health.Accessed 12/03/12.
20. Ward C, Sarah L, Coleman T (2005) Prevalence of Maternal Smoking & Environmental Tobacco Smoke Exposure During pregnancy & Impact on Birth Weight: Retrospective Study Using Millennium Cohort. BMC Public Health 2007, 7: 81
21. FASTER Trial, Dolan et al (2007) The Contribution of Birth defects to Preterm and Low Birth Weight. Obstetrics & Gynaecology, 110; 318-324
22. Conde-Agudelo A, Rosas-Bermudez A (2006) Birth spacing and risk of adverse perinatal outcomes. The Journal of the American Medical Association 295(15): 1809-1823.
23. Casanueva E &Viteri FE (2005) Effects of prenatal multimicronutrient supplements on birth weight and perinatal mortality: a randomized, controlled trial in Guinea-Bissau. European Journal of Clinical Nutrition 59, 1081-1089.
24. Copper RL, et al. The preterm prediction study: maternal stress is associated with spontaneous preterm at less than 35 weeks’ gestation. National Institute of Child Health and Human Development Maternal-Fetal Medicine Units Network, 1996. PubMed Abstract. Accessed 24/08/2012
25. Goldenberg RL, Culhane JF: low birth weight in the United States. American Journal of Clinical Nutrition 2007, 85: 584-590, 2007
26. Vega J, Saez G, et al: Risk factors for low birth weight and IUGR in Santiago, Chile. Rev Med Chile 121: 1210-9, 1993
27. Battaglia FC, Lubchenco LO: A practical classification of newborn infants by weight and gestational age. Journal of Pediatrics 71: 159, 1967
28. Kingdom JCP, McQueen J, Connell JMC, et al: Fetal endothelin levels and placental vascular endothelin receptors in IUGR. Obstet Gynecol 82:992, 1993
29. Simpson JW, Lawless RW, Mitchell AC: Responsibility of the obstetrician to the fetus, 2. Influence of prepregnancy weight and pregnancy weight gain on birth weight. Obstet Gynecol 45:481, 1975
30. Rode L, Hergaard HK, et al: Association between maternal weight gain and birth weight. Obstet Gynecol 112: 300, 2008
31. Wilcox MA, et al: The effect of social deprivation on birthweight, excluding physiological and pathological effects. British Journal of Obstet Gynecol 102:918, 1995
32. Fisher SJ, McMaster M, Roberts JM: The placenta in normal pregnancy and preeclampsia. Chesley’s hypertension in pregnancy, 3rd ed. Elsevier, New York, 2009, p73
33. Grote NK, Bridge JA, et al: A meta-analysis of depression during pregnancy and the risk of preterm birth, LBW, and IUGR. Arch Gen Psychiatry 67: 1012-1024, 2010
34. Central Statistics Office, Zimbabwe (2002)
35. Zimbabwe Demographic and Health Survey, 2010-2011; Zimbabwe national Statistics Agency; March 2012
36. Salafia CM, Minior VK, et al: IUGR in infants of less than thirty-two week’s gestation: associated placental pathological features.
37. Zhou W, Sorensen HT, and Olsen J: Induced abortion and LBW in the following pregnancy. International Journal of Epidemiology 29: 100-106, 1999
38. Mavalankar DV, Gray RH, Trivedi CR: Risk Factors for Preterm & Term LBW in Ahmedabad, India. International Journal of Epidemiology 21: 263-272, 1991
39. Khan N, Jamal M: Maternal risk factors associated with LBW. J Coll Physicians Surg Pak 13: 25-28, 2003
40. Feresu SA, Harlow SD, Woelk GB: Risk factors for prematurity at Harare Maternity Hospital, Zimbabwe. International Journal of Epidemiology 2004; 33: 1194-1201
41. Low Birthweight; Country, Regional and Global Estimates. WHO, 2004
42. WHO Technical Consultation, ‘Towards the development of a strategy for promoting optimal fetal growth’, Report of a meeting (draft), World Health Organization, Geneva, 2004.
43. Wadhwa PD, Sandman CA, Porto M, Dunkel-Schetter C, Garite TJ: The association between prenatal stress and infant birth weight and gestational age at birth: a prospective investigation.. American Journal of Obstetrics and Gynaecology 1993, 169(4): 858-865
44. Adamson H. Low birth weights in relation to maternal age and multiple pregnancies at Muhimbili National Hospital; DMSJ VOL. 14 no.3.doc
45. Rich-Edwards JW, Buka SL, et al: diverging associations of maternal age with low birth weight for black and white mothers. Int. J. Epidemiology (2003), 32(1): 83-90
46. Sawchuk LA, Burke SD, Benady S: Assessing the impact of adolescent pregnancy and the premarital conception stress complex on birth weight among young mothers in Gibraltar’s civilian community. J. Adolescent Health. 1997; 21(4): 259-66
47. Newton R, Hunt LP: Psychosocial stress in pregnancy and its relation to low birth weight: BMJ 1984, 288: 1181 – 94
48. Chuku SN: Low Birth Weight in Nigeria: Does Antenatal Care Matter. Presented at The Hague, The Netherlands. Nov. 2004
49. Gomes NC, Hassan MA, Mondal NT: Relationship between Antenatal-care Visit of Mothers and Birth weight of Baby in a rural NGO Hospital. ICDDR, B Publications. Accessed 24/09/2012
50. Brown CA, et al: Antenatal care and perinatal outcomes in Kwale district, Kenya. BMC Pregnancy and Childbirth.2008, 8(2):1471
51. Vaktkjold A, et al: Parity and Birth weight in the KhanhHoa Province, Vietnam. The Open Women’s Journal, 2010, 4: 1-4
52. Brocklehurst P, French R. the association between maternal HIV infection and perinatal outcome: a systemic review of the literature and meta-analysis. Br J Obstet Gynaecol, 1998; 105:836-48
53. Asavapiriyanont S, Kasiwat S. prevalence of LBW in HIV-infected women delivered in Rajavithi Hospital. J Med Assoc Thai. 2011;94(2):S66-70
54. Misra DP. The effect of the pregnancy-induced hypertension on fetal growth: a review of the literature. Paediatric Perinat Epidemiol 1996;10: 202-3
55. Tufail A, HashmiAH, Naheed F. risk factors for preterm labour in a rural cohort 2009; 15(2):55-7
56. Morris JM, et al. protocol for the immediate delivery versus expectant care of a woman with preterm prelabour rapture of membranes close to term (PROMMY) trial. BMC Pregnancy & Childbirth 2006;6:9
57. Fehmi A, Lallo DD, et al. Mode of delivery and mortality among preterm newborns. Ginekologia Polska, 2010 vol. 81 (3): 203-207.
58. Hudelist G, Gellen J, et al. Factors predicting severe perineal trauma during child birth: Role of forceps routinely combined with mediolateral episiotomy. American J. Obstet Gynecol 2005, 192(3):875-881.
59. Dibben C, Sigala M & Macfarlane: Area deprivation, individual factors and low birth weight in England: is there evidence of an “area effect”? J Epidemiol Community Health. 2006 December; 60(12): 1053–1059.
60. RCOG Guideline. Recent Developments in HIV and Women’s Health. 2008
APPENDIX
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[...]
- Citar trabajo
- Elton Sengurayi (Autor), 2013, Low birth weight babies. Risk factors and perinatal outcomes in Zimbabwe, Múnich, GRIN Verlag, https://www.grin.com/document/539233
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¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X. -
¡Carge sus propios textos! Gane dinero y un iPhone X.