Reduction in neonatal mortality has been slower than anticipated in many low income countries including Tanzania. Adequate neonatal care may contribute to reduced mortality. We studied factors associated with transfer of babies to a neonatal care unit (NCU) in data from a birth registry at Kilimanjaro Christian Medical Centre (KCMC) in Tanzania.
Methods
A total of 21 206 singleton live births registered from 2000 to 2008 were included. Multivariable analysis was carried out to study neonatal transfer to NCU by socio-demographic factors, pregnancy complications and measures of the condition of the newborn.
Results
A total of 3190 (15%) newborn singletons were transferred to the NCU. As expected, neonatal transfer was strongly associated with specific conditions of the baby including birth weight above 4000 g (relative risk (RR) = 7.2; 95% confidence interval (CI) 6.5-8.0) or below 1500 g (RR = 3.0; 95% CI: 2.3-4.0), five minutes Apgar score less than 7 (RR = 4.0; 95% CI: 3.4-4.6), and preterm birth before 34 weeks of gestation (RR = 1.8; 95% CI: 1.5-2.1). However, pregnancy- and delivery-related conditions like premature rupture of membrane (RR = 2.3; 95% CI: 1.9-2.7), preeclampsia (RR = 1.3; 95% CI: 1.1-1.5), other vaginal delivery (RR = 2.2; 95% CI: 1.7-2.9) and caesarean section (RR = 1.9; 95% CI: 1.8-2.1) were also significantly associated with transfer. Birth to a first born child was associated with increased likelihood of transfer (relative risk (RR) 1.4; 95% CI: 1.2-1.5), while the likelihood was reduced (RR = 0.5; 95% CI: 0.3-0.9) when the father had no education.
Conclusions
In addition to strong associations between neonatal transfer and classical neonatal risk factors for morbidity and mortality, some pregnancy-related and demographic factors were predictors of neonatal transfer. Overall, transfer was more likely for babies with signs of poor health status or a complicated pregnancy. Except for a possibly reduced use of transfer for babies of non-educated fathers and a high transfer rate for first born babies, there were no signs that transfer was based on non-medical indications.
The online version of this article (doi:10.1186/1471-2393-11-68) contains supplementary material, which is available to authorized users.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
BTM: Study design, methodology, data analysis and manuscript writing. RTL, GSK, RO, GK, AKD: Study design, methodology, manuscript writing. All authors approved the final manuscript.
Background
Progress on United Nations' Millennium Development Goal 4 (MDG4) to reduce the under-five mortality has been slower than anticipated due to high neonatal mortality in developing countries. Worldwide, about 4 million neonatal deaths occur each year, of these three quarter occur in the first week of life with the highest risk at the first day of life [1]. Estimated neonatal mortality in Tanzania is about 35 per 1000 live births, and neonatal deaths are estimated to account for 28% of the under-five mortality [2]. Both the infant mortality rate and the under -five mortality rate have decreased from 1990 to 2004; by 31% (from 99 to 68 deaths per 1000 live births) and 24% (from 147 to 112 deaths per 1000 live births), respectively. This decline was, however, observed for post-neonatal mortality only, while neonatal as well as maternal mortality remained unchanged [2, 3]. Adequate neonatal care may therefore be an important factor for continued improvement. Socio-economic deprivations are known to cause poor perinatal outcome such as neonatal care admission [4‐7], low birth weight [8‐10] and increased perinatal mortality [10‐13]. A review of international evidence in socio-economic inequalities in childhood mortality in low and middle income countries showed higher childhood mortality in low socio-economic groups within each country [14]. Absolute inequalities were found to be higher for infant mortality than for child mortality. It was also estimated that 20-25% of under-five mortality inequalities arise in the neonatal period [14]. Making sure that health care is provided independent of social status is important for overall improvement in health.
Most studies on neonatal health in developing countries have focused on mortality rather than morbidity. However, in order to reduce neonatal mortality it is also of importance to consider factors associated with neonatal morbidity. Transfer of babies to neonatal care unit (NCU) may represent an indicator of morbidity that can be used for designing and implementing interventions aimed at improving health and increasing neonatal survival. Although previous studies have reported on the relationship of socio-demographic, maternal, or neonatal factors with neonatal admission [5, 6, 15], the combined effect of socio-demographic, maternal health factors and neonatal factors in relation to admission to NCU has not been well explored.
Anzeige
Referral in pregnancy and child birth can be categorised as self-referral or referral performed by health workers [16]. Self-referral implies that a woman (perhaps with the help of her family) seeks care at a health centre or a hospital. A study of 415 maternity admissions in Tanzania found that about 70% of the admissions could be categorized as self-referrals [16].
The presence of a NCU at the hospital gives an opportunity for all at risk babies to be admitted and managed by a paediatrician. The paediatric department at KCMC has established guidelines for care and management of newborns based on the condition of the newborn. Decision for transfer is usually done by midwives or a paediatrician based on the condition of the newborn; low Apgar score, prematurity, birth weight <1800 or birth weight >4000 g, congenital malformation and suspected infection. In addition, some obstetric conditions may necessitate baby transfer because they could represent a risk to the newborn. When a pregnancy complication indicates that the baby needs to be seen by a paediatrician, the paediatrician is informed in advance and attends the delivery to take care of the newborn in the labour ward or in NCU if transfer is necessary. The parents are usually informed about the reason for babies transfer but they are not asked for decision. Although KCMC is a private hospital, payment for the hospital bill is not considered as initial criteria for transfer or management of admitted newborns, therefore, all admitted babies receive same quality of care irrespective of the social background. The social welfare department within the hospital usually takes care of the hospital bills for families unable to pay.
The aim of our analysis was to estimate the influence of social background, pregnancy-related conditions and the condition of the newborn in relation to neonatal transfer to NCU. We explore these associations in a structured series of analyses, expecting most of the associations to be explained by the condition of the newborn. First, we expect social conditions to impact the likelihood of transfer by their effects on pregnancy complications and the condition of the newborn. Then we expect pregnancy complications to impact the likelihood of transfer by their effects on the condition of the newborn. Deviations from these expectations will appear as residual effects of social background and pregnancy complications after we adjust for the condition of the newborn. Such deviations will be inspected further since they could represent priority-settings or clinical judgment that incorporates social background or the background history of the delivery.
Methods
Setting
This study was done at Kilimanjaro Christian Medical Centre (KCMC) in Northern Tanzania. The hospital is a zonal hospital serving more than 13 million people from 4 regions namely; Kilimanjaro, Arusha, Tanga and Manyara. We established a cohort of babies based on records from the Medical Birth Registry comprising all deliveries at the hospital from July 2000 to September 2008 and followed the cohort in a registry of neonates transferred from the labour ward to NCU. The KCMC Medical Birth Registry system was established in 1999 as a collaboration between Kilimanjaro Christian Medical College, Tumaini University and the University of Bergen, Norway. The annual number of deliveries is around 3000 of which nearly two thirds are from urban area. Approximately 10-15% of the neonates are transferred to NCU for observation and management.
Anzeige
A total of 26 025 births were recorded in the Medical Birth Registry from July 1st 2000 to September 30th 2008. We excluded multiple deliveries, stillbirths, neonatal deaths in labour ward and neonates with missing child status record after delivery (Figure 1). In order to obtain a study group that reflected the general population, we excluded deliveries where mothers residing in rural areas had been referred for delivery at KCMC for medical reasons. Women residing in Moshi urban were not excluded since they could have delivered at KCMC anyway. KCMC is located in Moshi Urban and that 50% of the deliveries at KCMC are from Moshi Urban district [11]. We finally analyzed a total of 21 206 singleton live births.
×
Data collection
Information from all mothers who delivered at KCMC were collected within the first 24 hours after delivery. Trained midwife nurses conducted the interviews on a daily basis with all eligible subjects using a standardized questionnaire. A verbal consent was obtained from the participants prior to the interview. Mothers also provided their antenatal visit card for more information such as date of first ANC visit, immunization history, malaria prophylaxis, drugs, illnesses recorded during follow up, weight at first ANC visit, number of ANC visits, as well as referral to ANC (self-referred or referred by health worker).
Information in the birth registry includes maternal health conditions before and during pregnancy, parents' socio-demographic characteristics, complications during labour and delivery, and information on the newborn; sex, gestational age, birth weight, Apgar score, and child status in four categories: 1) live born 2) live born transferred to NCU 3) neonatal death in labour ward, 4) stillborn.
The paediatric registry form was recorded in the NCU for all neonates who were transferred. The neonatal registry includes information on primary reasons for transfer, management, and discharge/death diagnoses. The two databases were linked using the unique child identification number, the mother's hospital registration, and the newborn's birth registration number.
Variable definition
Transfer to NCU was the main outcome. Independent variables include socio-demographic characteristics including maternal, paternal and environmental factors, maternal health conditions before and during pregnancy, and complications during labour and delivery, as well as condition of the newborn (Tables 1, 2 and 3).
Table 1
Transfer to neonatal care unit (n = 3190) among 21 206 live-born according to socio-demographic factors
Risk factors
Number
live-born
deliveries
Proportion (%)
live-born babies
transferred to NCU
RR (95% CI)
p-value
Maternal factorsx
Maternal age (years)
0.106
Under 18
480
17.9
1.2 (1.0-1.5)
18-25
8328
14.5
1.0
26-35
10 272
15.3
1.0 (1.0-1.1)
Over 35
2070
15.7
1.0 (1.0-1.2)
Mother's tribe
0.032
Chagga
12 311
14.5
1.0
Pare
2496
16.2
1.0 (1.0-1.2)
Others
6355
15.6
1.0 (1.0-1.2)
Marital status
<0.0001
Married
19 016
14.6
1.0
Single
2086
18.6
1.3 (1.2-1.4)
Birth order
<0.0001
1st Child
8220
16.4
1.2 (1.1-1.3)
2nd Child
5985
13.4
1.0
3rd Child
3287
16.5
1.0 (0.9-1.1)
4th or more
3714
13.5
1.2 (1.1-1.4)
Mother's education
0.060
No education
348
17.8
1.2(1.0-1.7)
Primary
12 990
15.3
1.0(1.0-1.1)
Sec/higher
7819
14.4
1.0
Mother's occupation
<0.0001
Professional
3355
14.3
1.0
Business
4821
14.8
1.0 (0.9-1.2)
Service
1538
15.4
1.1 (0.9-1.2)
Farmer
4003
16.3
1.1 (1.0-1.3)
Housewife
5401
15.4
1.1 (1.0-1.2)
Others
1955
13.3
1.0 (0.8-1.1)
Body height (cm)
<0.0001
<150
1505
18.3
1.4 (1.2-1.5)
150+
18 342
14.1
1.0
BMI (kg/m2)
0.013
<18.5
1277
14.1
1.1 (0.9-1.2)
18.5-24.9
4787
14.8
1.0
25-29.9
6793
13.3
1.1 (1.0-1.2)
30+
1496
16.2
1.2 (1.1-1.4)
Genital mutilation
0.086
Yes
4752
15.8
1.0 (0.9-1.0)
No
16 389
14.8
1.0
Drinking in pregnancy
0.033
Yes
8278
14.4
1.0
No
12 882
15.4
1.1 (1.0-1.2)
Paternal factorsx
Father's age (years)
0.003
Under 26
3002
16.7
1.1 (1.1-1.3)
26-35
11 794
14.6
1.0
36-45
5428
14.5
1.0 (0.9-1.1)
Over 45
827
17.7
1.2 (1.0-1.4)
Father's tribe
0.004
Chagga
11 157
14.2
1.0
Pare
2463
16.0
1.1(1.0-1.3)
Others
7451
15.8
1.1(1.0-1.2)
Father's Occupation
<0.0001
Professional
4483
14.0
1.0
Business
6798
14.8
1.1 (1.0-1.2)
Service
4321
15.0
1.1 (1.0-1.2)
Farmer
2070
18.7
1.3 (1.2-1.5)
Skilled
2808
14.1
1.0 (0.9-1.1)
Others
643
15.9
1.1 (0.9-1.4)
Father's education
0.013
No education
110
20.9
1.5 (1.0-2.1)
Primary
10 563
15.5
1.1 (1.0-1.2)
Sec/higher
10 446
14.4
1.0
Environmental factorsx
Type of toilet
0.006
Pit latrine
12 515
15.6
1.1 (1.0-1.2)
Flush
8608
14.2
1.0
Source of water
0.030
Tap water
19 555
14.9
1.0
Well
459
16.6
1.1 (0.9-1.4)
River
432
19.7
1.3 (1.1-1.6)
Spring
644
16.0
1.1 (0.9-1.3)
Boil drinking water
<0.0001
Yes
6672
13.3
No
14 449
15.8
1.2 (1.1-1.3)
x-The total in some variables does not sum to 21 206 due to missing data
Table 2
Transfer to neonatal care unit (n = 3190) among 21 206 live-born according to maternal health conditions
Risk factors
Number
live-born
deliveries
Proportion (%)
live-born babies
transferred to NCU
RR (95% CI)
p-value
Before pregnancya
Medication regular
493
18.9
1.3 (1.1-1.5)
0.013
Diabetes
49
69.4
4.7 (3.9-5.6)
<0.0001
Hypertension
143
21.7
1.5 (1.1-2.0)
0.021
Epilepsy
64
25.0
1.7 (1.1-2.6)
0.026
Gyn. Disease
1122
17.5
1.2 (1.0-1.4)
0.020
Lung disease
1950
16.6
1.1 (1.0-1.2)
0.040
Malaria
12 258
14.9
1.0 (0.9-1.1)
0.899
Anaemia
406
17.0
1.2 (0.9-1.5)
0.267
Tuberculosis
77
18.2
1.3 (0.7-2.2)
0.703
During pregnancya
No ANC attendance
137
34.3
2.3 (1.8-2.9)
<0.0001
Referred to ANC§
2284
21.0
1.5 (1.4-1.6)
<0.0001
ANC < 5 visits
13 168
16.2
1.3 (1.2-1.4)
<0.0001
Anaemia
449
18.3
1.2 (1.0-1.5)
0.050
Gestational Diabetic
17
47.1
3.1 (1.9-5.2)
<0.0001
Hypertension
72
30.6
2.0 (1.4-2.9)
<0.0001
Preeclampsia
711
32.1
2.2 (2.0-2.5)
<0.0001
Eclampsia
27
70.4
4.7 (3.7-6.0)
<0.0001
Bleeding
239
23
1.5 (1.2-2.0)
<0.0001
Malaria
4314
14.4
1.0 (0.9-1.0)
0.167
Tuberculosis
414
15.0
1.0 (0.8-1.3)
0.969
HIV infection
784
16.1
1.0 (0.8-1.1)
0.528
Complicationsa
Abruptio placenta
29
65.5
4.4 (3.4-5.7)
<0.0001
PROM
468
54.7
3.9 (3.5-4.2)
<0.0001
Bleeding >500 mls
36
33.3
2.2 (1.4-3.5)
0.001
Placenta previa
51
45.1
3.0 (2.2-4.1)
<0.0001
Caesarean section
6472
24.2
2.3 (2.2-2.5)
<0.0001
Other Vaginal delivery
317
33.4
3.2 (2.7-3.8)
<0.0001
Other unspecified
373
24.7
1.7 (1.4-2.0)
<0.0001
a- Numbers for reference categories not given, each variable had complete data
§- First ANC visit triggered by health workers
Table 3
Transfer to neonatal care unit (n = 3190) among 21 206 live-born according to newborn health conditions
Risk factorsx
Number
live-born
deliveries
Proportion (%)
live-born babies
transferred to NCU
RR (95% CI)
p-value
Birth weight (g)
<0.0001
500-1499
173
95.4
9.8 (9.3-10.4)
1500-2499
1652
41.5
4.3 (4.0-4.6)
2500-3999
18 607
9.7
4000-6000
714
69.7
7.2 (6.7-7.7)
Apgar score 5 min
<0.0001
<7
442
91.9
6.9 (6.6-7.2)
7+
20 590
13.4
Gestation age (weeks)
<0.0001
25-33
447
70.5
5.6 (5.2-6.1)
34-36
1401
27.3
2.2 (2.0-2.4)
37+
17 603
12.5
1.0
Presentation
<0.0001
Cephalic
20 862
14.8
1.0
Breech
238
28.2
1.9 (1.6-2.3)
Transverse
28
21.4
1.5 (0.7-3.0)
Sex
<0.0001
Male
10 904
16.6
1.2 (1.2-1.3)
Female
10 162
13.3
1.0
x-The total in some variables does not sum to 21 206 due to missing data
Data analysis
Data were analyzed using Statistical Package for Social Science (SPSS) program Version 15.0 for Windows (SPSS 15.0 Chicago Inc. III, USA). Cross tabulations and generalized linear models were used to obtain relative risks (RR) and corresponding 95% confidence intervals. From the bivariate analyses we present all variables with p-value less than 0.1, which were then entered into the multivariable analysis. Three steps were involved in the multivariable analysis. In the first step (model A) all socio-demographic factors and maternal health condition before pregnancy were included. In the second step (model B) we included all variables in step one as well as pregnancy and labour-related conditions. In the third and final step (model C), we included all variables in step two as well as neonatal conditions. We used Poisson regression with robust variances to obtain a valid confidence interval when a log-binomial analysis failed to converge [17]. A priori we also considered some maternal conditions to be important and included in the final analysis, these were hypertensive conditions (preeclampsia, eclampsia and abruption placenta) and diabetes (pre-gestational or gestational).
Ethical approval
The birth registry at Kilimanjaro Christian Medical Centre obtained ethical clearance from the Tanzania Ministry of Health, Institute of Science and Technology, from the Norwegian National ethics committee and from the Kilimanjaro Christian Medical College (KCM-College) research ethics committee in 1999. The protocol for this study was approved by KCM-College research ethics committee, with certificate no. 333 of 15th July 2010.
Results
A total of 21 206 live-born singletons were analysed. The majority of the mothers were married (89.7%), were residing in urban areas (61.9%), had primary school education (61.3%), and belonged to the Chagga tribe (58.2%). Mean maternal age at child birth was 27.4 (SD = 6.1) years, and 38.8% of the mothers had their first born child. Mean maternal pre-pregnancy weight and height were 62.7 (SD = 12.5) kilograms and 160.0 (SD = 6.7) centimetres, respectively. The mean number of antenatal care visits per women was 5 (SD = 2.1). Mean gestational age and birth weight were 39.1 (SD = 2.5) weeks and 3090 (SD = 544 grams), respectively.
Anzeige
A total of 3190 (15%) were transferred to NCU. Descriptive associations between transfer and socio-demographic, pregnancy-related and neonatal factors are shown in Tables 1, 2 and 3.
Socio-demographic characteristics and pre pregnancy conditions
After mutual adjustment of the socio-demographic and maternal pre-pregnancy health factors, most of the factors remained associated with neonatal transfer (Table 4; model A). First born babies and fourth or later born babies (RR 1.3; 95% CI: 1.2-1.4 and 1.2; 95% CI: 1.0-1.3, respectively) were shown to have a high risk of being transferred compared with second born babies. Babies of single mothers were more likely to be transferred compared to babies of married mothers (RR 1.3; 95% CI: 1.1-1.5). Both maternal overweight and obesity increased the risk of babies transfer. Babies born from families who do not boil water for drinking had increased risk of being transferred to NCU (RR 1.2; 95% CI: 1.1-1.3).
Table 4
Linear regression model risk factors for neonatal transfer to neonatal care unit
Model Aa
Model Ba
Model Ca
Risk factors
RR (95%CI)
RR (95%CI)
RR (95%CI)
Pre-pregnancy factors
Maternal age (Ref. 18-25 years)
Under 18 years
1.0 (0.8-1.4)
1.0 (0.8-1.4)
0.9 (0.7-1.2)
26-35 years
1.3 (1.1-1.4)**
1.2 (1.1-1.3)**
1.2 (1.1-1.3)**
Over 35 years
1.1 (0.9-1.3)
1.0 (0.8-1.3)
1.0 (0.8-1.2)
Birth order (Ref. 2nd child)
1st child
1.3 (1.2-1.4)**
1.3 (1.2-1.5)**
1.4 (1.2-1.5)**
3rd child
1.0 (0.8-1.1)
1.0 (0.9-1.1)
1.0 (0.9-1.1)
4th or more
1.2 (1.0-1.3)
1.3 (1.1-1.4)**
1.1 (1.0-1.3)
Body mass index(Ref 18.5-24.9)
Underweight (<18.5)
1.0 (0.9-1.2)
1.0 (0.9-1.2)
1.0 (0.9-1.2)
Overweight (25-29.9)
1.2 (1.1-1.3)**
1.2 (1.0-1.3)**
1.1 (1.0-1.2)
Obesity(30+)
1.3 (1.1-1.5)**
1.2 (1.1-1.4)**
1.1 (1.0-1.3)
Single marital status
1.3 (1.1-1.5)**
1.2 (1.1-1.4)*
1.2 (1.0-1.3)*
Body height <150 cm
1.2 (1.1-1.4)*
1.0 (0.9-1.2)
1.1 c(0.9-1.2)
Paternal age (Ref 26-35 years)
Under 26 years
1.2 (1.0-1.3)
1.1 (1.0-1.3)
1.2 (1.0-1.3)*
36-45 years
1.0 (0.9-1.1)
0.9 (0.8-1.0)
0.9 (0.8-1.1)
Over 45 years
1.1 (0.9-1.4)
1.1 (0.9-1.4)
1.1 (0.9-1.3)
Father's education (Ref sec/high)
No education
1.2 (0.7-2.3)
0.8 (0.5-1.5)
0.5 (0.3-0.9)*
Primary school
1.0 (0.9-1.1)
1.0 (0.9-1.1)
1.0 (0.9-1.1)
Pre-gestational diabetic
4.4 (3.3-5.8)**
3.5 (2.6-4.7)**
1.6 (0.7-3.3)
Maternal Lung disease
1.2 (1.1-1.4)**
1.2 (1.1-1.4)**
1.2 (1.0-1.3)*
Maternal Epilepsy
1.6 (1.0-2.6)
1.9 (1.2-2.9)**
1.4 (0.9-2.2)
Not boiling drinking water
1.2 (1.1-1.3)**
1.1 (1.0-1.3)**
1.1 (1.0-1.2)
Pregnancy, labour and delivery
Mother referred to ANC§
-
1.3 (1.1-1.4)**
1.2 (1.0-1.3)*
ANC < 5 visits
-
1.3 (1.2-1.4)
1.2 (1.1-1.3)**
Gestational Diabetic
-
1.4 (0.6-3.4)
1.4 (0.5-4.5)
Hypertension
1.5 (0.9-2.4)
1.2 (0.7-1.9)
Preeclampsia
2.0 (1.7-2.3)**
1.3 (1.1-1.5)**
Eclampsia
-
2.8 (1.7-4.4)**
0.9 (0.6-1.6)
Abruptio placenta
-
2.6 (1.6-4.1)**
1.1 (0.7-1.8)
Premature rupture of membrane
-
2.9 (2.6-3.4)**
2.3 (1.9-2.7)*
Caesarian section
-
2.1 (1.9-2.3)**
1.9 (1.8-2.1)**
Other vaginal delivery
-
2.9 (2.3-3.6)**
2.2 (1.7-2.9)**
Other unspecified complications
-
1.8 (1.4-2.3)**
1.5 (1.2-1.9)**
Neonatal factors
Birth weight >4000 g
-
-
7.2 (6.5-8.0)**
Birth Weight 1500-2500 g
-
-
2.8 (2.5-3.1)**
Birth weight <1500 g
-
-
3.0 (2.3-4.0)**'
Gestational age below 34 weeks
-
-
1.8 (1.5-2.1)**
Gestational age 34-36 weeks
-
-
1.3 1.3 (1.1-1.5)**
Five minutes Apgar score <7
-
-
4.0 (3.4-4.6)**
Male sex
1.2 (1.1-1.3)**
*p-value less than 0.05
**p-value less than 0.01
a In each step variables entered were all which had p-value of < 0.1 in univariable analysis including maternal age although p-value was slightly above 0.1 (0.106). The lowest risk category in each group was used as a reference. Results are presented for all variables which were significant at least once in any of the three steps.
Model A, first step; adjusted for pre pregnancy factors
Model B, second step; variables in model A plus conditions in pregnancy, labor and delivery
Model C, third step; variables in model B plus neonatal factors
§- First ANC visit triggered by health workers
Pre-gestational diabetes mellitus was strongly associated with neonatal transfer to NCU (RR 4.4; 95% CI: 3.3-5.8). A history of acute or chronic lung disease other than tuberculosis showed a weaker association (RR 1.2; 95% CI: 1.1-1.4).
Pregnancy, labour and delivery
Factors related to pregnancy, labour and delivery were included in the multivariable model in B. Hypertensive conditions such as eclampsia and preeclampsia (RR 2.8; 95% CI:1.7-4.4 and 2.0; 95% CI: 1.7-2.3, respectively), labour-related complications such as premature rupture of membrane and abruption placenta (RR 2.9; 95% CI: 2.6-3.4 and 2.6; 95% CI: 1.6-4.1, respectively), and other vaginal delivery (i.e. breech, vacuum or forceps) and caesarean section delivery (RR 2.9; 95% CI: 2.3-3.6 and 2.1; 95% CI: 1.9-2.3, respectively) were all associated with transfer (Table 4; model B). Gestational diabetes increased the risk of babies transfer by 40% although not statistically significant. Referral to ANC and few ANC visits were also found to be important predictors of neonatal transfer to NCU (RR 1.3; 95% CI: 1.1-1.4 and 1.3; 95% CI: 1.2-1.4), respectively.
Anzeige
Significant factors in model A continued to be independent predictors for neonatal transfer also in model B, except for maternal body height below 150 cm. However, addition of variables in model B slightly reduced the relative risk for most factors.
Neonatal factors
In model C, neonatal factors were added into the multivariable model. All the selected neonatal factors were significantly associated with transfer to NCU, with the highest relative risks being for birth weight above 4000 g (RR 7.2; 95% CI: 6.5-8.0) and five minutes Apgar score below 7 (RR 4.0; 95% CI: 3.4-4.6) (Table 4; model C).
After inclusion of the neonatal factors, some pre-pregnancy factors, such as women giving birth to their first babies (RR 1.4; 95% CI: 1.2-1.5), maternal age 26-35 years (RR 1.2; 95% CI: 1.1-1.3), and single marital status (RR 1.2; 95% CI: 1.0-1.3) were still significantly associated with neonatal transfer. Lack of paternal education (RR: 0.5; 95% CI: 0.3-0.9) was negatively associated with transfer to NCU. Birth to fourth or later born babies, maternal overweight or obesity, pre-gestational diabetes and epilepsy were no longer significantly associated with neonatal transfer.
Discussion
In this registry based study from a tertiary hospital in Tanzania, we identified patterns of neonatal transfer to NCU. In a three-step analysis we studied socio-demographic factors, maternal health factors, and neonatal factors in relation to transfer. A particular aim was to assess whether socio-demographic factors were related to transfer to NCU beyond their association with well-defined medical risks. The analyses showed that neonatal factors by far had the strongest association with neonatal transfer, but that pre-pregnancy and pregnancy factors were also independently associated with transfer.
Anzeige
The incidence of neonatal transfer in this study was 15%, which is slightly higher than reported in previous studies both from developed [4, 5] and developing countries [7, 18].
Neonatal factors
The studied neonatal factors included classical risk factors for morbidity and mortality, such as birth weight, preterm delivery, Apgar score and sex, and were as expected strongly related to neonatal transfer. Although the causal effect of birth weight is controversial [19] low birth weight is a good predictor of need for neonatal care. Low birth weight has been proposed to contribute to 40-80% of neonatal morbidity and mortality [20, 21]. Preterm delivery is estimated to account for 28% of all neonatal deaths [20].
We also found a very high admission rate of newborns with a birth weight above 4000 g. Fetal macrosomia is associated with obstetric complications and neonatal morbidity such as injuries, respiratory distress and hypoglycaemia. Observation for transient or persistent hypoglycaemia is a common reason for admission of high birth weight babies to NCU [22]. At KCMC, such babies will be discharged within 24 hours if there is no risk of persistent hypoglycemia and the blood glucose level is normal. The outcome is in general good for these babies, and one may speculate whether observation without transfer to NCU for many of these babies would represent a better use of resources.
In general, male neonatal morbidity exceeds female morbidity, partly due to a higher occurrence of preterm birth and other neonatal risk factors [23]. The male-to-female ratio of transfer 1.24, declining to 1.18 in the adjusted analyses, corresponds well with the established higher risk in males, and does not indicate a difference in care according to infant sex.
Pregnancy, labour and delivery
Risk of neonatal transfer was high in mothers with preeclampsia, eclampsia and abruption placenta, however no or weak effects were observed after inclusion of neonatal factors in the model. Hypertensive conditions in pregnancy are associated with preterm birth and low birth weight [15, 24‐27], and many cases of abruption placenta occur at a low gestational age, which explain the indirect association between these complications and neonatal transfer. The direct cause of transfer would be the preterm birth.
Other conditions, such as premature rupture of membrane, caesarean section and operative vaginal delivery, showed a high risk of neonatal transfer also after accounting for the neonatal condition of the baby. The high rate of transfer for babies born with mothers having PROM is similar to what is reported elsewhere [15]. Premature rupture of the membrane (PROM) is associated with preterm delivery and low birth weight [15, 27]. A previous study at KCMC reported a high prevalence (38%) of low birth weight babies after PROM [27]. Such babies are at higher risk of developing neonatal infection. Antibiotic prophylaxis given to mothers with PROM has shown to reduce risk of infection in the newborn [28, 29]. The high transfer rate after PROM in our data is likely to be explained by the fact that a majority of mothers with a history of PROM did not receive antibiotic prophylaxis prior to delivery, due to late arrival to the centre.
Mothers with less than five antenatal care visits were more likely to have their baby transferred and this association persisted after we took into account our measures of the condition of the newborn. Amount of antenatal care plays a role in neonatal outcome [30‐32], and each additional ANC visit has previously been found to offer a protective effect on neonatal outcome [31]. When the mother had been referred for antenatal care, however, the risk of transfer was increased.
Pre pregnancy factors
Among diseases that the mothers had before the pregnancy, only lung disease remained significantly associated with neonatal transfer when pregnancy conditions and neonatal conditions were accounted for (Table 4, model C). Pre-gestational diabetes was strongly related to transfer in models A and B, but the association disappeared after accounting for the neonatal conditions in model C. Noteworthy, gestational diabetes had a weak and non-significant association with transfer, and the relative risk was not affected by adjustment for neonatal factors. The low risk of transfer in babies born to mothers with gestational diabetes compared to babies of mothers with pre-gestational diabetes is also reported elsewhere [5, 15, 33].
Women giving birth to their first child and single mothers were more likely to have their baby transferred to NCU, also after accounting for pregnancy conditions and neonatal conditions. Birth to a first child and single motherhood are classical risk factors for neonatal morbidity and mortality [9, 10, 12, 18, 34, 35]. However, the 40% higher risk of admission for a first born child in the fully adjusted model (model C), is higher than what one would expect according to previous knowledge on morbidity and mortality associated with first delivery. In a previous study from the same hospital, perinatal mortality was not associated with birth order except for a higher perinatal mortality in offsprings of mothers with three or more previous pregnancies [11]. To further elaborate this finding, we performed a regression analysis with a finer categorization of Apgar score. In this model, the parity effect was still statistically significant, however reduced. In a setting with limited obstetric services, the generally higher neonatal stress on first born babies might be even more evident.
In line with previous findings [36‐38] we found that overweight and in particular obese mothers had a high risk of having their baby transferred to NCU. Maternal obesity is associated with some pregnancy complications [33, 36‐40] and overweight or obese mothers are more likely to have high birth weight babies [37, 38, 40]. A meta-analysis review showed a lower risk of low birth weight among babies of overweight or obese mothers compared to normal weight mothers, however the risk of very low birth weight and extremely low birth weight was increased due to more induced preterm deliveries in overweight or obese mothers [41]. In our data, the association of neonatal transfer associated with maternal overweight and obesity was weakened but still statistically significant after adjustment for pregnancy conditions, however disappeared after adjustment for neonatal conditions. Hence, pregnancy conditions and neonatal conditions seem to be mediators in the association between maternal overweight and neonatal transfer. A similar pattern was seen for mothers of short stature, where an increased risk seen in model A seemed to be linked to a higher rate of pregnancy complications for these mothers.
Drinking unboiled water was one of the factors associated with neonatal transfer. Waterborne disease including diarrhoea and dysentery is prevalent in Tanzania, therefore, it is recommended to boil water for drinking including tap water. In our study 92% of the participants used tap water, however only 31% boiled water for drinking. In a study from Tanzania, lack of boiling water prior to consumption was more common in households with low income, and lack of proper knowledge on the importance of how to handle and store water safely was associated with E.coli occurrence [42]. Both ignorance and poverty might be the major barriers to boiling drinking water.
Lack of paternal education was associated with a low chance of neonatal transfer (RR = 0.5; 95% CI: 0.3-0.9) in the fully adjusted model. Although our results should be interpreted with care due to the low numbers (110 fathers with no education) and a confidence interval close to one, the findings could reflect low focus on neonatal health care in deprived families. A previous study using the same birth registry reported that paternal socio-demographic factors seemed to be more important predictors of perinatal mortality than maternal socio-demographic factors in this area [11]. However, such an interpretation is not compatible with the principle that transfer mechanisms should be unaffected by parental and family influence.
Strengths and limitations
The study was based on a hospital based birth registry, where data are carefully collected according to standardized procedures, ensuring complete coverage of births on a daily basis including weekends and holidays. Information was collected by designated midwives using a structured questionnaire-based interview, and medical records were used to verify the information from the questionnaire. The sample size was relatively large and enabled us to study many risk factors in relation to neonatal transfer. Hence, the data allowed us to study the relationship between socio-demographic characteristics, maternal health and complications during delivery, and neonatal characteristics, with transfer to neonatal intensive care unit. Selection bias was reduced by excluding all medically indicated referral births from rural areas where the mother would not probably deliver at KCMC if not referred. The excluded cases accounted for 52% of all referrals and 75% of all medical referrals.
About 29% of the deliveries in the Kilimanjaro region occur at home [20], and the study results may not be representative of the entire population within the area. Although women who give birth at the hospital largely differ with respect to socio-demographic status, the socio-demographic variation in the community may be even larger and towards a less privileged population. It is therefore possible that the observed risks are underestimated as compared to the region.
We applied an analytical approach where the various classes of variables were included in regression models through three steps. The purpose of this was to identify which factors that mediated any association with transfer. Our analyses are based on a limited set of variables, and there may be important risk factors of neonatal transfer that we have not been able to account for. Hence, the effects obtained in the models may represent a mixture of effects of the studied factors and effects of factors not accounted for. In particular, our measures of the condition of the newborn were probably too crude to fully account for the clinical judgement of the baby's condition and the need for transfer.
Despite these limitations, we believe that our study, based on structured collection of information with a hospital based design combined with careful considerations of possible biases, represent findings of importance. True population data are difficult to collect in sub-Saharan Africa. Investment in competence building and data collection should start with key hospitals, and efforts should be done to include well-defined populations, in order to generate relevant and representative data to address the important public health issues within the general population.
Conclusions
Our study has demonstrated the combined effect of socio-demographic, maternal health conditions and neonatal factors in predicting transfer to NCU. The relationship between socio-demographic, maternal health characteristics and neonatal factors observed in this study reflects traditionally known predictors of neonatal morbidity and mortality. As for the pre-pregnancy factors, most of the associations with transfer were accounted for by pregnancy complications and neonatal factors. An exception from this was a possibly reduced use of transfer for babies of non-educated fathers. The potential effect of paternal social status both on neonatal health and on access to health care for mother and baby needs more attention. Another exception that needs to be further explored is the 40% higher rate of transfer among first born babies. With respect to neonatal factors, one might speculate whether the high number of babies above 4000 g transferred to the NCU represents an optimal use of resources, as the outcome of these babies is in general good.
Acknowledgements
We acknowledge the Norwegian Council for Higher education program for Development Research (NUFU) for funds support. We thank the staff of the birth registry department in Norway for ongoing supervision and technical support for the KCMC birth registry. We also thank the birth registry team, labour ward and NCU staff at KCMC for their support in data collection, and in taking care of mothers and their newborns. To our participants' mothers who delivered at KCMC during the period of data collection, we say "Thank you" for y our consent and participation in giving needed information.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Competing interests
The authors declare that they have no competing interests.
Authors' contributions
BTM: Study design, methodology, data analysis and manuscript writing. RTL, GSK, RO, GK, AKD: Study design, methodology, manuscript writing. All authors approved the final manuscript.
Laser- und Lichtbehandlungen können bei Frauen mit polyzystischem Ovarialsyndrom (PCOS) den übermäßigen Haarwuchs verringern und das Wohlbefinden verbessern – bei alleiniger Anwendung oder in Kombination mit Medikamenten.
Müssen sich Schwangere einer Krebstherapie unterziehen, rufen Immuncheckpointinhibitoren offenbar nicht mehr unerwünschte Wirkungen hervor als andere Mittel gegen Krebs.
Durch die Häufung nach der COVID-19-Pandemie sind Infektionen mit dem Respiratorischen Synzytial-Virus (RSV) in den Fokus gerückt. Fachgesellschaften empfehlen eine Impfung inzwischen nicht nur für Säuglinge und Kleinkinder.
Update Gynäkologie
Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert – ganz bequem per eMail.