2Department of Epidemiology & Biostatistics, Institute of Public Health, Kilimanjaro Christian Medical University College, Moshi, Tanzania.
3Department of Community Health, Institute of Public Health, Kilimanjaro Christian Medical Centre, Moshi, Tanzania
4Kilimanjaro Christian Medical University College, Moshi, Tanzania
Methods:A matched case-control study was conducted at the Bugando Medical Centre from May to June 2015. A total of 50 women with preterm birth (cases) were matched with 50 women who had term births (controls). Cases were matched with controls by date of delivery. We excluded mothers with multiple gestations and those who were sick and unsuitable for the interview. A structured questionnaire was used to collected relevant information from all participants. Data analysis was performed using SPSS version 20.0. Odds ratios with 95% confidence interval were estimated in a multivariate regression model to determine factors associated with preterm delivery.
Results:The preterm birth rate was 13%. Numerous factors were associated with increased odds of preterm birth. These include regular menstrual cycle (OR 5.8; 95% CI: 2.3- 14.9); planned abortion (OR 3.8; 95% CI: 1.1-13.1); use of fertility treatment during the index pregnancy (OR 7.0; 95% CI: 1.9-27.3); inadequate ANC visits (OR 9.0; 95% CI: 3.2-28.3); antepartum haemorrhage (OR 3.1 95% CI: 1.1-8.8); uterine pain during the index pregnancy (OR 5.0 95% CI: 1.7-14.4); urinary tract infections during the current pregnancy (OR 5.7 95% CI: 2.1-14.9); abnormal vaginal discharge in the current pregnancy (OR 7.4; 95% CI:2.6-20.7) and use of traditional medicine (OR 5.6; 95% CI: 2.1-14.9). The association between preterm birth and previous miscarriage, chronic hypertension, physical abuse during pregnancy and previous preterm birth disappeared after controlling for other covariates.
Conclusions:The rate of preterm birth in our study corresponds with the national prevalence. A number of maternal factors increase women likelihood of having preterm delivery. Early identification of these factors during prenatal care and provide with appropriate care may reduce the risk of preterm birth.
Keywords:Giant oocyte; meiotic spindle; polarization microscopy
Numerous factors have been associated with increased risk of preterm birth. These include extreme maternal age (<20 and >35 years), obesity, parity, history of miscarriage, history of preterm delivery, period on titis history of abortion, low social economic status and alcohol use, living in rural areas, use of herbal medicine, maternal anaemia, diabetes mellitus, shoulder dystocia, hypertension, premature rupture of membrane (PROM), untreated bacterial vaginosis, human immune deficiency virus infection (HIV) and Escherichia coli infection [3, 4-18].
Tanzania is among the countries that have succeeded in achieving the United Nations Millennium Development Goal 4 (MDG4) [19]. Despite this achievement, the neonatal mortality rate is still high. In 2013 the neonatal mortality rate was 21 per 1000 live births which is still higher as compared to the target which is 19 per 1000 live births by 2015 [19,10]. Tanzania ranked twenty-fifth in the world for the number of preterm births with 11.4% of babies born in 2010 being preterm. One out of four deaths of new-borns is due to prematurity [13]. It is estimated that 23% of all neonatal deaths in Tanzania are due to complications of prematurity [10].
The aim of this study was to determine the risk factors for preterm birth among women who delivered preterm babies at Bugando Medical Centre in Tanzania. Identification of risk factors for preterm birth would facilitate the formulation of appropriateinterventions that could help prevent these complications.
The estimation of gestational age was based on dates of the last menstrual period (LMP). Preterm birth was defined as giving birth at less than 37 completed weeks of gestation.
Characteristics |
Total |
Cases |
Controls n (%) |
OR |
(95% CI) |
P-Value |
Maternal age (years)* |
25.4 |
23.3(5.2) |
27.5(5.8) |
<0.001 |
||
Maternal age (years) |
||||||
<30 |
81 |
46 (92) |
35 (70) |
4.92 |
(1.516.15) |
0.005 |
>30 |
19 |
4 (8) |
13 (30) |
|||
Education level |
||||||
Primary and none |
52 |
16 (32) |
36 (72) |
0.18 |
(0.070.43) |
<0.001 |
Secondary and above |
48 |
34 (64) |
14 (28) |
|||
Maternal Occupation |
||||||
Employed |
40 |
23 (46) |
17 (34) |
1.65 |
(0.733.70) |
0.22 |
Non employed |
60 |
27 (54) |
33 (66) |
|||
Marital status |
||||||
Married |
83 |
40 (80) |
47 (94) |
0.25 |
(0.660.99) |
0.037 |
Non married |
13 |
10 (20) |
3 (6) |
|||
Residence |
||||||
Urban |
55 |
18 (36) |
37 (74) |
0.19 |
(0.080.46) |
<0.001 |
Rural |
45 |
32 (64) |
13 (26) |
Factors |
Cases |
Controls |
COR (95%CI) |
AOR (95%CI) |
Menstrual cycle** |
||||
Regular |
18 (36) |
40 (80) |
7.1 (2.8-17.52) |
5.8 (2.3-14.86)* |
Irregular |
32 (64) |
10 (20) |
1 |
1 |
Previous miscarriage*** |
||||
Yes |
12 (24) |
9 (18) |
1.4 (0.54-3.79) |
1.6 (0.62-4.49) |
No |
38 (76) |
41 (82) |
1 |
1 |
Previous still birth |
||||
Yes |
5 (10) |
0 (0) |
2.1 (1.70-2.61)* |
- |
No |
45 (90) |
50 (100) |
1 |
|
Planned abortion*** |
||||
Yes |
12 (24) |
4 (8) |
3.6 (1.0-12.18) |
3.8 (1.1-13.10)* |
No |
38 (76) |
46 (92) |
1 |
1 |
Previous preterm birth |
||||
Yes |
8 (16) |
0 (0) |
2.1 (1.752.73)* |
- |
No |
42 (84) |
50 (100) |
1 |
|
Chronic HTN** |
||||
Yes |
6 (12) |
1 (2) |
6.6 (0.77-57.69) |
7.9 (0.89-70.33) |
No |
49 (98) |
44 (88) |
1 |
1 |
* p< 0.05 ***Adjusted for marital status, **Adjusted for fertility treatment before this pregnancy,
Factors |
Cases |
Controls |
COR |
AOR |
Fertility treatment before this pregnancy****** |
||||
Yes |
15 (30) |
3 (6) |
6.0 |
7.0 |
No |
35 (70) |
47 (94) |
1 |
1 |
ANC visits** |
||||
<4 |
28(57.1) |
8 (16) |
7.0 |
9.0 |
≥4 |
21(42.9) |
42 (84) |
1 |
1 |
Ante partum haemorrhage*** |
||||
Yes |
22 (44) |
7 (14) |
4.1 |
3.1 |
No |
28 (56) |
43 (86) |
1 |
1 |
Uterine pain in the current pregnancy*** |
||||
Yes |
25 (50) |
7 (14) |
6.1 |
5.0 |
No |
25 (50) |
43 (86) |
1 |
1 |
Abnormal vaginal discharge in the current pregnancy **** |
||||
Yes |
30 (60) |
8 (16) |
7.0 |
7.4 |
No |
20 (40) |
42 (84) |
1 |
1 |
UTI in the current pregnancy*** |
||||
Yes |
34 (68) |
12 (24) |
6.7 |
5.7 |
No |
16 (32) |
38 (76) |
1 |
1 |
Physical abuse in the current pregnancy |
||||
Yes |
4 (8) |
0 (0) |
2.0 |
- |
No |
46 (92) |
50 (100) |
1 |
|
Use of traditional medication in the current pregnancy*** |
||||
Yes |
32 (64) |
6 (12) |
7.1 |
5.6 |
No |
18 (36) |
44 (88) |
1 |
1 |
A previous study in Zimbabwe reported that women with previous history of still birth were nearly two times more likely to have preterm birth [20]. This was consistency with our study where the odds of preterm birth increased by 2-folds among women previous history of still birth as compared to those who had delivered a live infant. This slight difference could be due to a smaller sample size in our study or the nature of women studied between populations. Our result suggests the need for still birth prevention to reduce the risk of future preterm birth.
In the present study history of planned abortion was associated with and increased odds of preterm birth. Similar findings were reported elsewhere [2, 20]. The increased odds or preterm birth among women who experienced abortion in our study could be explained by the differences in the studied populations where most of our study population was less than 30 years of age who were more likely to get unplanned pregnancies which led them to attempt abortion. This implies that practicing illegal abortion should be stopped to prevent the occurrence of preterm birth.
The role of fertility treatment as the risk factor of preterm birth was significant in this study. A study in Israel found that women who reported using fertility treatment in their index pregnancy had more than 4-fold increased risk of preterm birth compared with those who were not using [6]. It’s not clear if fertility treatment is really the risk factor of preterm or if the conditions that necessitates the treatment is the risk factor but this was not assessed in our study. Despite this, fertility treatment should be used with care and with clinician prescription.
As would be expected, lack of prenatal care was associated with preterm birth in our study. We found that women who did not use prenatal care services (< 4 ANC visits) as recommended by WHO had 9-folds an increased odds of having preterm birth as compared to women who had 4 or more ANC visits. This association was also reported by Passing in Brazil, where the risk of preterm birth due to ANC visits < 4 times was found to increase by 1.52 fold [11]. In Washington, it was found that the risk of preterm birth due to ANC visits < 4 times increased by 5.7 times [21]. This difference in risk may be due to the fact that most of the women in our study were from rural areas where there is scarcity of health care services as compared to women in the previous studies [11, 21]. The study in Brazil was a multicentre cross-sectional study and hence included a larger sample size as compared to our study. Nevertheless pregnant women should be encouraged to attend to antenatal services as recommended by the World Health Organization (WHO).
In agreement with reports from several studies, conditions like ante-partum haemorrhage and uterine pain were found to increase the risk of preterm birth in this study. This is consistent with a study done in Zimbabwe where ante-partum haemorrhage increased the risk of preterm birth by about three fold [20]. In Brazil ante-partum haemorrhage increased the risk of preterm birth by about two fold [11]. In Australia it was reported that ante-partum haemorrhage increased the risk by 6.4 fold [2]. The difference in these findings could be explained by different sample size and nature of the studied population. It is important that ante-partum haemorrhage be appropriately treated and its causes be addressed to prevent the occurrence of preterm birth. In addition, abnormal vaginal discharge was found to increase the risk of preterm birth in this study. Contrary to our findings, a study in Rwanda could not find any correlation between abnormal vaginal discharge and preterm birth [22].
In agreement with reports from several studies, conditions like ante-partum haemorrhage and uterine pain were found to increase the risk of preterm birth in this study. This is consistent with a study done in Zimbabwe where ante-partum haemorrhage increased the risk of preterm birth by about three fold [20]. In Brazil ante-partum haemorrhage increased the risk of preterm birth by about two fold [11]. In Australia it was reported that ante-partum haemorrhage increased the risk by 6.4 fold [2]. The difference in these findings could be explained by different sample size and nature of the studied population. It is important that ante-partum haemorrhage be appropriately treated and its causes be addressed to prevent the occurrence of preterm birth. In addition, abnormal vaginal discharge was found to increase the risk of preterm birth in this study. Contrary to our findings, a study in Rwanda could not find any correlation between abnormal vaginal discharge and preterm birth [22].
Like in other studies we found that the risk of preterm birth was fivefold higher among women who had UTI. However, much lower risk has been reported among Zimbabwean [20] and in Brazilian women [11]. The difference in findings could be explained by the difference in exposure to UTI pathogens between these three populations and hence the variations in the chances of acquiring infection. Since pregnant women are prone to infections due to decreased immunity during pregnancy, preventive measures such as drinking a lot of water should be taken to prevent UTI infection and if present it should be aggressively treated to prevent preterm birth.
Use of local medication was also associated with preterm birth in our study. The risk of preterm birth increased 6- foldamong women who reported use of local medication as compared to non-user counterparts. A much higher increase in risk of preterm birth with the use of local medications was also reported in Kenya [4]. The similarities in findings between the two studies could be attributed to similarities in social-cultural among women between these neighbouring countries. Our finding with those of others suggests that community awareness of about the risk of prematurity with local medication use is important, and hence stop this practice.
Despite the important information obtained in this study, our findings are likely to have some laminations. This study was conducted in a referral hospital. Therefore, there is a possibility of studying a selected group of women with high risk pregnancies because most of the women who are diagnosed with risk pregnancy during prenatal care are more likely to be referred or advised by their health care providers to deliver at the tertiary hospital. If this happened in our study it may have introduced selection bias and hence it can overestimate or underestimate the occurrence of preterm and associated risks as compared to other women in the general population.
- Kinney MV, Lawn JE, Howson CP, Belizan J. 15 Million preterm births annually: what has changed this year? Reproductive Health 2012;9:28. Doi: 10.1186%2F1742-4755-9-28
- World Health Organization: Born Too Soon. The Global Action on Preterm Birth. Geneva: World Health Organization 2012.
- Demmouche A, Mai AH, Kaddouri MS, Ghani A, Rahmani S, Beddek F et al. Etiology of Preterm Birth in Relizane Region (West of Algeria). J Nutr food sci. 2004;4(5):4–6.
- Kaburi N. Medication-Related Risk Factors for Preterm Birth in in Kitui County, Kenya. PloS one. 2014;36:42–43.
- Laughon SK, Reddy UM, Sun L, Zhang J. Precursors for Late Preterm Birth in Singleton Gestations. Obstet Gynecol. 2010;116(5):1047–1055. Doi: 10.1097/AOG.0b013e3181f73f97
- Linder N, Haskin O, Levit O, Klinger G, Prince T, Naor N, et al. Risk factors for intraventricular hemorrhage in very low birth weight premature infants: a retrospective case-control study. Pediatric 2003;111(5 Pt 1):e590–595.
- Hasoon SM. Assessment of risk factors for preterm birth: Case Control Study, AL- Taqani, 2013;26(3):83–91.
- Mosha D, Mazuguni F, Mrema S, Sevene E, Abdulla S, Genton B. Safety of artemether-lumefantrine exposure in first trimester of pregnancy, Malar J. 2014;13(1):197. Doi: 10.1186/1475-2875-13-197
- Manji K. Situation analysis of newborn health in Tanzania: Current situation, existing plans and strategic next steps for newborn health. Dar es Salaam: Ministry of Health and Social Welfare save the Children. 2009.
- Mwakyusa DH. The national road map strategic plan 200-2015, Tanzania, Ministry of Health and Social welfare. 2008.
- Passini R Jr, Cecatti JG, Lajos GJ, Tedesco RP, Nomura ML, Dias TZ, et al. Brazilian Multicentre Study on Preterm Birth (EMIP): Prevalence and Factors Associated with Spontaneous Preterm Birth. PLoS ONE. 2014;9(10): e109069. Doi:10.1371/journal.pone.0109069
- Perinatal A, Collaborative E. APEC Guidelines Preeclampsia, version 2, California, CMQCC. 2014.
- Evidence for Action. Mama Ye Factsheet on Preterm Birth in Tanzania 2014. London: Evidence for Action. 2014.
- Räisänen S, Gissler M, Saari J, Kramer M, Heinonen S. Contribution of Risk Factors to Extremely, Very and Moderately Preterm Births – Register-Based Analysis of 1,390,742 Singleton Births. PLoS ONE. 2013;8(4): e60660. doi:10.1371/journal.pone.0060660
- Trilla CC, Medina MC, Ginovart G, Betancourt J, Armengol JA, Calaf J. Maternal risk factors and obstetric complications in late preterm prematurity. Eur J Obstet Gynecol Reprod Biol. 2014;179:105-109. Doi: 10.1016/j.ejogrb.2014.05.030
- Watson-Jones D, Weiss HA, Changalucha JM, Todd J, Gumodoka B, Bulmer J, et al. Adverse birth outcomes in United Republic of Tanzania--impact and prevention of maternal risk factors. Bull World Health Organ. 2007; 85 (1):9-18. doi: 10.2471/BLT.06.033258.
- WHO. General Guidline for methodologies on Resarch and Evaluation of Traditional Medicine. Geneva. 2000.
- Rachel M. Zack, Jenna Golan, Said Aboud, Gernard Msamanga, Donna Spiegelman, and Wafaie Fawzi, “Risk Factors for Preterm Birth among HIV-Infected Tanzanian Women: A Prospective Study,” Obstet and Gynecol Int. 2014;2014:1-9. Doi:10.1155/2014/261689.
- Bay G, Miller T, Faijer DJ. Levels and trends of child mortality.UNICEF Report 2014.
- Feresu SA, Harlow SD, Woelk GB. Risk factors for prematurity at Harare Maternity Hospital, Zimbabwe. Inte J Epidemiol. 2004;33:1194–1201. Doi:10.1093/ije/dyh120
- Sheryl L. Coley, Tracy R. Nichols, Kelly L. Rulison, Robert E. Aronson, Shelly L. Brown-Jeffy, and Sharon D. Morrison, “Race, Socioeconomic Status, and Age: Exploring Intersections in Preterm Birth Disparities among Teen Mothers,” Int J Popul Res. 2015;2015:1-10. Doi:10.1155/2015/617907
- Bayingana C, Muvunyi CM. & Africa CWJ. Risk factors of preterm delivery of low birth weight (plbw) in an African population. J Clinic Med and Res. 2010;2(7):114-118.