Evolution and Risk Factors of Maternal Mortality in Cameroon: A Case Control Study ()
1. Background
Maternal Mortality is the death of a woman while pregnant or within 42 days of termination of pregnancy, irrespective of the duration and site of the pregnancy, from any cause related to or aggravated by the pregnancy or its management, but not from accidental or incidental causes [1] .
The maternal mortality ratio (MMR) is defined as “the ratio of the number of maternal deaths during a given period per 100,000 live births during the same time period”. The global MMR is 210 per 100,000 live births. The maternal mortality ratio in developing countries is 240 per 100,000 births versus 16 per 100,000 in developed countries. There are large disparities between countries, with few having extremely high maternal mortality ratios of 1000 or more per 100,000 live births. There are also large disparities within countries, between people with high and low incomes, and between people living in rural and urban areas [2] .
Sub-Saharan Africa is the region of the world with high rates of maternal death [3] [4] and where about 25% of total births on the planet are registered each year.
According to the WHO, some facts have been observed; between 1990 and 2010, maternal mortality worldwide dropped by almost 50%; Every day, approximately 800 women die from preventable causes related to pregnancy and childbirth; 99% of all maternal deaths occur in developing countries; Maternal mortality is higher in women living in rural areas and among poorer communities; Young adolescents face a higher risk of complications and death as a result of pregnancy than older women; Skilled care before, during, and after childbirth can save the lives of women and newborn babies [5] .
In Cameroon, in 2018, according to the Demographic and Maternal Health Survey (DMHS), the maternal mortality ratio went from 782 deaths per 100,000 live births in 2011 to 467 deaths per 100,000 live births in 2018 [6] . This ratio is heterogeneous according to the health structures; in 2015 at central hospital Yaoundé, this rate was estimated at 964 per 100,000 live births and 247 per 100,000 live births at the regional hospital in Bamenda [7] . From 2011 to 2016 a Study performed at Laquintinie Hospital recorded an MMR of 1638 per 100,000 live births [8] .
The main direct causes of maternal death in developing countries include haemorrhage, sepsis, obstructed labour and hypertensive disorders [9] . The risk of death from haemorrhage is one in 1000 deliveries in developing countries, compared with one in 100,000 in developed countries, and accounts for one-third of the maternal deaths in Africa [10] . A retrospective study undertaken at a tertiary hospital in Nigeria in 2007 found that the most common risk factors for maternal mortality were primiparity, haemorrhage, anaemia, eclampsia and malaria [11] .
Many individual and socioeconomic factors have been associated with high maternal mortality. These include lack of education, parity, previous obstetric history, employment, socioeconomic status, and types of care-seeking behaviours during pregnancy. There is also evidence of an increased risk of death among young women [12] . In Nigeria, a cross-sectional survey revealed that the most common risk factors for maternal death were primigravidity (19%) and unbooked status (19%) [13] . Poverty has also been associated with adverse maternal outcomes, not directly, but as a contributor to maternal ability to access good health care centers [14] [15] .
Antenatal care (ANC) is very important during pregnancy. International organizations recommend a minimum of four visits, the administration of two doses of tetanus toxoid, and folic acid supplementation during ANC attendance [16] . When women receive good care during the pre-partum period, they have been shown to be at lower risk of maternal morbidity and mortality since they have a higher likelihood of using a professional health facility during birth [17] [18] .
The aim of this study is to identify risk factors associated with maternal mortality in Laquintinie hospital in Douala, Cameroon. To achieve this objective, we studied and analyzed four sets of determinants: socio-demographic, maternal history, obstetric, and hospital admission.
2. Methods
An unmatched case-control study of women who had been admitted at the maternity unit of Laquintinie Hospital between January 2017 and December 31, 2022, was conducted. Laquintinie Hospital is located in the Littoral region of Cameroon. As the largest regional hospital in Douala, it provides a range of curative, preventive, and rehabilitative health services to a population of about 3 million inhabitants. The maternity unit is made up of 05 birth rooms, each with a convertible bed, a pre-labour room with a capacity of five beds, and many rooms for postpartum. A functional operating theatre (with two immediate post-interventional treatment rooms with two beds each) is attached to this entire unit. The obstetrics and gynaecology department has a capacity of 80 beds and a filling rate of 80%. The cases (n = 166) were maternal deaths identified from a manual review of hospital records. The controls (n = 332) were selected in a ratio of 2 control per case. Controls were surviving women who were admitted immediately preceding and following cases.
2.1. Inclusion Criteria
All Cases registered as maternal deaths were selected retrospectively during the study period (January 1, 2017 to December 31, 2022). Abortion and ectopic pregnancy related deaths were included in the study. Trained staff collected information using a standard audit form.
2.2. Exclusion Criteria
We excluded all the cases of deaths in women who were not pregnant or in the postpartum period. Also, there were cases with incomplete data, such as the absence of age, address, occupation, past history or any other important information.
2.3. Data Collection
Data was collected using a data collection form. Sociodemographic data included the mother’s age, mother’s marital status, mother’s educational level, mother’s occupation, religion, and residence. Data on maternal medical history included smoking, alcohol use, abortion, multiple gestation, gravidity, number of ANC visits, and stage of labour. Health system factors included mode of delivery, and referral from another facility (yes or no). Maternal clinical data during admission was also collected and included the diagnosis on admission (e.g., already death, eclampsia, dystocia, haemorrhage, anemia), pulse rate on admission (beats per minute/bpm), clinical cause of death. The primary cause of maternal death was extracted from the patient’s medical record and post mortem records.
2.4. Statistical Analyses
Analyses were performed using the Statistical Package for Social Sciences version 26 software. The data was checked for obvious errors. Univariate logistic regression analysis was conducted for each potential risk factor. All variables with a p value < 0.2 in the univariate models were included in a multivariate model. Backward stepwise multiple logistic regression was undertaken separately for the four groups of risk factors in the framework adapted from the Delay Model, (individual and socio-demographic; maternal history; reproductive or obstetric; and admission). Variables were removed from the models where p-values ≥ 0.1 on the Likelihood Ratio Test. The variables in each of the final models were then included in a combined model and removed where p-values ≥ 0.1 in order to derive a final parsimonious model. Odds ratios (ORs), 95% confidence intervals and p-values are reported for all models. The reference group was the category with the lowest expected risk of death, or if there were few cases in this category, the group with the majority of respondents.
Assuming the probability of exposure in controls was 40% and the ratio of cases to controls was 1:2, with 80% power and a 5% level of significance, a sample of approximately 500 women (166 cases and 332 controls) was needed to detect an odds ratio of approximately 0.5 or 1.8.
Prior to our study, an ethical clearance was obtained from the Institutional review board of the University of Douala. Our study was conducted with strict compliance with the fundamental principles of medical research (principle of research safety and confidentiality).
3. Results
3.1. Trends in Maternal Mortality
A total of 166 maternal deaths against 14,114 live births were recorded from 2017 to 2022 giving a maternal mortality ratio of 1176 per 100,000 live births. Table 1 shows the distribution of maternal deaths and live births from January 1st, 2017, to December 31st, 2022. We observed a decrease of numbers of deliveries in 2020 due to the corona virus impact on people (fear of hospitals) (Figure 1).
3.2. Association between Sociodemographic Variables and Maternal Mortality
The age group of 25 - 34 had the highest proportion of maternal mortality (50.6%). However, the age group of 15 - 24 remained significantly associated with maternal mortality after multivariate logistic regression (aOR 0.11, 95% CI 0.00 - 0.76, p = 0.037). Mother’s occupation (Formal), also remained significantly associated with mortality after multivariate analysis (aOR 0.01, 95% CI 0.00 - 0.57, p = 0.027). Residence, religion, educational level, and marital status did not show any association with maternal mortality. Table 2 below summarizes the distribution and association between sociodemographic variables and maternal mortality at the Laquintinie hospital.
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Table 1. Distribution of maternal death at Laquintinie hospital from January 2017 to December 2022.
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Figure 1. Trend in Maternal mortality ratio.
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Table 2. Individual and Socio-demographic risk factors for maternal mortality in Laquintinie Hospital from January 2017 to December 2022.
3.3. Association between Maternal Mortality and Factors of Maternal History, and Obstetric Characteristics
The association between maternal mortality and maternal history of prevailing conditions, and obstetric and reproductive factors are shown on Table 3 below. Smoking was more common among cases compared to control (4.2% vs 3.3%) although the difference was not statistically significant (aOR: 1.31, 95% CI: 0.00 - 581). Alcohol consumption and abortion were more common amongst the cases (63.9% vs 41%, and 42.2% vs 8.7% respectively) and the differences were statistically significant (aOR: 22.79 95% CI: 1.04 - 501, p = 0.047 and aOR: 61.5 95% CI: 1.29 - 2927, p = 0.037 respectively). The proportion of cases that had no ANC visits, and only 1 - 3 visits were significantly higher compared to that of the controls with the odds of maternal mortality 388 times higher amongst those without ANC (aOR: 388 95% CI: 5.6 - 26,752, p = 0.006) and 421 times higher amongst those with only 1 - 3 ANC (aOR: 421, 95% CI: 11.5 - 15,503, p = 0.001). The differences in the distribution of twin gestation, gravidity, and mode of delivery did not differ significantly between the cases and controls.
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Table 3. Mother’s history of prevailing conditions and obstetric characteristics associated with maternal mortality in Laquintinie Hospital from January 2017 to December 2022.
3.4. Association between Maternal Admission Factors and Maternal Mortality
The proportion of death on arrival was higher amongst cases compared to controls (28.9% vs 0.0%). Eclampsia, severe preeclampsia, pulse rate ≥110 bpm had significantly higher proportions amongst cases than controls (eclampsia: 9% vs 2.1%; severe preeclampsia:12.7 vs 4.2%; pulse rate ≥110 bpm: 28.8% vs 2.7%) although on multivariate analysis, they did not reach statistical significance (eclampsia: aOR: 23.7, 95% CI: 0.08 - 7184; severe preeclampsia: aOR: 14.5, 95% CI: 0.33 - 634.50; pulse rate < 110 bpm: aOR: 0.07 95% CI: 0.00 - 1.70). Admission from comorbid complications like being admitted with hemorrhage (aOR 343.7, 95% CI 16.2 - 7276.0, p < 0.0001), being admitted with anemia (aOR 27,713.0, 95% CI 128.2 - 5,989,223.3, p < 0.0001), and being referred (aOR 0.00, 95% CI 0.00 - 0.18, p = 0.016) were all statistically significant risk factors for maternal mortality (Table 4).
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Table 4. Maternal admission factors associated with maternal mortality in Laquintinie hospital from January 2017 to December 2022.
3.5. Multivariate Logistic Regression Analysis
Table 5 shows the multivariate analysis combining all factors from the previous models. Statistically significant risk factors for maternal mortality included: young age (15 - 24 years) (aOR 0.11, 95% CI 0.00 - 0.76, p = 0.037), Alcohol intake (aOR 22.79, 95% CI 1.04 - 501.3, p = 0.047), Abortion or ectopic pregnancy (aOR 61.53, 95% CI 1.29 - 2927.3, p = 0.037), having no antenatal visits (aOR 388.3 95% CI 5.6 - 2675.9, p = 0.006), being admitted with heamorrage (aOR 343.7, 95% CI 16.2 - 7276.0, p < 0.0001), being admitted with anemia (aOR 27713.0, 95% CI 128.2 - 5,989,223.3, p < 0.0001), and being referred (aOR 0.00, 95% CI 0.00 - 0.18, p = 0.016).
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Table 5. Multivariable model showing risk factors for maternal mortality in Laquintinie Hospital from January 2017 to December 2022.
4. Discussion
4.1. Summary of Main Findings
Our study set out to determine the MMR and to identify associated factors for maternal mortality at the Laquintinie Hospital of Douala, Cameroon. We found an MMR of 1176 maternal deaths per 100,000 live births. Factors associated with maternal mortality include: young maternal age (15 - 24 years), formal occupation, alcohol consumption, abortion, no ANC visits and 1 to 3 ANC visits compared to 4 visits, hemorrhage, anemia, and being referred.
4.2. Maternal Mortality Ratio
The maternal mortality ratio in our study was one thousand one hundred and seventy-six per one hundred thousand live births (1176/100,000). This is lower than the ratio founded by Essome et al. in the same hospital from January 2011 to December 31st, 2016, who had a ratio of 1638 maternal deaths per 100,000 live births [8] . The lower ratio could be explained by improvements in the structural and functional capacity of the hospital as well as the fact that many other hospitals in the city of Douala could now act as referral hospitals. However, the ratio of 1176 is far higher than the national ratio of 467 per 100,000 live births. This could be explained by the fact that Laquintinie hospital remain the first reference hospital in Douala and being a public hospital, they do not screen nor refer patients and as such, they continue to receive all types of referred patients from the entire region including poor and vulnerable patients as well as cases that are already in worst states.
4.3. Factors Associated with Maternal Mortality
Young mother’s age between 16 to 24 years was significantly associated with maternal mortality. This is similar to WHO observations in many developing countries [2] . However, the age of 25 - 34 was the most representative. This finding is similar to that of Yego et al. in a study in kenya [19] . The age group of 25 - 34 years is the most active reproductive age group and this could explain the high proportion. Maternal employment was found to be negatively associated with maternal mortality in our study. Maternal employment provides financial autonomy to the women and together with marital status, is effective determinants in the fight against maternal deaths [20] [21] .
Over 60% of cases of maternal death in our study were unmarried women. Tiomela et al working in a hospital in Yaoundé, another town in Cameroon, found similar findings [22] . About 65% of cases of maternal deaths came from areas with poor socio-economic status (Bepanda, Bonaberi, Ndogpassi). These areas coupled with the low socioeconomic status, lack basic health infrastructure hence health inequities are high among women in these areas. Low socioeconomic status could be linked with maternal mortality in various ways. Firstly, with low socioeconomic status, the women will not attend ANC or attend just a few, and secondly, their health literacy will be low. Low socioeconomic status could therefore be an important determinant of maternal death. More so, poverty have been designated as a risk factor for maternal death [23] .
Alcohol consumption is associated with 23-fold increased odds of maternal mortality. Alcohol has been reported by WHO as a risk factor for maternal mortality. This can be explained by negative behaviours associated with alcohol and socio-economic factors [2] .
We found abortion or ectopic pregnancy to be significantly associated with maternal mortality with the odds of dying from abortion or ectopic pregnancy increased 61.5-folds. We included cases of maternal death following an abortion or an ectopic pregnancy in our study so as to be in conformity with the WHO definition [1] of maternal mortality. Surprisingly, abortions and ectopic pregnancies represented about 45% of maternal deaths in our study. This can be explained by the fact that abortion without medical indication is illegal in Cameroon. Most cases of abortions were induced criminal abortions who came consulting or were referred to Laquintinie hospital in critical or complicated states, or death on arrival.
The absence of antenatal visits or having only 1 - 3 antenatal visits were found to be risks factors in this study. This finding corroborates with those of other studies [24] [25] . Antenatal care is important in screening for pre-existing illnesses and complications in the early stages of pregnancy that could impact adversely during pregnancy and childbirth [26] . According to WHO recommendations, the qualitative follow-up of pregnancy includes among other things at least 4 prenatal consultations allowing education in behavioural change, the correction of nutritional deficiencies, the prevention, and treatment of infections [16] . Women who receive good care during the pre-partum period have been shown to be at less risk of maternal morbidity and mortality [17] [18] .
Hemorrhage still remains a main cause of maternal mortality at the Laquintinie hospital, Douala, accounting for over 70% of cases. This result is similar to those found by Essome et al. [8] but higher than the 56.4% reported in 2009 at the Yaoundé University Hospital center [7] . Hemorrhage is reported in literature to be a leading cause of maternal mortality especially in developing countries. In a WHO review of 35,197 maternal deaths in Africa, hemorrhage was found to be the leading cause of death [5] . Anemia is often a consequence of bleeding, however, some cases of anemia in our study had no history of bleeding.
Almost all cases (95%) were referred patients. This rate is similar to the previously reported 92.1% rate at the Laquintinie hospital [8] . This finding is certainly due to the fact that the Laquintinie hospital remains the first referral hospital in Douala. This does not imply referral is a bad practice but rather delays associated with referred case particularly the second and third delays could be the main determinants of survival in referred cases. Our rate is higher than the 82% reported in another study in the University Hospital center in Yaoundé by Fomulu et al. [7] . The high rate in our study could be an indication that capacities of many other health facilities have to be improved in order to provide timely and efficient care to these patients without necessarily referring them. It also implies that the Laquintinie hospital has to improve its preparedness in terms of structure and processes involved in the management of referred women with pregnancy related conditions.
5. Limitation of the Study
Since all those cases of maternal death have been presented at the hospital review and later at the regional review of maternal death cases, the patients files were well conserved. We did not face big difficulties for collecting data and carrying out this study.
6. Conclusion
This study highlights risk factors for mortality at Laquintinie hospital showing the importance of maternal education and amelioration of socio-economic level in preventing maternal mortality. Antenatal visits provide opportunities for the detection of risk factors for specific illnesses that may put a mother at risk during birth. This study also underlines the need to empower peripheral health structures in management of obstetrical emergencies, and training and recruitment of qualified personnel.
Acknowledgements
The authors thank the management of Laquintinie hospital and the staff of the obstetrics and gynecology department for all the facilities granted to them for the completion of this study.
Authors’ Contributions
Boten designed the study, collected the data and wrote the manuscript. Mandeng, Mforteh, Dissack, Ngo dingom, Mbi, Takang, and Dobgima have read and corrected the manuscript. Essome directed the study, supervised the writing of the manuscript and validated the final version.
Abbreviations
LB: Live births;
MDG: Millennium development goal;
MMR: Maternal mortality ratio;
ANC: Antenatal care;
NBU: Newborn unit;
WHO: World Health Organization;
HIV: Human immunodeficiency virus.
Appendix
Retrospective study on Evolution of maternal mortality at Laquintinie Hospital.
Name……………………………………………………………………..
1) Year:………………………………………….………………………..
Part 1: Socio-demographic characteristics.
2) Maternal Age………………………………………………...…………… ( ) 2
3) Occupation
a = Housewife
b = Formal employment
c = Student
d = Seller
e = Hairdresser
f = Others(specify)………………………………………….……………….. ( ) 3
4) Residence
a = Ndogpassi
b = Bepanda
c = Bonaberi
d = Others…………………………………………………………………..... ( ) 4
5) Marital Status
a = Single/Unmarried
b = Maried
c = Divorced
d = Widow………………………………...……………………………….… ( ) 5
6) Education level
a = None
b = Primary school
c = Secondary school
d = University ……………………………………………….………...…….. ( ) 6
7) Religion
a = Christian
b = Muslim
c = Other (specify)………………………………………………………..…. ( ) 7
Part 2: Past history and delivery
8) Gestity et parity:
a - Primigravida
b - Multigravida
c - Grandmultigravida…………………………...…….………………...….. ( ) 8
9) Smoking:
a - Yes
b - No………….……………………………………………………….…….. ( ) 9
10) Drinking Alcohol:
a - Yes
b - No……………………….…………………….………………………… ( ) 10
11) Abortion:
a - Yes
b -No……………..…………………………………………………….….... ( ) 11
12) Twin pregnancy:
a - Yes
b - No…………………………...…….……………..…………..…….……. ( ) 12
13) Mode of delivery:
a - Normal
b - Cesarian section
c - Assisted delivery
d - Did not deliver………………………………………………………….. ( ) 13
14) Pregnancy Stage:
a - Intrapartum
b - Antepartum
c - Postpartum………………………………………………………..…….. ( ) 14
15) Number of Antenatal consultations:
a - None
b - 1 - 3
c - Above 4………………………………………………………………….. ( ) 15
Part 3: Patient status at admission
16) Alive
a - Yes
b - No…………………………………………….…………………...…….. ( ) 16
17) Dystocia
a - Yes
b - No……………………………………………………...………………... ( ) 17
18) Pre-Eclampsia
a - Yes
b - No…………………………..………………………………….....…...… ( ) 18
19) Eclampsia
a - Yes
b - No……………………………………….………………………….…… ( ) 19
20) Haemorrhage
a - Yes
b - No……………………………………………………….………….…… ( ) 20
21) Anemia
a - Yes
b - No…………………………………………………………………….…. ( ) 21
22) Pulse
a - Less than 110 bpm
b - Superior or Egal to 110 bpm…………………………………………… ( ) 22
23) Referral
a - Yes
b - No……………………………………………………………….…….… ( ) 23
COMPARISON: CHI-SQUARE TEST
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Table A1. Sociodemographic risk factors.