Skip to main content
Download PDF
Download ePub

Prevalence and factors associated with short birth interval in the semi-rural community of Kaya, Burkina Faso: results of a community-based survey

Archives of Public Health volume 82, Article number: 171 (2024) Cite this article

Abstract

Background

A short birth interval adversely affects the health of mothers and children. This study aimed to measure the prevalence of short birth intervals and identify their associated factors in a semi-urban setting in Burkina Faso.

Methods

We conducted a cross-sectional study in which data were collected in households between May and October 2022. The dependent variable was the short birth interval (SBI), defined by the World Health Organization as the time between two live births. We performed a multilevel mixed-effects Poisson regression with robust variance to determine the factors associated with the SBI by reporting adjusted prevalence ratios (aPR) with a 95% confidence interval (CI).

Results

A total of 5544 birth intervals were recorded from 4067 women. A short birth interval was found in 1503 cases out of 5544, i.e., a frequency of 27.1%. The prevalence of short birth interval (time between two live births less than 33 months) was higher in never users of modern contraceptive users (aPR = 1.24; 95% CI [1.14–1.34] vs. previous users), in younger ages with aPR of 4.21 (95% CI [3.30–5.37]), 2.47 (95% CI [1.96–3.11]), and 1.45 (95% CI [1.16–1.81]), respectively for under 18, 18–24 years old, and 25–34 years old, compared to 35 and over. Childbirths occurring before the implementation of the maternal and infant free health care policy (aPR = 2.13; 95% CI [1.98–2.30]) and also before the free family planning policy (aPR = 1.53; 95% CI [1.28–1.81]) were more likely to have SBI. Women with low socio-economic positions were also more likely to have SBI.

Conclusion

This study found a high SBI in Burkina Faso (more than one woman out of four). Our results have programmatic implications, as some factors, such as contraceptive practice and socioeconomic status, are modifiable. These factors need particular attention to lengthen birth intervals and, in turn, improve mother–child couple health by reducing short birth interval consequences.

Peer Review reports

Text box 1. Contributions to the literature

• Many authors studied the prevalence and factors associated with short birth intervals and showed that the prevalence is country-dependent.

• Most authors have considered a single birth interval per woman.

• We studied the prevalence and factors associated with short birth intervals using surveillance data, and so, we included multiple birth intervals per woman

• This study is conducted in the context of introducing free care policies for pregnant women and free family planning.

• Apart from socio-demographic factors, both free policies were also found to be protective against short birth intervals.

Background

The short birth interval (time between two live births less than 33 months) has health consequences for both mother and child. It has been shown that a short birth interval, compared with a longer one (greater than or equal to 33 months), increases neonatal, infant, and child mortality by 85%, 116%, and 126%, respectively [1]. Despite the implementation of several strategies to improve maternal and infant health in many countries around the world [2,3,4], mortality rates remain very high globally. According to the United Nations Inter-agency Group for Child Mortality Estimation, if current trends continue, 48.1 million under-5 deaths are projected to occur between 2020 and 2030, almost half of them projected to occur during the neonatal period [5]. One of the factors contributing to these high mortality rates is the short birth interval, which could result in eclampsia, uterine rupture, post-partum haemorrhage, severe anaemia, or even maternal death [6]. The hypertensive and hemorrhagic consequences may account for more than 50% of maternal mortality worldwide [7].

According to the literature, high prevalences of SBI are noted in many African countries: 16.99% as pooled prevalence in 12 East African countries in a study published in 2023 [8], 43.91% in 35 sub-Saharan African countries with 14 of the 35 countries had a prevalence above 43.91% [9], 58.74% in 10 African countries with high fertility [10]. In Burkina Faso, unfortunately, there are few studies on short birth interval: the study by Belachew in 10 African countries reported a prevalence of SBI of 52.32% in 2010.

Several factors are associated with short birth interval: women aged 35 years and above [8, 11], educated women [8, 10], rich women [8, 10], contraceptive users [10], women with shorter breastfeeding [12], and women in rural areas [10] had significantly lower odds of having short birth intervals. In East Africa, Tessema et al. showed that women who belonged to the poorest household, made their own decisions with their husbands/partners or by their husbands or parents alone, lived in households headed by men, had unmet family planning needs, and were multiparous had higher odds of having a short birth interval [8]. Most studies have considered only the woman's most recent birth interval and therefore excluded her previous birth intervals. Some other studies did not use the World Health Organization (WHO) definition of a short birth interval, thus limiting the comparability of the findings across studies, as Islam et al. showed in their published systematic review and meta-analysis [13]. Also, a multicenter study in eight African countries concluded that the determinants of the short birth interval varied from one country to another [11]. Pimentel et al., in a systematic review, noted that shorter breastfeeding and the female sex of the previous child were the only factors systematically associated with a short birth interval. They concluded that future quantitative research should use longitudinal and experimental designs and ensure consistency of outcome and exposure definitions in the search for determinants of short birth intervals [12].

Considering the limitations of previous studies, this study aimed to estimate the prevalence and identify the factors associated with the short birth interval in a semi-urban Municipality in Burkina Faso using the WHO definition and including all women's birth intervals.

Materials and methods

Study setting

The study was conducted in the Kaya Health and Demographic Surveillance System (Kaya-HDSS) catchment area in Kaya municipality, North Central, Burkina Faso. This demographic and health surveillance site has been described elsewhere [14]. It has been operational since 2007 and is managed by the Institut de Recherche en Sciences de la Santé (IRSS). According to the latest General Census of Population and Housing, in 2019, Kaya’s population was estimated at 208,682 [15]. In 2022, the results of the Kaya-HDSS showed a resident population of 82,723, including 21,854 women aged 15 to 49 and 4,888 children under 5. This population-based observatory covers one medical centre, six urban primary health centres known as the Centre de Santé et de Promotion Sociale (CSPS), six rural health centres, and some private health centres. In addition to these primary health centres, the observatory area is also home to the Regional Hospital (CHR), which provides specialist care and acts as a referral centre for the health centres in the four provinces of the Centre-Nord region. The Kaya-HDSS site aims to study demographic, infectious, and chronic disease indicators in the district, observe changes in health over time, evaluate health programs, and provide a basis for policy decisions and capacity to improve the community's health [14].

Study design and period

We conducted a population-based cross-sectional study. Data were collected between May and October 2022 in the Kaya-HDSS catchment area.

Study population

The study population consisted of women of childbearing age (15 to 49 years) living in the Kaya-HDSS site.

Inclusion criteria

This study included women who had had at least two consecutive live births in the previous ten years (2012–2022) and were present in the households when the interviewers visited.

Study variables

The dependent variable in our study was the birth interval for two consecutive live births, a binary variable coded '1' for a birth interval of less than 33 months (considered as short) and '0’ for a birth interval of 33 months or more (considered as optimal), based on the WHO definition [16]. We used all children's dates per woman from 2012 to 2022. Due to the hierarchical type of the variables, we considered trois levels: (i) the delivery level, the woman level (woman could have many deliveries), and the village level. For each level, independent variables were defined, as shown in Table 1.

Table 1 Level-related independent variables
Full size table

Data source and collection

Data were collected through individual interviews with women who met the inclusion criteria and were present in the households when the interviewers visited. Some data were extracted from women's health records and children's birth certificates. The questionnaire included variables such as past and current contraceptive use, the outcome of each pregnancy, the survival of each child, and so on. The data from this study were supplemented by data from the Kaya-HDSS, which are repeated cross-sectional study data. The data extracted from Kaya-HDSS mainly concerned the socio-demographic characteristics of women and their households, socio-economic level, etc.

Data analysis

The data were analyzed using Stata software version 18.0 [17]. Qualitative variables were described using frequencies. Because of the data structure (women have multiple birth intervals), we performed a multilevel mixed-effects Poisson regression with robust variance to determine the factors associated with the short birth interval by reporting prevalence ratios (PR) with a 95% confidence interval rather than odds ratios to avoid a poor approximation of risk because the prevalence found was not low [18,19,20]. After fitting the null model, we first included the level-1 variables (model 1), then the level-2 variables (model 2), and lastly, the level-3 variables (model 3). These models are available in Supplementary File 1. The final multivariable model was selected based on the Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). All statistical tests were two-sided; a p-value < 0.05 was considered statistically significant.

Ethical considerations

The study protocol was approved by the Burkina Faso Health Research Ethics Committee (Deliberation Number 2021–07-165). Each participant provided informed consent before the questionnaire was administered. Women's anonymity and confidentiality were ensured throughout data collection and processing.

Results

Four thousand one hundred eight women had at least two consecutive live births between 2012 and 2022 and were included in this study. Of these, 40 were excluded because of inconsistent data on birth dates. In total, 5,544 birth intervals were analyzed. Figure 1 below shows the flow chart.

Fig. 1
figure 1

Study flow chart

Full size image

Characteristics of pregnancies and deliveries

Out of the deliveries, 81.5% occurred during maternal and infant-free healthcare (after 1 June 2016), and 13.3% of pregnancies began during free family planning (after 1 July 2020), as detailed in Table 2.

Table 2 Characteristics of pregnancies and births (N = 5544)
Full size table

Characteristics of the women

Women who had ever used a modern method of contraception were 71.0%, and 95.7% of women were in union. Table 3 shows the socio-demographic characteristics of the women.

Table 3 Socio-demographic characteristics of the included women (N = 4068)
Full size table

Prevalence of short birth interval and associated factors

A short birth interval was observed in 1503 cases out of 5544, i.e., a frequency of 27.1% (95% CI: 26.0–28.3). Table 4 shows the factors associated with a short birth interval in univariable and multivariable analyses. For example, the adjusted analyses showed that the prevalence of short birth interval was increased by 24% in women who had never used a modern contraceptive method (aPR = 1.24; 95% CI [1.14–1.34]) compared with those who ever used it. Women aged under 18 during their pregnancies, and those aged 18–24, and 25–34, were respectively, 4.21, 2.47, and 1.45 times more likely to experience a SBI, compared with those aged over 35. Other factors, such as pregnancy rank, wealth quintiles, the infant and mother free healthcare policy, and the free family planning policy, were strongly associated with the short birth interval.

Table 4 Univariate and multivariate analyses on factors associated with short birth interval in Burkina Faso (N = 5544)
Full size table

Discussion

The proportion of short birth intervals was 27.1% in our study. This is high in a context where many actions are being undertaken to promote modern contraceptive methods. Some of the factors found in our research can be addressed by implementing or reinforcing specific health policies. For example, our results show that the prevalence of the short birth interval has significantly decreased after the start of the free family planning policy nationwide in 2019. This policy, therefore, needs to be monitored to ensure that it continues to be effective with women. This high prevalence should raise questions and lead to a strengthening of health policies aimed at birth spacing.

This high prevalence is common in many African countries. It has also been noted in the literature, ranging from 16.99% to 58.74%: analyses carried out on Demographic and Health Survey (DHS) databases showed that the pooled prevalence was 16.99% for 12 East African countries in a study published in 2023 [8], and 58.74% as a pooled prevalence in 10 African countries with high fertility [10]. Another study in 35 sub-Saharan African countries found a pooled prevalence of 43.91%, with South Africa having the lowest prevalence (23.25%) and Chad having the highest (59.28%).

Our study has shown that women's age during pregnancy, contraceptive use in the woman's reproductive life, socioeconomic status of the woman, and pregnancy rank were associated with SBI. Several studies [21,22,23] have also found similar results. This study showed that women are more likely to have short birth intervals when young. This association has been found in previous studies [8, 11, 24, 25] in several African countries and Pakistan. Similarly, a scoping review on the determinants of unmet need for family planning among women of childbearing age in low- and middle-income countries found that women's age was negatively associated with unmet need for family planning. This means that as women age, their unmet need for family planning decreases [26]. In our context, this could be explained by young women's desire to have children as soon as possible after marriage. Difficulties in young people's access to contraception could also explain this high likelihood of a short birth interval among young women. For example, a study by Kigongo et al., Uganda, found a significant gap in perceived access to family planning services among young in Lira City [27]. Barriers to family planning use among these young include privacy concerns, fear of mistreatment, and difficulty making decisions [27, 28]. In addition to barriers, socio-cultural and religious norms may encourage the desire to have many children. So, certain religious beliefs may also influence fertility and family planning decisions by promoting the idea of procreation, which may encourage couples to have short birth intervals, as reported by several authors in Nigeria and Uganda [29,30,31]. For example, the study in Nigeria on the social context of fertility desire among young men and women aged 15–24 showed that 71% of 2674 young men and 53% of 9637 young women had an ideal number of children greater than four [29]. These results suggest reinforcing all the sensibilizations to young people and also developing and implementing health interventions, especially family planning interventions, to target young women better and, therefore, improve their access to family planning services.

However, these results are inconsistent with our results, which show the association between pregnancy rank and short birth interval. Indeed, our results showed that second and third-order pregnancies tended to occur more after an appropriate birth interval than higher-order pregnancies. Although we could not find a study to better compare our results, given the strong association between age and short birth interval on the one hand, and given that this result is consistent with the results of previous studies, we might think that some interaction or confounding factor may have contributed to this weak association between pregnancy rank and short birth interval. This is particularly true as the univariate analysis found no association between pregnancy rank and short birth interval.

Our results also showed that the wealth index was associated with a short birth interval: the prevalence of a short birth interval was higher among women in the poor and very poor quintiles than their counterparts in the rich and very rich quintiles. This result supports the conclusions of several other studies [12, 32,33,34]. Women in the wealthiest groups had greater access to quality primary care than women in the poorest group. For example, women in the rich and very rich quintiles would benefit from more prenatal contacts. However, an increase in antenatal visits has been shown to reduce the risk of having a short birth interval [35].

Furthermore, women in the rich and very rich quintiles may be better educated than those in the poorer groups. Given the strong link between education level and desire for children (negative association between formal schooling and desired fertility) [36, 37], they could, therefore, space births better than poor women. However, a study in Ethiopia showed that poor households were less likely than wealthy households to have a short birth interval [38]. This author nevertheless pointed out the presence of recall bias in his study concerning the actual interval between births and bias in the measurement of the wealth index, which could explain his results, which were at odds with ours and the data in the literature.

In our study, the place of residence did not determine the birth interval length. While some studies have shown no difference between rural and urban women regarding the birth interval length [39, 40], others have shown that rural women are more likely to have a short birth interval than urban women [34, 41, 42]. A difference in the composition of the place of residence in these countries could justify the differences between these results. Furthermore, in our study, the Nord Central region, where the Kaya-HDSS is located, has been affected by security issues for nearly eight years now, and many rural women from rural areas have moved to the city of Kaya. Therefore, the place of residence variable is subject to significant misclassification, which may explain the lack of association between the place of residence and the short birth interval.

Finally, it should be noted that the short birth interval may be the result of a deliberate choice on the part of the woman or even the couple: in Nigeria, in 2010, a study reported as its main findings the fact that the women attributed responsibility for a high parity to their husbands. They had deliberately given birth to many children to inhibit men's tendency to divorce or enter into multiple marriages [43].

The main strengths of this study are (i) its design, which uses data from all women's birth intervals over ten years, and (ii) the multilevel mixed-effects Poisson regression with robust variance we performed to determine the factors associated with the short birth interval by reporting prevalence ratios, compared to previous studies. The main limitation is the recall bias that arises when women are asked about past events, such as past childbirths, if the existing documentation does not allow the event to be located accurately.

Conclusion

At the end of this study, we found that the prevalence of short birth intervals is still high in Burkina Faso (more than one woman in four). Our results have programmatic implications because some factors, such as contraceptive practice and socioeconomic status, and woman age, are modifiable. These factors merit particular attention to lengthening birth intervals and, in turn, reduce their consequences by improving the health of the mother–child couple. Activities to encourage contraceptive use should, family planning interventions to target young women better and, therefore, be stepped up to increase the number of new users and retain existing users. These users will increase their chances of having an appropriate birth interval.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Shifti DM, Chojenta C, Holliday E, Loxton D. Effects of short birth interval on neonatal, infant and under-five child mortality in Ethiopia: a nationally representative observational study using inverse probability of treatment weighting. BMJ Open. 2021;11(8):e047892.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Gülmezoglu AM, Lawrie TA, Hezelgrave N, Oladapo OT, Souza JP, Gielen M, et al. Interventions to Reduce Maternal and Newborn Morbidity and Mortality. In: Black RE, Laxminarayan R, Temmerman M, Walker N, editors. Reproductive, Maternal, Newborn, and Child Health: Disease Control Priorities, Third Edition (Volume 2). Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2016. Available from: http://www.ncbi.nlm.nih.gov/books/NBK361904/. Cited 2024 Jan 10.

  3. Lassi ZS, Bhutta ZA. Community-based intervention packages for reducing maternal and neonatal morbidity and mortality and improving neonatal outcomes. Cochrane Database Syst Rev. 2015;2015(3):CD007754.

    PubMed  PubMed Central  Google Scholar 

  4. Kuruvilla S, Schweitzer J, Bishai D, Chowdhury S, Caramani D, Frost L, et al. Success factors for reducing maternal and child mortality. Bull World Health Organ. 2014;92(7):533–44 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121875/. Cited 2024 Jan 10 .

    Article  PubMed  PubMed Central  Google Scholar 

  5. Sharrow D, Hug L, You D, Alkema L, Black R, Cousens S, et al. Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. Lancet Glob Health. 2022;10(2):e195–206.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Sanga LA, Mtuy T, Philemon RN, Mahande MJ. Inter-pregnancy interval and associated adverse maternal outcomes among women who delivered at Kilimanjaro Christian Medical Centre in Tanzania, 2000–2015. PLoS ONE. 2020;15(2): e0228330.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Say L, Chou D, Gemmill A, Tuncalp O, Moller A, Daniels J. Global causes of maternal death: a WHO systematic analysis. Lancet Glob Heal. 2014;2(6):323–33.

    Article  Google Scholar 

  8. Tesema GA, Wolde M, Tamirat KS, Worku MG, Fente BM, Tsega SS, et al. Factors associated with short birth interval among reproductive-age women in East Africa. Womens Health.  2023;19:17455057231209880. Available from:  https://doi.org/10.1177/17455057231209879. Cited 2024 Jan 10.

  9. Mare KU, Sabo KG, Mohammed AA, Leyto SM, Mulaw GF, Tebeje TM, et al. Suboptimal birth spacing practice and its predictors among reproductive-age women in Sub-Saharan African countries: a multilevel mixed-effects modeling with robust Poisson regression. Reprod Health. 2023;20:132. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10476311/. Cited 2024 Jan 11.

  10. Belachew TB, Asmamaw DB, Negash WD. Short birth interval and its predictors among reproductive age women in high fertility countries in sub-Saharan Africa: a multilevel analysis of recent demographic and health surveys. BMC Pregnancy Childbirth. 2023;23(1):81 Available from: https://bmcpregnancychildbirth.biomedcentral.com/articles/10.1186/s12884-023-05403-0. Cited 2024 Jan 11 .

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ajayi AI, Somefun OD. Patterns and determinants of short and long birth intervals among women in selected sub-Saharan African countries. Medicine (Baltimore). 2020;99(19):e20118.

    Article  PubMed  Google Scholar 

  12. Pimentel J, Ansari U, Omer K, Gidado Y, Baba MC, Andersson N, et al. Factors associated with short birth interval in low- and middle-income countries: a systematic review. BMC Pregnancy Childbirth. 2020;20:156 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7069040/. Cited 2024 Jan 11 .

    Article  PubMed  PubMed Central  Google Scholar 

  13. Islam MZ, Billah A, Islam MM, Rahman M, Khan N. Negative effects of short birth interval on child mortality in low- and middle-income countries: a systematic review and meta-analysis. J Glob Health. 2022;3(12):04070.

    Article  Google Scholar 

  14. Kouanda S, Bado A, Yaméogo M, Nitièma J, Yaméogo G, Bocoum F, et al. The Kaya HDSS, Burkina Faso: a platform for epidemiological studies and health programme evaluation. Int J Epidemiol. 2013;42(3):741–9.

    Article  PubMed  Google Scholar 

  15. Institut National de la Statistique et de la Démographie du Burkina Faso et ICF. 2023. Enquête démographique et de santé du Burkina Faso. 2021. Ouagadougou, Burkina Faso et Rockville, Maryland, USA: INSD et ICF.

  16. World Health Organization. Report of a WHO technical consultation on birth spacing: Geneva, Switzerland 13–15 June 2005. 2005. Available from: https://www.who.int/publications-detail-redirect/WHO-RHR-07.1. Cited 2024 Mar 1.

  17. StataCorp. Stata Statistical Software: Release 18. College Station, TX: StataCorp LLC; 2023.

  18. Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702–6.

    Article  PubMed  Google Scholar 

  19. Chen W, Qian L, Shi J, Franklin M. Comparing performance between log-binomial and robust Poisson regression models for estimating risk ratios under model misspecification. BMC Med Res Methodol. 2018 Jun 22;18(1):63. Available from: https://doi.org/10.1186/s12874-018-0519-5. Cited 2024 Jan 11.

  20. Zou G, Donner A. Extension of the modified poisson regression model to prospective studies with correlated binary data. Stat Methods Med Res. 2013;22(6):661–70. Available from: https://doi.org/10.1177/0962280211427759. Cited 2024 Jan 11.

  21. de Jonge HCC, Azad K, Seward N, Kuddus A, Shaha S, Beard J, et al. Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study. BMC Pregnancy Childbirth. 2014;24(14):427.

    Article  Google Scholar 

  22. Dim CC, Ugwu EO, Iloghalu EI. Duration and determinants of inter-birth interval among women in Enugu, south-eastern Nigeri. J Obstet Gynaecol. 2013;33(2):175–9.

    Article  CAS  PubMed  Google Scholar 

  23. Ejigu AG, Yismaw AE, Limenih MA. The effect of sex of last child on short birth interval practice: the case of northern Ethiopian pregnant women. BMC Res Notes. 2019;12(1):75.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Nausheen S, Bhura M, Hackett K, Hussain I, Shaikh Z, Rizvi A, et al. Determinants of short birth intervals among married women: a cross-sectional study in Karachi, Pakistan. BMJ Open. 2021;11(4):e043786.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ajong AB, Mangala FN, Bekolo CE, Yakum MN, Waffo LM, Kenfack B. Risk factors for short birth interval: A hospital-based cross-sectional study among women in the Nkongsamba Health District, Littoral Region, Cameroon. PLOS Glob Public Health. 2023;3(7):e0001446. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10389728/. Cited 2024 Jul 9.

  26. Wulifan JK, Brenner S, Jahn A, De Allegri M. A scoping review on determinants of unmet need for family planning among women of reproductive age in low and middle income countries. BMC Womens Health. 2016;15(16):2.

    Article  Google Scholar 

  27. Kigongo E, Tumwesigye R, Anyolitho MK, Musinguzi M, Kwizera G, Achan E, et al. Access to family planning services and associated factors among young people in Lira city northern Uganda. BMC Public Health. 2024;24(1):1146.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hall KS, Manu A, Morhe E, Dalton VK, Challa S, Loll D, et al. Bad girl and unmet family planning need among Sub-Saharan African adolescents: the role of sexual and reproductive health stigma. Qual Res Med Healthc. 2018;2(1):55–64 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6292434/. Cited 2024 Jul 17 .

    Article  PubMed  Google Scholar 

  29. Akinyemi JO, Odimegwu CO. Social contexts of fertility desire among non-childbearing young men and women aged 15–24 years in Nigeria. Reprod Health. 2021;18:186.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Kabagenyi A, Reid A, Ntozi J, Atuyambe L. Socio-cultural inhibitors to use of modern contraceptive techniques in rural Uganda: a qualitative study. Pan Afr Med J. 2016;25(78). Available from: https://www.panafrican-med-journal.com/content/article/25/78/full. Cited 2024 Jul 17.

  31. Srikanthan A, Reid RL. Religious and cultural influences on contraception. J Obstet Gynaecol Can JOGC. 2008;30(2):129–37.

    Article  PubMed  Google Scholar 

  32. Shifti DM, Chojenta C, Holliday EG, Loxton D. Individual and community level determinants of short birth interval in Ethiopia: a multilevel analysis. PLOS ONE. 2020;15(1):e0227798.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Hailu D, Gulte T. Determinants of short interbirth interval among reproductive age mothers in Arba Minch district Ethiopia. Int J Reprod Med. 2016;2016:6072437 Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4863097/. Cited 2021 Nov 12 .

    Article  PubMed  PubMed Central  Google Scholar 

  34. Shifti DM, Chojenta C, Holliday EG, Loxton D. Socioeconomic inequality in short birth interval in Ethiopia: a decomposition analysis. BMC Public Health. 2020;20(1):1504.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Mihretie GN, Yenealem Beyene F, Getnet Kassa B, Degu Ayele A, Muche Liyeh T, Minuye BB. Determinants of short birth interval among women in South Gondar, Ethiopia: community-based unmatched case-control study. Arch Public Health Arch Belg Sante Publique. 2021;79(1):47.

    Article  Google Scholar 

  36. Church AC, Ibitoye M, Chettri S, Casterline JB. Traditional supports and contemporary disrupters of high fertility desires in sub-Saharan Africa: a scoping review. Reprod Health. 2023;20(1):86. Available from: https://doi.org/10.1186/s12978-023-01627-7. Cited 2024 Jan 11.

  37. Bongaarts J. Trends in fertility and fertility preferences in sub-Saharan Africa: the roles of education and family planning programs. Genus. 2020;76(1):32. Available from: https://doi.org/10.1186/s41118-020-00098-z. Cited 2024 Jan 11.

    Article  Google Scholar 

  38. Yohannes S, Wondafrash M, Abera M, Girma E. Duration and determinants of birth interval among women of child bearing age in Southern Ethiopia. BMC Pregnancy Childbirth. 2011;11(1):38.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Chirwa TF, Mantempa JN, Kinziunga FL, Kandala JD, Kandala NB. An exploratory spatial analysis of geographical inequalities of birth intervals among young women in the Democratic Republic of Congo (DRC): a cross-sectional study. BMC Pregnancy Childbirth. 2014;13(14):271.

    Article  Google Scholar 

  40. Exavery A, Mrema S, Shamte A, Bietsch K, Mosha D, Mbaruku G, et al. Levels and correlates of non-adherence to WHO recommended inter-birth intervals in Rufiji, Tanzania. BMC Pregnancy Childbirth. 2012;13(12):152.

    Article  Google Scholar 

  41. Aychiluhm SB, Tadesse AW, Mare KU, Abdu M, Ketema A. A multilevel analysis of short birth interval and its determinants among reproductive age women in developing regions of Ethiopia. PLoS ONE. 2020;15(8): e0237602.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ngianga-Bakwin K, Stones RW. Birth intervals and injectable contraception in sub-Saharan Africa. Contraception. 2005;71(5):353–6.

    Article  PubMed  Google Scholar 

  43. Izugbara CO, Ezeh AC. Women and high fertility in Islamic northern Nigeria. Stud Fam Plann. 2010;41(3):193–204.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

We sincerely thank Fatou Sissoko, Vincent Bagnoa, Bouraima Kabré, Ambroise Bamogo, and all the interviewers for their support during data collection.

Funding

This study received no specific funding. The data come from the Kaya-HDSS and are collected annually. Our research centre funded only the cost of data collection.

Author information

Authors and Affiliations

  1. Département Biomédical et Santé Publique, Institut de Recherche en Sciences de La Santé (IRSS), Centre National de La Recherche Scientifique et Technologique (CNRST), Ouagadougou, Burkina Faso

    Abou Coulibaly, Adama Baguiya, Ivlabèhirè Bertrand Meda, Franck Garanet & Seni Kouanda

  2. Institut Africain de Santé Publique, Ouagadougou, Burkina Faso

    Tiéba Millogo, Aristide Marie Arsène Koumbem & Seni Kouanda

Authors
  1. Abou Coulibaly
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adama Baguiya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ivlabèhirè Bertrand Meda
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tiéba Millogo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Aristide Marie Arsène Koumbem
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Franck Garanet
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Seni Kouanda
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: AC. Methodology: AC. Supervision of data collection: AC, AB, FG. Validation: AC, AB, FG. Formal analysis:  AC, AB, IBM, TM. Writing-original draft preparation: AC. Writing-review and editing: AC, AB, IBM, TM, AMAK. Project administration: AB, SK.  All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Abou Coulibaly.

Ethics declarations

Ethics approval and consent to participate

The study protocol was approved by the Burkina Faso Health Research Ethics Committee (Deliberation Number 2021–07-165). Each participant provided informed consent before the questionnaire was administered. Women's anonymity and confidentiality were ensured throughout data collection and processing.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coulibaly, A., Baguiya, A., Meda, I.B. et al. Prevalence and factors associated with short birth interval in the semi-rural community of Kaya, Burkina Faso: results of a community-based survey. Arch Public Health 82, 171 (2024). https://doi.org/10.1186/s13690-024-01398-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13690-024-01398-y

Keywords

Archives of Public Health

ISSN: 2049-3258