Inter pregnancy interval is defined as ‘the time between the end of a pregnancy and the start of another pregnancy’ (World Health Organization (WHO), 2005). A short interpregnancy interval has been defined by the WHO (2013) as ‘a period of less than 24 months from last delivery to the current pregnancy’ while a long interval is defined as ‘an interval of longer than 59 months’. The recommended optimal interpregnancy interval according to many international agencies is to leave at least 2 years after a live birth or 6 months after spontaneous miscarriage or induced abortion before conceiving another pregnancy (Marinovich et al, 2019).
Although birth spacing is becoming a prominent health promotion intervention for women and children's health, the prevalence of short interpregnancy intervals is rising. In low-income countries such as Nigeria, the prevalence of short interpregnancy interval ranges from 19.4–65.9% (Bassey et al, 2016). Pregnancies conceived after a short interpregnancy interval place both mother and fetus in danger, while the optimal interpregnancy interval is a crucial driver of maternal health and favours perinatal outcomes (Arabin and Baschat, 2017). Therefore, maintaining an optimal interval between pregnancies is necessary to avoid high-risk pregnancies (Gilmore et al, 2015).
Globally, the prevalence of short interpregnancy intervals is around 25% of live births (Ajayi and Somefun, 2020). The prevalence varies globally. In the USA, approximately one in three pregnancies are conceived within 18 months of a previous pregnancy (Belaid et al, 2021). The estimated prevalence of a short interpregnancy interval is 33% in Central Asia, which is equivalent to 19.4–65.9% in low-income countries (Rutstein, 2011; Mamo et al, 2021), around 26% in Bangladesh, affecting more than 1 million live births per year (Khan et al, 2020) and approximately 34.2% in Egypt (Mahfouz et al, 2018). According to the annual health report from 2019, in Oman, 22.7 % of Omani women have a short interpregnancy interval (Ministry of Health (MoH), 2012).
An interpregnancy interval of ≤24 months is linked with an increased risk of adverse maternal and perinatal outcomes (Lilungulu et al, 2015). Specifically, it is associated with higher maternal risks, such as iron deficiency anaemia, gestational diabetes mellitus, postpartum haemorrhage, failure of vaginal birth after caesarean, preterm premature rupture of membrane and pre-eclampsia (Lilungulu et al, 2015; Shrestha et al, 2020). The evidence indicates that a short interpregnancy interval is linked with an increased risk of maternal morbidities and mortality before, during and after pregnancy and birth (Saral and Cambaz Ulaş, 2019). Women who have had a previous caesarean section and have a short interpregnancy interval are at increased risk of uterine rupture (Zhang et al, 2018a).
A short interval is linked with increased perinatal health risks as well, such as being small for their gestational age, a preterm birth, a low birth weight and a low APGAR score (Gebremedhin et al, 2018). Adverse perinatal outcomes such as neonatal mortality, intrauterine growth retardation and intrauterine fetal death have been reported in neonates of women with short interpregnancy intervals (Coo et al, 2017; Ahrens et al, 2019).
There are also long-term complications that have been found to be associated with a short interpregnancy interval including socioeconomic burdens, reduced parental longevity and developmental delay or intellectual disabilities in the child (Cheslack-Postova et al, 2011; Read et al, 2011; Grundy and Kravdal, 2014). A short interpregnancy interval contributes to approximately 30% of maternal and 20% of child mortality (Cleland et al, 2012). It is therefore important to encourage increased efforts by healthcare providers to support women's access to and use of contraceptive services, to allow for birth spacing.
Researchers have reported that the association between interpregnancy interval and adverse pregnancy outcomes is not causal and is instead attributable to the few predictors correlated with interpregnancy interval (Ball et al, 2014). Risk factors, including maternal demographics, socioeconomic status, lifestyle and ethnicity, influence interpregnancy interval (Islam, 2017). Additionally, the length of interpregnancy intervals has been found to be influenced by a lack of contraceptive use, short or lack of exclusive breastfeeding, number of living children, absence of a male child, a couple's educational background, a history of infertility, number of antenatal visits, mode of birth in a previous pregnancy, and history of perinatal death or pregnancy loss in the previous pregnancy (Begna et al, 2013; Shimels Hailemeskel et al, 2020; Addisu et al, 2021).
In Oman, the MoH began the birth spacing programme in 1994. The main objective of the programme is to improve the wellbeing of women and their children by encouraging spacing of births by 3 years or more through contraceptive methods (MoH, 2012; Al-Balushi et al, 2015). This allows women time to recover after birth and restore their health and fitness. It also means that the newborn receives adequate time and attention from their mothers between pregnancies (MoH, 2012). Birth spacing counselling services are offered across all primary and secondary health centers throughout Oman, as part of maternal and child health services. Through these centers, a wide range of free and different contraceptive methods are made available to all women who wish to plan for an optimal interval between pregnancies. These methods include condoms, intrauterine contraceptive devices, combined oral contraceptive pills, progesterone-only pills, hormonal injections and implant devices (WHO, 2005).
However, it has been found that these services are underused by Omani women (Al-Balushi et al, 2015). In 2019, the total number of women who attended the birth spacing clinics was 20 263, a reduction from the 20 909 women who attended in 2015. Cultural, social and religious reasons may discourage Omani women from participating in counselling. These beliefs emphasis the importance of increased family size and a short interpregnancy interval in Omani society (Al-Barwani and Albeely, 2007). This is despite the fact that the birth spacing programme was initiated with the approval of the nation's religious leaders. Birth spacing is addressed in the Holy Quran, where women are advised to breastfeed their infants for 2 years.
The birth spacing programme can protect women and their babies from adverse pregnancy outcomes caused by short interpregnancy intervals (Al Kindi and Al Sumri, 2019). In Oman, birth spacing has been found to be a significant predictor of low birth weight and preterm birth (Islam, 2017). Exploring adverse pregnancy outcomes and predictors of short interpregnancy interval in Oman is essential to understanding high-risk pregnancies and how they are related to short interpregnancy intervals. This knowledge will help inform appropriate policies within Oman's birth spacing programme. The present study aimed to determine the association between short interpregnancy interval and adverse pregnancy outcomes among Omani women and examine associated risk factors.
Methods
This study used a quantitative research approach with a retrospective, matched case-control design. It was conducted in the obstetric units of Sultan Qaboos University Hospital and Al-Rustaq Hospital. Sultan Qaboos University Hospital is a tertiary care teaching hospital located in Muscat Governorate with a 600-bed capacity. Al-Rustaq Hospital is located in South Batinah Governorate with a 235-bed capacity. Women from urban and rural communities seek obstetric care from these hospitals, and so they were selected for the study, to ensure a diverse sample. The study used the medical records from the hospitals to draw the data for the study.
Study population
All women of reproductive age who had at least two births were the target population. The accessible population was women who gave birth in the study settings between January and December 2020.
The medical records of Omani women aged 20–49 years old who had completed 20 weeks' gestation in their current pregnancy, who had a spontaneous vaginal birth during the study period in the study setting within 24 months of their last birth and who had complete medical records were selected for the ‘case’ group. The records of those who gave birth more than 24 months after their last birth (24–59 months) were selected for the ‘control’ group. Matching between the case and control groups was done based on maternal age and parity.
The exclusion criteria for both groups were records from women who gave birth to multiple infants (twins or more), who had a history of recurrent abortion or miscarriage, who gave birth prematurely before 20 weeks' gestation, were primipara, were known to have chronic medical conditions (such as hypertension, diabetes mellitus, cancer, heart diseases, myasthenia gravis, sickle cell disease, systemic lupus erythematosus) or whose medical records were 10% or more incomplete.
Sampling
OpenEpi (version 3) and an open-source calculator for epidemiologic statistics were used to estimate sample size. Using a two-sided test, 95% confidence level, 80% power, and a case-to-control ratio of 1:2, the minimum required sample size for the case group was 187 and 374 for the control group. After manually matching cases with controls in a ratio of 1:2, the researcher obtained a final sample size of 199 for the case group and 398 for the control group.
Data collection
Participants' medical records and delivery registry books were used to retrieve the data. A standardised report form was developed by the researchers for the study and used to collect the participants' demographic characteristics, and data on maternal and neonatal outcomes. The form was developed based on an extensive literature review of previously published literature.
The tool's content validity was ascertained in consultation with experts in midwifery and neonatology. The tool was pre-tested to assess its usability through a pilot study with 10% of the total sample (19 participants from both groups). The pilot study helped determine documentation and recording styles in both hospitals. To ensure the collected data's quality for the pilot study, the study researchers verified the authenticity of collected data. The samples used were excluded from the main study and the pilot study revealed that no information was available regarding mother's occupational status, smoking status and pregnancy intention. These variables were removed from the data collection sheet.
The researcher evaluated potential medical records to determine their eligibility for inclusion in the study. After screening, the researcher prepared the groups of cases and controls, and categorised them based on age and parity. After finalising the required number of participants in both groups, the researcher collected the data from the medical records and delivery register books using hospital identification numbers. Medical record systems, including ‘Trakcare’ and ‘Alshifa'a’ were used to extract information not included in the delivery register books.
An extensive quality check was performed by the researchers to ensure the collected data's completion and validity. The information extracted from the registry was found to be valid and a second data quality check was performed after entering the data into the Statistical Package for Social Sciences.
Data analysis
The data were analysed using the Statistical Package for Social Sciences (version 26). Continuous variables were expressed as means and standard deviations. Categorical variables were expressed as numbers and percentages. Bivariate analysis was conducted to ascertain the unadjusted associations between short interpregnancy interval and each outcome variable separately. Multivariable analysis was performed to obtain adjusted odds ratios. A logistic regression model was used to ascertain significant predictors of short interpregnancy intervals. A P value of less than 0.05, with a 95% confidence interval, was considered significant.
Ethical considerations
Ethical approvals were obtained from three different research committees, the Medical Research Ethics Committee at Sultan Qaboos University Hospital, the Research and Ethical Review and Approve Committee of the Ministry of Health and the College of Nursing at Sultan Qaboos University. The director generals of the two hospitals were contacted to seek permission to start the data collection. As a result of the study's retrospective design, informed consent for this study was not required.
During data collection, women's information remained confidential. Hard copies of the data collection sheets were secured in a locked cupboard and accessed only by the study researcher. All data were stored in a password-protected computer and will be disposed of 2 years after the study period.
Results
A total of 597 eligible women were included in the study, 297 from Sultan Qaboos University Hospital and 300 from Al-Rustaq Hospital. A third (33.3%) of the included records were from women who had a short interpregnancy interval (cases). The average maternal age was 31 years (standard deviation=4.8 years), and the average maternal age at first birth was 24.2 years (standard deviation=3.6 years) for the case group and 23.0 years (standard deviation=3.5 years) for the control group.
Most women (56%) in both groups had attended secondary education and had a similar average pre-pregnancy body mass index at booking (28.9 kg/m2). Women with short interpregnancy intervals had an average haemoglobin level of 10.9g/dl (standard deviation=1.16g/dl), while those with optimal interpregnancy intervals had an average level of 11.3g/dl (standard deviation=1.32g/dl). At birth, a greater proportion of women with short interpregnancy intervals (25.1%) required induced labour than women with optimal interpregnancy intervals (12.6%) (Table 1).
Table 1. Demographic and health-related characteristics
| Characteristic | Category | Frequency, n (%) | |
|---|---|---|---|
| Case, n=199 (%) | Control, n=398 (%) | ||
| Setting | Sultan Qaboos University Hospital | 67 (33.7) | 230 (57.8) |
| Al Rustaq | 132 (66.3) | 168 (42.2) | |
| Age (years) | 20–24 | 17 (8.5) | 35 (8.8) |
| 25–29 | 56 (28.1) | 113 (28.4) | |
| 30–34 | 70 (35.2) | 140 (35.2) | |
| 35–39 | 45 (22.6) | 88 (22.1) | |
| >39 | 11 (5.5) | 22 (5.5) | |
| Education | Primary | 10 (5.0) | 28 (7.0) |
| Secondary | 112 (56.3) | 226 (56.8) | |
| Higher | 77 (38.7) | 144 (36.2) | |
| Parity | ≤2 | 83 (41.7) | 152 (38.2) |
| >2 | 116 (58.3) | 246 (61.8) | |
| Type of birth | Spontaneous | 149 (74.9) | 347 (87.2) |
| Induced | 50 (25.1) | 51 (12.8) | |
| Baby's sex | Male | 94 (47.2) | 212 (53.3) |
| Female | 105 (52.8) | 186 (46.7) | |
| Preterm birth | Yes | 14 (7.0) | 16 (4.0) |
| No | 185 (93.0) | 382 (96.0) | |
| Preterm premature rupture of membrane | Yes | 5 (2.5) | 3 (0.8) |
| No | 194 (97.5) | 395 (99.2) | |
| Low birth weight | Yes | 17 (8.5) | 22 (5.5) |
| No | 182 (91.5) | 376 (94.5) | |
| Gestational diabetes mellitus | Yes | 30 (37.0) | 51 (12.8) |
| No | 169 (84.9) | 347 (87.2) | |
| Postpartum haemorrhage | Yes | 1 (0.5) | 1 (0.3) |
| No | 198 (99.5) | 397 (99.7) | |
| Gestational age | Mean (standard deviation) | 37.87 (2.39) | 38.24 (1.98) |
| Body mass index at booking | Mean (standard deviation) | 28.92 (5.5) | 28.96 (5.6) |
| Live babies | Mean (standard deviation) | 2.99 (1.96) | 2.97 (1.53) |
| HB level | Mean (standard deviation) | 10.9 (1.16) | 11.36 (1.32) |
| Hematocrit level | Mean (standard deviation) | 34.72 (5.36) | 35.91 (4.43) |
Adverse outcomes
Analysis of the prevalence of adverse pregnancy outcomes showed iron deficiency anaemia (56.8% vs 35.8%), gestational diabetes mellitus (31.7% vs 29.6%), postpartum haemorrhage (10.6% vs 2.8%), preterm premature rupture of membrane (3% vs 1.5%), preterm birth (13.6% vs 5.8%) and low birth weight (16.5% vs 6.4%) were more prevalent among women with short interpregnancy intervals (Table 2). The Chi-squared tests, shown in Table 3, showed a significant relationship between interpregnancy interval and the prevalence of postpartum haemorrhage (P<0.001), iron deficiency anaemia (P<0.001), preterm birth (P=0.002) and low birth weight (P<0.001).
Table 2. Prevalence of adverse pregnancy outcomes
| Outcome | Frequency, n (%) | |
|---|---|---|
| Case, n=199 | Control, n=398 | |
| Iron deficiency anaemia | 113 (56.8) | 142 (35.8) |
| Postpartum haemorrhage | 21 (10.6) | 11 (2.8) |
| Gestational diabetes mellitus | 63 (31.7) | 118 (29.6) |
| Preterm premature rupture of membrane | 6 (3.0) | 6 (1.5) |
| Preterm birth | 27 (13.6) | 23 (5.8) |
| Low birth weight | 32 (16.5) | 25 (6.4) |
Table 3. Analysis of interpregnancy interval and adverse pregnancy outcomes
| Variable | Category | Frequency, n (%) | Chi-squared | Unadjusted odds ratio | Relative risk | Confidence interval | P value | |
|---|---|---|---|---|---|---|---|---|
| Case | Control | |||||||
| Postpartum haemorrhage | Yes | 21 (10.6) | 11 (2.8) | 15.86 | 4.151 | 3.818 | 1.959–8.794 | <0.001 |
| No | 178 (89.4) | 387 (97.2) | ||||||
| Gestational diabetes mellitus | Yes | 63 (31.7) | 118 (29.6) | 0.254 | 1.099 | 1.068 | 0.761–1.588 | 0.637 |
| No | 136 (68.3) | 280 (70.4) | ||||||
| Preterm premature rupture of membrane | Yes | 6 (3.0) | 6 (1.5) | 1.531 | 2.031 | 2.000 | 0.647–6.380 | 0.228 |
| No | 193 (97.0) | 392 (98.5) | ||||||
| Iron deficiency anaemia | Yes | 113 (56.8) | 142 (35.8) | 2.392 | 2.360 | 1.588 | 1.667–3.340 | <0.001 |
| No | 86 (43.2) | 255 (64.2) | ||||||
| Preterm birth | Yes | 27 (13.6) | 23 (5.8) | 10.488 | 2.559 | 2.348 | 1.426–4.593 | 0.002 |
| No | 172 (86.4) | 375 (94.2) | ||||||
| Low birth weight | Yes | 32 (16.5) | 25 (6.4) | 15.213 | 2.908 | 1.582 | 1.582–1.669 | <0.001 |
| No | 162 (83.5) | 368 (93.6) | ||||||
The regression analysis indicated that there was a statistically significant positive relationship between interpregnancy interval and the risk of developing iron deficiency anaemia during pregnancy (P<0.001), and postpartum haemorrhage after birth (P<0.001) as well as with giving birth to a baby with low birth weight (P=0.012) (Tables 3 and 4).
Table 4. Regression analysis (adjusted odds ratios) of interpregnancy interval and outcomes
| Variable | B | Standard error | Wald | Df | P value | Exp (B) | 95% confidence interval |
|---|---|---|---|---|---|---|---|
| Postpartum haemorrhage | 1.097 | 0.405 | 7.347 | 1 | 0.007 | 2.994 | 1.355–6.617 |
| Iron deficiency anemia | 0.799 | 0.187 | 18.201 | 1 | 0.000 | 2.222 | 1.540–3.207 |
| Low birth weight | 0.892 | 0.355 | 6.336 | 1 | 0.012 | 2.441 | 1.218–4.891 |
| Preterm birth | 0.282 | 0.390 | 0.521 | 1 | 0.471 | 1.325 | 0.617–2.849 |
Predictors of short interpregnancy intervals
Binary logistic regression was used to examine predictors of a short interpregnancy interval; the variables tested were mother's age, age at first birth, parity, number of live babies, education (of both a mother and her partner), gender of previous baby, history of perinatal loss and history of infertility. The multicollinearity assumption was assessed before conducting the test by using Spearman's bivariate matrix was used to test for possible collinearity. The matrix showed no significant correlation (>0.6), suggesting a weak to moderate association between variables. Table 5 shows the results of bivariate analysis, with the significant risk factors being entered into the logistic regression model to calculate adjusted odd ratios (Table 6).
Table 5. Bivariate correlation matrix for predictors of a short interpregnancy interval
| Variable | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|
| 1. Age of mother | 1.000 | 0.005 | 0.582† | 0.424† | -0.122† | 0.069 | -0.084* | -0.048 | 0.591† |
| 2. Husband's education | 0.005 | 1.000 | -0.108† | 0.096* | -0.006 | -0.019 | 0.083* | 0.374† | -0.098* |
| 3. Parity | 0.582† | -0.108† | 1.000 | -0.156† | -0.036 | 0.030 | -0.068 | -0.228† | 0.979† |
| 4. Age at first birth | 0.424† | 0.096* | -0.156† | 1.000 | -0.054 | -0.008 | -0.038 | 0.278† | -0.145† |
| 5. History of infertility | -0.122† | -0.006 | -0.036 | -0.054 | 1.000 | 0.053 | 0.050 | -0.027 | -0.032 |
| 6. Previous perinatal loss | 0.069 | -0.019 | 0.030 | -0.008 | 0.053 | 1.000 | 0.031 | -0.059 | 0.119† |
| 7. Sex of previous children | -0.084* | 0.083* | -0.068 | -0.038 | 0.050 | 0.031 | 1.000 | -0.028 | -0.053 |
| 8. Mother's education | -0.048 | 0.374† | -0.228† | 0.278† | -0.027 | -0.059 | -0.028 | 1.000 | -0.239† |
| 9. Living children | 0.591† | -0.098* | 0.979† | -0.145† | -0.032 | 0.119† | -0.053 | -0.239† | 1.000 |
Significant at 0.01 level (2-tailed)
Table 6. Bivariate analysis of significant predictors of short interpregnancy interval
| Characteristic | Category | Frequency, n (%) or mean (standard deviation) | P value | |
|---|---|---|---|---|
| Case, n=199 | Control, n=398 | |||
| Mother's age | 31.42 (4.85) | 31.64 (4.85) | <0.001 | |
| Age at first birth (years) | <20 | 16 (8.0) | 55 (14.7) | 0.031 |
| 20–29 | 168 (84.4) | 303 (80.8) | ||
| 30–39 | 15 (7.5) | 17 (4.5) | ||
| Parity | Median (interquartile range) | 3 (2–4) | 3 (2–4) | <0.001 |
| Living children | Median (interquartile range) | 3 (2–4) | 3 (2–4) | 0.421 |
| Mother's education | Primary | 10 (5.0) | 28 (7.0) | 0.584 |
| Secondary | 112 (56.3) | 226 (56.8) | ||
| Higher | 77 (38.7) | 144 (36.2) | ||
| Husband's education | Primary | 4 (2.0) | 16 (4.0) | 0.415 |
| Secondary | 105 (52.8) | 211 (53.0) | ||
| Higher | 90 (45.2) | 171 (43.0) | ||
| Sex of previous children | Male | 98 (49.2) | 180 (45.2) | 0.384 |
| Female | 101 (50.8) | 218 (54.8) | ||
| Previous perinatal loss | Yes | 12 (6.0) | 8 (2.0) | 0.015 |
| No | 187 (94.0) | 390 (98.0) | ||
| History of infertility | Yes | 5 (2.5) | 4 (1.0) | 0.168 |
| No | 194 (97.5) | 395 (99.0) | ||
The logistic regression model was statistically significant. The model explained 5.9% (Nagelkerke R2) of the variance in the interpregnancy interval and correctly classified 66% of cases. Advanced maternal age (P=0.003), younger maternal age at first birth (P<0.001), low parity (P=0.004) and having a history of previous perinatal loss (P=0.031) were significant predictors of short interpregnancy intervals (Table 7).
Table 7. Predictors of a short interpregnancy interval
| Variable | B | Standard error | Wald | Df | P value | Exp (B) | 95% confidence interval |
|---|---|---|---|---|---|---|---|
| Mother's age | 0.095 | 0.031 | 9.111 | 1 | 0.003 | 1.099 | 1.034–1.169 |
| Age at first birth | -0.144 | 0.035 | 17.279 | 1 | 0.000 | 0.866 | 0.809–0.927 |
| Parity | -0.235 | 0.082 | 8.270 | 1 | 0.004 | 0.791 | 0.674–0.928 |
| Perinatal loss | 1.017 | 0.472 | 4.649 | 1 | 0.031 | 0.362 | 0.143–0.912 |
Discussion
The present study investigated short interpregnancy intervals in Oman, to explore the associated risk factors and significantly associated adverse outcomes. This is an important area of research, as it can inform policies to encourage optimal birth spacing, which will reduce the prevalence of adverse maternal and neonatal outcomes.
Iron deficiency anaemia
The findings showed that women with short interpregnancy intervals were at higher risk of developing iron deficiency anaemia during pregnancy. Lilungulu et al (2015) and Ugwu et al (2020) also found this relationship in their studies in Tanzania and Nigeria. In contrast, a study in Egypt revealed no significant association between short interpregnancy intervals and iron deficiency anaemia during pregnancy (Mahfouz et al, 2018). These contradictory findings should be explored in future studies.
A possible explanation for the link with iron deficiency anaemia is the ‘maternal depletion hypothesis’ (Winkvist et al, 1992). Six months after the postpartum period, approximately 20% of women have low iron levels (Ekin et al, 2015). Replenishing the maternal iron store often takes several months to account for losses during pregnancy, birth and lactation (Conde-Agudelo et al 2012; Ugwu et al, 2020). Women who become pregnant shortly after a previous birth are at greater risk of developing iron deficiency anaemia, which increases the likelihood of intrauterine growth retardation, preterm birth and neonatal birth defects (Ekin et al, 2015).
Iron deficiency anaemia is diagnosed when haemoglobin levels are <11g/dl and hematocrit is less than 33% (American College of Obstetricians and Gynecologists, 2008). In the present study, women with short interpregnancy intervals had a mean haemoglobin of 10.9 mg/dl. To help prevent this issue, the Omani healthcare system recommends iron supplementation of 150mg of folic acid for all pregnant women, in line with WHO guidelines (Al-Yaqoobi et al, 2015). Policymakers have a role to play in controlling the prevalence of short interpregnancy intervals, which would help to reduce the incidence of iron deficiency anaemia and its related negative impact on pregnancy outcomes.
Postpartum haemorrhage
Postpartum haemorrhage is defined as blood loss of 500ml or more within 24 hours after vaginal birth (Wormer et al, 2022). The present study showed that women with short interpregnancy intervals were at greater risk of developing postpartum haemorrhage. This parallels other studies, which reported increased risk of postpartum haemorrhage among women with short interpregnancy intervals (Uthman et al, 2013; Lilungulu et al, 2015; Bauserman et al, 2020). A short interpregnancy interval interferes with endometrial remodelling after birth, meaning there is not enough time for the uterus to recover and prepare for another pregnancy (Conde-Agudelo et al, 2013; Uthman et al, 2013). Optimal birth spacing should be encouraged to prevent the incidence of postpartum haemorrhage.
Preterm premature rupture of membrane
Preterm premature rupture of membrane is a rupture that occurs before 37 weeks of pregnancy. Globally, preterm premature rupture of membrane complicates up to 3% of pregnancies and is strongly associated with 30–40% of preterm births (Tsakiridis et al, 2018). The data from the present study showed that an interpregnancy interval of ≤24 months was not significantly associated with increased risk of preterm premature rupture of membrane. However, multiple other studies have reported an association between these factors (Getahun et al, 2010; Ekin et al, 2015; Shree et al, 2018) among women with an interpregnancy interval of <6 months.
It is believed that inflammation of the genital tract from a previous pregnancy could explain this link. In shortly spaced pregnancies, subclinical genital infections may continue for several weeks or months after birth, leading to increased risk of rupture (Shachar and Lyell, 2012; Lilungulu et al, 2015).
Another explanation is that cervical collagen concentration increases gradually after birth, with significant changes noted up to 9 months later (Sundtoft et al, 2011). This suggests that short interpregnancy interval might contribute to incomplete cervical remodelling leading to a short cervix in subsequent pregnancy (Shree et al, 2018).
Gestational diabetes
Gestational diabetes mellitus is a common metabolic pregnancy complication affecting 6–13% of pregnancies worldwide (Zhu and Zhang, 2016). The present study observed no statistically significant association between a short interpregnancy interval and gestational diabetes. Although few studies have explored this link, similar results were found in two previous studies (Brunner Huber et al, 2018; Gebremedhin et al, 2018). However, Hanley et al (2017) reported that there was a significant association.
Having a short interpregnancy interval and high parity may increase the risk of maternal obesity, as weight can change significantly in the interpregnancy interval. This is either because of weight retained from pregnancy or gained postpartum. Women who become obese during pregnancy have been found likely to remain significantly overweight or obese for 5 years after childbirth (Davis et al, 2009). Increased body weight predisposes women to develop gestational diabetes mellitus in a subsequent pregnancy (Hanley et al, 2017). The reasons for this should be further explored.
Low birth weight
According to the WHO (2014), low birth weight is defined as <2500g. Worldwide, it is estimated that 15–20% of all neonates have low birth weight, which accounts for more than 20 million births per year (WHO, 2014). The results of the present study found a significant association between low birth weight and a short interpregnancy interval, supporting findings from Australia, India, Qatar and Tanzania (Bener et al, 2012; Ball et al, 2014; Lilungulu et al, 2015; Kannaujiya et al 2020).
The relationship between short interpregnancy interval and perinatal outcomes may occur as a result of maternal nutritional depletion and subsequent postpartum stress, including from breastfeeding (Bener et al, 2012; Conde-Agudelo et al, 2012; Zhang et al, 2018b). In maternal depletion syndrome, negative changes occur in maternal nutritional status that poses a biological competition between a mother's physical demands and the growing fetus (Winkvist et al, 1992). This could explain the increased risk of giving birth to babies with low birth weight among women with short interpregnancy intervals.
Preterm birth
Preterm birth takes place before 37 weeks' gestation, and is a significant problem in more than 60% of African and South Asian countries (WHO, 2018). Most previous research has demonstrated a direct positive association between short interpregnancy intervals and preterm birth (Adane et al, 2014; Murad et al, 2017; Brhane et al, 2019). However, Mexican women have been shown to experience less frequent preterm births associated with short interpregnancy intervals (Gwin et al, 2012). The inconsistency between studies may be the result of socioeconomic differences between study subjects, as socioeconomic factors are a known predictor of preterm birth (Brhane et al, 2019). Further studies are recommended to explore this finding.
An explanation for the link between interpregnancy interval and preterm birth may be that cervical insufficiency occurs after birth, which may contribute to early labour in a subsequent pregnancy. Muscle tone in the reproductive tissue needs adequate time to regain strength, and failure of uterine G protein-coupled receptors to return to pre-pregnancy levels could predispose women with short interpregnancy intervals to preterm onset of labour (Tessema et al, 2021).
Maternal age
The findings of this study showed a significant association between maternal age and short interpregnancy intervals. Specifically, advanced maternal age was a risk factor for a short interval. Older women may be more likely to have shorter interpregnancy intervals as they become aware that their conception chances decline with age. In Bangladesh, a study observed that the likelihood of having a short interpregnancy interval increased by 11% with each additional year of maternal age (de Jonge et al, 2014). Older women are also more likely to experience recurrent spontaneous abortion, congenital anomalies and genetic disorders (Ikamari et al, 2013; Tessema et al, 2021), which may encourage women to have a shorter interpregnancy interval if they wish to have more children.
Parity
Women with lower parity were more likely to have a shorter interpregnancy interval. A study in Manipur indicated that birth interval decreased among women with lower parity (Singh et al, 2011), as did de Jonge et al (2014) in Bangladesh, who theorised that women who had achieved their desired family size were less likely to experience pressure to become pregnant quickly.
History of perinatal loss
The study findings indicated that a history of perinatal loss was significantly associated with a short interpregnancy interval. Ejigu et al (2019) similarly observed that a woman whose last child had died was 3.6 times more likely to have a short interpregnancy interval than a woman whose last child was alive. Ikamari et al (2013) supported this finding, showing that women who experienced child loss were more likely to have a shorter interpregnancy interval. A mother who loses a child is not protected by lactational amenorrhea, and therefore is at higher risk of unintended pregnancy (Tessema et al, 2021).
Strengths and limitations
One of the major strengths of this study is that it is the first to examine the prevalence of adverse maternal and neonatal outcomes among women with short interpregnancy intervals in Oman. Thus, it can be considered a national reference for future studies in this field. The correlations reported between short interpregnancy intervals and pregnancy outcomes will aid in planning evidence-based interventions to improve pregnancy outcomes. Further, this study considered outcomes among women of a diverse population in terms of socioeconomic backgrounds, which increases the generalisability of the resuts. The matched case–control design used in this study is a robust method that helped to reduce possible bias between the two groups.
The limitations of he study include that the researcher did not have access to registered information on breastfeeding, pregnancy intentions, smoking status or folate use, which have previously been found to be connected with interpregnancy interval and pregnancy outcomes. Some outcomes, such as preterm premature rupture of membrane and postpartum haemorrhage, occurred infrequently and had wider confidence intervals. A larger sample size is suggested to improve the study's precision. As the data were gathered retrospectively and the participants were not interviewed directly, it was not possible to gather data on a wider range of risk factors, which should be born in mind when generalising the results to other populations.
It is possible that there were confounding effects from adverse pregnancy outcomes, meaning the observed associations between interpregnancy interval and adverse outcomes may be uncertain. A broader set of confounders or a more robust design is required to overcome this limitation. Moreover, the present study only considered a single interpregnancy interval; further research involving more than two interpregnancy intervals should be carried out to construct more informative findings.
Implications
The authors strongly recommend that optimal birth spacing is encouraged at a national level. For clinical practice, Omani women conceiving shortly after birth need to be informed about the adverse outcomes linked to short interpregnancy intervals, and be monitored closely during the antenatal, intranatal, and postnatal periods. Effective family planning counselling is essential for promoting an optimal interpregnancy interval during the postnatal period.
Health awareness programmes on the association between adverse pregnancy outcomes and interpregnancy interval should be organised to highlight the benefit of birth spacing. Health education programmes on family planning and recommended birth spacing are vital to improving knowledge and attitudes towards family planning. The birth spacing programme should consider using a definition of interpregnancy interval that considers previous pregnancy outcomes.
It is hoped that this research will be used by healthcare planners and programme managers to design scientifically sound interventions that address the gap in the use of family planning methods for optimal birth spacing. This study is also intended to add to the recommendations made by international organisations on the importance of optimal interpregnancy intervals. Adhering to global recommendations for optimising interpregnancy intervals could prevent adverse pregnancy outcomes and subsequently reduce its financial burden. Broader implications at the regional and national level need to be considered.
Conclusions
This study provides baseline information on the association between interpregnancy interval and adverse birth outcomes, which requires further robust follow-up studies in Oman. More research is needed to explore the mechanisms that drive the reported associations between interpregnancy interval and various risk factors, in order to direct proper interventions. Further studies should consider the definition of interpregnancy interval when measuring adverse pregnancy outcomes after miscarriage.
Key points
- Adverse maternal and neonatal outcomes are linked to short interpregnancy intervals, making it important to encourage optimal birth spacing for women.
- Women who have had a short interpregnancy interval need to be closely monitored during the antenatal, intranatal, and postnatal periods.
- Effective family planning counselling is essential for encouraging optimal birth spacing during the postnatal period.
- A short interpregnancy interval was found to influence pregnancy outcomes among Omani women.
- The birth spacing programme in Oman should reconsider the definition of optimal birth spacing to account for these findings.
- This study adds to recommendations made by international organisations on the importance of optimal interpregnancy intervals.
CPD reflective questions
- What challenges might women experience when pursuing optimal birth spacing?
- What barriers might women face when using family planning methods for birth spacing?
- How can women be encouraged to practice optimal birth spacing?