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MATERNAL CORRELATES OF SPONTANEOUS PRETERM BIRTH IN KAZAKHSTAN: A MATCHED CASE-CONTROL STUDY
- Authors: Oralkhan Z.1, Zhurabekova G.2, Sarsenova L.1, Kopbayeva M.3, Tastambek K.1, Grjibovski A.4, Berdalinova A.5, Balmagambetova A.6
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Affiliations:
- Al-Farabi Kazakh National University, Almaty, Kazakhstan
- West Kazakhstan Marat Ospanov State Medical University, Aktobe, Kazakhstan Al-Farabi Kazakh National University, Almaty, Kazakhstan
- Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
- Al-Farabi Kazakh National University, Almaty, Kazakhstan Northern State Medical University, Arkhangelsk, Russian Federation Northern (Arctic) Federal University, Arkhangelsk, Russian Federation Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
- Al-Farabi Kazakh National University, Almaty, Kazakhstan West Kazakhstan Marat Ospanov State Medical University, Aktobe, Kazakhstan
- West Kazakhstan Marat Ospanov State Medical University, Aktobe, Kazakhstan
- Section: ORIGINAL STUDY ARTICLES
- Submitted: 12.03.2024
- Accepted: 18.04.2024
- Published: 13.06.2024
- URL: https://hum-ecol.ru/1728-0869/article/view/629001
- DOI: https://doi.org/10.17816/humeco629001
- ID: 629001
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Abstract
Background: Preterm birth (PTB) continues to be a persistent health issue that significantly impacts neonatal morbidity and mortality worldwide. In Kazakhstan, the prevalence of preterm births is 7% making a substantial contribution to adverse health outcomes among infants. However, there is a lack of comprehensive research on the factors contributing to preterm birth in Kazakhstan.
Aims: To study maternal factors associated with spontaneous PTB among Kazakh women.
Methods: A case control study was conducted in three major reproductive hospitals in Atyrau, Aktobe and Kyzylorda from October 2022 to January 2023. The sample consisted of 90 cases with singleton live spontaneous PTB and 180 controls with spontaneous full-term delivery. Bivariate associations between categorical variables were assessed by chi-squared tests. Independent variables with p-values < 0.1 in the bivariate analysis were entered into a conditional logistic regression model. Odds ratios (OR) with 95% confidence intervals (CI) were calculated.
Results: Maternal education, periodontitis, body mass index and a history of PTB in previous pregnancies were associated with PTB in bivariate analysis. In multivariable models, only prior PTB (OR=38.1; 95% CI: 8.34–142) and periodontal disease (OR=2.09; 95% CI: 1.15–3.80) were associated with an increased risk of extremely and very preterm births while higher education (OR=0.44; 95% CI: 0.19–0.98) and a history of PTB (OR=27.2; 95% CI: 5.38–137) were associated with moderate to late PTB.
Conclusion: Our results are in line with the international evidence on prior PTB being the most important determinant of PTB in the index pregnancy. Moreover, our findings on the associations with periodontal disease underline the importance of a targeted, individualized and interdisciplinary antenatal care to the reduction in the prevalence of PTB.
Full Text
INTRODUCTION
Preterm birth (PTB) is a complex syndrome with significant long-term health implications. It refers to the delivery of a live baby before 37 completed weeks of gestation [1]. Clinically, approximately half of all PTB are idiopathic, characterized by spontaneous onset of labor. The other half can be attributed to preterm premature rupture of membranes (PPROM) or medically indicated reasons [2]. Globally, more than one in ten babies is born preterm, and these PTB account for about 75% of perinatal deaths [3]. PTB affects both developed and developing countries regardless of social vulnerability [3-4].
PTB presents numerous challenges for both maternal and fetal outcomes. Preterm babies are more susceptible to a range of health problems, including mental retardation, vision impairment, and cerebral palsy, when compared to full-term babies [5]. Furthermore, prematurity has been linked to the development of cardiovascular disease, diabetes, and cancer in adulthood [6]. Additionally, a history of preterm birth increases the risk of subsequent preterm deliveries for mothers [7].
As other pregnancy outcomes, the probability of PTB is influenced by both the external environment and maternal factors. Interestingly, the risk factors for PTB vary among different countries and even within neighborhoods of the same country [8-9]. Some commonly reported maternal risk factors for PTB include socio-economic characteristics, a history of PTB [7, 10], smoking during pregnancy [11], a short cervical length [12], periodontal diseases [13], multiple pregnancies [14], maternal overweight, chronic somatic diseases, and pregnancy complications [15-17]. Furthermore, genetic factors have been identified that predispose individuals to preterm labor [18]. Inadequate prenatal care services may also contribute to the disparities in preterm birth rates [19].
In Kazakhstan, pregnant women are entitled to receive free antenatal care through the public health system, regardless of their socioeconomic status or geographic location. This service model has successfully achieved a remarkable 99.2% coverage of antenatal care [20]. Gaining a comprehensive understanding of the factors influencing the current population is essential for implementing effective preventive strategies, particularly in the case of preterm birth (PTB). The prevalence of PTB in Kazakhstan is around 7% with an increasing trend over the recent decades. Given that PTB are responsible for a substantial proportion of infant deaths, identification of their determinants or associated factors may have an important contribution to reduction of infant mortality.
The aim of this study was to identify predictors of spontaneous PTB among Kazakh women.
MATERIAL AND METHODS
This hospital-based case-control study was conducted on a sample of 270 Kazakh women, including 90 cases of singleton live spontaneous preterm birth and 180 controls. Minimal required sample size was calculated at the planning phase of the study. The abovementioned sample size ensures a statistical power of 87% for the level of alpha error of 5% for two-tailed tests for the odds ratios of 2.0 or above. All data were collected in the Atyrau and Aktobe regions in Western Kazakhstan, and in Kyzylorda region in Southern Kazakhstan. Data collection took place from October 2022 to January 2023 in reproductive and perinatal centers. During this period, 90 women who delivered before 37 gestational weeks were considered for this study. Exclusion criteria were twin- or triplet pregnancies, pre-eclampsia, pregnancy-induced hypertension, gestational diabetes, induced labor, and Caesarean section, were excluded from the study. Women with term babies weighing over 2500 g without any pregnancy complications comprised a control group. Controls were selected in a 2:1 ratio and matched to cases according to infant sex and delivery date. More than 99% of pregnant women in Kazakhstan receive their maternal care from these local health centers, therefore the risk of selection bias was considered as low [18]. All of the health care centers provided free maternal and child care for their target groups under the same conditions.
Potential participants were provided with an information sheet that explained the aims and procedures of the study, their responsibilities, possible risks and side effects, potential benefits, alternatives to participation, the confidentiality of data, and the voluntary nature of participation. Those who were willing to participate provided signed consent to take part in the study. They were then given a questionnaire, which took approximately 5 minutes to complete. The questionnaire was pre-tested for clarity prior to the study initiation. A trained researcher who was fluent in both Kazakh and Russian conducted a pilot survey among 30 pregnant visitors at the Aktobe reproductive and perinatal center.
A structured self-administered questionnaire was used to explore the risk factors related to spontaneous preterm birth, including the mother's age, educational level, marital status, employment, income, current smoking status, exposure to secondhand smoke, alcohol intake habits, number of pregnancies, pre-gestational weight and height, complications during pregnancy, previous obstetric history, gestational week at labor, and type of delivery. Data on maternal weight, placental weight, weight and length of the baby as well as infant sex were obtained from the medical documentation. A normal pre-pregnancy weight was defined as having a BMI of 18.0–24.99 kg/m2. Pre-pregnancy overweight was defined as having a BMI between 25.0 and 29.99 kg/m2, while pre-pregnancy obesity was defined as having a BMI ≥ 30.0 kg/m2 [22].
The periodontal health condition was assessed shortly after filling out the questionnaire by a dentist who measured bleeding on probing, probing depth, and clinical attachment loss. This assessment was conducted at six different sites using a periodontal probe and dental mirror. Periodontitis was diagnosed in cases of the presence of pocket depth ≥ 4 mm on one or more sites of more than four teeth, as well as the presence of clinical attachment loss of 3 mm or above [21]. Births that occurred prior to the 28th week of gestation were classified as extremely preterm births (EPTB) while births between the 28th and the 32nd weeks were termed as very preterm births (VPTB). The final groups of PTB after the completed 32nd week were classified as moderate to late preterm births (MLPTB).
Independent associations between PTB and potential predictors were studied using a multivariable conditional logistic regression model. Crude and adjusted odds ratios (OR) were calculated with 95% confidence intervals (CI). Multivariable analysis was performed only on variables associated with the outcome in crude analysis at the level of significance below 0.1. The analyses were repeated separately for MLPTB and EPTB+VPTB. All analyses were performed using Stata software, version 18.0 (Stata Corp., TX).
The study was approved by the al-Farabi Kazakh National University Ethical Committee (Protocol IRB-A308). Written consent was obtained from all the participants. Permissions for the use of medical records were obtained from the concerned hospital authorities. Surveys were administered by the medical personnel. The authors analyzed the dataset with no personal information and they did not have access to personal data.
RESULTS
Among the 90 singleton PTB included in the study, 17 were extremely preterm, 37 were very preterm and 36 were moderate to late preterm. The mean age of the pregnant women was 28.7 (SD=6.1) years with no difference between cases and controls (p=0,921). The mean BMI of the participants was 24.0 (SD=4.2) kg/m2. No differences between cases and controls were observed when age (p=0.921) and pre-gestational BMI (p=0.094) were treated as continuous variables. Only 7 % of the women had duration of education below 12 years. At the same time, 36% of women were out of work. All the women were ethnic Kazakhs. None reported smoking and consuming alcohol. However, 20% of the participating women were reported being exposed to smoking because of having a smoking family member. Statistically significant differences between cases and controls were observed by mothers' education, BMI, periodontal diseases, and history of PTB in previous pregnancies in the bivariate analysis (Table 1).
Table 1. Distribution of socio-demographic, anthropometric characteristics, periodontitis, and a history of preterm birth across cases and controls in four cities in Kazakhstan.
Variables | Controls (n=180) | Cases (n=90) | P |
Age, years |
|
|
|
< 25 | 50 (27.8) | 31 (34.4) | 0.566 |
25-29 | 58 (32.2) | 25 (27.8) |
|
30-34 | 38 (21.1) | 15 (16.7) |
|
35+ | 34 (18.9) | 19 (21.1) |
|
Education |
|
| 0.024 |
Secondary | 70 (38.9) | 48 (53.3) |
|
Higher | 110 (61.1) | 42 (46.7) |
|
Employment |
|
| 0.422 |
Out of work | 63 (35.0) | 36 (40.0) |
|
Employed | 117 (65.0) | 54 (60.0) |
|
Income |
|
| 0.533 |
≤ 2 minimum wages | 30 (16.7) | 20 (22.2) |
|
2-5 minimum wages | 101 (56.1) | 48 (53.3) |
|
≥ 6 minimum wages | 49 (27.2) | 22 (24.4) |
|
Gravidity |
|
| 0.251 |
1 | 45 (25.0) | 24 (26.7) |
|
2-4 | 101 (56.1) | 42 (46.7) |
|
≥ 5 | 34 (18.9) | 24 (26.7) |
|
Pre-pregnancy weight |
|
|
|
Obese / overweight | 53 (29.4) | 38 (42.2) | 0.040 |
Normal weight | 127 (70.6) | 52 (57.8) |
|
Periodontitis |
|
|
|
Yes | 45 (25.0) | 39 (43.3) | 0.002 |
No | 135 (75.0) | 51 (56.7) |
|
History of preterm birth |
|
| < 0.001 |
Yes | 2 (1.1) | 26 (28.9) |
|
No | 178 (98.9) | 64 (71.1) |
|
In multivariable analysis, women with a history of previous preterm birth were more likely to have PTB compared to women with no PTB. Moreover, women who had periodontitis during pregnancy had twice as high odds of PTB compared to women with who did not). Restriction of the analysis to EPTB and VPTB yielded similar findings. At the same time, MLPTB were associated with a history of PTB and maternal education while associations with periodontitis reduced to non-significant level.
Table 2. Associations between preterm birth and socio-demographic, anthropometric characteristics, periodontitis, and a history of preterm birth in four cities in Kazakhstan
| All preterm births | Very- and extremely preterm births | Moderate to late preterm births | ||||||
Variables | Adjusted OR | 95% CI | P | Adjusted OR | 95% CI | P | Adjusted OR | 95% CI | P |
Education |
|
| 0.201 |
|
| 0.697 |
|
| 0.047 |
Secondary | 1.00 | Reference |
| 1.00 | Reference |
| 1.00 | Reference |
|
Higher | 0.69 | 0.39-1.22 |
| 0.87 |
|
| 0.44 | 0.19-0.98 |
|
Pre-pregnancy weight |
|
| 0.123 |
|
| 0.462 |
|
| 0.122 |
Obese / overweight | 1.56 | 0.86-2.82 |
| 1.32 | 0.63-2.73 |
| 1.90 | 0.84-4.29 |
|
Normal weight | 1.00 | Reference |
| 1.00 | Reference |
| 1.00 | Reference |
|
Periodontitis |
|
| 0.016 |
|
| 0.048 |
|
| 0.131 |
Yes | 2.09 | 1.15-3.80 |
| 2.08 | 1.01-4.29 |
| 1.89 | 0.83-4.31 |
|
No | 1.00 | Reference |
| 1.00 | Reference |
| 1.00 | Reference |
|
History of preterm birth |
|
| < 0.001 |
|
| < 0.001 |
|
| < 0.001 |
Yes | 32.5 | 7.43-142 |
| 38.1 | 8.34-174 |
| 27.2 | 5.38-137 |
|
No | 1.00 | Reference |
| 1.00 | Reference |
| 1.00 | Reference |
|
DISCUSSION
Our study is among the first multicenter studies in Kazakhstan exploring factors associated spontaneous PTB in Kazakhstan. Our findings are in line with the international evidence regarding a history of PTB being the most important predictor of PTB in the index pregnancy. Moreover, our findings corroborate the evidence on the associations between periodontitis and PTB. Interestingly, education was a predictor of MLPTB, but not VPTB and EPTB.
Prediction of PTB remains a challenge for practicing obstetricians due to its multifactorial etiology. PTB may result from a constellation of environmental, psychological, social, and genetic risk factors [2, 11]. The conflicting results of the different studies point to the complexity of the association between possible risk factors and spontaneous PTB [8, 11, 14, 15]. Ethnicity and behavioral habits such as smoking and alcohol consumption are part of highlighted factors in other studies [11, 23-24]. However, only ethnic Kazakh women took part in this study and none of them reported smoking or drinking alcohol. The mean age of the participants in our study was similar to what has been reported from other countries [11, 23].
In literature, the most studied socio-economic factors include age, education, household income and employment status of the mother [8-11]. However, the results remain controversial. The contribution of inequalities in maternal educational level to the outcome of PTB found in our study is generally in line with other studies, which highlighted educational level is more clearly related to inequalities in preterm birth than occupation and household income [25]. Moreover, it appeared that education was more important predictor of MLPTB than for VPTB and EPTB. Contrary to the results of large Canadian and Danish studies who reported an advanced or younger maternal age is one of the risk contributors, we failed to observe associations between PTV and maternal age [26-27].
Unlike other studies [14, 28], the number of pregnancies prior to the index pregnancy was not associated with PTB that might be a result of a small sample size that cannot detect small effects.
Greater odds for PTB were observed among women who were overweight or obese before pregnancy and women with periodontitis which is in line with results of the studies conducted in other countries [13, 15-16]. Physiological changes during pregnancy may influence the onset and development of gingivitis and can also worsen the clinical course of already existing periodontitis [29-31]. Periodontal diseases affecting oral health during pregnancy are highly prevalent, and have consequences not only for physical well-being, but also impair quality of life [32-33]. Our results highlight the importance of the effect of BMI and periodontal diseases on spontaneous PTB and may assist in risk assessment and counseling during even before pregnancy.
Our findings of association between prior and subsequent preterm birth is consistent with most of the similar studies which support that history of preterm first birth was a major risk factor for subsequent preterm birth [7, 36-39]. In a prior study with risk estimates reported more than one in six women with preterm history had a preterm second birth [7]. Genetics, susceptible to inflammation and placental disorders including placental insufficiency may be pronounced for the common pathways of the recurrence of the adverse pregnancy outcome [7, 40]. Our study, consistent with the similar studies confirms the importance of a targeted, individualized, and interdisciplinary antenatal care while the nature of the preterm birth is multifactorial [7, 21].
The current study was one of the few epidemiological studies on pregnant women in Kazakhstan and provides a snapshot of factors associated with preterm birth among Kazakh women [41]. The sample size was sufficient to detect the odds of 2.0 or greater limiting the possibility to study the factors that have not so strong effects on the outcome. Moreover, the use of three settings for data collection and participation of only ethnic Kazakh women limits the generalizability of the findings to the national level. However, it covers a representative sample in Atyrau, Aktobe and Kyzylorda which are the areas predominantly populated by ethnic Kazakhs. Additionally, the regional reproductive and prenatal hospitals in our study cover more than 90% of PTB in the regions reducing the probability of selection bias. Nevertheless, this study demonstrates that studies in the field of perinatal epidemiology are feasible in Kazakhstan outside large cities and that the main findings are in line with the international evidence. Large cohort studies or nation-wide studies using medical information systems are required for better understanding of the factors involved in the etiology of PTB in Kazakhstan.
CONCLUSIONS
The findings suggest that a history of preterm birth and periodontal disease are important predictors of spontaneous PTB, particularly EPTB and VPTB. Maternal education was found significant predictor for MLPTB only. More research is warranted with the further going aim to provide targeted, individualized and interdisciplinary approach to prevent PTB.
ACKNOWLEDGEMENTS
We thank the pregnant women who took part in this study and the hospital staff in Atyrau, Aktobe and Kyzylorda, especially Erasyl Kabi, Lazzat Bimaganbetova and Oleg Kim.
ADDITIONAL INFORMATION:
Authors’ contribution: All authors fulfill the authorship criteria through participating in designing the study, data collection, data analysis, drafting the manuscript and making substantial contribution to its contents in subsequent versions. All authors approved the final version of the paper prior to submission.
FUNDING SOURCES: This research is funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP14869249, AP14972889).During the preparation of the manuscript in 2023 AMG was supported by the visiting professor program at Asfendiyarov Kazakh National Medical University.
COMPETING INTERESTS: The authors declare no competing interests.
About the authors
Zhibek Oralkhan
Al-Farabi Kazakh National University, Almaty, Kazakhstan
Email: september_becca@hotmail.com
ORCID iD: 0000-0002-8884-6523
Scopus Author ID: 56892790400
Al farabi avenue 71A,Almaty, Kazakhstan
Gulmira Zhurabekova
West Kazakhstan Marat Ospanov State Medical University, Aktobe, KazakhstanAl-Farabi Kazakh National University, Almaty, Kazakhstan
Author for correspondence.
Email: gzhurabekova@gmail.com
ORCID iD: 0000-0002-2166-3095
candidate of medical science, associated professor
KazakhstanLazzat Sarsenova
Al-Farabi Kazakh National University, Almaty, Kazakhstan
Email: lazzat.sarsenova@kaznu.kz
ORCID iD: 0000-0001-8643-0703
Kazakhstan
Maira Kopbayeva
Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
Email: m_kopbay@mail.ru
ORCID iD: 0000-0002-7439-5573
Kazakhstan
Kuanysh Tastambek
Al-Farabi Kazakh National University, Almaty, Kazakhstan
Email: Tastambeku@gmail.com
ORCID iD: 0000-0002-2338-8816
Kazakhstan
Andrej M Grjibovski
Al-Farabi Kazakh National University, Almaty, KazakhstanNorthern State Medical University, Arkhangelsk, Russian Federation
Northern (Arctic) Federal University, Arkhangelsk, Russian Federation
Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan
Email: a.grjibovski@yandex.ru
ORCID iD: 0000-0002-5464-0498
Akzhenis Berdalinova
Al-Farabi Kazakh National University, Almaty, KazakhstanWest Kazakhstan Marat Ospanov State Medical University, Aktobe, Kazakhstan
Email: berdalinova77@mail.ru
ORCID iD: 0000-0002-5735-9538
Kazakhstan
Aru Balmagambetova
West Kazakhstan Marat Ospanov State Medical University, Aktobe, Kazakhstan
Email: aru.b.84@mail.ru
ORCID iD: 0000-0003-1151-5651
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