Факторы риска спонтанных преждевременных родов в Казахстане: исследование случай-контроль методом подобранных пар

Обложка


Цитировать

Полный текст

Аннотация

Обоснование. Преждевременные роды (ПР) остаются актуальной проблемой здравоохранения, оказывающей значительное влияние на неонатальную заболеваемость и смертность во всем мире. В Казахстане распространённость ПР составляет 7%, что вносит существенный вклад в неблагоприятные исходы в младенческом периоде. Тем не менее в Казахстане отсутствуют комплексные исследования факторов риска ПР.

Цель. Изучить факторы риска спонтанных ПР у казахских женщин.

Материал и методы. Исследование методом случай-контроль проводили в трёх крупных учреждениях родовспоможения в городов Атырау, Актобе и Кызылорда с октября 2022 по январь 2023 г. Выборка состояла из 90 женщин со спонтанными ПР и 180 — со срочными родами. В исследование включали только одноплодные беременности. Бивариантные связи между категориальными переменными оценивали с помощью критерия хи-квадрат Пирсона. Независимые переменные, связанные с исходом на уровне значимости менее 0,1 в бивариантном анализе были введены в условную логистическую регрессионную модель. Силу связи определяли с помощью отношения шансов (ОШ) с 95% доверительными интервалами (ДИ).

Результаты. Образование матери, пародонтит, индекс массы тела и наличие ПР в анамнезе были значимо связаны с ПР при проведении бивариантного анализа. В многомерных моделях только ПР в анамнезе (ОШ=38,10; 95% ДИ: 8,34–142,00) и заболевания пародонта (ОШ=2,09; 95% ДИ: 1,15–3,80) были связаны с повышенным риском ПР в срок до 32 недель. Более высокий уровень образования (ОШ=0,44; 95% ДИ: 0,19–0,98) и наличие ПР в анамнезе (ОР=27,20; 95% ДИ: 5,38–137,00) были связаны с ПР в срок от 32 до 36 недель.

Заключение. Результаты исследования не противоречат международным данным о том, что ПР в анамнезе являются наиболее сильным прогностическим фактором для ПР. Кроме того, полученные данные о сильной связи с заболеваниями пародонта подчёркивают важность целенаправленной, индивидуализированной и междисциплинарной дородовой помощи для снижения распространенности ПР.

Полный текст

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 PTB 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 PTB 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 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 PTB 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 with cross-verify the responses from medical report was used to explore the risk factors related to spontaneous PTB, 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)

р

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

Secondary

70 (38.9)

48 (53.3)

0.024

Higher

110 (61.1)

42 (46.7)

Employment

Out of work

63 (35.0)

36 (40.0)

0.422

Employed

117 (65.0)

54 (60.0)

Income

≤2 minimum wages

30 (16.7)

20 (22.2)

0.533

2–5 minimum wages

101 (56.1)

48 (53.3)

≥6 minimum wages

49 (27.2)

22 (24.4)

Gravidity

1

45 (25.0)

24 (26.7)

0.251

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

Yes

2 (1.1)

26 (28.9)

<0.001

No

178 (98.9)

64 (71.1)

 

In multivariable analysis, women with a history of previous PTB 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).

 

Table 2. Associations between preterm birth and socio-demographic, anthropometric characteristics, periodontitis, and a history of preterm birth in four cities in Kazakhstan

Parameters

All preterm births

Very- and extremely preterm births

Moderate to late preterm births

Variables

Adjusted OR

95% CI

р

Adjusted OR

95% CI

р

Adjusted OR

95% CI

р

Education

Secondary

1.00

Reference

0.201

1.00

Reference

0.697

1.00

Reference

0.047

Higher

0.69

0.39–1.22

0.87

0.44

0.19–0.98

Pre-pregnancy weight

Obese / overweight

1.56

0.86–2.82

0.123

1.32

0.63–2.73

0.462

1.90

0.84–4.29

0.122

Normal weight

1.00

Reference

1.00

Reference

1.00

Reference

Periodontitis

Yes

2.09

1.15–3.80

0.016

2.08

1.01–4.29

0.048

1.89

0.83–4.31

0.131

No

1.00

Reference

1.00

Reference

1.00

Reference

History of preterm birth

Yes

32.5

7.43–142

<0.001

38.1

8.34–174

<0.001

27.2

5.38–137

<0.001

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 PTB 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 PTB is consistent with most of the similar studies which support that history of preterm first birth was a major risk factor for subsequent PTB [7, 34–39]. 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 PTB 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 PTB 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 PTB 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.

ADDITIONAL INFORMATION

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.

Authorscontribution. 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.

×

Об авторах

Жибек Оралхан

Казахский национальный университет имени аль-Фараби

Email: september_becca@hotmail.com
ORCID iD: 0000-0002-8884-6523
Scopus Author ID: 56892790400

MD

Казахстан, Проспект Аль-Фараби, 71, Алматы, 050040

Лаззат Сарсенова

Казахский национальный университет имени аль-Фараби

Email: lazzat.sarsenova@kaznu.kz
ORCID iD: 0000-0001-8643-0703

PhD

Казахстан, Проспект Аль-Фараби, 71, Алматы, 050040

Маира Копбаева

Казахский национальный медицинский университет имени Асфендиярова

Email: m_kopbay@mail.ru
ORCID iD: 0000-0002-7439-5573

PhD, профессор

Казахстан, Алматы

Куануш Тастамбек

Казахский национальный университет имени аль-Фараби

Email: tastambeku@gmail.com
ORCID iD: 0000-0002-2338-8816

PhD

Казахстан, Алматы

Андрей Мечиславович Гржибовский

Казахский национальный университет имени аль-Фараби; Западно-Казахстанский государственный медицинский университет имени Марата Оспанова; Северный государственный медицинский университет; Северный (Арктический) федеральный университет; Казахский национальный медицинский университет имени Асфендиярова

Email: a.grjibovski@yandex.ru
ORCID iD: 0000-0002-5464-0498
SPIN-код: 5118-0081

MD, MPhil, PhD

Казахстан, Проспект Аль-Фараби, 71, Алматы, 050040; Актобе; Архангельск; Архангельск; Алматы

Акженис Бердалинова

Казахский национальный университет имени аль-Фараби; Западно-Казахстанский государственный медицинский университет имени Марата Оспанова

Email: berdalinova77@mail.ru
ORCID iD: 0000-0002-5735-9538
Казахстан, Проспект Аль-Фараби, 71, Алматы, 050040; Актобе

Ару Балмагамбетова

Западно-Казахстанский государственный медицинский университет имени Марата Оспанова

Email: aru.b.84@mail.ru
ORCID iD: 0000-0003-1151-5651

MD, PhD

Казахстан, Актобе

Гульмира Журабекова

Казахский национальный университет имени аль-Фараби; Западно-Казахстанский государственный медицинский университет имени Марата Оспанова

Автор, ответственный за переписку.
Email: zhurabekova.gulmira@kaznu.kz
ORCID iD: 0000-0002-2166-3095

доцент

Казахстан, Проспект Аль-Фараби, 71, Алматы, 050040; Актобе

Список литературы

  1. Romero R, Espinoza J, Mazor M, Chaiworapongsa T. The preterm parturition syndrome. In: Critchley H, Bennett P, Thornton S, eds. Preterm Birth. London: RCOG Press; 2004. P. 28–60.
  2. Goldenberg RL, Culhane JF, Iams JD, Romero R. Epidemiology and causes of preterm birth. Lancet. 2008;371(9606):75–84. doi: 10.1016/S0140-6736(08)60074-4
  3. Vogel JP, Chawanpaiboon S, Moller AB, et al. The global epidemiology of preterm birth. Best Pract Res Clin Obstet Gynaecol. 2018;52:3–12. doi: 10.1016/j.bpobgyn.2018.04.003. Chawanpaiboon S, Vogel JP, Moller AB, et al. Global, regional, and national estimates of levels of preterm birth in 2014: a systematic review and modelling analysis. Lancet Glob Health. 2019;7(1):e37–e46. doi: 10.1016/S2214-109X(18)30451-0
  4. Behrman RE, Butler AS, Institute of Medicine (US) Committee on Understanding Premature Birth and Assuring Healthy Outcomes, eds. Preterm Birth: Causes, Consequences, and Prevention. Washington (DC): National Academies Press (US); 2007. doi: 10.17226/11622
  5. National Guideline Alliance (UK). Developmental follow-up of children and young people born preterm. London: National Institute for Health and Care Excellence (NICE); August 2017.
  6. Tingleff T, Vikanes A, Räisänen S, et al. Risk of preterm birth in relation to history of preterm birth: a population-based registry study of 213 335 women in Norway. BJOG. 2022;129(6):900–907. doi: 10.1111/1471-0528.17013
  7. Wahabi HA. Socio-economic risk factors of spontaneous preterm birth among Saudi women: A case-control study. Int J Women's Health Reproduct Sci. 2019;7(3):276–280. doi: 10.15296/ijwhr.2019.46
  8. Garcia-Subirats I, Pérez G, Rodríguez-Sanz M, et al. Neighborhood inequalities in adverse pregnancy outcomes in an urban setting in Spain: a multilevel approach. J Urban Health. 2012;89(3):447–463. doi: 10.1007/s11524-011-9648-4
  9. Wood S, McNeil D, Yee W, et al. Neighbourhood socio-economic status and spontaneous premature birth in Alberta. Can J Public Heal. 2014;105(5):e383–e388. doi: 10.17269/cjph.105.4370
  10. Ye CX, Chen SB, Wang TT, et al. Risk factors for preterm birth: a prospective cohort study. Zhongguo Dang Dai Er Ke Za Zhi. 2021;23(12):1242-1249. doi: 10.7499/j.issn.1008-8830.2108015
  11. Son M, Miller ES. Predicting preterm birth: Cervical length and fetal fibronectin. Semin Perinatol. 2017;41(8):445–451. doi: 10.1053/j.semperi.2017.08.002
  12. Oralkhan Z, Walia GS, Zhurabekova G, et al. The impact of periodontitis on the risk of preterm birth: Systematic review and meta-analysis. J Clin Med Kaz. 2023;20(3):56–62. doi: 10.23950/jcmk/13322
  13. Koullali B, van Zijl MD, Kazemier BM, et al. The association between parity and spontaneous preterm birth: a population based study. BMC Pregnancy Childbirth. 2020;20(1):233. doi: 10.1186/s12884-020-02940-w
  14. McDonald SD, Han Z, Mulla S, Beyene J. Overweight and obesity in mothers and risk of preterm birth and low birth weight infants: Systematic review and meta-analyses. BMJ. 2010;341:c3428. doi: 10.1136/bmj.c3428
  15. Berger H, Melamed N, Davis BM, et al. Impact of diabetes, obesity and hypertension on preterm birth: Population-based study. PLoS One. 2020;15(3):e0228743. doi: 10.1371/journal.pone.0228743
  16. Rasmussen S, Ebbing C, Irgens LM. Predicting preeclampsia from a history of preterm birth. PLoS One. 2017;12(7):e0181016. doi: 10.1371/journal.pone.0181016
  17. Bhattacharjee E, Thiruvengadam R, Ayushi, et al. Genetic variants associated with spontaneous preterm birth in women from India: a prospective cohort study. Lancet Reg Health Southeast Asia. 2023;14:100190. doi: 10.1016/j.lansea.2023.100190
  18. Medley N, Vogel N, Care A, Alfirevic Z. Interventions during pregnancy to prevent preterm birth: an overview of Cochrane systematic reviews. Cochrane Database Syst Rev. 2018;11(11):CD012505. doi: 10.1002/14651858.CD012505.pub2
  19. Multiple Indicator Cluster Survey (MICS) in the Republic of Kazakhstan 2010–2011. Monitoring the Situation of Children and Women; Statistics Committee of the Ministry of National Economy of the Republic of Kazakhstan: Astana, 2012.
  20. Lopez NJ, Smith PC, Gutierrez J. Periodontal therapy may reduce the risk of preterm low birth weight in women with periodontal disease: a randomized controlled trial. J Periodontol. 2002;73(8):911–924. doi: 10.1902/jop.2002.73.8.911
  21. Caracho RA, Foratori-Junior GA, Fusco NDS, et al. Systemic conditions and oral health-related quality of life of pregnant women of normal weight and who are overweight. Int Dent J. 2020;70(4):287–295. doi: 10.1111/idj.12547
  22. Woday A, Muluneh MD, Sherif S. Determinants of preterm birth among mothers who gave birth at public hospitals in the Amhara region, Ethiopia: A case-control study. PLoS One. 019;14(11):e0225060. doi: 10.1371/journal.pone.0225060
  23. Soneji S, Beltrán-Sánchez H. Association of maternal cigarette smoking and smoking cessation with preterm birth. JAMA Netw Open. 2019;2(4):e192514. doi: 10.1001/jamanetworkopen.2019.2514
  24. Granés L, Torà-Rocamora I, Palacio M, et al. Maternal educational level and preterm birth: Exploring inequalities in a hospital-based cohort study. PLoS One. 2023;18(4):e0283901. doi: 10.1371/journal.pone.0283901
  25. Schmidt Morgen C, Bjørk C, Andersen PK, et al. Socioeconomic position and the risk of preterm birth — a study within the Danish National Birth Cohort. Int J Epidemiol. 2008;37(5):1109–1120. doi: 10.1093/ije/dyn112
  26. Fuchs F, Monet B, Ducruet T, et al. Effect of maternal age on the risk of preterm birth: A large cohort study. PLoS One. 2018;13(1):e0191002. doi: 10.1371/journal.pone.0191002
  27. Ananth CV, Peltier MR, Getahun D, et al. Primiparity: an “intermediate” risk group for spontaneous and medically indicated preterm birth. J Matern Fetal Neonatal Med. 2007;20(8):605–611. doi: 10.1080/14767050701451386
  28. Himalatha VT, Manigandan T, Sarumathi T, et al. Dental considerations in pregnancy-a critical review on the oral care. J Clin Diagn Res. 2013;7(5):948–953. doi: 10.7860/JCDR/2013/5405.2986
  29. Ramos-E-Silva M, Martins NR, Kroumpouzos G. Oral and vulvovaginal changes in pregnancy. Clin Dermatol. 2016;34(3):353-358. doi: 10.1016/j.clindermatol.2016.02.007
  30. Wu M, Chen S-W, Jiang S-Y. Relationship between gingival inflammation and pregnancy. Mediators Inflammation. 2015;2015:623427. doi: 10.1155/2015/623427
  31. Fakheran O, Saied-Moallemi Z, Khademi A, Sahebkar A. Oral health-related quality of life during pregnancy: a systematic review. Curr Pharm Des. 2020;26(32):4014–4021. doi: 10.2174/1381612826666200523171639
  32. Bobetsis YA, Graziani F, Gürsoy M, Madianos PN. Periodontal disease and adverse pregnancy outcomes. Periodontol 2000. 2020;83(1):154–174. doi: 10.1111/prd.12294
  33. Melve KK, Skjaerven R, Gjessing HK, Oyen N. Recurrence of gestational age in sibships: implications for perinatal mortality. Am J Epidemiol. 1999;150(7):756–762. doi: 10.1093/oxfordjournals.aje.a010078
  34. Phillips C, Velji Z, Hanly C, Metcalfe A. Risk of recurrent spontaneous preterm birth: a systematic review and meta-analysis. BMJ Open. 2017;7(6):e015402. doi: 10.1136/bmjopen-2016-015402
  35. Mazaki-Tovi S, Romero R, Kusanovic JP, et al. Recurrent preterm birth. Semin Perinatol. 2007;31(3):142–158. doi: 10.1053/j.semperi.2007.04.001
  36. Adams MM, Elam-Evans LD, Wilson HG, Gilbertz DA. Rates of and factors associated with recurrence of preterm delivery. JAMA. 2000;283(12):1591–1596. doi: 10.1001/jama.283.12.1591
  37. Ananth CV, Getahun D, Peltier MR, et al. Recurrence of spontaneous versus medically indicated preterm birth. Am J Obstet Gynecol. 2006;195(3):643–650. doi: 10.1016/j.ajog.2006.05.022
  38. Mercer BM, Goldenberg RL, Moawad AH, et al. The Preterm Prediction Study: effect of gestational age and cause of preterm birth on subsequent obstetric outcome. Am J Obstet Gynecol. 1999;181(5 Pt 1):1216–1221. doi: 10.1016/s0002-9378(99)70111-0
  39. Langhoff-Roos J, Krebs L, Klungsoyr K, et al. The Nordic medical birth registers — a potential goldmine for clinical research. Acta Obstet Gynecol Scand. 2014;93(2):132–137. doi: 10.1111/aogs.12302
  40. Imankulova B, Aimagambetova G, Saiddildina L, Ukybassova T. Pregnancy outcomes complicated by preterm premature rupture of membranes: retrospective review of cases in three institutions in Kazakhstan. Cent Asian J Glob Health. 2014;3(Suppl):222. doi: 10.5195/cajgh.2014.222

Дополнительные файлы

Доп. файлы
Действие
1. JATS XML

© Эко-Вектор, 2023

Creative Commons License
Эта статья доступна по лицензии Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

СМИ зарегистрировано Федеральной службой по надзору в сфере связи, информационных технологий и массовых коммуникаций (Роскомнадзор).
Регистрационный номер и дата принятия решения о регистрации СМИ: серия ПИ № ФС 77 - 78166 от 20.03.2020.