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Evaluation of Preterm Birth and its Associated Risk Factors in Southeast Iran in 2020: A Glance to Social and Care Factors
Abstract
Aims:
This study aimed to assess pregnancy health care and the incidence of PTB in the south of Kerman province.
Background:
For the plan and management of prevention programs effectively, it is important to consider the incidence and trend of preterm births (PTB).
Methods:
In this cross-sectional (descriptive and analytical) study, the national code of mothers of premature infants was extracted by reporting from the national system of the Ministry of Health. The data collection tool was a researcher-made checklist. Data analysis was carried out by SPSS version 20 software and the significance level was <0.05.
Results and Discussion:
A total of 554 premature infants were examined, and 55% of them were boys. The gender of the infant and the number of cares received (p<0.01), the level of education of the mother and father (p < 0.001), the mother’s occupation (p < 0.01), the father's occupation (p < 0.001), monthly income and participation in preparatory classes of childbirth (p<0.01), place of residence (p<0.05), appropriateness of receiving care with pregnancy age (p<0.001) had statistically significant relationship with the number of care received.
Conclusion:
This study showed potential risk factors associated with preterm delivery and subsequent management to prevent preterm delivery in low-risk and high-risk women with singleton or multiple pregnancies. A history of premature birth is the most important risk factor for premature birth in the next pregnancy.
1. INTRODUCTION
The prevalence of PTB in 184 countries has been estimated by the World Health Organization (WHO) between 5 and 18%. PTB is increasing in almost all countries. About one-third of infant deaths are directly attributable to prematurity, preventing the achievement of the Third Sustainable Development Goals (SDG)-3 (Good Health and Well-being) [1, 2].
More than three-quarters of all PTBs occur in Africa and Asia. Additionally, 15.5% of all children are born with low birth weight (LBW), defined as a birth weight of fewer than 2500 grams, and 95.6% of these children are born in low-income countries [3]. For the prevention of PTB, prenatal care should follow the recommended protocols, and more attention is needed on multiparous women and unplanned pregnancies. A history of PTB is the most important risk factor for PTB in the next pregnancy. General risk factors with a much smaller effect include ethnicity, low socioeconomic status, maternal weight, smoking, and periodontal status [4].
A study in the United States found that nearly 1 in 10 babies are PTBs, and PTB and LBW infants are at higher risk for vaccine-preventable infections and related complications [5]. The infant mortality rate (IMR) is used as a standard index for the development of educational and social health care in a country [6] and undoubtedly, the first step in reducing the mortality rate and improving the level of this index is to identify the causes and risk factors of death and mortality [7]. Many studies have been conducted in this field and PTB and LBW were found to be among the most common causes of infant mortality [8-12].
Although many studies have considered multiple pregnancies as a risk factor for increased infant mortality, Cande et al. (2004) reported that despite the increase in preterm births among twin pregnancies, no increased risk of any kind, even in their mortality rate, due to obstetric interventions has been reported [13]. Fallahian et al. demonstrated that infant mortality increased 7.5 times in the group of pregnant mothers suffering from hypertension [12]. While Chen et al. (2006) stated that blood pressure caused by pregnancy is associated with a decrease in the mortality of premature babies [14].
Preeclampsia, a common disorder during pregnancy related to high blood pressure, can have significant effects on both the mother and the baby. It is characterized by new-onset hypertension after 20 weeks of gestation, along with maternal or placental dysfunction or proteinuria. Preeclampsia can impact the blood supply to the placenta, leading to poor fetal growth and an increased risk of preterm labor. It is associated with 12% of babies born small for gestational age and one-fifth of premature births. In developing countries, preeclampsia contributes to a quarter of stillbirths and infant deaths [15-17].
The family-centered medical home (FCMH) is the recommended healthcare delivery model for children. It is unknown how often PTB receive care in an FCMH and how this affects health service utilization [18]. Contraception after childbirth is an important tool for preventing recurrent preterm birth. Antepartum contraceptive counseling increases the uptake of postpartum contraceptives, indicating that women with preterm labor are less likely to be exposed to prenatal contraceptive counseling [19].
Women who give birth between 16 and 36 weeks of pregnancy have an increased risk of preterm birth in subsequent pregnancies. The approximate risk of recurrent preterm birth can be estimated by a comprehensive reproductive history, emphasizing the mother's race, number, and gestational age of previous births, and the sequence of events preceding the index preterm birth. Interventions, including smoking cessation, eradication of asymptomatic bacteriuria, progestational agents, and cervical cerclage, can reduce the risk of recurrent preterm birth if used appropriately [20].
In a multivariate logistic analysis, the young mother's age, pregnancy complications, and fetal anomalies in the second pregnancy as well as previous abortions, short interval between pregnancies and length of pregnancy in the first pregnancy, the incidence of adverse pregnancy outcomes (perinatal mortality, small for gestational age, gestational age less than 34 weeks, Apgar ≤ 7), and lack of prenatal care were significantly associated with adverse pregnancy outcomes and incidence of recurrent preterm birth [21].
In a study titled “Perspectives in the Prevention of Premature Birth”, Pierre-Yves Ancel showed that obstetric and neonatal interventions can improve the survival of premature babies [22]. Pregnancy and newborn care is a combination of appropriate and timely interventions for the prevention and/or management of preterm birth, including pre-pregnancy and intra-pregnancy care [23].
Therefore, interventions should be made to find ways to prevent and reduce preterm birth. Although there are several programs available in the form of guidelines on how to prevent the frequency of premature births, the results of several studies [24, 25] showed that most of the interventions that are carried out to prevent premature birth have not had a favorable effect on reducing the rate of premature birth. Therefore, public health approaches and public awareness at the community level of the factors involved in premature birth, regular screenings, and midwifery interventions as soon as possible can play a role in preventing premature birth [22].
Effective interventions for healthy PTB infants are needed to increase the use of preventive care and reduce the use of acute care in the first few months after discharge from the NICU [26]. Moreover, some studies reported that there are certain changes in neonatal outcomes between different countries [27]. In order to plan and manage prevention programs effectively, it is important to consider the incidence and trend of PTB. The purpose of this study was to determine the incidence of PTB and process evaluation of pregnancy health care in the south of Kerman province, Iran.
2. METHODS AND MATERIALS
In this cross-sectional study, first, the national PTB maternal care code was entered into the national system of the Ministry of Health (Iman), and information on premature children was extracted. Finally, 554 premature babies were identified and included in the study. According to the checklist made by the researcher, which was extracted by studying various sources and scientific articles, the available information was extracted from the system, and the information that was not in the system was completed by asking the mothers. Premature babies whose prematurity disorder occurred from April 1st, 2018, to the end of March, 2018, were included in the study. The data collection tool was a researcher-made checklist that included the demographic characteristics of the preterm infants and parents, the place of residence, and the habit/or attitudes of healthcare and mothers, which could contribute to PTB.
Data analysis was carried out using SPSS version 20. Descriptive statistics include number, percentage, mean, and standard deviation, and also for comparing demographic variables with the health care of preterm infants, statistical tests, including one-way analysis of variance, chi-square, t-test, and Spearman's correlation, were used with a significance level <0.05.
3. RESULTS
A total of 554 premature babies were included in the study, 55% of them were boys. About 80% of mothers of premature babies were between 18 and 35 years old, most parents had primary education (mothers and fathers with 13.70% and 20%, respectively), most mothers were housewives (87.90%) and most fathers were farmers (37%) and 58/50 parents lived in the village (Table 1).
This study indicated that 95% of mothers did not participate in childbirth preparation classes, 33% did not receive pre-pregnancy care, about 7% did not go to healthcare centers due to their gestational age, and about 9% of mothers were under the supervision of only one health service provider (Table 2).
Variable | Category/Scale | Mean ± SD or N (%) |
---|---|---|
Mother's age in the recent pregnancy | 18Years> | 12 (2.20%) |
18-35 Years | 437 (78.90%) | |
35Years< | 105 (19.00%) | |
Infant’s gender | Male | 307 (55.40%) |
Female | 247 (44.60%) | |
Mother education | Illiterate | 34 (6.1) |
Elementary | 76 (13.17) | |
Guidance | 87 (15.7) | |
High school | 72 (13) | |
Diploma | 162 (29.2) | |
Associate degree | 31 (5.6) | |
Bachelor≤ | 92 (16.6) | |
Father education | Illiterate | 47 (8.5) |
Elementary | 111 (20) | |
Guidance | 93 (16.8) | |
High school | 74 (13.4) | |
Diploma | 124 (22.4) | |
Associate degree | 35 (6.3) | |
Bachelor≤ | 70 (12.6) | |
Accommodations | City | 230 (41.5) |
Village | 324 (58.5) | |
Mother occupation | Employee | 32 (5.8) |
Housewife | 477 (87.9) | |
Farmer/breeder | 9 (1.6) | |
Manual worker | 8 (1.4) | |
Other | 18 (3.2) | |
Father occupation | Employee | 65 (11.7) |
Farmer/breeder | 205 (37) | |
Manual worker | 133 (24) | |
Driver | 23 (4.2) | |
The seller | 17 (3.1) | |
Unemployed | 13 (2.3) | |
Other | 98 (17.7) | |
Monthly family income | 5 million> | 102 (18.4) |
5-10 Million | 219 (39.5) | |
10 million< | 233 (42.1) | |
Type of residential house | Personal | 422 (76.2) |
Rental | 132 (22.8) | |
Drinking water source | Piping network | 512 (42.4) |
Well | 10 (1.8) | |
Tanker | 27 (4.9) | |
Other | 5 (0.9) |
There was a statistical relationship between the number of risk factors related to the occurrence of preterm infants in the context of receiving health care and demographic variables, between the gender of the baby and the number of cares received (p<0.01), the level of education of the mother and father and the number of cares received (p < 0.001), mother's occupation and the number of care received (p < 0.01), father's occupation and the number of care received (p < 0.001), monthly income and participation in childbirth preparatory classes and the number of cares received (in both cases), the type of residential home and the number of cares received (p<0.01), place of residence and pre-pregnancy cares (p<0.05), appropriateness of receiving care with pregnancy age (0.5) (p<0.001), and the number of people providing healthcare services (p<0.001) (Table 3).
Variable | Category/Scale | Mean ± SD or N (%) |
---|---|---|
Mother's participation in birth preparation classes | Yes | 28 (5.1) |
No | 526 (94.9) | |
Pre-pregnancy care | Yes | 369 (66.6) |
No | 185 (33.4) | |
Proportion of receiving care with gestational age | Yes | 514 (92.8) |
No | 40 (7.2) | |
Number of pregnant women cared for by the service provider | Behvarz (rural health workers) | 1 (0.2) |
Midwife | 33 (6) | |
General practitioner | 0 | |
Obstetricians | 14 (2.52) | |
Combination of caregivers | 506 (91.3) |
Factors Related to Prenatal Care | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
Each Pregnant Woman Received Health Care from Multiple Healthcare Providers | Proportion of Receiving Care with Gestational Age | Pre-pregnancy Care | Mother's Participation in Birth Preparation Classes | Category/Scale | Variable | |||||
1person | 2person | 2person< | Yes | No | Yes | No | Yes | No | ||
11 | 39 | 197 | 228 | 19 | 160 | 87 | 14 | 233 | Girl | Baby gender |
37 | 47 | 223 | 286 | 21 | 209 | 98 | 14 | 293 | Boy | |
0.00 | 0.70 | 0.41 | 0.55 | p-value* | ||||||
0 | 0 | 12 | 12 | 0 | 9 | 3 | 2 | 10 | 18> | Mother's age in the recent pregnancy |
40 | 65 | 332 | 409 | 28 | 300 | 137 | 22 | 415 | 18-35 | |
8 | 21 | 76 | 93 | 12 | 60 | 45 | 4 | 101 | 35< | |
0.22 | 0.12 | 0.06 | 0.15 | p-value | ||||||
25 | 2 | 7 | 2 | 32 | 11 | 23 | 32 | 2 | Illiterate | Mother literacy |
66 | 2 | 8 | 4 | 72 | 28 | 48 | 71 | 5 | Elementary | |
80 | 2 | 5 | 5 | 82 | 32 | 55 | 80 | 7 | Guidance | |
58 | 8 | 6 | 4 | 68 | 17 | 55 | 65 | 7 | High school | |
124 | 28 | 10 | 14 | 148 | 52 | 110 | 159 | 3 | Diploma | |
20 | 11 | 0 | 1 | 30 | 11 | 20 | 31 | 0 | Associate Degree | |
47 | 33 | 12 | 10 | 82 | 34 | 58 | 88 | 4 | Bachelor≤ | |
0.00 | 0.65 | 0.58 | 0.10 | p-value | ||||||
38 | 2 | 7 | 3 | 44 | 11 | 36 | 43 | 4 | Illiterate | Father literacy |
96 | 5 | 10 | 8 | 103 | 46 | 65 | 103 | 8 | Elementary | |
82 | 4 | 7 | 5 | 88 | 26 | 67 | 88 | 5 | Guidance | |
61 | 10 | 3 | 5 | 69 | 20 | 54 | 70 | 4 | High school | |
83 | 32 | 9 | 110 | 114 | 47 | 77 | 120 | 4 | Diploma | |
21 | 11 | 3 | 0 | 35 | 11 | 24 | 35 | 0 | Associate Degree | |
39 | 22 | 9 | 9 | 61 | 24 | 46 | 67 | 3 | Bachelor≤ | |
0.00 | 0.34 | 0.16 | 0.53 | p-value | ||||||
14 | 10 | 8 | 6 | 26 | 17 | 15 | 31 | 1 | Employee | Mother’s occupation |
376 | 73 | 38 | 31 | 456 | 154 | 333 | 461 | 26 | Housewife | |
9 | 0 | 0 | 0 | 9 | 3 | 6 | 9 | 0 | Farmer/breeder | |
8 | 0 | 0 | 0 | 8 | 4 | 4 | 8 | 0 | manual worker | |
13 | 3 | 2 | 3 | 15 | 7 | 11 | 17 | 1 | Other | |
0.00 | 0.03 | 0.11 | 0/871 | p-value | ||||||
33 | 21 | 11 | 7 | 58 | 22 | 43 | 63 | 2 | Employee | Father’s occupation |
173 | 16 | 16 | 6 | 199 | 60 | 145 | 191 | 14 | Farmer/breeder | |
121 | 7 | 5 | 11 | 122 | 38 | 95 | 128 | 5 | manual worker | |
13 | 7 | 3 | 2 | 21 | 13 | 10 | 23 | 0 | Driver | |
5 | 9 | 3 | 3 | 14 | 6 | 11 | 16 | 1 | the seller | |
66 | 24 | 8 | 8 | 90 | 40 | 58 | 93 | 5 | Unemployed | |
9 | 2 | 2 | 3 | 10 | 6 | 7 | 12 | 1 | Other | |
0.00 | 0.02 | 0.06 | 0.7 | p-value | ||||||
92 | 5 | 5 | 8 | 94 | 33 | 69 | 89 | 13 | 5 million> | Monthly family income |
184 | 15 | 20 | 9 | 210 | 63 | 156 | 209 | 10 | 5-10 Million | |
144 | 66 | 23 | 23 | 210 | 89 | 144 | 228 | 5 | 10 million< | |
0.00 | 0.05 | 0.10 | 0.00 | p-value | ||||||
332 | 53 | 37 | 30 | 392 | 138 | 284 | 400 | 22 | Personal | Type of residential house |
88 | 33 | 11 | 10 | 122 | 47 | 85 | 126 | 6 | Rental | |
0.00 | 0.85 | 0.53 | 0.76 | p-value | ||||||
381 | 84 | 47 | 38 | 474 | 175 | 337 | 487 | 25 | Piping network | Drinking water source |
9 | 1 | 0 | 0 | 10 | 3 | 7 | 10 | 0 | the well | |
26 | 0 | 1 | 2 | 25 | 5 | 22 | 24 | 3 | Tanker | |
4 | 1 | 0 | 0 | 5 | 2 | 3 | 5 | 0 | Other | |
0.18 | 0.75 | 0.39 | 0.4 | p-value | ||||||
104 | 83 | 43 | 24 | 206 | 89 | 141 | 221 | 9 | City | Accommodations |
316 | 3 | 5 | 16 | 308 | 86 | 228 | 305 | 19 | Village | |
0.00 | 0.01 | 0.02 | 0.3 | p-value |
4. DISCUSSION
Prematurity is considered one of the risk indicators causing infant mortality in any society. Many factors are related to this defect, including various maternal care and cultural, social, and economic situations, etc. This study surveyed potential risk factors associated with preterm delivery and subsequent management to prevent preterm delivery. This was done in low- and high-risk women with singleton or multiple pregnancies. A history of premature birth is the most important risk factor for premature birth in the next pregnancy.
In this study, there was a statistical relationship between the number of risk factors related to the occurrence of PTB in the context of receiving health care and demographic variables, the gender of the baby and the number of cares received, the care of the mother and father and their literacy status and the number of cares received, occupation of mother and the number of cares received, income and father's occupation and the number of cares received, participation in preparation classes and the number of cares received, place of residence and pre-pregnancy care, and the proportion of receiving care with gestational age and the number of health care providers.
Our study showed a significant relationship between the receipt of health care and the birth of a premature baby with the variables of gender, literacy and occupation of the mother and father, income, participation in childbirth preparation classes, gestational age, and the number of health service providers, which was consistent with the results of other studies. Moreover, a study by Xu et al. showed that older maternal age, less maternal education, use of assisted reproductive technology (ART), higher income, living in urban areas, and the gender of the infant were independently associated with a higher incidence of preterm delivery [28].
This study showed that the lower education level of the parents has a statistical association with PTB, which was similar to the results of the studies by Enayat Rad et al. [14] and Eshghizadeh et al. [29], and also, most cases occurred in mothers with a low education level, which was consistent with a study conducted in Spain demonstrating that most cases of premature babies occurred in mothers with secondary education. This is also confirmed by the results of other similar studies conducted in other countries [30, 31].
Razeq et al. showed that male gender, first pregnancy, high blood pressure, preeclampsia, and diabetes were significantly associated with an increased risk of preterm delivery [32].
Our study showed that the mother's illness increases the chance of giving birth to a PTB, which was similar to the results of a study by Enayat Rad et al. [14], while the results of the study by Valadan et al. [33] in Tehran did not show a significant relationship between the mother's illness and the birth of a PTB. This difference in the results can be in the type of selected diseases for examination and their relationship with pregnancy.
This study showed health care during pregnancy was low, which was consistent with the findings of a study by George et al. that showed that health care can prevent adverse pregnancy outcomes, including low birth weight and preterm birth [34]. Moreover, a study by Huybrechts et al. showed that large databases of healthcare utilization should be considered for monitoring drug safety and pregnancy stages [35].
This study reported that preterm infants occurred in mothers with low-education levels. Ghaffari et al. also reported that educational intervention in pregnant women referring to health centers has an effect on maternal and newborn health [36].
In the present study, the mothers of premature babies had less prenatal care. It has been reported that with the increase in the number of care, the chance of having a premature baby decreases, and one of the reasons for this can be more attention to dangerous signs during pregnancy care and proper medical and health advice by health personnel. Islam et al. showed that many maternal and newborn health problems can be prevented with accessible, simple, and cost-effective maternity care interventions during pregnancy, delivery, and the postpartum period [37].
Edu et al. highlighted the importance of antenatal care and stated that the government must address other deterrents to significantly increase the use of maternal health care services [38]. Several studies have shown that improving the condition of prenatal care reduces the risk of premature birth [39, 40].
One of the limitations of the present study that can be mentioned is the nutritional status of women during pregnancy, which is affected by some cases and consequences of pregnancy, and the unwillingness to clearly express personal issues related to the birth of preterm infants among women in society. In order to solve the mentioned limitations, it is suggested to conduct related studies on a larger scale and with a larger number of samples.
CONCLUSION AND RECOMMENDATIONS
In this study, potential risk factors associated with preterm delivery and subsequent management to prevent preterm delivery in low-risk and high-risk women with single or multiple pregnancies were reviewed. A history of premature birth is the most important risk factor for premature birth in the next pregnancy. Performing prenatal care and identifying mothers at risk can reduce the birth of preterm infants.
LIST OF ABBREVIATIONS
PTB | = Preterm births |
WHO | = World health organization |
LBW | = Low birth weight |
IMR | = Infant mortality rate |
FCMH | = Family-centered medical home |
IMR | = Infant mortality rate |
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
This article reports the results of a research project approved by Jiroft University of Medical Sciences with the code of ethics (IR.JMU.REC.1399.086).
HUMAN AND ANIMAL RIGHTS
No animals were used in the studies that are the basis of this research. All human procedures followed were per the guidelines of the Helsinki Declaration of 1975.
CONSENT FOR PUBLICATION
In order to comply with ethical considerations in this research, the information of the participants was kept confidential and other people were not able to access this information. The names and surnames of the participants were not used for data collection, and data collection was done after obtaining the code of ethics from the Jiroft University of Medical Sciences.
AVAILABILITY OF DATA AND MATERIALS
The data that support the findings of this study are available from the corresponding author [S.D] upon reasonable request.
FUNDING
This research was done with the financial support of Jiroft University of Medical Sciences (Grant No. 401178).
ACKNOWLEDGEMENTS
The authors would like to thank and appreciate the cooperation of the health department of Jiroft University of Medical Sciences and the staff of the health centers.