Type of delivery lacks the association with dietary patterns followed by pregnant women in their third trimester

Abstract

Background: Maternal nutrition plays a crucial role in fetal development, women's health, and reproductive capacity. Dietary pattern (DP) is a measure of overall diet and has become widespread in nutrition research as an alternative method to studying individual components of the diet. Aim: this study aims to determine the adopted DPs by Jordanian pregnant women and evaluate their potential associations with the mode of delivery. Methods: A cross-sectional study included 249 healthy Jordanian pregnant women in their third trimester of pregnancy who attended antenatal clinics at Jordan University. Personal information was gathered using a pre-tested structured questionnaire. To investigate dietary patterns, a valid and reliable food frequency questionnaire was employed, and a pregnant physical activity questionnaire was used to estimate physical activity levels. The mode of delivery data was collected from the medical records after delivery. Results: The majority of pregnant women (82.3%) fell within the age range of 20 to 35 years. Notably, 34.5% of the mothers were classified as overweight or obese. Additionally, around one in five deliveries involved emergency cesarean sections. Four distinct DPs were identified and labelled as “fruit and vegetables”, “healthy”, “traditional”, and ‘fat and sugar” dietary patterns. However, no significant association was found between these identified dietary patterns and the occurrence of Caesarean section (CS) across all tertiles. Conclusion: The analysis revealed no substantial protective effect of the DPs against the occurrence of CS across all tertiles of dietary patterns. However, further studies are needed to either confirm or challenge our findings.

Keywords

Type of delivery dietary patterns pregnant women pregnancy third trimester

Key messages

One in five deliveries involved emergency cesarean sections.

Four distinct DPs were identified and categorized them as follows: fruit and vegetables, healthy, traditional, and fat and sugar.

No significant association was found between the identified dietary patterns and Caesarean section across all tertiles.

Introduction

Childbirth is a significant event in a woman's life, but it can also come with health issues. There are different types of childbirth like vaginal delivery (VD) assisted vaginal deli vary, and cesarean section (CS) (Evans et al., 2022). The global rate of CS has been increasing over the years, it reaches 21%, exceeding the recommended rate of 10%–15% set by the World Health Organization (WHO) (WHO, 2021). This high rate of CS may be due to non-medical reasons, such as maternal anxiety or fear of pain from VD or physician's preference, and financial incentives for hospitals (Angolile et al., 2023).

Cesarean section is a surgical procedure where the baby is delivered through an incision in the mother's abdomen. It is typically recommended when there are risks associated with VD (Rahman et al., 2022), such as prolonged or obstructed labor, fetal distress, or certain medical conditions (Evans et al., 2022; Keag et al., 2018). However, CS comes with their own set of risks and adverse health outcomes for both the mother and the child. Mothers who undergo CS are at a higher risk of maternal mortality, severe complications, and adverse outcomes in subsequent pregnancies (Sandall et al., 2018). They may also experience psychological effects such as postnatal depression and difficulties in the mother-infant relationship (Clement, 2001). Infants born via CS may have an increased risk of immune-related conditions, allergies, and reduced diversity of the gut microbiome (Sandall et al., 2018).

The nutrition of a mother has a significant impact on the development of the fetus, and the health of both the infant and the mother. It also affects the woman's reproductive capacity (Paknahad et al., 2019). Dietary pattern approach gives more comprehensive knowledge about the relationship between nutrition and disease (Tucker, 2010). Foods are not consumed in isolation and people eat foods as a mixture of nutrients and non-nutrients. Additionally, the biological complexity resulting from interactions between nutrients is not taken into consideration by the individual nutrient approach (Chen et al., 2016). However, a dietary pattern of a population can be influenced by socio-cultural factors (Völgyi et al., 2013) and the availability of food (Mishra et al., 2010).

Limited data are available related to the association between maternal nutrient intake and dietary patterns (DPs) and mode of delivery (Abdollahi et al., 2021). A systematic review reported that a healthy diet may be associated with decreased odds of CS (5 studies, 3921 participants; OR: 0.83; 95% CI: 0.68, 1.00; P = 0.06) (Abdollahi et al., 2021). However, in Jordan and up to the researcher's knowledge, no study has been conducted to find the association between diet and type of delivery. Therefore, this study aimed to evaluate the maternal DPs and their associations with the type of delivery in a sample of Jordanian pregnant women.

Materials and methods

Study design and participants

A hospital-based cross-sectional study was conducted to investigate the association between DPs and the type of delivery among Jordanian pregnant women who were in their third trimester of pregnancy (>28 weeks of gestation) who came to Jordan University Hospital for routine antenatal care between November 2019 and December 2021. Inclusion criteria were being a healthy pregnant woman in the third trimester with no medical conditions such as pregnancy-induced hypertension or gestational diabetes mellitus, or using any type of medication other than vitamin/mineral supplements and multivitamins; being 18 years or older; having a singleton pregnancy; being her first CS; and having Jordanian nationality (Hajianfar et al., 2018; Shakeri and Jafarirad, 2019). Women with scheduled cesarean birth due to in vitro fertilization or any other reasons such as mother's request, or for clinical reasons; women who smoked, were mentally unstable, or were seriously ill; and moms who followed a specified diet were all excluded (Hajianfar et al., 2018).

The sample size was determined using a single population proportion formula with a 95% confidence interval and a 5% margin of error. The rate of CS in Jordan was calculated as 31.0% (Salem, 2021). With these assumptions, the overall sample size was 229; however, the final sample size was 249 healthy Jordanian pregnant women. The study participants were recruited conveniently.

This study was conducted in accordance with the Declaration of Helsinki 1964, and the study protocol was approved by the Institutional Review Board. A consent form was obtained from all participants. The data retrieved from the medical records was treated with absolute secrecy; neither the case records nor the data extracted were utilized for any other reason, and all information gathered from the participants was retained anonymously.

Data collection tools and procedure

A well-trained dietitian conducted face-to-face interviews to collect data. Three structured questionnaires were used: a personal information questionnaire, a food frequency questionnaire (FFQ) (Tayyem et al., 2020), and a pregnant physical activity questionnaire (PPAQ) (Chasan-Taber et al., 2004; Papazian et al., 2020).

A pre-tested structured questionnaire was used to collect personal information. Sociodemographic data such as maternal age, monthly income, and educational level were collected. Maternal health data such as maternal anthropometric measurements (height, pre-pregnancy weight, and weight before delivery), pregnancy history and birth information (number of pregnancies, number and type of previous deliveries, and duration between the last two pregnancies) as well as type of current delivery was gathered.

Dietary Intake Assessment

A valid, reliable, and Arabic quantitative FFQ that included 117 food items was used to assess usual maternal dietary intake over a period of one trimester (Tayyem et al., 2020). A total of 117 food items were categorized into 11 food groups based on the similarity of nutrition profiles and cooking method: vegetables (21 items); meats such as red meat (lamb and beef), chicken, fish, cold meat, and others (16 items); fruits and fruit juices (19 items); milk and dairy products (5 items); cereals (10 items); beans (3 items); soups and sauces (4 items); drinks (4 items); snacks and sweets (12 items); fats and oils (6 items); and vitamins and minerals supplements and herbs and spices (9 items). The questionnaire has 10 frequency selections that ranged from “never” throughout the past 4 weeks to “≥ 6 per day” for beverages, and nine frequency selections that ranged from “never” throughout the past 4 weeks to “≥2 per day” for foods. The data on food consumption frequency was converted into the number of times each food was consumed over a week.

Physical Activity Level

A valid, reliable and Arabic semi-quantitative pregnancy physical activity questionnaire (PPAQ) was used to evaluate maternal physical activity level during the third trimester (Papazian et al., 2020). In the PPAQ, participants were asked to recall how much time they spent in the current trimester participating in 36 different types of activities divided into four categories: household/caregiving (16 activities); occupational (5 activities); sports/exercise (9 activities = 7 questions + two open questions, allowing participants to recall any activities not previously itemized); transportation (3 activities); and inactivity (3 activities). The number of hours spent on each activity was multiplied by its intensity to calculate a weekly average of metabolic equivalent of activity (MET) units (MET h/wk), which was then added together to calculate the overall activity score per week. The total number of MET hour per week was also calculated for each activity categorization and intensity level (sedentary activity [1.5 METs], light intensity activity [1.5–3.0 METs], moderate-intensity activity [3.0–6.0 METs], or severe intensity activity [> 6.0 METs] (Chasan-Taber et al. 2004; Papazian et al., 2020).

Anthropometric Measurements of Pregnant Women

Pre-pregnancy BMI (weight in kilograms/height in meters²) was calculated using recalled height and weight from the personal information questionnaire and was categorized as follows: underweight (BMI less than 18.5 kg/m²), normal weight (BMI 18.5–24.9 kg/m²), overweight (BMI 25.0–29.9 kg/m²), obese (BMI 30.0 kg/m² or greater) (Deputy et al., 2015). Gestational weight gain (weight before delivery – pre-pregnancy weight) was calculated (Voerman et al., 2019) and was categorized based on the Institute of Medicine recommendations: 28–40 pounds (12.5–18 kg) for underweight women, 25–35 pounds (11.5–16 kg) for normal weight women, 15–25 (7–11.5 kg) pounds for overweight women, and 11–20 pounds (5–9 kg) for obese women) (Deputy et al., 2015).

Statistical analysis

The Statistical Package for the Social Sciences (SPSS) version 22.0 (IBM SPSS Statistics for Windows, IBM Corporation) was used to analyze data. Categorical variables were expressed as frequency (%) and continuous variables were expressed as median and interquartile (25 and 75th percentiles). Factor analysis (principal component analysis) is a multivariate statistical method, which uses information reported on food frequency questionnaires or in dietary records to estimate common underlying factors or patterns of food consumption (Hu, 2002). Factor analysis was applied to identify the major posterior DPs based on 63 food groups. Food groups were sorted by the size of loading coefficients, with those having absolute rotated factor loadings >0.30 considered significant contributors to identifying DPs. The KMO was 0.58. Food groups can be included in more than one dietary pattern. The consumption of the food items identified were divided into tertiles (T) in which T1 was the lowest intake and theT3 was the highest intake. Normal delivery was considered the reference group. Two-level logistic regression (binary logistic regression model) was then conducted to detect odds ratios (OR) and 95% confidence intervals (CI) based on calculated tertiles, to investigate the association between DPs and CS. The binary model was adjusted for maternal age (continuous), infant weight (continuous), gestational week (continuous), physical activity (continuous), and nutritional problems (categorical). P-values were calculated using a linear logistic regression test, with a significant P-value of trend set at <0.05.

Results

The sociodemographic and anthropometric characteristics of 249 pregnant women are shown in Table 1. The means of pre-pregnancy BMI and total GWG kg were 24.2 kg/m² and 12.9 kg, respectively. Whereas the mean of PA was 162.7 MET-h wk⁻¹. The majority of pregnant women were aged between 20–35 years (82.3%). Over half of the sample were graduate studies and bachelor-educated (61.4). Approximately, one over five of the labor spontaneity was emergency cesarean.

Table 1.

Sociodemographic and health characteristics of the study population.

Variables
Characteristics of the mothers	Median (25^th −75^th percentile)
Pre-Pregnancy Weight (kg)	63.0(55.0–72.0)
Height (m)	1.6(1.6–1.7)
Pre-Pregnancy BMI (kg/m²)	23.7(21.1–26.7)
Total GWG (kg)	12.0(9.0–16.0)
Total Physical Activity (MET-h· $w k^{- 1}$ )	163.5(80.2–233.3)
Age (Year)	28.0(25.0–33.0)
Education N (%)
- Primary education	20(8.0)
- Secondary education	49(19.7)
- Diploma	26(10.4)
- Bachelor	140(56.2)
- Graduate studies	13(5.2)
- Missing	1(0.4)
Occupation
- Yes	83(33.3)
- No	166(66.7)
Monthly Family Income (Jordan Dinar)
-<300	22(8.8)
-300–500	114(45.8)
→500	101(40.6)
-Missing	12(4.8)
Pre-pregnancy BMI (kg/m2)
- Underweight	18(7.2)
- Normal weight	133(53.4)
- Overweight	67(26.9)
- Obese	19(7.6)
- Missing	12(4.8)
Total Gestational Weight Gain
- Inadequate	67(26.9)
- Normal	82(32.9)
- Excessive	78(31.3)
- Missing	22(8.8)
Gravity
- One	64(25.7)
- Two	46(18.5)
-≥Three	139(55.8)
Parity
- One	75(30.1)
- Two	54(21.7)
-≥Three	120(48.2)
Labor Spontaneity
- Vaginal delivery	202(81.1)
- Emergency cesarean	47(18.9)
History of Induced Delivery
- No	132(53)
- Yes	117(47)
Inter-Delivery Interval (Year)
First delivery	66(26.5)
-≤Two years	60(24.1)
→Two years	123(49.4)

Categorical variables are presented in frequency (%), and continuous variables are presented as mean ± SD.

Abbreviations: BMI, body mass index; GWG, gestational weight gain.

Table 2 shows four distinct DPs were identified according to the results obtained from the factor loading matrix. The key factors accounted for 26.8% of the total variance in food group intakes. Fruit and vegetable DP included orange, pomegranate, tomato paste, pomelo, cooked vegetables, sweet potato, onion, cooked cabbage, labneh, spinach pastry, and olive pickles. The second dietary pattern, the healthy DP consisted of other fruits, lemon juice, dried fruits, white cheeses, pickles, orange or grapefruit juice, strawberry, regular salad, butter, olive pickles, minced meat, canned tuna, bulgur, colored pepper, tahini/tahini halva, baked sheep meat, baked sheep meat, fresh vegetable, fried potato, and cream. Cooked vegetables, dried fruits, carrots, mixed vegetables, peas, boiled potato, hot tea, soups, cooked jute, hamburger, olive oil, added sugar, okra, fried vegetables, stuffed vegetables, fresh vegetables, and fats were the main constituents of a traditional dietary pattern. Finally, fat and sugar dietary patterns had positive factor loadings for biscuits, falafel, candies, chocolate, cheese pastry, hummus, American coffee, soft drinks, milk, fig, macaroni, fried potato, ketchup, Arabic sweets, cream, cake, and cabbage salad.

Table 2.

Factor loading matrix for Major dietary patterns based on the 63 food groups.

Food	Dietary patterns
Food	Fruits and Vegetables	Healthy	Traditional	Fat and Sugar
Ice cream	−0.667	–	–	–
Orange	0.647	–	–	–
Peach	−0.611	–	–	–
Watermelon	0.554	–	–	–
Grapes	−0.551	–	–	–
Pomegranate	0.543	–	–	–
Tomato paste	0.528	–	–	–
Pomelo	0.518	–	–	–
Melon	0.504	–	–	–
Cooked vegetables^a	0.487	–	0.330	–
Sweet potato	0.479	–	–	–
Onion	0.406	–	–	–
Cooked cabbage	0.405	–	–	–
Other fruits^b	0.361	0.345	–	–
Labneh	0.337	–	–	–
Spinach pastry	0.323	–	–	–
Lemon juice	–	0.486	–	–
Dried fruits ^c	–	0.460	0.376	–
White cheeses	–	0.454	–	–
Pickles	–	0.449	–	–
Orange or grapefruit juice	–	0.447	–	–
Strawberry	–	0.445	–	–
Regular salad	–	0.421	–	–
Butter	–	0.418	–	–
Olive pickles	0.390	0.397	–	–
Minced meat	–	0.394	–	–
Canned tuna	–	0.385	–	–
Bulgur	–	0.380	–	–
Colored pepper	–	0.379	–	–
Tahini/Tahini halva	–	0.353	–	–
Baked sheep meat	–	0.341	–	–
Carrots	–	–	0.584	–
Mixed vegetables ^d	–	–	0.574	–
Peas	–	–	0.530	–
Boiled potato	–	–	0.445	–
Hot tea	–	–	0.436	–
Soups ^e	–	–	0.432	–
Cooked Jute	–	–	0.431	–
Hamburger	–	0.407	0.425	–
Olive oil	–	–	0.424	–
Added sugar	–	–	0.386	–
Okra	0.329	–	0.349	–
Fried vegetables ^f	–	–	0.341	–
Stuffed vegetable ^g	–	–	0.338	–
Fresh vegetables ^h	–	0.305	0.324	–
Fats ⁱ	–	–	0.302	–
Biscuits	–	–	–	0.565
Falafel	–	–	–	0.533
Candies	–	–	–	0.476
Chocolate	–	–	–	0.448
Cheese pastry	–	–	–	0.444
Hummus	–	–	–	0.443
American coffee	–	–	–	0.431
Soft drinks	–	–	−0.374	0.427
Milk ^j	–	–	–	0.416
Fig	0.376	–	–	0.405
Macaroni	–	–	–	0.402
Fried potato	–	0.339	0.342	0.384
Ketchup	–	–	–	0.378
Arabic sweets	–	–	–	0.377
Cream	–	0.318	–	0.369
Cake	–	–	–	0.354
Cabbage salad	–	–	–	0.318
% of Variance	8.3	6.3	6.1	6.1

Food groups were sorted by the size of loading coefficients. Food groups with factor loadings below 0.3 were not listed for increasing accuracy. Food groups can be included in more than one dietary pattern. KMO = 0.58. ^a Cooked vegetable: spinach and jute. ^b Other fruits: pineapple, kiwi, and cherries. ^c Dried fruit: dried figs, apricots, and raisins. ^d Mixed vegetables: peas, potato, carrots, tomato, onion, and garlic. ^e Soups: lentils, cream of mushroom, vegetables, ramen noodles, and freekeh. ^f Fried vegetables: eggplant, tomato, and squash. ^g Stuffed vegetables: eggplant and squash. ^h Fresh vegetables: arugula and parsley. ⁱ Fats: vegetable oil, olive oil, butter, and margarine. ^j Milk: added milk to the tea or coffee.

Table 3 demonstrates that there were no associations between extracted DPs (fruit and vegetables, healthy, traditional, and fat and sugar) and CS across all tertiles. The ORs (%CI) for the second and the third tertiles of fruit and vegetable, healthy, traditional, and fat and sugar DPs were [T2: 0.64(0.24–1.70), T3: 0.49 (0.18–1.39), P = 0.193; T2:1.46(0.53–4.01), T3:1.34(0.51–3.48), P = 0.0464; T2:1.37(0.51–3.69), T3:1.23(0.45–3.38), P = 0.725; T2:1.16(0.43–3.19), T3:1.45(0.53–3.97), P = 0.636], respectively.

Table 3.

The association between four dietary patterns and cesarean section delivery.

Dietary patterns	OR (95%CI)^a
Dietary patterns	T1^b Reference	T2	T3^c	P- trend*
Fruit and Vegetable	1	0.64(0.24–1.70)	0.49 (0.18–1.39)	0.193
Healthy	1	1.46(0.53–4.01)	1.34(0.51–3.48)	0.464
Traditional	1	1.37(0.51–3.69)	1.23(0.45–3.38)	0.725
Fat and Sugar	1	1.16(0.43–3.19)	1.45(0.53–3.97)	0.636

Adjusted for maternal age, infant weight, gestational week, physical activity, and nutritional problems.

T1 = the lowest intake.

T3 = the highest intake. *P-values were calculated by linear logistic regression.

Discussion

This study analyzed DPs in a sample of Jordanian pregnant on their third trimester and the association between DPs and CS. In this study, four DPs (fruit and vegetables, healthy, traditional and fat and sugar) were identified. These findings align with several studies that have identified certain similar dietary patterns in pregnant women (Flynn et al., 2016; Ghorbani-Kafteroodi et al., 2023; Papazian et al., 2022; Tayyem et al., 2021).

Tayyem et al. (2021) revealed that three distinct DPs were followed over the entire pregnancy period among Jordanian pregnant women: “high-fat, high-sugar”, “fruit and vegetables”, and “high protein”. They reported that the educational level of the participants showed an association with their DPs. Specifically, the “fruit and vegetables” and “healthy” patterns were notably favored by highly educated women, particularly during their third trimester. This suggests a significant association between educational background and the choice of DPs during pregnancy. However, they did not test the association between DPs and the type of delivery. Similarly, another study performed by Flynn et al. (2016) identified four distinct baseline DPs were defined; fruit and vegetables, African/Caribbean, processed, and snacks, and they were differently associated with social and demographic factors.

A more recent study found that maternal education and income were negatively linked with the intake of a “protein-rich diet with non-alcoholic beverages”, “typical diet with alcohol”, and “legumes” in a dose response. Employed women consumed more fruits (adjusted β: 0.33(0.02; 0.65) P = 0.040) than non-working women (Adeoye and Okekunle, 2022). The study conducted by Paknahad et al. (2019) showed that the consumption of a high carbohydrate, high fat dietary pattern and a high fiber dietary pattern was significantly associated with fetal macrosomia, which may increase the likelihood of performing a CS (Turkmen et al., 2018).

DPs are influenced by culture, geography, and regional conditions, which can impact health outcomes (Englund-Ögge et al., 2019; Hu, 2002; Teixeira et al., 2018). Englund-Ögge et al. (2019) found that the definitions of “healthy” and “unhealthy” vary throughout groups, making comparisons challenging. Comparing study results from different populations can assist in comprehending and interpreting findings (Englund-Ögge et al. 2019).

This study also found that there were no associations between DPs and CS. This result was consistent with the literature. A recent systematic review stated that there were no associations between unhealthy (3 studies, 1922 participants; OR: 1.16; 95% CI: 0.81, 1.67; P = 0.39) or mixed (3 studies, 1922 participants; OR: 0.91; 95% CI: 0.68, 1.22; P = 0.54) DPs and CS (Abdollahi et al., 2021). Additionally, the small number of CS cases included in this study could be a potential explanation for the absence of significant associations between DPs and CS. This limited sample size may have hindered the ability to detect meaningful relationships. On another hand, a very recent cross-sectional study performed on 5688 pregnant women from 10 distinctive Greek areas revealed that pregnant women who adhered to the Mediterranean diet had considerably higher rates of vaginal delivery compared to those who did not. Indicatively, among the women coming with enhanced compliance to the Mediterranean diet, 41.5% of them delivered by SC, but this frequency was significantly raised among the women presenting with extremely low levels of adherence to the Mediterranean diet as 66.5% of them delivered via CS (Antasouras et al., 2023).

The strength of this study is that it examined the effect of food combinations on SC, which a single nutrient analysis may not be able to detect. Furthermore, the FFQ utilized to gather data was designed exclusively for pregnant Jordanian women. We also considered lifestyle and nutritional factors, in addition to all sociodemographic and health characteristics. It is also important to note the study's eligibility requirements, which call for healthy women who do not have any chronic diseases or pregnancy-related diseases such as diabetes mellitus hypertension, gestational diabetes mellitus, pregnancy-induced hypertension, or preeclampsia and do not require special dietary regimens. Another key advantage is that dietary consumption was examined before the results were known.

A primary limitation of this study is its cross-sectional research design, preventing the assertion of a causal association between DPs and CS. Prospective investigations are essential to validate the findings presented here. Although the total number of pregnant women included in the study is acceptable, the number of those who underwent CS is somewhat low. If the study had a larger number of participants who had undergone CS, it might have been possible to identify significant associations between DPs and CS. The study is also vulnerable to recall biases, especially concerning dietary data, even though we limited our assessment to food intake for just one trimester. Furthermore, our focus on the one trimester food intake does not guarantee a representation of dietary patterns throughout the entire pregnancy. A long, detailed FFQ was used, which demands remembering and recalling food intake during the third trimester, potentially leading to recall bias. Additionally, pre-pregnancy BMI and gestational weight gain (GWG) were calculated using recalled weight and height. Lastly, the study primarily examined food consumption frequency, and the approach may not accurately reflect variations in diet quality and total calorie intake, as individuals with similar consumption frequencies may have different genuine consumptions due to changes in portion sizes (De Keyzer et al., 2013). This aspect might have impacted the precision of measuring diet quality and overall calorie intake.

Conclusions

In conclusion, four DPs were identified and labeled as follows: fruit and vegetables, healthy, traditional, and fat and sugar. These DPs demonstrated no significant protective impact on the occurrence of CS across all tertiles. Nevertheless, further prospective cohort research is warranted to either validate or refute our findings.

Footnotes

Acknowledgements

The authors would like to express their thanks to the Deanship of Scientific Research at The University of Jordan for funding the research projects.

Authors’ contribution

RT were responsible for the study conception and design and responsible for the development of the methodology. AY and QA was responsible for the acquisition of data. RT and AY were responsible for the analysis and interpretation of data. RT, AY, QA and SA were responsible for drafting the manuscript, critically revising the manuscript, and reading and approving the final manuscript.

Availability of data and materials

Competing interests

The authors declare that they have no competing or conflict of interest.

Consent for publication

The authors permit the publisher to publish the findings of this review.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

The study protocol was approved by The University of Jordan Institutional Review Board (IRB) committee and the study was conducted according to the guidelines of the Declaration of Helsinki. The IRB number of the study was 2019/235 and it was obtained in September 2019. A consent form was obtained from the participants after explaining the purpose of the study and before starting the data collection.

Funding

The Deanship of Scientific Research at The University of Jordan funded this work.

ORCID iDs

Reema F. Tayyem

Sabika Allehdan

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