A New Model for Improving Quality of Hypertension’s Determinant Factors in Pregnancy

1. INTRODUCTION

In 2020, about 800 women per day passed away from pregnancy- and childbirth-related avoidable causes. In low- and lower-middle-income countries, maternal fatalities accounted for about 95% of all deaths in 2020 [1]. In 2021, the Ministry of Health reported the number of maternal deaths of 7,389 in Indonesia. Based on the causes, the majority of maternal deaths in 2021 were related to COVID-19 with 2,982 cases, 1,330 cases of bleeding, and 1,077 cases of hypertension in pregnancy. Cases of preeclampsia in North Sumatra Province contributed to 23.7% of maternal deaths, especially in Deli Serdang Regency of 21.1% [2]. Several efforts by the Indonesian Government to reduce Maternal Mortality Rate (MMR) include the “Safe Motherhood Initiative” which focuses on the concept of death prevention by providing antenatal care [3], deliveries performed by health personnel, family planning, and managing complications [2]. Currently in Indonesia, Mother & Child Health Book, and Health Score-card are used together to determine the risk level of pregnancy in mothers. Because it is only used by doctors and midwives during antenatal visits, so there is no involvement of pregnant women in knowing whether their pregnancy is classified as at risk and experiencing complications of hypertension in pregnancy. The participation of pregnant women, families, communities, and health workers is crucial to success as an effort to prevent delays in detection [4]. A recent study has developed a prediction model using a combination of biomarkers that had good discriminatory performance for hypertension in pregnancy [5]. A recent study discovered that the majority of high-risk pregnancies in rural areas—nearly one-fifth of all pregnancies—were caused by maternal age and pregnancy-induced hypertension. High-risk pregnancies were independently correlated with parity and socioeconomic level [6,7]. A limitation of the safe motherhood program is the challenge of accessing healthcare services in various regions of Indonesia, attributable to geographical constraints and the unequal distribution of healthcare personnel. Furthermore, comprehensive and consistent antenatal care fails to encompass all areas of Indonesia, resulting in unmet targets for antenatal visits. Consequently, prioritizing the implementation of early detection for pregnancy hypertension becomes imperative [8]. The proposed model can be applied in the public health service centers as primary care for the prevention of complications of pregnancy hypertension. Hence, this study focuses on the improvement of determinant factors that empower pregnant women to know the risk factors for the occurrence of hypertension in pregnancy, recognize the early signs of hypertension in pregnancy, and efforts to increase antenatal visits so that mothers' pregnancies are maintained with standard antenatal services [9,10].

2. METHODS

This research used a mixed method with an embedded design approach, which means that qualitative and quantitative data were collected simultaneously. A qualitative method was employed via in-depth interviews to identify existing problems and to assess the needs, thus determinant factors of delay in the detection of hypertension could be recognized. The quantitative method has been used to test the validity and reliability of data obtained by questionnaires. Simple random sampling was applied where the participants were midwives, midwives’ coordinators, and pregnant women. Inclusion criteria are pregnant women in trimesters I, II, and III and having spouses. The sample size was 164 people selected by considering the protocol of Lemeshow, 1997 [11]. All participants were then classified by sociodemographic background of age, education, occupation, parity, gestational age, economic level, history of hypertension, obesity, and exercise. This research was conducted in rural areas, so there is no classification between urban and rural. In-depth interviews were conducted at the community health center. This study chose married women because married women are the focus of antenatal care and these women want to have children and are obliged to maintain a healthy pregnancy without complications. Data from randomly selected respondents was obtained from the results of anamnesis that the respondent had a history of hypertension before pregnancy, there was no connection between hypertension in menopausal women and the research sample. Respondents were taken from 164 married women in the working areas of the Deli Tua, Talun Kenas, and Biru-biru health centers by randomly drawing numbers. This model was designed entirely by the author based on literature, hypothesis testing results and expert discussions. Training in this research was carried out four times for 1 month. The participants were interviewed to examine the determinant factors of hypertension risk such as their level of knowledge, self-efficacy, attitude, family support, midwife support, antenatal care, and healthcare family. The determinant factors were measured by ordinal scales. After checking the questionnaire's fulfillment, the data entry was done by using EpiData Entry 3.1. We also used SPSS ver.24 to analyze the statistical data. Data obtained were tested by univariate, bivariate, and multivariate analyses with confidence level 95% and alpha 5% on both sides. The establishment of a new model in this research has surpassed the five steps of the ADDIE method; analysis, design, development, implementation, and evaluation [12]. The feasibility study of the MEGA-model was based on assessment criteria on the quality of the developed module, including; Introduction, Presentation, Closing, Glossarium. The feasibility study of module construction has involved the module experts, midwife coordinators, and midwives. The effectiveness of MEGA-model was evaluated by the quality improvement of determinant factors before and after implementation (p < 0.05). This research was conducted from June to October 2022 in Deli Serdang Regency, Province of North Sumatra, Indonesia. The experimental method was approved by the Ethics Committee of the Faculty of Medicine, Andalas University, under approval number 817/UN.16.2/KEP-FK/2022.

3. RESULTS

3.1. Step 1. Analysis

The social background of hypertension in pregnancy can be seen in the sociodemographic data presented in Table 1. All risk factors showed a significant correlation with hypertension in pregnancy (sig. < 0.05).

Table 1.

No	Risk Factors	f	%	Sig.
1	Age	-	-	0.011
-	≥ 20 and ≤ 35	72	43.9	-
	<20 and >35	92	56.1	-
2	Education	-	-	0.002
-	High (College/Univ)	73	54.5	-
	Low (Elementary-Mid School)	91	55.5	-
3	Occupation	-	-	0.007
-	Working	76	46.3	-
	No Work	88	53.7	-
4	Parity	-	-	0.004
-	Primipara	53	32.3	-
	Multigravida	111	67.7	-
5	Gestational Age	-	-	0.013
-	Trimester I	75	45.7	-
	Trimesters II and III	89	54,3	-
6	Economic level	-	-	0.008
-	Low	75	48.2	-
	Adequate	89	54.3	-
7	History of Hypertension	-	-	0.007
-	Yes	79	48.2	-
	No	85	51.8	-
8	History of Hypertension in Family	-	-	0.002
-	Yes	67	40.9	-
	No	97	59.1	-
9	Obesity	-	-	0.004
-	Yes	30	18.3	-
	No	134	81.7	-
10	Sport/Exercise	-	-	0.007
-	Not Active	72	43.9	-
	Active	92	56.1	-

Table 2.

No.	Determinant Factors	f	%	Sig.
1	Knowledge	-	-	0.001
-	Good	63	38.4	-
	Not Good	101	61.6	-
2	Self-efficacy	-	-	0.002
-	Good	78	47.6	-
	Not Good	86	52.4	-
3	Attitude	-	-	0.001
-	Positive	74	45.1	-
	Negative	90	54.9	-
4	Family Supports	-	-	0.001
-	Good	79	48.2	-
	Not Good	85	51.8	-
5	Midwives Support	-	-	0.001
-	Good	90	54.9	-
	Not Good	74	45.1	-
6	ANC (Antenatal Care)	-	-	0.001
-	Good	92	56.0	-
	Not Good	72	44.0	-
7	Healthcare Facility	-	-	0.001
-	Good	81	49.4	-
	Not Good	83	50.6	-

Furthermore, the data showed several factors that influence the determinant factors of hypertension in pregnancy as presented in Table 2. All determinant factors showed a significant correlation with early detection of hypertension in pregnancy (sig. < 0.05).

4. DISCUSSION

Based on our data, the majority of respondents have low education (Table 1). Insufficient educational attainment implies that pregnant women may have limited awareness and knowledge regarding the criticality of self-detection in pregnancy hypertension. In line with previous studies reported, the majority of pregnant women in Ethiopia initiate their ANC late [14]. Most of the complications of gestational hypertension are related to the lack of knowledge of pregnant women and the negative attitude of pregnant women toward early detection and lack of prevention practices [15,16]. Occupation exhibits a substantial correlation with early detection, wherein individuals in lower occupational strata are more prone to delayed initiation of gestational hypertension early detection. Empirical data on the association between employment and the risk of experiencing a high-risk pregnancy is scarce; however, existing evidence generally indicates that women are capable of handling work-related tasks effectively [17].

The significance of this study lies in its pioneering approach of empowering pregnant women as a moderating factor, influencing various social conditions, namely, the knowledge and understanding of pregnant women, self-efficacy, intentions and attitudes of pregnant women, husband/family psychosocial support, midwives' psychosocial support, access to and quality of antenatal care, as well as healthcare facilities [13].

Our research findings also demonstrate a notable correlation between parity and early detection, indicating that lower parity is associated with a higher likelihood of delayed initiation of gestational hypertension early detection. This finding was consistent with Behrens et al.'s (2017) claim that parity was a confounding factor in the connection between hypertensive diseases of pregnancy [18]. Moreover, gestational age exhibits a relationship with early detection, whereby lower gestational age is linked to a higher probability of delayed initiation of gestational hypertension early detection [19]. A previous study reported that older women (≥40 years old) had increased odds of mild preeclampsia, fetal distress, and poor fetal growth [20]. Strategic implementation related to the relationship between economic factors and early detection of pregnancy hypertension is important for pregnant women, realizing that economic factors greatly affect health conditions, especially during pregnancy [21]. Therefore, for pregnant women with unfavorable economic factors, it is advisable to limit their pregnancies [22].

Our study indicated that respondents who have a history of hypertension are more anticipative by emphasizing pregnancy checks so that they avoid the risk of severe preeclampsia [23]. The results of the data analysis showed that the majority of respondents who were late for early detection of pregnancy hypertension were respondents with a family history of family hypertension [24]. Pregnant women who are obese or who have the potential to get body fat should strategically apply strategies related to the association between obesity and early identification of prenatal hypertension to reduce the number of pregnancies and control their lifestyle, particularly concerning eating [25] and sports or exercise [26].

The MEGA model for early detection of gestational hypertension has a significant effect on preventing delays in the implementation of early detection of gestational hypertension. Before the development of the early detection model (pre), out of 164 research samples, there were 68 people (41.5%) who were late and 96 people (58.5%) did early detection of pregnancy hypertension. After developing the model by empowering pregnant women, out of 164 research samples, only 27 people (16.5%) were late and 137 people (83.5%) were not late for early detection of pregnancy hypertension. This means that there is an increase in the number of samples (pregnant women) who are not late for early detection of gestational hypertension. On the other hand, there was a decrease in the number of samples (pregnant women) who were late for early detection of gestational hypertension.

With the application of the MEGA model, pregnant women experience the benefits of empowering pregnant women such as education in increasing the understanding and knowledge of pregnant women about early detection of hypertension in pregnancy, lifestyle improvements, and antenatal services so that pregnant women recognize that empowering pregnant women has succeeded in increasing the delay of pregnant women early detection of gestational hypertension.

CONCLUSION

Based on the research results, we conclude that the design of the early detection model has a moderating factor in the form of empowering pregnant women, which includes education with counseling to increase knowledge and lifestyle improvement. The empowerment intervention in this study encompassed educational sessions highlighting the importance of early detection of pregnancy hypertension, lifestyle enhancement, and counseling regarding midwives' services.

REFERENCES