Intention to use maternal health services and associated factors among women who gave birth at home in rural Sehala Seyemit district: a community-based cross-sectional study

Background: Low maternal healthcare service utilization contributes to poor maternal and newborn health outcomes in rural Ethiopia. ‘Motivational factors influence women’s intention to perform a specific health behavior, and the intention of subsequent home delivery and related risks that may contribute to women’s death is less known. Therefore, this study aimed to assess the intention of maternal health service utilization among women who gave birth at home in the rural Sehala Seyemit district. Methods: A community-based cross-sectional study was conducted from September 1st to October 15th, 2020, among 653 women. A two-stage sampling technique was used to select the study participants. First, a semi-structured, pretested, and interviewer-administered questionnaire were used. The mean of the sum score was also used to categorize the intention as intended and not intended. Second, multivariable logistic regression analysis was computed to identify factors associated with women’s intention to use maternal health services. Adjusted odds ratio (AOR) with a 95% confidence interval at a p-value of ≤ 0.05 were used to declare statistical association. Results: Of the women who gave birth at home the intention to use maternal health service was 62.3% (95% CI; 59, 66). Women’s age of > 30 years (AOR = 6.04; 95%CI: 2.34, 15.60), short time to reach health facility (AOR = 2.52; 95% CI: 1.57, 4.10), media exposure (AOR = 2.10; 95% CI: 1.16, 3.65), history of obstetric danger signs (AOR = 4.60; 95% CI: 2.33, 9.10), positive subjective norms (AOR = 11.20; 95% CI; 6.77, 18.50) and last delivery assisted by traditional birth attendants (AOR = 0.15; 95% CI: 0.06, 0.33) were factors associated with women’s intention to use maternal health services. Conclusion: In this study, maternal health service utilization intention is still unsatisfactory compared to the national target plan. Maternal age, media exposure, obstetric danger signs, distance to a health facility, positive subjective norms, and delivery assistant at delivery were predictors of women’s intention to use maternal healthcare services. Improving women’s awareness of maternal healthcare services and developing strategies to increase women’s access to mass media, skilled birth attendants, and transportation for rural women may enhance their intention to use maternal healthcare services. A Community-based cross-sectional study was conducted from September 1st to October 15th, 2020. This study was conducted in rural Sehala Seyemit district, Waghimra zone, Amhara regional state, northern Ethiopia. Sehala Seyemit district is located 285 km northeast of Bahir Dar (the capital city of Amhara regional state) and about 799 km north of Addis Ababa (the capital city of Ethiopia). Accessing health services in the district is difficult because of the lack of transportation to each “kebeles” (which is the smallest administrative unit in Ethiopia). The district has 13 “kebeles”; 12 rural and one urban “kebeles”. Currently, the district has a population of about 39,435. Almost 90% of the population are farmers. There are three health centers and 13 health posts serving the community. During the data collection period, the study population was all women who gave birth at home in the last two years in the selected “kebeles”. Critically ill women throughout the data collection period were excluded. The sample size for this study was determined by using a single population proportion formula by considering the following assumptions: women’s intention to deliver in a health facility 30.3% [17], 95% level of confidence, and 5% margin of error. By considering a design effect of 2 and a 5% non-response rate; (i.e., adding 5% of 325 = 325 + 16.25 and multiplying by two), the minimum adequate sample size was 683. Stud participants were selected using a multi-stage sampling technique. Eight kebeles were selected randomly in the first stage among the 12 “kebeles”. The list of the study participants was gained from health extension workers (HEWs) and local administrators. Next, we designed a sampling frame by numbering the list of women. Then the total sample size was distributed in proportion to the size of each selected “kebeles”. Lastly, the study participants were selected by a simple random sampling technique using a random generation table. Intention to use maternal health services (Intended/ not intended). Age of the women, marital status, women’s educational status, women’s occupation, husband educational status, husband occupation, family size, exposure to mass media, time to reach the nearby health facility, parity, history of ANC, number of ANC, birth assistant, history of PNC, husband involvement in maternal and children’s health, household decision-making power, history of abortion, history of neonatal death, history of obstetric danger signs during the recent pregnancy, status of the pregnancy, knowledge of MHS, subjective norms, perceived behavioral control, and attitude towards MHS utilization. Is when women deliver at home or birth in a residence rather than a birthing center without a skilled birth attendant [18]. Women’s intention to use MHS was measured using five questions: 1) Intention to use ANC; 2) Intention to use MWHs; 3) Intention to pay for ANC/ delivery if it is with a cost; 4) Intention to deliver in a health facility 5) Intention to use postnatal care (PNC). Each question has five-point Likert scales (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The total score was ranged from 5–25 and women who scored approaching the maximum score of the total item were considered to have good intentions to use maternal health services. The mean of the sum score was also used to categorize the intention as intended and not intended if women were scored above mean and below mean respectively [19]. This refers to the extent to which an individual has a positive or negative estimation of the behavior of interest. Women’s attitude towards MHS utilization was measured using 13 questions: 1) All pregnant women should have ANC and PNC follow up; 2) Pregnant and lactating women should use a variety of foods rich in protein and vitamins; 3) The healthcare provided by health providers is important; 4) Timely ANC follow-up will be safer for both mother and baby during labor and delivery; 5) Taking medication during pregnancy without a doctor’s prescription can cause problems for the fetus; 6) Husbands should be present during ANC, delivery and PNC; 7) It is important to be prepared during pregnancy; 8) Maternity waiting homes are very important for women far from health facilities; 9) Heavy weight lifting and strenuous exercise during pregnancy is dangerous and may be unsafe for the fetus; 10) Advice regarding proper health during pregnancy and childbirth can be found outside the hospital; 11) Follow up during pregnancy may decrease intrapartum and postpartum complications; 12) Health facility delivery is safer and better than home delivery; 13) Women may have problems without ANC, health facility delivery and PNC. Each question has five points Likert scale (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The total score was 13–65, and women who scored above the mean were considered to have a favorable attitude [20, 21]. This refers to whether the majority of people support or reject the behavior. It was measured using five questions: 1) People who are important to me think that I should use antenatal care during pregnancy; 2) Important people to me think that I should use maternal waiting homes in the last 2–4 weeks of my pregnancy; 3) People who are important to me think that I have to deliver in a health facility; 4) Important people to me think that I have to get a skilled birth attendant during delivery; 5) Important people to me think that I should follow postnatal care and immunization services. Each question has five-point Likert scales (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). The minimum and maximum scores were 5 and 25, respectively. Women who scored above the mean value were considered positive subjective norms. This refers to an individual’s perception of the simplicity or complexity of performing the behavior of interest. It was measured using five questions: 1) For me attending antenatal care is simple, and I can do it; 2) For me using maternity waiting homes in the last 2–4 weeks of my pregnancy is simple, and I can do it; 3) For me health facility delivery is very simple, and I can do it; 4) Getting a skilled birth attendant is easy for me and I can do it; 5) Using postnatal and immunization services are easy to me, and I can do it. The cumulative score ranged from 5 to 25 and women who scored above the mean value were considered to have positive subjective norms. Includes knowledge of ANC, PNC, and pregnancy, knowledge of obstetric danger signs, knowledge of birth preparedness and complication readiness, knowledge of malaria prevention, knowledge of anemia prevention, knowledge of helminthic infection prevention, knowledge of tetanus prevention during pregnancy and knowledge of complications of home delivery. The study participants were asked 16 questions (See Additional file 1). These items comprise “Yes” or “No” and multiple response options. One point was given for all the correct answers, while zero point for incorrect answers. Then, women’s knowledge was composed (knowledgeable which was coded as “1” and not knowing which was coded as “0”). Thus, based on the summative score of variables designed to assess knowledge with a score above the mean was considered as knowledgeable and vice versa [20–22]. Husband involvement in maternal and child health-related activities was measured using nine questions: 1) Did your husband go with you for ANC follow-up at least once in your most recent pregnancy? 2) Did your husband provide transport/give money for transport during your recent pregnancy or delivery? 3) Did your husband accompany you to the hospital during labor for your recent delivery? 4) Did your husband discuss with health care providers during your recent pregnancy or delivery? 5) Did your husband look after the child at home/stay with the babies while you are outside the home? 6) Did your husband bathe a newborn/infant while you were busy? 7) Did your husband buy clothes/other things for infants/neonates? 8) Did your husband go with you for immunization services? 9) Did your husband assist you while you breastfed the newborn/infant? Each question was coded as 0 for “no” and 1 for “yes”. The total score ranged from 0–9, and a score above the mean was considered as husband involved [23, 24]. Household decision-making power was assessed using nine questions: 1) who decides about health care for you? 2) Who decides on the large household purchase or sell? 3) Who decides on intra-household resource allocation/ daily household purchases? 4) Who decides where and when to seek medical care for sick newborns/children? 5) Who decides on visits of family, friends, or relatives? 6) Who decides when to have an additional child? 7) Who usually decides how your partner’s/husband earnings will be used? 8) Who decides to go for ANC, PNC, where to deliver, and infant immunization? 9) Who usually decides what foods to be cooked each day? The possible answers were me alone, which was coded as 2, both of us which was coded as 1, the husband alone, which was coded as 0. The score ranged from 0 to 18 and a woman who scored above the mean was considered to have higher household decision-making power [25]. The data collection tool was developed by reviewing the literature [17, 26, 27] and collected using a semi-structured, interviewer-administered questionnaire through face-to-face interviews ( See Additional file 2). First, the questionnaire was prepared in English, translated into Amharic, and returned to English to confirm consistency. The questionnaire contains questions about socio-demographic characteristics, reproductive and childbirth-related health care characteristics, women’s knowledge of MHS, attitudes towards maternal health services, and their intention to use MHS. Before the actual data collection, we did a pretest on 5% of the calculated sample size (34 women) at Ziquala Woreda, which has similar socio-cultural and living standards as the study area. The necessary amendments were done accordingly. Eight female HEWs and four male midwifery diploma holders were recruited for data collection and supervision. Two-day training was given regarding the overall data collection process. At the time of data collection, the questionnaire was checked for completeness daily by the supervisors. Then, feedback was given to data collectors. The data collected from the field were checked for completeness and consistency, coded and entered into Epi-info version 7.1.2, and exported to SPSS version 25 computer software package for analysis. Frequencies and cross-tabulations were used to summarize descriptive statistics. Texts, tables, and graphs presented the data. Moreover, binary logistic regression was used to identify factors associated with the future intention of home-delivered women on MHS utilization. Then variables were fitted to multivariable logistic regression using the backward likelihood ratio method. Both COR and AOR with 95% CI were computed to show the strength of the association. Finally, a statistically significant association of variables was declared based on AOR with 95% CI and p-value < 0.05.