Personal and environmental factors associated with the utilisation of maternity waiting homes in rural Zambia

BMC Pregnancy and Childbirth, Volume 17, No. 1, Year 2017

Interpretation

Background: Although the association between the presence of maternity waiting homes (MWHs) and the personal and environmental factors that affect the use of MWHs has been explained in qualitative terms, it has never been tested in quantitative terms. The aim of this study was to test the association between the presence of MWHs and personal and environmental factors that affect the use of MWHs. Methods: A cross-sectional study was conducted using an interviewer-administered questionnaire from 1st July to 31st August, 2014 among 340 women of reproductive age in 15 rural health centres in Kalomo district, Zambia. Tests of association (chi square, logistic regression analysis, odds ratio) were conducted to determine the strength of the association between the presence of MWHs and personal and environmental factors. Differences between respondents who used MWHs and those who did not were also tested. Results: Compared to respondents from health centres without MWHs, those from centres with MWHs had higher odds of expressing willingness to use MWHs (adjusted odds ratio [aOR] = 4.58; 95% confidence interval [CI]:1.39-15.17), perceived more benefits from using a MWH (aOR = 8.63; 95% CI: 3.13-23.79), perceived more social pressure from important others to use MWH (aOR = 27.09; 95% CI: 12.23-60.03) and higher personal risk from pregnancy and childbirth related complications (aOR = 11.63; 95% CI: 2.52-53.62). Furthermore, these respondents had higher odds of staying at a health centre before delivery (aOR = 1.78; 95% CI: 1.05-3.02), giving birth at a health facility (aOR = 3.36; 95% CI: 1.85-6.12) and receiving care from a skilled birth attendant (aOR = 3.24; 95% CI: 1.80-5.84). In contrast, these respondents had lower odds of perceiving barriers regarding the use of MWHs (aOR = 0.27; 95% CI: 0.16-0.47). Factors positively associated with the use of MWHs included longer distances to the nearest health centre (p = 0.004), higher number of antenatal care (ANC) visits (p = 0.001), higher proportions of complications during ANC (p = 0.09) and women’s perception of benefits gained from staying in a MWH while waiting for delivery at the health centre (p = 0.001). Conclusion: These findings suggest a need for health interventions that focus on promoting ANC use, raising awareness about the risk and severity of pregnancy complications, promoting family and community support, and mitigating logistical barriers. The study used cross-sectional design, and data were collected from 15 health centre catchment areas of Kalomo district, Zambia [27–29]. For details on Kalomo district profile see Sialubanje et al., [4, 5, 8, 9]. The study participants were sampled from women of childbearing age (mean age 25.60 years, SD = 6.85). Of these, 203 women (mean age = 24.69 years, SD = 6.61) were recruited from health facilities with a MWH, and 137 women (mean age = 26.94, SD = 7.01) from health facilities without a MWH. To be eligible to participate in the interview, women must have delivered in the past 12 months prior to the survey and resided in the area for more than six months. The study utilised a multi-stage convenience sampling method. All ten health centres with a MWH in the district were identified and included in the study, after which, five out of a total 25 health centres without a MWH were purposefully selected and included in the study. Fourteen villages from the fourteen rural health centres and one compound from the semi-urban health centre were randomly sampled. Since there was more than one village in each health centre catchment area, one village was purposively selected based on accessibility and advice from community health workers and headmen. The number of respondents surveyed from each village was evenly distributed. However, due to a lack of information and the unstructured nature of housing units in the area, it was not possible to select respondents using systematic sampling methods. The Tropical Disease Research Centre Ethics Review Committee and the Ministry of Health Research and Ethics Committee in Zambia provided the ethical approval for the study (study number TDRC/ERC/2OO5/29/12). Before starting the survey, research assistants read out the aims of the study to the participants. They also explained that the respondents’ names would not be written on the questionnaire or on the informed consent form. Moreover, respondents were informed that survey participation was voluntary, that they would not receive any direct benefits from the study, and that they were free to discontinue the survey at any point if they felt uncomfortable. Participants were informed that the purpose of the survey was to collect information on what they thought affected their use of MWHs, and that the information would be used to inform and guide future government policies on MWHs. Written informed consent was obtained by having the participants either sign the consent form or mark with an ‘X’. Respondents who were able to write were made to sign on the consent form, whereas those who could not write were made to mark with an ‘X’. Two trained research assistants who were supervised by the principal investigator collected the data. The research assistants were recruited from within Kalomo district and were both female, aged 22 and 25 respectively, and had a full grade 12 certificate. The research assistants received a one day face-to-face training on the study and the questionnaire. Female research assistants were preferred to male for cultural reasons and in order to ensure optimal interaction with the mothers. Moreover, to minimise information concealment from the respondents during the survey, research assistants spoke both English (the official language) and Tonga, the local language. A week before the survey, women were informed about the survey date by the village headmen and neighbourhood health committee (NHC) members. On the agreed day, the principal investigator and the research assistants travelled to the respective health centres from which the research assistants were directed into the households by the NHC members and community volunteers. Because of high illiteracy levels in the area, the questionnaire was translated into Tonga. Women who were able to read were allowed to go through the questionnaire by themselves; the interviewer merely confirmed whether the questionnaire was correctly and completely answered. All the interviews took place in the participant’s home or at a nearby convenient place-normally a quiet place under a tree, a few meters from the participant’s house. Each survey lasted between thirty to forty minutes. The questionnaire was developed by the research team based on variables described by social cognitive theories of human behaviour, including the theory of Reasoned Action Approach [24] and the Health Belief Model [25] as well as findings from our previous studies in the area [4, 8, 9]. The research instrument was first developed in English, translated to Tonga by an independent bi-lingual expert, and then back-translated to English. The final version of the questionnaire was both in Tonga and English (see supplementary file for the English version of the questionnaire). All items were answered on a 5-point Likert scale ranging from 1 = fully disagree to 5 = fully agree, or similar labels. We used factor analysis to check which items, based on theory, should measure a particular psychosocial construct combined into one factor or not. Items that showed strong internal consistency (Cronbach’s alpha > 0.6 or r > 0.40) were combined and averaged into one index. If items did not combine into one index, factor analyses were conducted using principal axis factoring as an extraction method, and an oblimin rotation. After inspection of the scree plot (that is, a plot which displays the eigenvalues associated with a component or factor in descending order versus the number of the component or factor), sum measures were created with Eigenvalue score of 1.0 or higher and included those items that had factor loadings of 0.4 or higher. See Table 1 for the different items used in the present study and how they were clustered to measure underlying psychosocial constructs. Factor analysis Intention was measured using one item: “If I am pregnant again and due for labour, I will make efforts to go and stay at the maternity waiting home as I wait for labour at the clinic”. In total, 25 items were constructed to measure attitude (table 1). Factor and reliability analyses revealed two underlying variables: cognitive attitude towards MWHs (17 items, α = 0.75). The other attitude variable was affective attitude toward staying in a MWH (7 items, α = 0.72). Similarly, factor and reliability analyses were performed on the 22 items measuring perceived social norms, which resulted in two variables: one of these was descriptive social norms towards MWH use (13 items, α = 0.60), and injunctive social norms towards MWHs (9 items, α = 0.82). Seventeen items were constructed to measure perceived behavioural control (PBC), and factor and reliability analyses resulted in one variable (15 items, α = 0.60). The five items measuring risk perception were also averaged into one variable (with five items, α = 0.83). Finally, perceived barriers towards using MWHs were measured using seventeen items. Factor analysis revealed one variable (14 items, α = 0.70). Descriptive statistics were used to compute percentages of respondents’ demographic and past maternal health seeking behaviour. After inspection of the data and descriptive analysis, we noticed that the data were severely negatively skewed and the assumption of normality was violated. We performed a median split procedure on the psychosocial measures-such that scores including the median and below were dummy-coded as 0 (representing low to moderate scores); and scores above the median were dummy-coded as 1 (representing high scores). To investigate the univariate association between psychosocial measures and intention to use a MWH, and to compare scores on psychosocial measures, sociodemographic variables and past behaviour between those with and those without access to MWHs, Chi-square tests and logistic regression analyses were used. Crude odds ratios (ORs) with 95% confidence intervals (CI) were computed to estimate the effect size. Furthermore, independent t-tests and Cohen’s d [30] were used to investigate whether the respondents from the two groups differed with regard to sociodemographic and economic factors (age, number of children, and distance to the nearest health centre). Finally, adjusted odds ratios (aOR) were calculated to control for confounding due to age, parity, and distance to the nearest health centre (p < 0.05).

AI Digest

Study Justification:

This study aimed to test the association between the presence of maternity waiting homes (MWHs) and personal and environmental factors that affect their use in rural Zambia. The study fills a gap in the existing literature by providing quantitative evidence on the factors associated with MWH utilization, which had previously only been explained qualitatively. The findings of this study can inform health interventions and guide future government policies on MWHs.

Highlights:

– The study found that women from health centers with MWHs had higher odds of expressing willingness to use MWHs, perceiving more benefits from using them, and perceiving more social pressure to use them.
– These women also had higher odds of staying at a health center before delivery, giving birth at a health facility, and receiving care from a skilled birth attendant.
– Factors positively associated with MWH use included longer distances to the nearest health center, higher number of antenatal care visits, higher proportions of complications during antenatal care, and women’s perception of benefits gained from staying in a MWH.

Recommendations:

Based on the study findings, the following recommendations can be made:

1. Promote antenatal care use to increase the likelihood of MWH utilization.
2. Raise awareness about the risk and severity of pregnancy complications to encourage women to stay in MWHs.
3. Promote family and community support for MWH utilization.
4. Mitigate logistical barriers that may hinder women from using MWHs.

Key Role Players:

1. Ministry of Health: Responsible for implementing health interventions and policies related to MWHs.
2. Health Center Staff: Involved in providing care and support to women using MWHs.
3. Community Health Workers: Play a crucial role in raising awareness and promoting MWH utilization at the community level.
4. Non-Governmental Organizations: Can provide support and resources for implementing interventions related to MWHs.

Cost Items for Planning Recommendations:

1. Training and Capacity Building: Budget for training health center staff and community health workers on MWH utilization and related interventions.
2. Awareness Campaigns: Allocate funds for conducting awareness campaigns to raise awareness about MWHs and their benefits.
3. Infrastructure Development: Consider the cost of constructing or improving MWH facilities to accommodate more women.
4. Transportation: Budget for transportation services to facilitate women’s access to MWHs, especially for those living in remote areas.
5. Monitoring and Evaluation: Allocate resources for monitoring and evaluating the effectiveness of interventions and policies related to MWHs.
Please note that the cost items provided are general categories and the actual cost will depend on the specific context and implementation plan.

Strength of Evidence

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it presents the results of a cross-sectional study conducted among 340 women in rural Zambia. The study used tests of association, such as chi-square and logistic regression analysis, to determine the strength of the association between the presence of maternity waiting homes (MWHs) and personal and environmental factors. The study found significant associations between the presence of MWHs and factors such as willingness to use MWHs, perceived benefits, social pressure, personal risk, staying at a health center before delivery, giving birth at a health facility, receiving care from a skilled birth attendant, and perceived barriers. The study also identified factors positively associated with the use of MWHs, including longer distances to the nearest health center, higher number of antenatal care visits, higher proportions of complications during antenatal care, and women’s perception of benefits gained from staying in a MWH. To improve the evidence, future studies could consider using a longitudinal design to establish causality and include a larger sample size to enhance generalizability.

Abstract

The study used cross-sectional design, and data were collected from 15 health centre catchment areas of Kalomo district, Zambia [27–29]. For details on Kalomo district profile see Sialubanje et al., [4, 5, 8, 9]. The study participants were sampled from women of childbearing age (mean age 25.60 years, SD = 6.85). Of these, 203 women (mean age = 24.69 years, SD = 6.61) were recruited from health facilities with a MWH, and 137 women (mean age = 26.94, SD = 7.01) from health facilities without a MWH. To be eligible to participate in the interview, women must have delivered in the past 12 months prior to the survey and resided in the area for more than six months. The study utilised a multi-stage convenience sampling method. All ten health centres with a MWH in the district were identified and included in the study, after which, five out of a total 25 health centres without a MWH were purposefully selected and included in the study. Fourteen villages from the fourteen rural health centres and one compound from the semi-urban health centre were randomly sampled. Since there was more than one village in each health centre catchment area, one village was purposively selected based on accessibility and advice from community health workers and headmen. The number of respondents surveyed from each village was evenly distributed. However, due to a lack of information and the unstructured nature of housing units in the area, it was not possible to select respondents using systematic sampling methods. The Tropical Disease Research Centre Ethics Review Committee and the Ministry of Health Research and Ethics Committee in Zambia provided the ethical approval for the study (study number TDRC/ERC/2OO5/29/12). Before starting the survey, research assistants read out the aims of the study to the participants. They also explained that the respondents’ names would not be written on the questionnaire or on the informed consent form. Moreover, respondents were informed that survey participation was voluntary, that they would not receive any direct benefits from the study, and that they were free to discontinue the survey at any point if they felt uncomfortable. Participants were informed that the purpose of the survey was to collect information on what they thought affected their use of MWHs, and that the information would be used to inform and guide future government policies on MWHs. Written informed consent was obtained by having the participants either sign the consent form or mark with an ‘X’. Respondents who were able to write were made to sign on the consent form, whereas those who could not write were made to mark with an ‘X’. Two trained research assistants who were supervised by the principal investigator collected the data. The research assistants were recruited from within Kalomo district and were both female, aged 22 and 25 respectively, and had a full grade 12 certificate. The research assistants received a one day face-to-face training on the study and the questionnaire. Female research assistants were preferred to male for cultural reasons and in order to ensure optimal interaction with the mothers. Moreover, to minimise information concealment from the respondents during the survey, research assistants spoke both English (the official language) and Tonga, the local language. A week before the survey, women were informed about the survey date by the village headmen and neighbourhood health committee (NHC) members. On the agreed day, the principal investigator and the research assistants travelled to the respective health centres from which the research assistants were directed into the households by the NHC members and community volunteers. Because of high illiteracy levels in the area, the questionnaire was translated into Tonga. Women who were able to read were allowed to go through the questionnaire by themselves; the interviewer merely confirmed whether the questionnaire was correctly and completely answered. All the interviews took place in the participant’s home or at a nearby convenient place-normally a quiet place under a tree, a few meters from the participant’s house. Each survey lasted between thirty to forty minutes. The questionnaire was developed by the research team based on variables described by social cognitive theories of human behaviour, including the theory of Reasoned Action Approach [24] and the Health Belief Model [25] as well as findings from our previous studies in the area [4, 8, 9]. The research instrument was first developed in English, translated to Tonga by an independent bi-lingual expert, and then back-translated to English. The final version of the questionnaire was both in Tonga and English (see supplementary file for the English version of the questionnaire). All items were answered on a 5-point Likert scale ranging from 1 = fully disagree to 5 = fully agree, or similar labels. We used factor analysis to check which items, based on theory, should measure a particular psychosocial construct combined into one factor or not. Items that showed strong internal consistency (Cronbach’s alpha > 0.6 or r > 0.40) were combined and averaged into one index. If items did not combine into one index, factor analyses were conducted using principal axis factoring as an extraction method, and an oblimin rotation. After inspection of the scree plot (that is, a plot which displays the eigenvalues associated with a component or factor in descending order versus the number of the component or factor), sum measures were created with Eigenvalue score of 1.0 or higher and included those items that had factor loadings of 0.4 or higher. See Table 1 for the different items used in the present study and how they were clustered to measure underlying psychosocial constructs. Factor analysis Intention was measured using one item: “If I am pregnant again and due for labour, I will make efforts to go and stay at the maternity waiting home as I wait for labour at the clinic”. In total, 25 items were constructed to measure attitude (table 1). Factor and reliability analyses revealed two underlying variables: cognitive attitude towards MWHs (17 items, α = 0.75). The other attitude variable was affective attitude toward staying in a MWH (7 items, α = 0.72). Similarly, factor and reliability analyses were performed on the 22 items measuring perceived social norms, which resulted in two variables: one of these was descriptive social norms towards MWH use (13 items, α = 0.60), and injunctive social norms towards MWHs (9 items, α = 0.82). Seventeen items were constructed to measure perceived behavioural control (PBC), and factor and reliability analyses resulted in one variable (15 items, α = 0.60). The five items measuring risk perception were also averaged into one variable (with five items, α = 0.83). Finally, perceived barriers towards using MWHs were measured using seventeen items. Factor analysis revealed one variable (14 items, α = 0.70). Descriptive statistics were used to compute percentages of respondents’ demographic and past maternal health seeking behaviour. After inspection of the data and descriptive analysis, we noticed that the data were severely negatively skewed and the assumption of normality was violated. We performed a median split procedure on the psychosocial measures-such that scores including the median and below were dummy-coded as 0 (representing low to moderate scores); and scores above the median were dummy-coded as 1 (representing high scores). To investigate the univariate association between psychosocial measures and intention to use a MWH, and to compare scores on psychosocial measures, sociodemographic variables and past behaviour between those with and those without access to MWHs, Chi-square tests and logistic regression analyses were used. Crude odds ratios (ORs) with 95% confidence intervals (CI) were computed to estimate the effect size. Furthermore, independent t-tests and Cohen’s d [30] were used to investigate whether the respondents from the two groups differed with regard to sociodemographic and economic factors (age, number of children, and distance to the nearest health centre). Finally, adjusted odds ratios (aOR) were calculated to control for confounding due to age, parity, and distance to the nearest health centre (p < 0.05).

Materials

N/A

Innovations

The study recommends implementing health interventions to improve access to maternal health. These interventions should focus on promoting antenatal care (ANC) use, raising awareness about the risk and severity of pregnancy complications, promoting family and community support, and mitigating logistical barriers. By implementing these interventions, it is expected that the utilization of maternity waiting homes (MWHs) will increase, leading to improved access to maternal health services.

The study found that women from health centers with MWHs had higher odds of expressing willingness to use MWHs, perceived more benefits from using a MWH, perceived more social pressure from important others to use MWH, and had higher personal risk from pregnancy and childbirth-related complications. These women also had higher odds of staying at a health center before delivery, giving birth at a health facility, and receiving care from a skilled birth attendant. On the other hand, they had lower odds of perceiving barriers regarding the use of MWHs.

Factors positively associated with the use of MWHs included longer distances to the nearest health center, higher number of ANC visits, higher proportions of complications during ANC, and women’s perception of benefits gained from staying in a MWH while waiting for delivery at the health center.

Based on these findings, innovations to improve access to maternal health could include strategies such as:

1. Promoting ANC use: Implementing programs to increase the number of ANC visits and raise awareness about the importance of ANC in preventing pregnancy complications.

2. Raising awareness about pregnancy complications: Conducting community education campaigns to inform women about the risks and severity of pregnancy complications, and the benefits of using MWHs for safe delivery.

3. Promoting family and community support: Engaging families and communities in supporting pregnant women to use MWHs, through community mobilization activities and involvement of community leaders.

4. Mitigating logistical barriers: Addressing challenges such as transportation, distance to health centers, and availability of MWHs by improving infrastructure, providing transportation support, and expanding the number of MWHs in areas with high demand.

These innovations can help improve access to maternal health services and increase the utilization of MWHs, ultimately leading to better maternal and child health outcomes. The study was published in BMC Pregnancy and Childbirth in 2017.

AI Innovations Description

The recommendation from the study to improve access to maternal health is to implement health interventions that focus on promoting antenatal care (ANC) use, raising awareness about the risk and severity of pregnancy complications, promoting family and community support, and mitigating logistical barriers. These interventions can help increase the utilization of maternity waiting homes (MWHs) and improve access to maternal health services. The study found that women from health centers with MWHs had higher odds of expressing willingness to use MWHs, perceived more benefits from using a MWH, perceived more social pressure from important others to use MWH, and had higher personal risk from pregnancy and childbirth-related complications. These women also had higher odds of staying at a health center before delivery, giving birth at a health facility, and receiving care from a skilled birth attendant. On the other hand, they had lower odds of perceiving barriers regarding the use of MWHs. Factors positively associated with the use of MWHs included longer distances to the nearest health center, higher number of ANC visits, higher proportions of complications during ANC, and women’s perception of benefits gained from staying in a MWH while waiting for delivery at the health center. These findings suggest that interventions should focus on promoting ANC use, raising awareness about pregnancy complications, and addressing logistical barriers to improve access to maternal health. The study was published in BMC Pregnancy and Childbirth in 2017.

AI Innovations Methodology

The methodology used in the study to simulate the impact of the main recommendations on improving access to maternal health involved a cross-sectional design and data collection through an interviewer-administered questionnaire. The study was conducted in 15 rural health centers in Kalomo district, Zambia, and included 340 women of reproductive age.

The study utilized a multi-stage convenience sampling method, where all ten health centers with a maternity waiting home (MWH) in the district were included, and five out of 25 health centers without a MWH were purposefully selected. Fourteen villages from the rural health centers and one compound from the semi-urban health center were randomly sampled. The number of respondents surveyed from each village was evenly distributed.

Before starting the survey, the aims of the study were explained to the participants, and written informed consent was obtained. The questionnaire, developed by the research team, was administered by trained research assistants who spoke both English and the local language. The survey took place in the participant’s home or a nearby convenient place.

The questionnaire included items that measured various psychosocial constructs, such as attitude, perceived social norms, perceived behavioral control, risk perception, and perceived barriers towards using MWHs. Factor analysis was used to determine which items should be combined into one index to measure each construct.

Descriptive statistics were used to analyze the demographic and past maternal health-seeking behavior of the respondents. Chi-square tests, logistic regression analyses, and independent t-tests were conducted to examine the association between psychosocial measures, intention to use a MWH, and access to MWHs. Crude odds ratios (ORs) and adjusted odds ratios (aOR) were calculated to estimate the effect size.

The findings of the study suggested a need for health interventions that focus on promoting antenatal care (ANC) use, raising awareness about pregnancy complications, promoting family and community support, and mitigating logistical barriers to improve access to maternal health.

The study was published in BMC Pregnancy and Childbirth in 2017.

Author

Dima Health

Statistics:

Citations: 21

Identifiers:

DOI: 10.1186/s12884-017-1317-5

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Sexual and Reproductive Health, Social Determinants, Workforce

Study Countries:

Zambia

Study Design:

Case-Control Study, Cross Sectional Study

Study Approach:

Mixed-methods, Qualitative, Quantitative

Participants Gender:

Male & Female