Keywords
postnatal care, regional disparities, reduced inequalities
postnatal care, regional disparities, reduced inequalities
1. As suggested by the reviewer, we have changed the title into "Regional disparities in postnatal care among mothers aged 15-49 years old: An analysis of the Indonesian Demographic and Health Survey 2017"
2. On the abstract part, result section, we have changed the term middle to central and the term East of Indonesia into Eastern, the term husband to spouse.
3. On the abstract part, conclusion section, we have revised the conclusion as suggested by reviewer.
4. The term of "Jawa" mentioned in the article, has been changed into Java.
5. The references in the article must be written in chronologically way in the same pattern for all.
The reference list has been completed and corrected.
6. Table 3: Socio-demographic characteristic of participants PNC in Indonesia based on region (n=13,901). The total sum of (No) use of PNC is not right (4039) it is 4040
7. The discussion has been revised according to the reviewer suggested. The sentence has been revised accordingly.
8. The conclusion part has been revised accordingly as well as with data availability statement.
See the authors' detailed response to the review by Kusrini S. Kadar
See the authors' detailed response to the review by Asmaa Salah Eldin Mohamed Saleh
Maternal morbidity and mortality are serious global health challenges. In 2019, the World Health Organization (WHO) revealed that 94% of maternal mortality occurred in low and middle-income countries, of which Indonesia is one (World Health Organization, 2019; World Health Organization et al., 2015). During 2000 and 2017, the maternal mortality ratio plunged by about 38% worldwide. Even with this decline, Sub-Saharan Africa and Southern Asia accounted for approximately 86% of maternal deaths worldwide. Southern Asia alone accounted for nearly one-fifth (58,000), which demonstrated the struggle to improve maternal health (World Health Organization, 2019; World Health Organization et al., 2015). In the Indonesia context, the government determined a target to reach an important goal of reducing maternal mortality rate to 102 per 100,000 live births in 2015 (Bappenas, 2015; Ministry of Health Republic of Indonesia, 2018). Despite the significant efforts to expand maternal health programmes, recent evidence showed that Indonesia was off-track to reach the Millenium Development Goals (MDGs) target by 2015. In 2015, maternal mortality deaths in Indonesia were three times higher than the MDGs target (Ministry of Health Republic of Indonesia, 2018; UNICEF & World Health Organization, 2015; World Health Organization et al., 2015). Hence, reducing maternal mortality ratio to less than 70 per 100,000 by 2030 as one of the Sustainable Development Goals (SDGs) targets could be a critical challenge for Indonesia (UNICEF & World Health Organization, 2015; United Nations, 2017; World Health Organization, 2012).
Most maternal mortality deaths are preventable or treatable if skilled healthcare, such as midwives, is provided during the postnatal period. Critical interventions during the postnatal period must be delivered to prevent maternal mortality deaths (Lawn et al., 2016; World Health Organization et al., 2015). In the Indonesian setting, the cause of maternal mortality is predominantly due to postpartum haemorrhage, followed by indirect causes, such as heart disease, severe anaemia, malaria, HIV/ AIDS and hepatitis. Many factors have been linked to interventions of postpartum haemorrhage which cause emergency cases, and skilled health care required to respond effectively to emergencies (Adisasmita et al., 2015; Mahmood et al., 2018). However, PNC remains a critical intervention to reduce maternal deaths in Indonesia. A new health programme called EMAS or Expanding Maternal and Neonatal Survival) was implemented by the Indonesian government in 2012, focused on improving maternal health care. The programme aimed at ensuring that every woman has access to quality maternal healthcare, including childbirth assistance by skilled health personnel in healthcare facilities (a target of 2018 strategic plan: 82%), four visits of Antenatal care (ANC) (78% ), PNC, and providing ANC (87%). However, the national data revealed that utilisation of PNC among 34 provinces in Indonesia remain varied and was considered lower compared to the childbirth assistance by skilled health personnel coverage. Socioeconomic, geographical, and demographic factors influence the underutilisation of PNC. Current systematic reviews show that levels of education, poverty, and limitations of access to PNC services are common issues in low-and middle-income countries linked to inequities in the use of PNC services (Langlois et al., 2015).
The national data of Indonesia in 2018 revealed that the average percentage of PNC visits for the first time in Indonesia was 93.3%. The highest percentage of visits occurred in Yogyakarta (99.6%), and the lowest percentage of visits was in Papua (56.3%). However, there were regional gaps in PNC visits across the provinces in Indonesia. Also, PNC utilisation in rural areas was lower than in urban areas of Indonesia (Kementerian Kesehatan Republik Indonesia, 2018; Ministry of Health Republic of Indonesia, 2018; Probandari et al., 2017). It is worth noting that 61.59 % of maternal mortality rates occurred during the postnatal period in Indonesia. Additionally, evidence shows that the quality of PNC is lower in most districts and cities among the Eastern Region in Indonesia. PNC must be performed a minimum of three times: within the first six hours to the third day after the delivery, from the fourth day to the 28th after the delivery and the 29th day to the 42nd day after childbirth. The standards of PNC including examination for vital signs; the apex of the uterus; lochia and other per vagina fluids; breasts and counselling for exclusive breastfeeding; provision of communication, information about and education of PNC, and family planning (Ministry of Health Republic of Indonesia, 2018; Probandari et al., 2017).
Several studies show that regional disparities in PNC occur in several countries. In Ethiopia, there were differences in each region and variations at regional levels at the utilisation of PNC among women (Sisay et al., 2019). PNC service in Zambia was also reported to experience regional disparities (Jacobs et al., 2017). In the same vein, in Bangladesh, disparities in the utilisation of maternal health services were also reported (Raheem et al., 2019). However, research focused on regional disparities on PNC among mothers aged 15–49 years old in Indonesia are not well investigated. This study was conducted to analyse the gap between regions in PNC service utilisation among mothers aged 15 – 49 years old who have had live births during the last five years in Indonesia. This study is significant because it can be a source of information and a reference regarding regional disparities in the utilisation of PNC services in Indonesia. This research could complete a bigger picture for consideration in resolving discrepancies in maternal services in Indonesia.
This study was a secondary data analysis using the most recent data from the 2017 Indonesian Demographic Data Survey (IDHS). In this study, unit analysis data consist of women aged 15–49 years old having had live births in the last five years preceding the survey.
The purpose of the cross-sectional study of the IDHS conducted by the Inner City Fund (ICF) international together with the national implementer in Indonesia was to offer up-to-date projections of fundamental demographic and health indicators. The IDHS study demonstrates a broad overview of population problems in Indonesia.
We utilised the data conducted by the national and provincial representatives. This cross-sectional study represents 1,970 census blocks in urban and rural areas of Indonesia. The census block obtained 59,100 female respondents aged 15–49 years old. The survey employed a two-stage stratified cluster sampling method. The first stage was the selection of several census blocks by systematic sampling proportional size. In the second stage, 25 ordinary households were selected with systematic sampling from the listing. In this study, a sample of 13,901 women aged 15–49 years from 34 provinces in Indonesia was analysed. The inclusion criteria were taken from IDHS that included all women aged 15–49 years who had given birth in the last five years. The exclusion criteria were whether the variables incomplete or missing. In order to allow replicate the DHS data, the guide for using datasets for DHS analysis is available at https://dhsprogram.com/data/Using-DataSets-for-Analysis.cfm.
Ethical review boards approved ethical clearance for the Inner City Fund OCR Macro (number 45 CFR 46) and the national board review from the Ministry of Health of Republic Indonesia. Before the survey, an informed consent was obtained from the respondents based on voluntary participation.
The dependent variable of this study was PNC visits. According to the recommendation of the Ministry of Health Republic of Indonesia, PNC must be performed at minimum three times: at the first six hours to the third day after the delivery, on the fourth day to the 28th after the delivery and the 29th day to the 42nd day after childbirth (Ministry of Health Republic of Indonesia, 2018). This data was based on the mother’s perception of PNC utilisation during the postnatal period. Independent variables analysed in this study were the related geographic and socioeconomic factors, including a region of residence, the place of residence, wealth quintile, health insurance, access to a health facility, age, gender, birth rank, education, and occupation.
The residence region was grouped as six regions, namely Sumatera, Java, Bali & Nusa Tenggara, Kalimantan, Sulawesi, Maluku & Papua, and of which were also categorised as Western Indonesia, Central Indonesia and Eastern Indonesia. The place of residence was determined as rural and urban areas. The wealth quintile of households was set into five categories: poorest, poorer, middle, richer, and richest. The wealth quintile of households was scored based on wealth criteria (DHSProgram, 2016). Health insurance was divided into two categories, namely yes and no. Access to the health facility was categorised into two, namely difficult and not. Children’s age was divided into five categories: less than one month, one month, two months, three months, four months. The gender of the child, namely female and male. Birth rank was categorised as a first child, second, third, fourth and so on. Mother’s age was divided into six categories: 15–24, 25–29, 30–34, 35–39, 40–49, and 45–49, while spouse’s age was divided into seven categories: 11–20, 21–30, 31–40, 41–50, 51–60, 61–70, 71–80. Mother’s and spouses' education levels were grouped into no education, primary, secondary, and higher education. Mother’s and spouse’s occupation was divided into two categories: not working and working. Determination of each category on the variables based on DHS report (BKKBN-BPS-Kemenkes-ICF, 2018) which was adjusted to the minimum number of sample on each category to meet the statistical assumption.
Data were analysed using STATA version 16.0 by conducting descriptive analysis. The chi-square test was performed to determine variables correlated to the PNC utilisation. Binary logistic regression was utilised to determine disparity in this study. Measurement of associations among variables was expressed as Odds Ratio (OR) and 95% Confidence Interval (CI). Significant variables were tested with a p-value of 0.05 and 95% CI, which are considered the disparity in PNC among mothers aged 15–49 years in Indonesia.
A total of 13,901 women aged 15–49 years old with live births in the last five years preceding the survey were interviewed. Table 1 shows the bivariate analysis that there were ten categories among some variables associated with the utilisation of PNC visits (p-value < 0.05). These variables include geographic factors, region, socio-economy (wealth quintile and access to the health facility), children (age of child and birth rank), mother factors (age, education and occupation), spouse factors (age, education, and occupation). Residence, socioeconomic (health insurance ownership), child gender, mother’s age and spouse’s occupation did not show associations with the utilisation of PNC visits among mothers aged 15–49 years old in Indonesia (Table 1). More detail results can be found in Table 1.
Characteristic | Utilization of PNC | X2 | p-value | |||
---|---|---|---|---|---|---|
No | Yes | |||||
n | % | n | % | |||
The geographic factors | ||||||
Indonesia | ||||||
Western Indonesia | 3265 | 29.1 | 7946 | 70.9 | 41.45*** | 0.00 |
Central Indonesia | 611 | 26.5 | 1693 | 73.5 | ||
Eastern Indonesia | 164 | 42.4 | 222 | 57.6 | ||
Region | ||||||
Sumatera | 1056 | 34.3 | 2027 | 65.7 | 116.36*** | 0.00 |
Java | 2028 | 26.3 | 5691 | 73.7 | ||
Bali & Nusa Tenggara | 232 | 26.5 | 642 | 73.5 | ||
Kalimantan | 291 | 33.5 | 578 | 66.5 | ||
Sulawesi | 270 | 27.8 | 701 | 72.2 | ||
Maluku & Papua | 164 | 42.4 | 222 | 57.6 | ||
Place of residence | ||||||
Rural | 2051 | 28.6 | 5116 | 71.4 | 1.45 | 0.49 |
Urban | 1989 | 29.5 | 4745 | 70.5 | ||
Socioeconomic factors | ||||||
Wealth quintile | ||||||
Poorest | 928 | 34.6 | 1757 | 65.4 | 58.56*** | 0.00 |
Poorer | 827 | 29.5 | 1980 | 70.5 | ||
Middle | 781 | 26.9 | 2127 | 73.1 | ||
Richer | 753 | 26.3 | 2109 | 73.7 | ||
Richest | 751 | 28.4 | 1888 | 71.6 | ||
Health insurance | ||||||
No | 1713 | 29.8 | 4026 | 70.2 | 3.00 | 0.19 |
Yes | 2326 | 28.5 | 5835 | 71.5 | ||
Access to the health facility | ||||||
Difficult | 555 | 36.0 | 985 | 64.0 | 41.46*** | 0.00 |
Not | 3485 | 28.2 | 8877 | 71.8 | ||
Child’s factors | ||||||
Age of child (in month) | ||||||
Less than one month | 1007 | 33.0 | 2045 | 67.0 | 58.13*** | 0.00 |
One month | 938 | 29.9 | 2198 | 70.1 | ||
Two months | 840 | 30.0 | 1956 | 70.0 | ||
Three months | 631 | 24.7 | 1929 | 75.3 | ||
Four months | 623 | 26.4 | 1733 | 73.6 | ||
Sex of child | ||||||
Male | 2118 | 29.9 | 4963 | 70.1 | 5.11 | 0.06 |
Female | 1922 | 28.2 | 4898 | 71.8 | ||
Birth rank | ||||||
First child | 1251 | 27.1 | 3368 | 72.9 | 41.25*** | 0.00 |
Second | 1400 | 28.7 | 3469 | 71.3 | ||
Third | 761 | 29.0 | 1864 | 71.0 | ||
Fourth and more | 628 | 35.1 | 1160 | 64.9 | ||
Mother’s factors | ||||||
Age of mother in year | ||||||
15–24 | 796 | 30.6 | 1808 | 69.4 | 6.26 | 0.52 |
25–29 | 1032 | 29.2 | 2502 | 70.8 | ||
30–34 | 995 | 27.7 | 2594 | 72.3 | ||
35–39 | 808 | 29.0 | 1975 | 71.0 | ||
40–44 | 336 | 29.3 | 809 | 70.7 | ||
45–49 | 73 | 29.5 | 174 | 70.5 | ||
Mother’s level of education | ||||||
No education | 63 | 50.0 | 63 | 50.0 | 55.19*** | 0.00 |
Primary | 1117 | 31.2 | 2458 | 68.8 | ||
Secondary | 2357 | 28.9 | 5803 | 71.1 | ||
Higher | 503 | 24.6 | 1537 | 75.4 | ||
Mother’s occupation | ||||||
Working | 1917 | 27.2 | 5136 | 72.8 | 24.97*** | 0.0001 |
Not working | 2123 | 31.0 | 4725 | 69.0 | ||
Spouse’s factor | ||||||
Age of spouse in year | ||||||
11–20 | 44 | 45.8 | 52 | 54.2 | 23.83** | 0.0068 |
21–30 | 1164 | 29.6 | 2772 | 70.4 | ||
31–40 | 1901 | 28.2 | 4843 | 71.8 | ||
41–50 | 817 | 29.2 | 1985 | 70.8 | ||
51–60 | 106 | 35.7 | 192 | 64.3 | ||
61–70 | 8 | 33.8 | 15 | 66.2 | ||
71–80 | 0 | 0.0 | 2 | 100.0 | ||
Spouse’s level of education | ||||||
No education | 51 | 37.0 | 86 | 63.0 | 39.21*** | 0.0001 |
Primary | 1254 | 32.5 | 2610 | 67.5 | ||
Secondary | 2255 | 28.0 | 5803 | 72.0 | ||
Higher | 479 | 26.0 | 1362 | 74.0 | ||
Spouse’s occupation | ||||||
Working | 4016 | 29.1 | 9799 | 70.9 | 0.15 | 0.72 |
Not working | 23 | 27.2 | 63 | 72.8 |
Table 2 shows that the least distribution of respondents is in the Eastern of Indonesia. Nearly half of participants who live in the Eastern of Indonesia did not use the PNC services. More than half of participants who live in the Eastern of Indonesia was classified as the lowest. Interestingly, most participants who live in the Eastern of Indonesia stated that there was no problem with access to the health facility. More detail characteristics of participants can be found in Table 2.
Table 3 reveals that nearly half of participants who live in Sumatera, Kalimantan, Maluku and Papua did not use the PNC service. The highest number of participants classified as lowest was found in Maluku & Papua. For health insurance ownership, more participants who live in Kalimantan did not have health insurance. The highest number of participants having four and more children per household were found in Maluku & Papua (Table 3).
In multivariate analysis, the participants who live in the Central of Indonesia utilised PNC services 2.54 times more than the participants who live in the Western of Indonesia (OR = 2.54; 95% CI = 1.77-3.65). The participants who live in the Eastern of Indonesia had 0.71 fewer odds than participants in Indonesia’s Western (OR = 0.71; 95% CI = 0.52-0.96). The participants who live in Java were 1.46 times more likely to use PNC services (OR = 1.46; 95% CI = 1.26-1.69) compared to participants living in Sulawesi (OR = 0.53; 95% CI = 0.35-0.80). (Table 4). Details of the results of multivariate analysis shown in Table 4.
Variable | The use of PNC | |||
---|---|---|---|---|
P | OR | 95% CI | ||
lower | upper | |||
Indonesia | ||||
Western Indonesia | Ref. | 1.0 | ||
Central Indonesia | 0.00*** | 2.54 | 1.77 | 3.65 |
Eastern Indonesia | 0.03* | 0.71 | 0.52 | 0.96 |
Region | ||||
Sumatera | Ref. | 1.0 | ||
Java | 0.00*** | 1.46 | 1.26 | 1.69 |
Bali & Nusa Tenggara | 0.007** | 0.57 | 0.38 | 0.86 |
Kalimantan | 0.007** | 0.66 | 0.48 | 0.89 |
Sulawesi | 0.002** | 0.53 | 0.35 | 0.80 |
Maluku & Papua | Omitted |
Table 5 reveals the middle category women based on wealth index had PNC service’s utilization increased by 1.25 greater odds (OR = 1.25; 95% CI = 1.07-1.47) more than the richer category mothers (OR = 1.23; 95% CI = 1.04-1.45). Participants who thought that access to the health facility was not a problem had an odds ratio of 1.29 greater than participants who considered access to the health facility to be a major problem in using PNC service (OR = 1.29; 95% CI = 1.10-1.51). Mothers having children aged three months had used PNC service 1.43 times (OR = 1.43; 95% CI = 1.23-1.66) more than mothers with children aged four months (OR = 1.30; 95% CI = 1.12-1.51). Mothers who had a second child had utilized PNC service 0.88 times (OR = 0.88; 95% CI = 0.78-0.99) more than mothers who had a third child (OR = 0.86; 95% CI = 0.74-0.99). Mothers who had higher education had 2.11 times the chance to utilize PNC visits (OR = 2.11; 95% CI = 1.24-3.59) compared to those with lower-level education (OR = 1.80; 95% CI = 1.09-2.98). Mothers with spouse’s aged 41–50 had a higher chance of utilization PNC visits (OR = 2.18; 95% CI = 1.31-3.63) compared to mothers with spouse’s aged 31–40 (OR = 2.07; 95% CI = 1.26-3.40). Details of the results of a multivariate analysis shown in Table 5.
Variable | The use of PNC | |||
---|---|---|---|---|
P | OR | 95% CI | ||
lower | upper | |||
Wealth quintile | ||||
Poorest | Ref. | 1.0 | ||
Poorer | 0.07 | 1.15 | 0.99 | 1.35 |
Middle | 0.007** | 1.25 | 1.07 | 1.47 |
Richer | 0.017* | 1.23 | 1.04 | 1.45 |
Richest | 0.86 | 1.02 | 0.85 | 1.22 |
Access to the health facility | ||||
Difficult | Ref. | 1.0 | ||
Not | 0.001** | 1.29 | 1.10 | 1.51 |
Age of child (in month) | ||||
Less than one month | Ref. | 1.0 | ||
One month | 0.06 | 1.13 | 0.99 | 1.28 |
Two months | 0.11 | 1.11 | 0.98 | 1.26 |
Three months | 0.00*** | 1.43 | 1.23 | 1.66 |
Four months | 0.001** | 1.30 | 1.12 | 1.51 |
Birth rank | ||||
First child | Ref. | 1.0 | ||
Second | 0.04* | 0.88 | 0.78 | 0.99 |
Third | 0.04* | 0.86 | 0.74 | 0.99 |
Fourth and more | 0.00*** | 0.68 | 0.58 | 0.81 |
Mother’s level of education | ||||
No education | Ref. | 1.0 | ||
Primary | 0.02* | 1.80 | 1.09 | 2.98 |
Secondary | 0.03* | 1.77 | 1.06 | 2.96 |
Higher | 0.006** | 2.11 | 1.24 | 3.59 |
Mother’s occupation | ||||
Working | Ref. | 1.0 | ||
Not working | 0.007** | 0.87 | 0.79 | 0.96 |
Age of spouse in year | ||||
11–20 | Ref. | 1.0 | ||
21–30 | 0.016* | 1.83 | 1.12 | 3.00 |
31–40 | 0.004** | 2.07 | 1.26 | 3.40 |
41–50 | 0.003** | 2.18 | 1.31 | 3.63 |
51–60 | 0.06 | 1.73 | 0.97 | 3.07 |
61–70 | 0.17 | 2.19 | 0.72 | 6.68 |
71–80 | Omitted | |||
Spouse’s level of education | ||||
No education | Ref. | 1.0 | ||
Primary | 0.98 | 1.01 | 0.67 | 1.51 |
Secondary | 0.50 | 1.15 | 0.76 | 1.74 |
Higher | 0.48 | 1.17 | 0.76 | 1.83 |
This study aimed to examine the gap across the region in Indonesia for PNC utilisation among mothers aged 15–49 years old using the 2017 IDHS data sets. PNC has been the primary strategy to improve maternal health outcomes to reduce the high maternal mortality deaths in Indonesia. Therefore, assessing the regional disparities in PNC may provide evidence for the government to resolve discrepancies in maternal services in Indonesia. This study demonstrated that the prevalence of PNC service utilisation among mothers aged 15–49 years was 70.94%. This finding was higher than other research in Sub-Saharan Africa and Ethiopia with Abebo & Tesfaye (2018) and Tessema et al. (2020), respectively finding that 47.9% and 52.48% of women had used PNC service. An intertwined complex factor, such as the health system, maternal health policies, and socio-cultural variations across countries, may hinder women’s use of the PNC service.
Among the geographic groups analysed in this study, mothers who settled in the Central of Indonesia had increased odds of using PNC service, while those who lived in the Eastern of Indonesia had decreased odds. Similarly in Ethiopia (Sisay et al., 2019), the geographic factor is correlated to the utilisation of PNC service due to the region's level of development and location. Evidence in Indonesia shows that the socio-economic development, such as industrial, housing, public transportation, road facilities and health facilities in the Eastern Indonesia, lagged compared to the Western of Indonesia (Ministry of Health Republic of Indonesia, 2018; Soewondo et al., 2019; Suparmi et al., 2018). Therefore, it is a call of action to provide equality in developing human resources and infrastructure to reduce the possibility of gaps.
Additionally, mothers who live in Java are 1.46 times more likely to use PNC services than mothers who live in Sulawesi where they are 0.53 less likely to utilise PNC services. Java has dominance development compared to other islands because this island is the centre of the Indonesian government (Laksono et al., 2020). The Java island oriented and centred development model has harmed maternal health outcomes in Indonesia (Bappenas, 2018). Natural resources, human resources and facilities must be equal throughout Indonesia, so the gap between islands could be minimised.
This study revealed that the wealth index was significantly linked to PNC service utilisation among mothers aged 15–49 years old in Indonesia. Mothers from the middle households based on the wealth index had PNC service’s utilisation increased by 1.25 greater odds (OR = 1.25; 95% CI = 1.07-1.47) more than the richer mothers (OR = 1.23; 95% CI = 1.04-1.45). However, earlier research is done in Pakistan, Ethiopia, and Tanzania, revealed where mothers from the richer wealth quintile were significantly associated with the utilisation of PNC services (Berhe et al., 2019; Mohan et al., 2017; Yunus et al., 2013). The odds ratio was quite similar between middle and richer households as shown on this study. Additionally, the previous study in other parts of Ethiopia demonstrated that sociodemographic factors, such as income, did not correlate with the use of PNC services (Angore et al., 2018). Mothers from richer households were more likely to access the PNC services. Ownerships of consumer goods at home, such as motorcycles and cars, may increase the risk at ease transportation, making them have no strain to access the health facility.
The present study showed that access to the health facility was correlated to PNC service in Indonesia. With mothers who thought that access to the health facility was not a problem, they had an odds ratio of 1.29 greater in using PNC service than mothers who considered access to the health facility difficult. Previous research conducted in Malawi has found a significant association between the health facility and the utilisation of PNC services. Other Ethiopia studies have demonstrated that physical accessibility plays an essential variable in health service utilisation (Kim et al., 2019; Tarekegn et al., 2014). Access to the health facility is related to the costs incurred, which is influenced by having transportation to the health facility, which is considered expensive. Long and shorter distances, better roads, and better public transportation may increase access to the health facility, primarily in Indonesia, with its massive gaps in development across the country (Bappenas, 2018).
In this study, mothers having children aged three months increased the likelihood to use PNC services about 1.43 times (OR = 1.43; 95% CI = 1.23-1.66) more than mothers with children aged four months (OR = 1.30; 95% CI = 1.12-1.51). A similar study in Nepal showed that PNC service utilisation in the early postnatal period was most likely due to the motherhood transition period (Sanjel et al., 2019). The possible reason could be that mothers with fewer children, and younger children, may want information and be petrified of complications during the postnatal period. In the Indonesia setting, the first neonatal examination (KN1) is carried out at 6–48 hours after the baby is born, which is at the same time for the first PNC visit (KF1). The second neonatal examination (KN2) is carried out between 3–7 days with the second PNC visit (KF2). The third neonatal examination (KN3) occurs alongside the third PNC visit (KF3), which is between 8–28 days after birth (Ministry of Health Republic of Indonesia, 2018).
Also, mothers who have second child had a 0.88 times likelihood to utilize PNC service (OR = 0.88; 95% CI = 0.78-0.99) than mothers having a third child (OR = 0.86; 95% CI = 0.74-0.99). Some studies in Ethiopia and India showed that the higher the child's birth order, the lower the utilisation of PNC services (Ali & Chauhan, 2020; Sisay et al., 2019). A possible reason could be that mothers who had more children were more likely experienced in motherhood and had appropriate knowledge from previous maternal experiences and childcare, hence restraining PNC service.
This study revealed that mothers who hold higher education qualifications have 2.11 times the chance of utilising PNC visits (OR = 2.11; 95% CI = 1.24-3.59) compared to those with lower-level education (OR = 1.80; 95% CI = 1.09-2.98). Earlier research in Ethiopia showed that a mother's education was significant to PNC utilisation (Tarekegn et al., 2014). The possible reason could be that educated women have a greater opportunity to be informed and are more aware of seeking advice and treatment from skilled healthcare personnel than uneducated women.
This study demonstrated that the spouse's age was significantly linked to the utilisation of PNC among mothers aged 15–49 years in Indonesia. Mothers who have spouses aged 41–50 have a higher chance of utilising PNC visits than mothers who have spouses aged 31–40. Similarly, in India showed that the spouse's age was associated with PNC's wives' service (Jungari & Paswan, 2019). Spouse's autonomy and power in decision-making regarding wive's needs, including their health care needs, remained persistent. The spouse's age may be linked to the level of maturity and primary controller, which exacerbates their wives' access to the health service (Jungari & Paswan, 2019; Sekine & Carter, 2019).
To the best of our knowledge, this is the first study to examine the gaps across the region in utilisation PNC service among mothers aged 15–49 years old in Indonesia, which is one of a country in Southeast Asia that contribute to the global burden of maternal mortality rates in the world. The strengths of our study that we utilised the national and provincial data representatives, which internationally standardised. However, we also note some limitations. The IDHS data analysed in this study was collected using the cross-sectional method and mother’s recall preceding survey prone to the possibility of bias information.
This study reveals the gap across the region for PNC utilisation among mothers aged 15–49 years old in Indonesia. This study's findings provide evidence to complete the bigger picture for the government to resolve discrepancies in maternal services in Indonesia. The results suggest the need for national policy focuses on service equality, accessible, and reliable implementation to improve postnatal care utilisation among mothers to achieve the maximum results for the Indonesian Universal Health Coverage plan. Future research should explore the interregional gaps and factors that cause maternal health service utilisation by using a different platform.
Data used in this study is available online from the Indonesian 2017 Demographic and Health Survey (DHS) website under the DHS VII recode column. Access to the dataset requires registration and is granted only for legitimate research purposes. A guide for how to apply for dataset access is available at: https://dhsprogram.com/data/Access-Instructions.cfm. Other researchers will be able to access the data set in the same way as the authors and the authors do not have special access rights that others do not have.
Views | Downloads | |
---|---|---|
F1000Research | - | - |
PubMed Central
Data from PMC are received and updated monthly.
|
- | - |
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Partly
Are sufficient details of methods and analysis provided to allow replication by others?
Partly
If applicable, is the statistical analysis and its interpretation appropriate?
I cannot comment. A qualified statistician is required.
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
References
1. Thamrin SA, Arsyad DS, Kuswanto H, Lawi A, et al.: Predicting Obesity in Adults Using Machine Learning Techniques: An Analysis of Indonesian Basic Health Research 2018.Front Nutr. 2021; 8: 669155 PubMed Abstract | Publisher Full TextCompeting Interests: No competing interests were disclosed.
Reviewer Expertise: Community health; health education; health promotion; nursing workforce
Is the work clearly and accurately presented and does it cite the current literature?
Yes
Is the study design appropriate and is the work technically sound?
Yes
Are sufficient details of methods and analysis provided to allow replication by others?
Yes
If applicable, is the statistical analysis and its interpretation appropriate?
Yes
Are all the source data underlying the results available to ensure full reproducibility?
Yes
Are the conclusions drawn adequately supported by the results?
Yes
Competing Interests: No competing interests were disclosed.
Reviewer Expertise: Community health nursing, maternal and children health nursing, geriatric health nursing, health promotion, health education, occupational health nursing, public health nursing, primary health nursing, rehabilitation nursing.
Alongside their report, reviewers assign a status to the article:
Invited Reviewers | ||
---|---|---|
1 | 2 | |
Version 2 (revision) 16 Aug 21 |
||
Version 1 26 Feb 21 |
read | read |
Provide sufficient details of any financial or non-financial competing interests to enable users to assess whether your comments might lead a reasonable person to question your impartiality. Consider the following examples, but note that this is not an exhaustive list:
Sign up for content alerts and receive a weekly or monthly email with all newly published articles
Already registered? Sign in
The email address should be the one you originally registered with F1000.
You registered with F1000 via Google, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Google account password, please click here.
You registered with F1000 via Facebook, so we cannot reset your password.
To sign in, please click here.
If you still need help with your Facebook account password, please click here.
If your email address is registered with us, we will email you instructions to reset your password.
If you think you should have received this email but it has not arrived, please check your spam filters and/or contact for further assistance.
Comments on this article Comments (0)