Scientific Papers

Trend of sociodemographic and economic inequalities in the use of maternal health services in Lao People’s Democratic Republic from 2006 to 2017: MICS data analysis. | Tropical Medicine and Health

Conceptual framework

As shown in Fig. 1, maternal health service utilization is determined by geographical accessibility to the service provider, availability of the relevant or desired service, and affordability and acceptability of the service [23]. Therefore, the implementation of the Free MCH policy primarily seeks to address barriers in geographic accessibility to the providers (cost of transportation) and the financial barriers to service utilization (out-of-pocket payments) [16].

Fig. 1
figure 1

(Source: Adapted from Levesque et al. [23], Tandon et al. [16], and Matthews et al. [58])

Access to maternal health service during the implementation of the Free MCH policy in Lao PDR

Study design and data source

The study was conducted using a repeated cross-sectional design. Three of the most recent Multiple Indicator Cluster Survey (MICS) and Lao Social Indicator Survey (LSIS) datasets of Lao PDR, which are accessible in the public domain at, were combined (MICS 2006, LSIS I of 2011–12, and LSIS II of 2017) for the analysis. LSIS and Lao MICS are nationally representative sample surveys that collect data to assess key social development indicators in Lao PDR such as the use of maternal health services, mortality rates, use of reproductive health services, education, health nutrition, water and sanitation, child development, child protection, and rates of human immunodeficiency virus/acquired immunodeficiency syndrome.

Study population

This study included 15–49-year-old women who had a live birth in 2 years before each survey. The women needed to reside in sampled households and agree to respond to questions related to maternal health service utilization including ANC services, birth attendance, and PNC services.


Existing variables in the datasets were used, whereas others were recategorized or created as necessary for our analyses. Then, all variables were harmonized across the datasets before use.

Mother’s age: we purposively recategorized women’s age at the time of the survey into four groups 15–19 years old, 20–24 years old, 25–34 years old, and 35–49 years old using an existing continuous variable of age [24]. The categorization was done to differentiate service use between adolescent women, young adult women, and older women and to avoid categories with very few women.

Educational attainment: women were grouped based on their highest education levels. Three categories were considered: “none” for women who had no formal education, and “primary” and “secondary or higher” for women whose highest educational levels were primary school and secondary school or higher, respectively.

Area of residence: according to the Lao Statistics Bureau, women were grouped depending on whether their locality is categorized as “urban”, “rural with road access”, or “rural without road access” [20, 21, 25].

Ethnicity: according to the MICS 2006, LSIS I 2011–12, and LSIS II 2017, women were asked what the ethnic group was of the heads of their households, and they were categorized as “Lao”, “Hmong”, “Khmu”, and “others” [20, 21, 25].

Wealth quintiles: these are equally sized groups generated using principal component analysis based on household ownership of 35 different assets [26]. We used this variable to approximate the socioeconomic position of the respondents’ households. Categories for this variable include “poorest”, “poor”, “middle”, “richer”, and “richest”.

Core indicators

Three key facility-based maternal health service uses were investigated depending on how relevant they are to target services of the Free MCH policy in Lao PDR. The services include a minimum of one ANC visit provided by skilled personnel, institutional delivery, and a minimum of one facility-based PNC visit by the mothers.

ANC provided by skilled personnel: women who had a live birth in 2 years before the surveys were asked whether they saw someone for ANC during their last pregnancy. Those who reported yes were further asked whom they saw for ANC. Based on the WHO definition of skilled health personnel and as applied in the MICS, we categorized women who received ANC provided by a doctor, nurse/midwife, or auxiliary midwife as ANC from skilled personnel [27] and that from other providers such as community health workers, traditional birth attendants, relatives/friends, and others as ANC from non-skilled personnel.

Institutional delivery: we considered women with a live birth within 2 years before the surveys and who had their last deliveries in hospitals, clinics, and maternity homes to have had an institutional delivery. We categorized deliveries in individuals’ or others’ homes as non-institutional deliveries.

Mother’s facility-based postnatal visit: we grouped women into three categories: those who had at least one PNC visit in a health facility including hospitals, clinics, or maternity homes; those who received PNC visits at individuals or relatives’ homes; and those who did not receive a PNC visit. As defined in MICS, PNC visits refer to a separate visit and do not include immediate checkups provided right after the delivery while at the place of delivery. For comparison purposes, we applied a 6-week limit after delivery for the PNC visit as defined in the MICS [21]. The use of at least one facility-based PNC visit by mothers within 6 weeks of delivery was extremely low, and below 4% across most social subgroups in 2017. Therefore, the assessment of inequalities was done only for ANC and institutional delivery.

Data analysis

Data analyses were conducted using Stata (V.17, StataCorp). We conducted a descriptive analysis to understand the socio-demographic characteristics of the study respondents and their use of maternal health services in 2006, 2011–12, and 2017. Chi-square tests were performed to compare the use of maternal health services between 2006 and 2017, and p-values with a 95% confidence interval (CI) were reported. Two of the commonly used summary measures of inequality were adopted in the present study including concentration curves and concentration indices (CIX), and equiplots. A concentration curve plots the cumulative sample population, ranked by a socioeconomic predictor variable with natural ordering such as wealth or education, against the cumulative proportion of health service utilization [28, 29]. The diagonal line from the origin also referred to as the equality line, reflects perfect equality in service utilization. For inequality measurement based on wealth, concentration curves lying below the diagonal indicate service disparities favoring the richest women while concentration curves above the equality line indicate service disparities in favor of the poorest. Similarly, in terms of educational attainment, concentration curves below the equality line show that services benefit women with secondary or higher education whereas service disparities are in favor of women with no education if the curves lie above the equality line. The CIX is calculated as twice the area between the concentration curve and the line of equality (diagonal) and measures the extent of inequality systematically associated with wealth [28, 29]. The index takes a value between − 1 and 1, with 0 indicating perfect equity. Stata commands used to generate the concentration curve plots and CIX are presented in a do-file attached as supplementary. We used equiplots to summarize absolute inequalities in access to services based on age groups, ethnicity, and area of residence as the use of concentration curves with those factors is not common in the literature [30]. Equiplots present coverage of maternal health service utilization by groups, which allows observation of levels of coverage and gaps between groups [31]. We used the svyset command to adjust for clustering, stratification, and the sampling weights of individual women in all analyses. Then, we displayed the absolute values of the CIX in graphs to analyze the trend in the magnitudes of socio-demographic and economic inequalities between 2006 and 2017.

Missing data

Of 10,526 women who had a live birth in the past 2 years before the surveys, 17 (0.2%) and 51 (0.5%) women had missing information for educational attainment and ethnicity, respectively. Regarding maternal health service utilization, 113 (1.1%) of the 10,526 women had missing data for the use of at least one ANC with skilled personnel as they did not answer about whether, and from whom, they received ANC, whereas 88 (0.83%) women did not answer about whether they had an institutional delivery. Moreover, of 8904 women in the MICS 2011–12 and LSIS II 2017 who were asked about PNC visits, 124 (1.4%) had missing data for using at least one facility-based PNC visit as they failed to answer about whether, when, and where they made a PNC visit. In each analysis, women were only excluded for sociodemographic and economic factors and maternal health services for which data were missing. Finally, all women in the MICS 2006 were excluded from PNC visit analyses as they were not asked questions regarding PNC.

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