INTRODUCTION
Malnutrition persists among Indonesian children under the age of 5 years, with rates varying across urban and rural regions. In Indonesia, about 17.1% of children less than 2 years old were stunted (16.2% in urban areas and 18.1% in rural areas), 7.2% were wasted (7.1% in urban areas and 7.5% in rural areas), and 11.4% were underweight (10.6% in urban areas and 12.3% in rural areas) [1]. In 2013, Basic Health Research discovered that 28.1% of children aged 1 to 5 years had iron-related nutritional anemia (30.3% in urban regions and 25.8% in rural areas) [2]. Anemia was found in 59.4% of children aged 6–23 months, and they were the most likely to suffer from anemia [3].
Adequate nutrition is critical for optimal health and growth in the first few months of life. After 6 months of age, breast milk is insufficient to meet the nutritional requirements of newborns. The shift from exclusive breastfeeding to family meals is essential between the ages of 6 and 23 months, making toddlers prone to malnutrition. In addition to breastfeeding, optimal complementary feeding practices are necessary to prevent malnutrition and child mortality [4].
Many factors affect infant and young feeding practices, such as sociodemographic characteristics, the economy, and the availability of rural and urban facilities. Significant variances exist between the geographic locations and wealth quintiles. According to the 2017 Indonesia Demographic and Health Survey (IDHS), the proportion of children aged 6–23 months who satisfied the infant and young feeding practice guidelines varied between urban (47.8%) and rural (35.3%) districts [5]. Approximately 33% of children within that age group did not reach the required minimum frequency of meals, one-quarter did not meet the minimum dietary variety requirement, and almost half did not meet the recommended diet quality requirement [6].
A composite metric called the minimum acceptable diet (MAD) considers dietary quality and quantity. To facilitate the healthy development of infants and young children, MAD must be fulfilled. Although MAD in children aged 6–23 months has been researched in Indonesia [7,8], no study has been conducted on the variables that impact MAD depending on the location of living in urban and rural settings. To enhance the prevalence of MADs and mitigate malnutrition rates in Indonesia, a comprehensive understanding of the underlying factors contributing to the low occurrence of MAD among children aged 6–23 months must be developed considering the issues encountered in both urban and rural areas. Therefore, this study aimed to identify the risk factors for MAD in 6–23-month-old infants in rural and urban Indonesia.
METHODS
1. Data Sources and Study Population
A nationally representative dataset from the IDHS 2017 (IDKR71FL) was used for the secondary data analysis. The IDHS used a two-stage stratified sampling design to select census blocks and households. The numbers of eligible households and women aged 15–24 years for the interview were 47,963 and 49,267, respectively. Details on the IDHS method have been provided elsewhere [5]. The analysis was limited to married women aged 15–49 years who had a last-born child aged 6–23 months living with her. A total of 4,688 children were included in this study. Figure 1 illustrates the participant selection process for the IDHS 2017 dataset.
2. Outcome Variables
The focus of the secondary data analysis was to examine the prevalence of MADs among children aged 6–23 months old who consumed a meal or drink other than breast milk on the day before the study. Children were characterized as receiving MAD if they met both the minimum dietary diversity (MDD) and minimum meal frequency (MMF) criteria, which was further categorized as meet and unmet MAD [9]. MDD is described as eating at least five out of the following eight food categories: (1) cereals, roots, and tubers; (2) legumes and nuts; (3) dairy products; (4) meat foods; (5) eggs; (6) vitamin A-rich fruits and vegetables; (7) other fruits and vegetables; and (8) breastmilk [10].
MMF refers to the proportion of children, both breastfed and non-breastfed, who have had solid, semi-solid, or soft meals at the minimum frequency required, taking into account milk feeds for non-breastfed children. MMF was defined as twice for breastfed infants aged 6–8 months, 3 times for breastfed children aged 9–23 months, and 4 times for non-breastfed children aged 6–23 months [9].
3. Independent Variables
Independent variables from the questionnaire were classified as child, mother, father, and household factors. Age and sex were the child-related factors. Mother-related factors included pregnancy and antenatal care (ANC) visits, age, education, employment, involvement in home decisions, living with husband, and access to the media. The level of media access observed was indicative of the mothers’ regular engagement with various forms of mass media, including print publications, radio broadcasts, and television programming. Mothers’ engagement in decision-making was built on the mother’s ultimate say or jointly with their husband in one of the following situations: receiving healthcare for herself, making large household purchases, or visiting family and relatives. Father-related factors included age, education, and occupation. The number of children under 5 years of age, number of household members, wealth index, and refrigerator ownership were the household variables. The wealth index of the household was used as a proxy measure for household socioeconomic status in the IDHS. The weighted scores for the household wealth index were further classified into quintiles.
4. Data Analysis
STATA ver. 15.1 (Stata Corp., College Station, TX, USA) was used to analyze the data using a multiple logistic regression model with stratification based on the area of residence (urban or rural). The size of the outcome and independent factors was examined using a descriptive analysis utilizing a frequency distribution for children living in each type of residential area (Table 1). The chi-square test was used to assess the differences in all independent variables in relation to the MAD status (Table 2). Variables with P-values less than 0.25 were then included in the multivariate logistic regression analysis to investigate the predictors of MAD in children aged 6–23 months in each area (Table 3). All independent variables included in the multivariate analysis were adjusted for the relationship between MAD status and other independent variables. The adjusted odds ratio (AOR) with a 95% confidence interval (CI) was used to assess the strength of the relationship (Table 3). Statistical significance was defined as a P-value <0.05. The percentage of Indonesian children aged 6–23 months at the national level was calculated using sample weights.
5. Ethical Statement
The Institutional Review Board (IRB) of the Inner-City Fund (ICF) International and ORC Macro approved the questionnaires for the standard IDHS 2017 surveys (ICF IRB no., FWA00000845), and the 2017 IDHS was granted ethical clearance. It adhered to the Department of Health and Human Services’ mandate to protect human subjects, and participant information was kept anonymous. All participants (the children’s parents) provided verbal informed consent before participating in the interviews, and their participation was voluntary.
RESULTS
1. Characteristics of the Study Population
Overall, a smaller proportion of rural participants (35.7%) received a MAD than did urban participants (47.4 %). Table 1 shows the detailed distribution of study participants.
2. Association between the Risk Factors and Minimum Acceptable Diet Status in Urban and Rural Areas
After bivariate analysis, we found that, the number of household members, gender of the child, whether pregnancy was desired, mother’s age, and father’s professional position had no significant relationship with MAD status in both urban and rural participants. Subsequently, multivariate logistic regression analysis was performed for all additional variables (Table 2).
3. Determinant Factors and Minimum Acceptable Diet Status in Urban and Rural Areas
Multivariate analysis revealed that the household wealth index, child’s age, mother’s working status, and father’s age were significant for both rural and urban households (Table 3). A dose-response relationship was observed between the household wealth index and MAD among children, especially in rural areas. In rural areas, the odds of MAD among children increased by 49%, 59%, 73%, or 160% as compared to those in the poorest households. Regardless of the household wealth index, owning a refrigerator was not observed as a significantly associated factor of MAD status for either rural or urban subjects.
Older children had a higher chance of receiving MAD than children aged 6–11 months (as the reference age group). Children aged 12–17 and 18–23 months have a 2–3 times higher chance of receiving MAD compared to children in the 6–11 month age group. This applies to children living in both urban and rural areas. In addition, in urban areas, the older the children, the better their MAD. Children belonging to the age groups of 12–17 months and 18–23 months were over 2 times (AOR, 2.44; 95% CI, 1.88–3.18; P<0.001 and AOR, 3.02; 95% CI, 3.02–3.94; P<0.001, respectively) more likely to have access to MAD than children aged 6–11 months. In rural areas, the opposite is true for the age groups of 12–17 months and 18–23 months. Children aged 12–17 months had the highest odds of receiving MAD (AOR, 2.90; 95% CI, 2.18–3.86; P<0.001).
Occupational status of the mother was among the significant variables affecting the odds of MAD status in both urban and rural areas. In urban areas, mothers who work were more likely than non-working mothers to ensure MAD access to their children, with those in formal sectors having higher odds (AOR, 1.62; 95% CI, 1.20–2.20; P=0.002) to meet the MAD of their children than the informal workers (AOR, 1.35; 95% CI, 1.05–1.72; P=0.016).
Meanwhile, in rural areas, the formal occupational status of mothers was a significant variable that affected the odds of receiving MAD in children. Mothers who work in formal sectors were more likely to feed their children MAD (AOR, 1.46; 95% CI, 1.01–2.13; P=0.049) to meet the MAD of their children than non-working or informal working mothers.
Instead of the father’s education, the father’s age had a key influence on children’s MAD status in both urban and rural areas. Fathers younger than 35 years had a better chance of having children with access to MAD; their odds of ensuring MAD in rural and urban areas increased by 42% (AOR, 1.42; 95% CI, 1.15–1.74; P=0.001) and 25% (AOR, 1.25; 95% CI, 1.01–1.58; P=0.049), respectively, compared to that of fathers aged 35 years or older.
However, when we looked further at residence type, there were some differences in the significant variables. In urban households, MAD status was more probable (AOR, 1.71; 95% CI, 1.18–2.47; P=0.005) if the mother lived together with her husband. On the contrary, in rural households, the mother’s involvement in decision making (AOR, 1.58; 95% CI, 1.04–2.39; P=0.033) and ANC visits for at least 4 times (AOR, 2.54; 95% CI, 1.30–4.98; P=0.007) significantly increased the likelihood of children’s MAD status.
DISCUSSION
This study indicated that over half of the children under 2 years of age in urban and rural areas did not meet the MAD. Area of living (rural and urban) influences the access to MAD in Indonesian children aged 6–23 months [11]. To explore this, we investigated the characteristics associated with MAD compliance in children aged 6–23 months living in urban and rural regions and examined the factors behind MAD achievement in both.
According to this study, socioeconomic and sociodemographic factors that were strongly associated with MAD in both rural and urban areas were the household wealth index, maternal working status, and father’s age. This study found that the higher the household wealth index, the greater the odds of ensuring MAD in children. A better wealth index provides a better opportunity for meeting MAD in children [12]. This means that the higher the household wealth index, the better the chance of accessing necessities, health care, and knowledge of excellent newborn and small-child feeding habits. Wealthier households also tend to consume nutritious and varied food because of sufficient resource supply [13]. Households in urban areas are more likely to employ domestic paid caregivers for childcare or domestic support. The higher the wealth index, the better the chance of accessing this service [14].
Regarding employment and MAD status, we observed that children whose mothers work, in either urban or rural areas, are more likely to receive MAD than those whose mothers stay at home. This indicates that MAD administration was relatively stable in both settings. This also highlights the positive impact of formal maternal employment on child nutrition and suggests potential areas for focused efforts to improve child nutrition in various economic settings.
The correlation between maternal employment and MAD adherence is contingent upon various factors, including working hours, job type, income levels, and access to food resources [11]. Similar patterns have been observed in other nations, such as Ethiopia, where working mothers exhibited a 1.7-fold higher likelihood of ensuring that their children meet MAD standards than did non-working mothers [15,16].
Although economic and educational levels normally increase with age, we discovered that children were less likely to have MAD if their fathers were older than 35 years. This indicates that there may be unidentified factors linking the father’s age and child’s MAD status, warranting further studies. In Indonesia, traditional divisions of household tasks are still relatively strong, with females being more responsible for childcare than their husbands [14,17]. This may explain why older fathers probably contribute less to childcare and feeding practices, as observed in our study. Nevertheless, this is only a minor fraction of the overall determinants of children’s MAD status, and the pattern may vary in different scenarios.
The characteristic of the child, in this case, was age, which was also associated with ensuring MAD. Our findings imply that the chance of meeting MAD increased remarkably with the increase in the child’s age, which is consistent with those from a similar study using IDHS 2012 data [18] and another study in developing countries [19]. Other meals are typically introduced to exclusively breastfed children at an age of 6 months, which may explain why babies aged 6–11 months are less likely to receive MAD [20]. These babies likely exhibit a decreased tendency toward selective eating habits as they grow older, because they will have more developed teeth and immune systems [21]. Mothers may also perceive that younger babies are not adequately equipped to digest certain foods [22].
Children living in urban areas were more likely to achieve MAD than those living in rural areas. Urban mothers had better access to information; health service institutions; and media such as the internet, television, and newspapers to enhance their knowledge of healthy feeding practices. Urban areas also facilitate mothers’ access to diverse foods through establishments such as markets, greengrocers, and malls and to prepared foods from restaurants, cafés, food stalls, bakeries, or urban eateries. We also found that children living in rural areas were more likely to have low dietary diversity. Better and equitable access to food producers, using a variety of locally available foods and employing vegetable gardens, is needed.
A few maternal factors have been linked to MAD exclusively in urban or rural areas. Mothers who participate in household decisions and perform ANC visits at least 4 times during pregnancy increase the likelihood of children in rural areas having MAD. In this study, most mothers visited ANC 4 times or more during pregnancy, with a higher proportion of these mothers being from urban areas than from rural areas. However, the number of mothers visiting ANC 4 or more times in urban areas was not related to child-feeding practices, especially MAD. In contrast to the results of other studies [23], our analysis showed that ANC visits were an independent factor associated with MAD only in children from rural areas.
As part of the important maternal healthcare services, ANC provides a platform to counsel mothers to prepare the foundations for healthy motherhood. During ANC, mothers can receive counseling from health workers about appropriate feeding for infants and young children, which may increase the odds of MAD. This indicates that a sufficient frequency of ANC visits may increase the chances of MAD access for children in rural areas, perhaps because of their practice of following the health workers’ advice. Furthermore, the mothers included in this study were relatively young, between 15–34 years old, and their education can influence their knowledge, attitudes, and behavior toward the information provided. Mothers who live in rural areas tend to listen more to the health workers [24]. Additionally, we observed that mothers in rural areas had more autonomy in feeding their children.
Maternal autonomy has emerged as a crucial social determinant that affects children’s health and development, particularly concerning MAD practices. Drawing on insights from studies conducted in Ghana [25] and Bangladesh [26], this study underscores the importance of financial decision-making autonomy in shaping MAD outcomes. Children whose mothers exhibit greater independence are more likely to receive nutrition that aligns with the recommended standards, encompassing diverse food choices and consistent meal frequencies. Our findings highlight a significant impact within rural households, where maternal involvement in decision making significantly increased the likelihood of a child attaining MAD status by 1.58 times. This study establishes a clear link between maternal autonomy and child nutrition and provides compelling evidence that highly autonomous mothers have the capacity to nourish their infants in accordance with global benchmarks. These findings emphasize the need for targeted interventions and policies that empower mothers, particularly in rural settings, to ensure improved child health and development.
Moreover, urban mothers living with their husbands were strongly associated with ensuring MAD to their children. Social assistance from the husband helps reduce psychological issues such as depression, while improving the well-being and viability of both mothers and offsprings.
A study in Uganda reported that children who were cared for by a combination of mothers and fathers had a greater chance of achieving MAD 2.7 times than children who were only cared for by their mothers [27]. Children raised by both parents had better complementary feeding behaviors, demonstrating that fathers may help mothers by providing extra support and incentives.
An association between living with a husband and MAD was not observed in families living in rural areas. This is probably because the traditional cultural roles of mothers as caretakers of children and fathers as breadwinners are common in rural families in Indonesia. According to a study conducted in Northern Ghana, fathers’ engagement in childcare chores such as feeding, cooking, maintaining company with the child, or washing the child remained a strong independent predictor of MAD [28]. Another study in Indonesia also reported the father’s influence on the success of breastfeeding practices measured by the father’s support during pregnancy, at birth, and first breastfeeding; postnatal support; fathers’ involvement in childcare; and positive attitude toward married life [29].
1. Study Limitations
This study did not account for the season during which the data were collected, which might have affected the diversity of meals ingested by the youngsters. In addition, this study did not consider whether the child was sick at the time or before data collection, which might have affected their appetite and food choices leading to overestimation of results.
2. Conclusion
MAD status was determined by older child age, higher level of parental education, younger father, working mother, and higher household wealth index in children aged 6–23 months in both urban and rural areas. Additionally, mothers living with their husbands determined the MAD status in urban areas. Meanwhile, in rural areas, more frequent ANC visits and mothers’ participation in household decisions were additional factors related to MAD. Therefore, the design of public health interventions must consider the location-wise characteristics or factors in rural and urban areas.
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