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Malnutrition is common among children under 5 years of age in Indonesia, with the rates varying between urban and rural areas. The minimum acceptable diet (MAD) assesses nutrient quality and quantity. This study aimed to identify the potential variables for MAD in 6–23-month-old children in both urban and rural Indonesia.
Methods
We used the data from the 2017 Indonesia Demographic and Health Survey to conduct this nationally representative study. A total of 4,688 children aged 6–23 months were included in the study. MAD was classified using the 2017 World Health Organization global nutrition monitoring framework. The determinants of MAD were analyzed using multiple logistic regression.
Results
Overall, 45% of children aged 6–23 months received the required MAD, with 47.4% receiving the MAD in urban areas and 35.7% in rural areas. Children’s age, fathers’ age, parents’ education level, mothers’ employment, and wealth index were strongly linked to MAD in both rural and urban homes. The factor specifically related to MAD in urban areas was mother living with her husband. For rural households, mothers’ involvement in decisionmaking and a minimum of four antenatal care (ANC) visits significantly increased the likelihood of their children’s MAD status.
Conclusion
MAD status was determined by increased child age, higher parent education, younger father, working mother, and higher wealth index in children aged 6–23 months in both urban and rural settings. Mothers living with a spouse determined the MAD status only in urban areas. More frequent ANC visits and mother participation in household decisions were other factors related to MAD status in rural areas.
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.
Notes
CONFLICT OF INTEREST
No potential conflict of interest relevant to this article was reported.
ACKNOWLEDGMENTS
We thank IDHS for providing the data used in this study.
Figure. 1.
Selection of participants.
Table 1.
Frequency distribution of characteristics of the household, child, and parents based on urban and rural areas
Characteristic
Urban
Rural
No. of participants
2,318
2,370
Child factors
Meet minimum acceptable diet
No
1,219 (52.6)
1,523 (64.3)
Yes
1,099 (47.4)
847 (35.7)
Child’s age (mo)
6–11
787 (34.0)
767 (32.3)
12–17
802 (34.6)
859 (36.3)
18–23
729 (31.4)
744 (31.4)
Child’s gender
Boy
1,199 (51.7)
1,232 (52.0)
Girl
1,119 (48.3)
1,138 (48.0)
Household factors
No. of toddlers in the household
>1
749 (32.3)
661 (27.9)
1
1,569 (67.7)
1,709 (72.1)
No. of household members
>4
1,517 (65.5)
1,498 (63.2)
2–4
801 (34.5)
872 (36.8)
Household wealth index
Poorest
409 (17.7)
482 (20.3)
Poor
488 (21.1)
434 (18.3)
Middle
502 (21.6)
512 (21.6)
Rich
488 (21.0)
423 (17.9)
Richest
431 (18.6)
519 (21.9)
Refrigerator ownership
No
543 (23.4)
1,301 (54.9)
Yes
1,775 (76.6)
1,069 (45.1)
Mother’s factors
Wanted pregnancy
No
430 (18.6)
306 (12.9)
Yes
1,888 (81.4)
2,064 (87.1)
Antenatal care visits
Never
26 (1.1)
84 (3.5)
<4 times
107 (4.6)
178 (7.5)
≥4 times
2,185 (94.3)
2,108 (89.0)
Mother’s age (y)
15–34
1,680 (72.5)
1,813 (76.5)
35–54
638 (27.5)
557 (23.5)
Mother’s education
Less than high school
351 (15.2)
760 (32.1)
High school or above
1,967 (84.8)
1,610 (67.9)
Mother’s working status
Not working
1,236 (53.3)
1,366 (57.7)
Informal
789 (34.1)
797 (33.6)
Formal
293 (12.6)
207 (8.7)
Mother’s media access
No
247 (10.7)
402 (16.9)
Yes
2,071 (89.3)
1,968 (83.1)
Mother participation in household decision
No
255 (11.0)
267 (11.2)
Yes
2,063 (89.0)
2,103 (88.8)
Living with husband
No
199 (8.6)
235 (9.9)
Yes
2,119 (91.4)
2,135 (90.1)
Father’s factors
Father’s age (y)
≥35
1,065 (46.0)
1,071 (45.2)
<35
1,253 (54.0)
1,299 (54.8)
Father’s education
Less than high school
386 (16.6)
876 (37.0)
High school or above
1,932 (83.4)
1,494 (63.0)
Father’s working status
Not working
12 (0.5)
15 (0.7)
Informal
2,030 (87.6)
2,214 (93.4)
Formal
276 (11.9)
141 (5.9)
Values are presented as number of participants or number (%).
Table 2.
Frequency distribution of respondents based on the characteristics of household, child, and parents and MAD status in urban and rural areas
Characteristic
Urban
Rural
Unmeet MAD
Meet MAD
P-value
Unmeet MAD
Meet MAD
P-value
No. of participants
1,219
1,099
1,523
847
Household factors
No. of toddlers
0.396
0.021
>1
404 (54.0)
345 (46.0)
454 (68.7)
207 (31.3)
1
815 (51.9)
754 (48.1)
1,069 (62.6)
640 (37.4)
No. of household members
0.881
0.800
>4
796 (52.4)
721 (47.6)
959 (64.1)
539 (35.9)
2–4
423 (52.9)
378 (47.1)
564 (64.7)
308 (35.3)
Household wealth index
<0.000
<0.000
Poorest
270 (65.9)
139 (34.1)
377 (78.3)
105 (21.7)
Poor
263 (53.8)
225 (46.2)
289 (66.7)
145 (33.3)
Middle
277 (55.2)
225 (44.8)
329 (64.2)
183 (35.8)
Rich
237 (48.6)
251 (51.4)
265 (62.7)
158 (37.3)
Richest
172 (40.0)
259 (60.0)
263 (50.6)
256 (49.4)
Refrigerator ownership
<0.000
<0.000
No
334 (61.6)
209 (38.4)
900 (69.2)
401 (30.8)
Yes
885 (49.9)
890 (50.1)
623 (58.3)
446 (41.7)
Child factors
Child’s age (mo)
<0.000
<0.000
6–11
527 (67.0)
259 (33.0)
597 (77.8)
170 (22.2)
12–17
386 (48.1)
417 (51.9)
492 (57.3)
367 (42.7)
18–23
306 (42.0)
423 (58.0)
434 (58.4)
310 (41.6)
Child’s gender
0.296
0.266
Boy
645 (53.8)
554 (46.2)
774 (62.9)
458 (37.1)
Girl
574 (51.3)
545 (48.7)
749 (65.8)
389 (34.2)
Mother’s factors
Wanted pregnancy
0.950
0.623
No
227 (52.8)
203 (47.2)
201 (66.0)
104 (34.0)
Yes
992 (52.6)
896 (47.4)
1,322 (64.0)
743 (36.0)
Antenatal care visits
0.959
<0.000
Never
14 (55.4)
12 (44.6)
73 (87.1)
11 (12.9)
<4 times
56 (52.7)
50 (47.2)
138 (77.6)
40 (22.4)
≥4 times
1,149 (52.6)
1,037 (47.4)
1,312 (62.3)
796 (37.7)
Mother’s age (y)
0.371
0.526
15–34
872 (51.9)
808 (48.1)
1,158 (63.9)
656 (36.1)
35–54
347 (54.4)
291 (45.6)
365 (65.7)
191 (34.3)
Mother’s education
<0.000
<0.000
Less than high school
219 (62.4)
132 (37.6)
555 (73.1)
205 (26.9)
High school or above
1,000 (50.8)
967 (49.2)
968 (60.1)
642 (39.9)
Mother’s working status
<0.000
<0.000
Not working
710 (57.5)
526 (42.5)
898 (65.7)
468 (34.3)
Informal
389 (49.4)
400 (50.6)
524 (65.8)
273 (34.2)
Formal
120 (40.9)
173 (59.1)
101 (48.9)
106 (51.1)
Mother’s media access
0.737
<0.000
No
127 (51.4)
120 (48.6)
297 (74.1)
104 (25.9)
Yes
1,092 (52.7)
979 (47.3)
1,226 (62.3)
743 (37.7)
Mother participation in household decision
0.764
0.014
No
137 (53.6)
119 (46.4)
196 (73.7)
70 (26.3)
Yes
1,082 (52.5)
980 (47.5)
1,327 (63.1)
777 (36.9)
Living with husband
0.004
0.201
No
127 (64.1)
72 (35.9)
139 (59.2)
96 (40.8)
Yes
1,092 (51.5)
1,027 (48.5)
1,384 (64.8)
751 (35.2)
Father’s factors
Father’s age (y)
0.021
0.116
≥35
592 (55.6)
473 (44.4)
712 (66.5)
359 (33.5)
<35
627 (50.0)
626 (50.0)
811 (62.4)
488 (37.6)
Father’s education
0.007
<0.000
Less than high school
231 (59.9)
155 (40.1)
634 (72.4)
242 (27.6)
High school or above
988 (51.1)
944 (48.9)
889 (59.5)
605 (40.5)
Father’s working status
0.169
0.107
Not working
7 (63.6)
4 (36.4)
9 (60.4)
6 (39.6)
Informal
1,083 (53.3)
948 (46.7)
1,437 (64.9)
777 (35.1)
Formal
129 (46.7)
147 (53.3)
77 (54.6)
64 (45.4)
Values are presented as number of participants or number (%). Statistical test with binary logistic regression, significant level P-value<0.05.
MAD, minimum acceptable diet.
Table 3.
Multivariate analysis on the variables related to household, child, and parents and MAD status in urban and rural areas
Characteristic
Urban (N=2,318)
Rural (N=2,370)
AOR (95% CI)
P-value
AOR (95% CI)
P-value
No. of toddlers in the household
>1
1 (Ref)
1 (Ref)
1
1.03 (0.84–1.27)
0.751
1.09 (0.86–1.39)
0.476
Household wealth index
Poorest
1 (Ref)
1 (Ref)
Poor
1.69 (1.19–2.41)
0.004
1.49 (1.04–2.13)
0.030
Middle
1.44 (0.99–1.08)
0.056
1.59 (1.13–2.25)
0.009
Rich
1.80 (1.22–2.64)
0.003
1.73 (1.11–2.71)
0.016
Richest
2.60 (1.65–4.10)
<0.000
2.60 (1.61–4.19)
<0.000
Refrigerator ownership
No
1 (Ref)
1 (Ref)
Yes
1.10 (0.83–1.44)
0.508
0.93 (0.69–1.25)
0.632
Child’s age (mo)
6–11
1 (Ref)
1 (Ref)
12–17
2.44 (1.88–3.18)
<0.000
2.90 (2.18–3.86)
<0.000
18–23
3.02 (2.32–3.94)
<0.000
2.78 (2.04–3.78)
<0.000
Mother’s education
Less than high school
1 (Ref)
1 (Ref)
High school or above
1.21 (0.89–1.63)
0.223
1.24 (0.91–1.67)
0.167
Mother’s working status
Not working
1 (Ref)
1 (Ref)
Informal
1.35 (1.05–1.72)
0.016
1.00 (0.77–1.30)
0.992
Formal
1.62 (1.20–2.20)
0.002
1.46 (1.01–2.13)
0.049
Mother’s media access
No
1 (Ref)
1 (Ref)
Yes
0.89 (0.64–1.23)
0.466
1.21 (0.89–1.65)
0.232
Mother participation in household decision
No
1 (Ref)
1 (Ref)
Yes
0.99 (0.73–1.35)
0.965
1.58 (1.04–2.39)
0.033
Living with husband
No
1 (Ref)
1 (Ref)
Yes
1.71 (1.18–2.47)
0.005
0.76 (0.52–1.11)
0.157
Antenatal care visits
Never
1 (Ref)
1 (Ref)
<4 times
0.95 (0.39–2.30)
0.900
1.40 (0.64–3.06)
0.397
≥4 times
0.73 (0.33–1.61)
0.436
2.54 (1.30–4.98)
0.007
Father’s age (y)
≥35
1 (Ref)
1 (Ref)
<35
1.42 (1.15–1.74)
0.001
1.25 (1.01–1.58)
0.049
Father’s education
Less than high school
1 (Ref)
1 (Ref)
High school or above
1.01 (0.75–1.37)
0.932
1.24 (0.95–1.62)
0.121
Adjusted for number of toddlers in the household (1 or more than one), household wealth index (poorest, poor, middle, rich, richest), refrigerator ownership (yes or no), child’s age (6–11, 12–17, 18–23 months), mother’s education (less than high school, high school or above), mother’s working status (not working, informal, formal), mother’s access to media (yes or no), mother’s participation in the household decision (yes or no), living with husband (yes or no), antenatal care visits (never, less than 4, 4 or more times), father’s age (35 or more, less than 35 years), and father’s education (less than high school, high school or above). Statistical test with multiple logistic regression, significant level P-value <0.05.
4. Bhutta ZA, Das JK, Rizvi A, Gaffey MF, Walker N, Horton S, et al. Evidence-based interventions for improvement of maternal and child nutrition: what can be done and at what cost? Lancet 2013;382:452-77.
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6. The Food and Agriculture Organization of the United Nations. Indonesia: food and nutrition security profiles [Internet]. Rome: The Food and Agriculture Organization of the United Nations; 2014 [cited 2024 Jan 20]. Available from: https://www.fao.org/3/at707e/at707e.pdf
7. Zebadia E, Mahmudiono T, Atmaka DR, Dewi M, Helmyati S, Yuniar CT. Factors associated with minimum acceptable diet in 6–11-month-old Indonesian children using the 2017 IDHS. Open Access Maced J Med Sci 2021;9(E):1403-12.
8. Yunitasari E, Al Faisal AH, Efendi F, Kusumaningrum T, Yunita FC, Chong MC. Factors associated with complementary feeding practices among children aged 6-23 months in Indonesia. BMC Pediatr 2022;22:727.
11. Putra MG, Dewi M, Kustiyah L, Mahmudiono T, Yuniar CT, Helmyati S. Factors affecting the minimum acceptable diet (MAD) for children aged 6-23 months in Indonesia. AcTion Aceh Nutr J 2022;7:156-68.
12. Birie B, Kassa A, Kebede E, Terefe B. Minimum acceptable diet practice and its associated factors among children aged 6-23months in rural communities of Goncha district, north West Ethiopia. BMC Nutr 2021;7:40.
14. Roshita A, Schubert E, Whittaker M. Child-care and feeding practices of urban middle class working and non-working Indonesian mothers: a qualitative study of the socio-economic and cultural environment. Matern Child Nutr 2012;8:299-314.
15. Tassew AA, Tekle DY, Belachew AB, Adhena BM. Factors affecting feeding 6-23 months age children according to minimum acceptable diet in Ethiopia: a multilevel analysis of the Ethiopian Demographic Health Survey. PLoS One 2019;14:e0203098.
16. Fadlina A, Februhartanty J, Bardosono S. Maternal attributes and child minimum acceptable diet during COVID-19 pandemic in Indonesia. Indones J Hum Nutr 2021;8:108-19.
18. Ng CS, Dibley MJ, Agho KE. Complementary feeding indicators and determinants of poor feeding practices in Indonesia: a secondary analysis of 2007 Demographic and Health Survey data. Public Health Nutr 2012;15:827-39.
19. Belay DG, Taddese AA, Gelaye KA. Minimum acceptable diet intake and its associated factors among children age at 6-23months in subSaharan Africa: a multilevel analysis of the sub-Saharan Africa demographic and health survey. BMC Public Health 2022;22:684.
20. Likhar A, Patil MS. Importance of maternal nutrition in the first 1,000 days of life and its effects on child development: a narrative review. Cureus 2022;14:e30083.
22. Nguyen PH, Avula R, Ruel MT, Saha KK, Ali D, Tran LM, et al. Maternal and child dietary diversity are associated in Bangladesh, Vietnam, and Ethiopia. J Nutr 2013;143:1176-83.
23. Molla A, Egata G, Getacher L, Kebede B, Sayih A, Arega M, et al. Minimum acceptable diet and associated factors among infants and young children aged 6-23 months in Amhara region, Central Ethiopia: community-based cross-sectional study. BMJ Open 2021;11:e044284.
26. Khan JR, Awan N, Sheikh MT. A multilevel and spatial analysis of the infant and young child feeding practices and associated factors among the under-2 aged children in Bangladesh. Child Care Pract 2022;28:178-95.
27. Komakech JJ, Emerson SR, Cole KL, Walters CN, Rakotomanana H, Kabahenda MK, et al. A peer-led integrated nutrition education intervention through care groups improved complementary feeding of infants in postemergency settlements in the West-Nile region in Uganda: a cluster randomized trial. Curr Dev Nutr 2023;7:100042.
28. Saaka M, Awini S, Kizito F, Hoeschle-Zeledon I. Fathers’ level of involvement in childcare activities and its association with the diet quality of children in Northern Ghana. Public Health Nutr 2022;26:1-8.
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Factors for Minimum Acceptable Diet Practice among 6–23-Month-Old Children in Rural and Urban Areas of Indonesia
Figure. 1. Selection of participants.
Figure. 1.
Factors for Minimum Acceptable Diet Practice among 6–23-Month-Old Children in Rural and Urban Areas of Indonesia
Characteristic
Urban
Rural
No. of participants
2,318
2,370
Child factors
Meet minimum acceptable diet
No
1,219 (52.6)
1,523 (64.3)
Yes
1,099 (47.4)
847 (35.7)
Child’s age (mo)
6–11
787 (34.0)
767 (32.3)
12–17
802 (34.6)
859 (36.3)
18–23
729 (31.4)
744 (31.4)
Child’s gender
Boy
1,199 (51.7)
1,232 (52.0)
Girl
1,119 (48.3)
1,138 (48.0)
Household factors
No. of toddlers in the household
>1
749 (32.3)
661 (27.9)
1
1,569 (67.7)
1,709 (72.1)
No. of household members
>4
1,517 (65.5)
1,498 (63.2)
2–4
801 (34.5)
872 (36.8)
Household wealth index
Poorest
409 (17.7)
482 (20.3)
Poor
488 (21.1)
434 (18.3)
Middle
502 (21.6)
512 (21.6)
Rich
488 (21.0)
423 (17.9)
Richest
431 (18.6)
519 (21.9)
Refrigerator ownership
No
543 (23.4)
1,301 (54.9)
Yes
1,775 (76.6)
1,069 (45.1)
Mother’s factors
Wanted pregnancy
No
430 (18.6)
306 (12.9)
Yes
1,888 (81.4)
2,064 (87.1)
Antenatal care visits
Never
26 (1.1)
84 (3.5)
<4 times
107 (4.6)
178 (7.5)
≥4 times
2,185 (94.3)
2,108 (89.0)
Mother’s age (y)
15–34
1,680 (72.5)
1,813 (76.5)
35–54
638 (27.5)
557 (23.5)
Mother’s education
Less than high school
351 (15.2)
760 (32.1)
High school or above
1,967 (84.8)
1,610 (67.9)
Mother’s working status
Not working
1,236 (53.3)
1,366 (57.7)
Informal
789 (34.1)
797 (33.6)
Formal
293 (12.6)
207 (8.7)
Mother’s media access
No
247 (10.7)
402 (16.9)
Yes
2,071 (89.3)
1,968 (83.1)
Mother participation in household decision
No
255 (11.0)
267 (11.2)
Yes
2,063 (89.0)
2,103 (88.8)
Living with husband
No
199 (8.6)
235 (9.9)
Yes
2,119 (91.4)
2,135 (90.1)
Father’s factors
Father’s age (y)
≥35
1,065 (46.0)
1,071 (45.2)
<35
1,253 (54.0)
1,299 (54.8)
Father’s education
Less than high school
386 (16.6)
876 (37.0)
High school or above
1,932 (83.4)
1,494 (63.0)
Father’s working status
Not working
12 (0.5)
15 (0.7)
Informal
2,030 (87.6)
2,214 (93.4)
Formal
276 (11.9)
141 (5.9)
Characteristic
Urban
Rural
Unmeet MAD
Meet MAD
P-value
Unmeet MAD
Meet MAD
P-value
No. of participants
1,219
1,099
1,523
847
Household factors
No. of toddlers
0.396
0.021
>1
404 (54.0)
345 (46.0)
454 (68.7)
207 (31.3)
1
815 (51.9)
754 (48.1)
1,069 (62.6)
640 (37.4)
No. of household members
0.881
0.800
>4
796 (52.4)
721 (47.6)
959 (64.1)
539 (35.9)
2–4
423 (52.9)
378 (47.1)
564 (64.7)
308 (35.3)
Household wealth index
<0.000
<0.000
Poorest
270 (65.9)
139 (34.1)
377 (78.3)
105 (21.7)
Poor
263 (53.8)
225 (46.2)
289 (66.7)
145 (33.3)
Middle
277 (55.2)
225 (44.8)
329 (64.2)
183 (35.8)
Rich
237 (48.6)
251 (51.4)
265 (62.7)
158 (37.3)
Richest
172 (40.0)
259 (60.0)
263 (50.6)
256 (49.4)
Refrigerator ownership
<0.000
<0.000
No
334 (61.6)
209 (38.4)
900 (69.2)
401 (30.8)
Yes
885 (49.9)
890 (50.1)
623 (58.3)
446 (41.7)
Child factors
Child’s age (mo)
<0.000
<0.000
6–11
527 (67.0)
259 (33.0)
597 (77.8)
170 (22.2)
12–17
386 (48.1)
417 (51.9)
492 (57.3)
367 (42.7)
18–23
306 (42.0)
423 (58.0)
434 (58.4)
310 (41.6)
Child’s gender
0.296
0.266
Boy
645 (53.8)
554 (46.2)
774 (62.9)
458 (37.1)
Girl
574 (51.3)
545 (48.7)
749 (65.8)
389 (34.2)
Mother’s factors
Wanted pregnancy
0.950
0.623
No
227 (52.8)
203 (47.2)
201 (66.0)
104 (34.0)
Yes
992 (52.6)
896 (47.4)
1,322 (64.0)
743 (36.0)
Antenatal care visits
0.959
<0.000
Never
14 (55.4)
12 (44.6)
73 (87.1)
11 (12.9)
<4 times
56 (52.7)
50 (47.2)
138 (77.6)
40 (22.4)
≥4 times
1,149 (52.6)
1,037 (47.4)
1,312 (62.3)
796 (37.7)
Mother’s age (y)
0.371
0.526
15–34
872 (51.9)
808 (48.1)
1,158 (63.9)
656 (36.1)
35–54
347 (54.4)
291 (45.6)
365 (65.7)
191 (34.3)
Mother’s education
<0.000
<0.000
Less than high school
219 (62.4)
132 (37.6)
555 (73.1)
205 (26.9)
High school or above
1,000 (50.8)
967 (49.2)
968 (60.1)
642 (39.9)
Mother’s working status
<0.000
<0.000
Not working
710 (57.5)
526 (42.5)
898 (65.7)
468 (34.3)
Informal
389 (49.4)
400 (50.6)
524 (65.8)
273 (34.2)
Formal
120 (40.9)
173 (59.1)
101 (48.9)
106 (51.1)
Mother’s media access
0.737
<0.000
No
127 (51.4)
120 (48.6)
297 (74.1)
104 (25.9)
Yes
1,092 (52.7)
979 (47.3)
1,226 (62.3)
743 (37.7)
Mother participation in household decision
0.764
0.014
No
137 (53.6)
119 (46.4)
196 (73.7)
70 (26.3)
Yes
1,082 (52.5)
980 (47.5)
1,327 (63.1)
777 (36.9)
Living with husband
0.004
0.201
No
127 (64.1)
72 (35.9)
139 (59.2)
96 (40.8)
Yes
1,092 (51.5)
1,027 (48.5)
1,384 (64.8)
751 (35.2)
Father’s factors
Father’s age (y)
0.021
0.116
≥35
592 (55.6)
473 (44.4)
712 (66.5)
359 (33.5)
<35
627 (50.0)
626 (50.0)
811 (62.4)
488 (37.6)
Father’s education
0.007
<0.000
Less than high school
231 (59.9)
155 (40.1)
634 (72.4)
242 (27.6)
High school or above
988 (51.1)
944 (48.9)
889 (59.5)
605 (40.5)
Father’s working status
0.169
0.107
Not working
7 (63.6)
4 (36.4)
9 (60.4)
6 (39.6)
Informal
1,083 (53.3)
948 (46.7)
1,437 (64.9)
777 (35.1)
Formal
129 (46.7)
147 (53.3)
77 (54.6)
64 (45.4)
Characteristic
Urban (N=2,318)
Rural (N=2,370)
AOR (95% CI)
P-value
AOR (95% CI)
P-value
No. of toddlers in the household
>1
1 (Ref)
1 (Ref)
1
1.03 (0.84–1.27)
0.751
1.09 (0.86–1.39)
0.476
Household wealth index
Poorest
1 (Ref)
1 (Ref)
Poor
1.69 (1.19–2.41)
0.004
1.49 (1.04–2.13)
0.030
Middle
1.44 (0.99–1.08)
0.056
1.59 (1.13–2.25)
0.009
Rich
1.80 (1.22–2.64)
0.003
1.73 (1.11–2.71)
0.016
Richest
2.60 (1.65–4.10)
<0.000
2.60 (1.61–4.19)
<0.000
Refrigerator ownership
No
1 (Ref)
1 (Ref)
Yes
1.10 (0.83–1.44)
0.508
0.93 (0.69–1.25)
0.632
Child’s age (mo)
6–11
1 (Ref)
1 (Ref)
12–17
2.44 (1.88–3.18)
<0.000
2.90 (2.18–3.86)
<0.000
18–23
3.02 (2.32–3.94)
<0.000
2.78 (2.04–3.78)
<0.000
Mother’s education
Less than high school
1 (Ref)
1 (Ref)
High school or above
1.21 (0.89–1.63)
0.223
1.24 (0.91–1.67)
0.167
Mother’s working status
Not working
1 (Ref)
1 (Ref)
Informal
1.35 (1.05–1.72)
0.016
1.00 (0.77–1.30)
0.992
Formal
1.62 (1.20–2.20)
0.002
1.46 (1.01–2.13)
0.049
Mother’s media access
No
1 (Ref)
1 (Ref)
Yes
0.89 (0.64–1.23)
0.466
1.21 (0.89–1.65)
0.232
Mother participation in household decision
No
1 (Ref)
1 (Ref)
Yes
0.99 (0.73–1.35)
0.965
1.58 (1.04–2.39)
0.033
Living with husband
No
1 (Ref)
1 (Ref)
Yes
1.71 (1.18–2.47)
0.005
0.76 (0.52–1.11)
0.157
Antenatal care visits
Never
1 (Ref)
1 (Ref)
<4 times
0.95 (0.39–2.30)
0.900
1.40 (0.64–3.06)
0.397
≥4 times
0.73 (0.33–1.61)
0.436
2.54 (1.30–4.98)
0.007
Father’s age (y)
≥35
1 (Ref)
1 (Ref)
<35
1.42 (1.15–1.74)
0.001
1.25 (1.01–1.58)
0.049
Father’s education
Less than high school
1 (Ref)
1 (Ref)
High school or above
1.01 (0.75–1.37)
0.932
1.24 (0.95–1.62)
0.121
Table 1. Frequency distribution of characteristics of the household, child, and parents based on urban and rural areas
Values are presented as number of participants or number (%).
Table 2. Frequency distribution of respondents based on the characteristics of household, child, and parents and MAD status in urban and rural areas
Values are presented as number of participants or number (%). Statistical test with binary logistic regression, significant level P-value<0.05.
MAD, minimum acceptable diet.
Table 3. Multivariate analysis on the variables related to household, child, and parents and MAD status in urban and rural areas
Adjusted for number of toddlers in the household (1 or more than one), household wealth index (poorest, poor, middle, rich, richest), refrigerator ownership (yes or no), child’s age (6–11, 12–17, 18–23 months), mother’s education (less than high school, high school or above), mother’s working status (not working, informal, formal), mother’s access to media (yes or no), mother’s participation in the household decision (yes or no), living with husband (yes or no), antenatal care visits (never, less than 4, 4 or more times), father’s age (35 or more, less than 35 years), and father’s education (less than high school, high school or above). Statistical test with multiple logistic regression, significant level P-value <0.05.
, Rika Rachmalina
