1Mauludyani et al. 2025Cross-sectional study using multilevel linear regression analysisIndonesiaPopulation: 514 districts/cities in Indonesia. Population: children under five years of age (toddlers)Sanitation and drinking water, food security1. At the district level, poverty, food expenditure >65%, lack of access to clean water, and length of schooling for women are significantly positively associated with stunting.2Fatimah et al. 2025Comparative study with cross-sectional designIndonesiaPopulation: Poor households in the urban area of Cianjur Regency. Sample: Total 126 respondents (mothers with children under the age of five (toddlers)Food Security1. Food Security: The majority of households experience food insecurity (92.1% in urban areas and 96.7% in rural areas)3Alristina et al. 2025Cross-sectional study using multilevel linear regression analysisIndonesiaPopulation: All mothers or primary caregivers of children attending Posyandu in Surabaya. Sample:
657 mothers who had at least one child between the ages of 36 and 59 monthsHousehold income, parental education, employment status, food security1. Prematurity: Low maternal education was associated with a 3-fold higher risk of preterm birth (AOR = 3.23; p < 0.001). In addition, prematurity correlates with home ownership.4Manrique-de Hitta et al. 2025Cross-sectional analyticsPhilippinesPopulation: Primary caregivers with infants and young children aged 0–23 months living in the Fourth District of Camarines Sur. Sample: 628 peoplehousehold income, parental education, Sanitation and drinking water, parental employment status, food security1. Stunting factors for infants aged 0–6 months include age (risk decreases), economic status, and non-college maternal education (lower risk), while for children aged 6–24 months, risk increases with age and is higher in males.5Mitra et al. 2025Case-control studyIndonesiaPopulation: All children aged 12–59 months in the Fifty Health Center Working Area, Pekanbaru, Indonesia. Sample: 108 childrenHousehold income, parental education, parenting, parental employment status1. Sociodemographic factors (knowledge, attitudes, and income) are indirectly related to stunting through its influence on parenting (β = 1.33; p < .001) 2. Parenting (practices of feeding, hygiene, sanitation, and health services) has a direct impact on stunting (β = 0.09; p = .049)6Agushybana et al. 2025Cross-sectional study designIndonesiaPopulation: Households in Indonesia that represent 83% of the population in 13 provinces. Sample: 3397 childrenparental education, Sanitation and drinking water, spatial gaps, parents’ employment status, maternal health, spatial gaps1. Key stunting drivers include older child age, low birth weight (LBW), incomplete prenatal care, poor sanitation, and lack of maternal health (KIA) books. Interestingly, in 1997, paternal elementary education was linked to higher stunting rates compared to fathers with no formal schooling.7Khoiruddin et al. 2025Quantitative using binary and multinomial logit regressionIndonesiaPopulation: Children in Indonesia. Sample: 261,673 children aged 5–15 yearsparental education, parental employment status, asset ownership, spatial gap, Smoking culture at home1. Informal work is consistently associated with a higher risk of multidimensional child poverty, especially in rural households 2. Single parent status, large number of children, and smoking increase children’s vulnerability to deprivation 3. There is a real territorial gap, where children in rural areas face a much higher risk of deprivation than in urban areas8Idawati et al. 2024Cross-sectional surveyIndonesiaPopulation: All married women under the age of 19 in rural areas of Aceh Province. Sample: 507 femalesEarly Marriage1. Parental influence is the primary driver of early marriage in Aceh, with a 10.34 times higher risk for women under heavy parental pressure. Economics also play a key role; women from the poorest families are 2.23 times more vulnerable than those from the wealthiest.9Ayu et al. 2024Observational quantitative analytics with case-control designIndonesiaPopulation: All short and very short toddlers living in rural areas in Batu Bara Regency. Sample: 100 households with short and very short toddlers with an age range of 12–59 monthsParental education, Sanitation and drinking water, maternal health, smoking culture at homeResearch identified several major risk factors for stunting: 1. Low maternal education, Birth weight, Formula feeding for less than 6 months, Lack of access to proper drinking water, Poor maternal nutritional status during pregnancy, Low family wealth index.10Seran & Sengkoen 2024Quantitative with descriptive and inferential analysis methods using multiple linear regressionIndonesiaPopulation: Households with children under five in the Belu Regency area, especially in Atambua City and Halilulik Village. Sample: 100 households with children under the age of five (toddlers)Parental Education, Household Income, Parent’s Employment Status1. Nutritional factors contribute the largest to the incidence of stunting (13.41%) 2. Children with low nutritional intake have a 4.913 times greater risk of stunting 3. In addition, low maternal education levels (≤ junior high school) increased the risk of stunting by 8,081 times, and low-income families.11Laksono et al. 2024Secondary data analysis with a cross-sectional study design using the two-stage stratified sampling methodIndonesiaPopulation: All Indonesian children under the age of five (toddlers) living in urban poor communities. Sample: 43,284 childrenParental Education, Parental Employment Status1. Factors that significantly increase the risk of stunting include: low maternal education, unemployed mothers, the poorest poverty rate, no ANC during pregnancy, older children (compared to the 0–11 month group), and male children12Iwo et al. 2024Longitudinal research using data from the Study of the Tsunami Aftermath and Recovery (STAR)IndonesiaPopulation: Individuals and households in 13 districts in Aceh and North Sumatra. Sample: 5,429 childrenParental Education, Post-Disaster 1. Disaster is one of the causes of children’s deprivation13Simaremare et al. 2024Observational studies with a cross-sectional approachIndonesiaPopulation: All households in Indonesia. Sample: 9,243 children aged 0–59 months from 60 disadvantaged areas in IndonesiaSanitation and drinking water1. Multivariate analysis showed that factors significantly related to increased risk of diarrhea were the age of children 12–23 months and 24–35 months, as well as a history of ISPA in the past month.14Fu. et al. 2023Qualitative research using curriculum vitae analysis and thematic analysisCambodiaPopulation: Children living in residential care institutions (RCIs) in Cambodia. Sample: 25 children aged 12 to 17 yearsIncomplete family structure1. Children feel material benefits and educational opportunities at RCI compared to previous difficult conditions 2. Peer support who have “similar sad stories” is an important factor for children’s adaptation15Andrestian et al. 2023Exploratory qualitative investigation with phenomenological methodsIndonesiaPopulation and sample: Youth marriage perpetrators, families, health workers, and related government agencies in South Kalimantan.Parental Education, Parenting, Early Marriage1. Teenage marriage in South Kalimantan is triggered by economic motives, adolescent desires, social pressure, and lack of motivation to complete formal education.16Bustos et al. 2023Cross-sectional study using multilevel linear regression analysisPhilippinesPopulation: Children living in extreme poverty in 10 regional regions of the Philippines. Sample: 2,945 children aged between 6 months and 12 yearsSpatial Gaps1. Enrollment in 4Ps was associated with a lower chance of stunting (adjusted OR = 0.55), although this relationship was influenced by geographic factors of the area of residence17Htet et al. 2023Repeated cross-sectional surveys or panel studiesMyanmarPopulation: Households in rural Chin State (mountainous), Magway Region (plain/dry zone), and Ayeyarwady Region (river delta). Sample: 3,745 childrenParent Education, Sanitation and Drinking Water, Food Security, Maternal Health1. Child age and short maternal height are consistently determinants of stunting in all three regions18Utami et al. 2023Qualitative: empirical legal researchIndonesiaPopulation and sample: children who enter into early marriage.Early Marriage1. Early marriage causes vulnerability to children’s rights, including vulnerability to education, the right to sustainable livelihood, the right to growth and development, and the right to be free from violence.19Um et al. 2023Analysis of secondary data from the cross-sectional population survey (Cambodia Demographic and Health Survey/CDHS)CambodiaPopulation: Children under the age of five in Cambodia. Sample: 29,171 children aged 0–59 monthsParental education, Sanitation and drinking water, parental employment status, smoking culture at home1. ISPA risk increases with child age (6–35 months), maternal smoking, and poor toilet hygiene. Conversely, high maternal education, breastfeeding, top-tier wealth, and more recent survey data correlate with lower risk.20Santri et al. 2023Cross-sectional studyIndonesiaPopulation of families with children under the age of 5 years in Indonesia whose data is recorded in SDKI 2017. Sample: 4,953 households with children under 5 years of ageparental education, Sanitation and drinking water, spatial gaps, smoking culture at home1. Symptoms of ISPA are significantly related to rural residence, high wealth index, frequency of father’s daily smoking, and low level of father’s education.21Tran et al. 2023Longitudinal studies that are a follow-up to a double-blind randomized controlled trialVietnamPopulation: Descendants of women participating in preconception micronutrient supplementation (PRECONCEPT) studies in 20 communes. Sample: 4,186 childrenParent education1. Maternal factors, home environment, and child nutrition mitigate cognitive gaps (7–42%) in early age 2. A high-quality home environment reduces the socio-emotional gap by 43% at the age of 6–722Herliana & Douiri 2017Cross-sectional studyIndonesiaPopulation: Children aged 12–59 months in Indonesia. Sample: 14,401 childrenparental education, Access to health facilities, parental employment status1. There are 13 factors that are significantly related to low immunization coverage, including: living in the Maluku and Papua regions, older children (36–47 months), high birth households, large family sizes, uneducated mothers, and the poorest households.23Suyanto et al. 2023Mixed method approachIndonesiaPopulation: Girls who perform early marriage in the Horseshoe area, East Java. Sample: 300 respondents for quantitative surveys and 30 informants for in-depth interviews.Parental Education, Early Marriage, Patriarchy1. Early marriage is driven by economic and sociocultural factors, including the old virginity stigma for those over 20. Consequently, 57.7% of respondents sacrificed their education. Strong patriarchy persists, burdening wives with domestic labor even during pregnancy and exposing them to domestic violence.24Kharisma et al. 2022This study uses secondary cross-sectional data with the Instrumental Variable (IV) analysis methodIndonesiaPopulation: All children in Indonesia covered by the IFLS-5 survey. Sample: 9,950 observations of children aged 5 to 14 yearsparental education, household income, parental employment status, Incomplete family structure, spatial gap1. Core parental presence (both parents) reduces child labor probability by 0.440 points versus single-mother households. Additional risks include increasing child age, the household head’s employment status, and large family size.25Kang & Kim 2019QuantitativeMyanmarPopulation: 76990 children. Samples: 4217 ages 0–59 monthsParents’ employment status, maternal health1. Stunting is related to: age and gender in children, nutritional status in mothers, access to care facilities, mother’s work, mother’s health status, 26Ulep & Casas 2022Cross-sectional studies using linear probability model (LPM) and Oaxaca-Blinder decomposition methodPhilippinesPopulation: All children aged 0–60 months in the Philippines covered in the national survey. Sample: 1,881 childrenParent education, Sanitation and drinking water, food security, maternal health1. Maternal factors (height, education, and BMI) account for more than 50% of the total gap. 2. Specifically, maternal height contributes 26%, maternal education 18%, maternal BMI 17%, quality of prenatal care 12%, dietary diversity 12%, and child iron supplementation 5% to stunting inequality.27Yunitasari et al. 2022Mixed methodsIndonesiaPopulation: Mothers involved in Maternal and Child Nutrition Security projects in rural areas. Sample: 152 mothers with children aged 0–23 monthsParental education, Sanitation and drinking water, access to health facilities, smoking culture at home1. Stunting drivers include male gender, older age, poverty, and poor ANC access. Critical contributors involve sanitation–water synergy, genetic misconceptions, condensed milk misuse, and cigarette spending prioritized over nutrition.28Blankenship et al. 2020Secondary data analysis using nationally representative data from the Demographic and Health Survey (DHS)MyanmarPopulation: Children under the age of 5 in Myanmar. Sample: 3,981 childrenSanitation and drinking water, parental employment status, maternal health, spatial disparities1. Stunting is driven by short maternal stature (<145 cm), perceived small birth size, non-clinical delivery, maternal employment, unsafe water, specific topography (delta/coastal/highlands), and poverty. Wasting stems from maternal underweight, open defecation, maternal work, and coastal residency.29Karpati et al. 2020Secondary analysis of national survey data using the Multiple Overlapping Deprivation Analysis (MODA) methodologyCambodiaPopulation: Children in Cambodia. Sample: 7,906 children under five years old (0–59 months)Parental education, Sanitation and drinking water, maternal health, spatial gaps1. Children who do not experience deprivation in three or more dimensions have a significant reduction in the probability of stunting. 2. Other significant risk factors include the mother’s height < 145 cm, being in the two lowest quintiles of wealth, and the child’s increasing age30Boulom et al. 2020Cross-sectional surveyLaosPopulation: All residents in 23 villages in Nong District are isolated and difficult to access. Sample: 173 households with a father, mother, and at least one child aged 12–47 monthsHousehold income, asset ownership, food security1. Factors that are significantly positively related to nutritional status include asset ownership (mobile phones or electric rice mills), collection of non-timber forest products (insects/ant eggs), and diversity of household diets. 2. As many as 90% of households experience food insecurity.31Sandra et al. 2020Quantitative research using the Ordinary Least Square (OLS) multiple regression analysis methodIndonesiaPopulation: All districts and cities in 34 provinces in Indonesia. Sample: 301 districts/cities in Indonesia, with a focus on children aged 11–17 yearsParent Education1. Educational participation has a negative and significant effect on child labor; The higher the child’s attendance at school, the lower their time to work32Adam & Salim 2018This study uses a survey design with a cross-sectional study approachIndonesiaPopulation: All students at SDN Salulayang, Mamuju District. Sample: 90 childrenHousehold income, parental education1. There was a significant relationship between maternal education level (p = 0.005) and parental income (p = 0.006) and stunting incidence. 2. Higher levels of education facilitate access to nutritional information, while adequate income allows families to obtain optimal nutritional intake33Minh et al. 2016Cross-sectional designVietnamPopulation: 11,663 Women in Vietnam. Sample: 1,383 women who had live births in the last two yearsParental education, Sanitation and drinking water, spatial gaps1. Stunting barriers are disproportionately high in poor rural ethnic minorities (38% vs. <1% wealthy urban). Low education and inadequate facilities significantly restrict access to professional birth attendants and ANC, directly increasing child mortality risks.34Bima et al. 2022Qualitative approach with cross-sectional study designIndonesiaPopulation: Children living in poor households in urban areas in Indonesia. Sample: Children aged 6–17 years old as main participants in six urban villages in three cities (North Jakarta, Makassar, and Surakarta)Parental Education, Identity1. Poor children in the city experience the impact of their parents’ economic difficulties. 2. In addition, it was found that 37% of poor children in urban areas do not have birth certificates, which hinders their access to various government assistance programs.35Tantan & Astuti 2021Quantitative research using the Multiple Overlapping Deprivation Analysis (MODA) frameworkIndonesiaPopulation: Children living in the Jakarta Metropolitan Area (JMA) which includes the DKI Jakarta area, part of West Java, and part of Banten. Sample: Children aged 0–17 years oldFood Security1. The Health and Food and Nutrition dimensions have the highest level of deprivation, where about 1 in 2 children experience it36Dat et al. 2015Longitudinal analysis using Young Lives survey data with an empirical approach of logit ordered regression model (cross-sectional) and fixed-effects model (panel)VietnamPopulation: Children in Vietnam. Sample: includes children aged 11–12 years in Round 2 and 14–15 years old.Sanitation and drinking water, parents’ employment status1. Children tend to prioritize deprivation that has a direct impact on their well-being, such as shelter and water and sanitation, over long-term deprivation such as children’s health and employment.