Understanding the Spatial Predictors of Malnutrition Among 0–2 Years Children in India Using Path Analysis

The study addresses persistent child malnutrition in India, where under-five stunting, wasting, and underweight remain high despite multiple programs. With India ranking 102/117 on the GHI, the research seeks to identify determinants that directly and indirectly affect stunting, wasting, and underweight among children aged 0–24 months, and to map spatial clustering of key predictors (low birth weight, diarrhea, water, sanitation, prenatal care, exclusive breastfeeding). The purpose is to inform targeted, geographically nuanced interventions during the critical first 1,000 days to reduce morbidity, mortality, and long-term developmental and economic impacts associated with malnutrition.

The paper situates its analysis within evidence linking maternal nutrition and BMI to birth outcomes and child nutrition; socioeconomic status and maternal education to dietary diversity, healthcare access, and child growth; and environmental conditions (WASH) to malnutrition. Prior studies note that low maternal education and poorer neighborhoods are associated with adverse birth outcomes, and that antenatal care utilization is influenced by literacy and wealth. Breastfeeding practices vary by maternal education and child sex in South Asia, with potential gender biases. Diarrheal disease is linked to child morbidity and mortality, while improved sanitation and water quality are associated with reduced undernutrition. The authors note gaps in India-specific analyses quantifying direct and indirect pathways to child malnutrition using structural equation modeling alongside spatial clustering of determinants.

Data source: NFHS-4 (2015–16), a nationally representative survey using a two-stage stratified sampling design (villages/rural and census enumeration blocks/urban as PSUs). The analysis covered 28 states and 8 union territories. Sample: 90,842 children aged 0–24 months; for exclusive breastfeeding, last-born children 0–5 months (n=21,151) per DHS guidelines. Outcomes: Stunting, wasting, underweight. Exogenous predictors: Birth weight (low/normal/high), exclusive breastfeeding (yes/no), children ever born (1, 2, 3, 4, 5, >5), prenatal visits (yes/no). Endogenous variables: Diarrhea in last 2 months (yes/no), maternal BMI (low/normal/high), residence (rural/urban), household wealth index (poor/middle/rich), mother’s education (illiterate, 6–8, 9–10, 11–12, >12 years), desired pregnancy timing (then/later/no more). Statistical analysis: Path analysis via structural equation modeling using weighted least squares adjusted for mean and variance. Model fit assessed with chi-square test, CFI, TLI, RMSEA (good fit thresholds: CFI/TLI>0.95 excellent; ≥0.90 acceptable; RMSEA ≤0.05 close fit, ≤0.08 acceptable). Significance at p<0.05. Software: STATA 15.1MP. Spatial analysis: Global Moran’s I to assess spatial autocorrelation; LISA statistics to identify local clusters (hotspots/cold spots). Queen’s first-order contiguity weights. Variables mapped: diarrhea, poor drinking water source, no exclusive breastfeeding, low birth weight, no prenatal visits, poor toilet facility. Software: GeoDa 1.14.

- Sample and model fit: 90,842 children aged 0–24 months; model fit indices CFI=0.980, TLI=0.927, RMSEA=0.036; p-close=1, indicating very good fit. - Direct effects: - Wasting: Exclusive breastfeeding, children ever born, and diarrhea showed significant positive direct effects; higher birth weight, maternal BMI, household wealth, and maternal education showed protective (negative) associations; sex and desired pregnancy had negative direct effects on outcomes as reported by the model. - Underweight: Children ever born and diarrhea had significant positive direct effects; higher birth weight, exclusive breastfeeding, prenatal visits, maternal BMI, maternal education, household wealth, sex of child, and desired pregnancy had significant negative direct effects. - Stunting: Children ever born had a significant positive direct effect; higher birth weight, exclusive breastfeeding, prenatal visits, maternal BMI, maternal education, household wealth, and sex of child had significant negative direct effects; diarrhea, residence, and desired pregnancy had non-significant direct effects. - Indirect effects: - Wasting: Prenatal visits, maternal education, maternal BMI, and household wealth had significant negative indirect effects; sex of child, residence, and desired pregnancy had significant positive indirect effects. - Stunting and underweight: Prenatal visits, sex of child, residence, and desired pregnancy had significant positive indirect effects; maternal BMI, household wealth, and maternal education had significant negative indirect effects. - Total effects: - Stunting: Children ever born positive; birth weight, exclusive breastfeeding, prenatal visits, maternal BMI, sex, household wealth, and maternal education negative; diarrhea and desired pregnancy non-significant. - Wasting: Exclusive breastfeeding, children ever born, diarrhea positive; birth weight, maternal education, maternal BMI, sex, and wealth negative; prenatal visits, residence, and desired pregnancy non-significant. - Underweight: Children ever born and diarrhea positive; birth weight, exclusive breastfeeding, prenatal visits, sex, maternal education, wealth, and maternal BMI negative; residence and desired pregnancy non-significant. - Spatial autocorrelation (Global Moran’s I): Diarrhea 0.446; poor drinking water source 0.638; no exclusive breastfeeding 0.345; low birth weight 0.439; no prenatal visits 0.620; poor toilet facility 0.727, indicating significant clustering. - Hotspots detected: Diarrhea 77; poor drinking water 102; no exclusive breastfeeding 63; low birth weight 88; no prenatal visits 81; poor toilet facility 160. - Geographic patterns: Low exclusive breastfeeding concentrated in Uttar Pradesh; poor toilet facilities in Bihar, Jharkhand, Odisha, Chhattisgarh, Madhya Pradesh; poor water sources in parts of Maharashtra; few prenatal visits in Arunachal Pradesh, Nagaland, Uttar Pradesh; high diarrhea prevalence in Uttar Pradesh; low birth weight prevalent in districts of Madhya Pradesh.

The analysis clarifies pathways through which maternal, household, environmental, and reproductive factors influence malnutrition in early childhood. Strong direct associations of diarrhea and parity with wasting, underweight, and stunting underscore the importance of infection control and family planning/spacing. Protective direct effects of exclusive breastfeeding, higher birth weight, maternal BMI, maternal education, and household wealth align with known mechanisms linking maternal and household resources to child growth. Indirect effects via maternal education, residence, and pregnancy intention highlight social determinants shaping care practices (e.g., ANC utilization, breastfeeding) and exposure to risks. Spatial clustering of key predictors indicates that malnutrition determinants are geographically patterned, justifying geographically targeted interventions (e.g., WASH improvements in hotspot districts, breastfeeding promotion in low-EBF areas, ANC access in northeastern states). Together, these findings support multisectoral strategies during the first 1,000 days addressing nutrition, infection prevention, WASH, maternal education, and equitable healthcare access.

The study identifies diarrhea, exclusive breastfeeding, and number of children ever born as robust direct determinants of stunting, wasting, and underweight among Indian children 0–24 months, with maternal education, residence, and pregnancy intention exerting important indirect effects. Spatial hotspots of adverse predictors (poor water and sanitation, low EBF, low birth weight, low ANC) can guide geographically tailored policy actions. Interventions focused on the first 1,000 days, coupled with multisectoral approaches (nutrition support, WASH, ANC coverage, breastfeeding promotion, and strengthened public distribution systems), and revitalization of programs like POSHAN Abhiyan, are recommended to reduce the burden of malnutrition.

- Use of NFHS-4 may entail data quality issues due to extensive questionnaires. - Cross-sectional design limits causal inference; observed associations in path analysis should not be considered causal and directional relationships may be reversible. - Spatial analysis conducted at district level may introduce ecological fallacy and cannot be generalized to individuals.