Urban-rural disparities in child linear growth
A decomposition analysis of digital, physical, and socioeconomic environments in seven least-developed countries
Bibliographic Data
| ID | 21874751 |
|---|---|
| Authors | Zhixin Liu (0000-0003-3337-0692, Peking University), Liu Z (0000-0002-3950-1350, Peking University), Rizhen Wang (Peking University), Xi Zhang (0009-0004-8281-1030, Peking University), Xiyu Zhang (0009-0001-6001-133X, Peking University), Qunhong Wu (0000-0002-2873-5266, Harbin Medical University) |
| Year | 2026 |
| Volume | 16 |
| Pages | 04158-04158 |
| Publication date | 2026-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Global Health (JOURNAL) |
| Journal identifiers | ISSN: 2047-2978 • E-ISSN: 2047-2986 |
| Publisher | International Society of Global Health (PUBLISHER • GB) |
| DOI | 10.7189/jogh.16.04158 |
| PMID | 42381566 |
| OpenAlex | W7166809714 |
| Language | EN |
| References cited | 42 |
Background: Child linear growth lags behind in rural areas compared to urban areas in least developed countries (LDCs). The extent to which household environments - digital, physical, and socioeconomic - are associated with this urban-rural gap remains unclear. We quantified how these household environments contribute to the urban-rural difference in linear growth among children. Methods: We pooled cross-sectional data from the demographic and health surveys conducted between 2015 and 2024 in seven LDCs. The analysis included children aged 0-59 months. Child linear growth was measured using the height-for-age Z-score (HAZ), computed from standard anthropometric measurements using the World Health Organization Child Growth Standards. We estimated the urban-rural difference in HAZ using hierarchical regression models and decomposed the mean gap into contributions from household digital, physical, and socioeconomic environments using Blinder-Oaxaca decomposition. Results: The pooled sample included 59 219 children (28.0% urban and 72.0% rural). The urban-rural difference in HAZ decreased from -0.29 (95% confidence interval (CI) = -0.32, -0.27) to -0.02 (95% CI = -0.05, 0.01) after adjustment for demographic characteristics and household environments. Blinder-Oaxaca decomposition indicated that over 95% of the pooled urban-rural HAZ gap was explained by measured household characteristics. The largest contributions were from household wealth (richest vs. poorest percentage explained = 38.8%), maternal education (secondary or higher vs. none = 19.6%), digital access (17.4%), and daily maternal Internet use (10.2%). Physical-environment indicators were smaller and less consistent across countries, although improved sanitation contributed positively in the pooled analysis (percentage explained = 10.4%). Conclusions: The urban-rural disparity in child linear growth is largely explained by unequal distributions of socioeconomic, digital, and physical household resources
Anthropometry · Confidence interval · Developing country · Improved sanitation · Linear growth · Linear regression · Multilevel model · Sanitation · Socioeconomic status · Breastfeeding Practices and Influences · Child Nutrition and Water Access · Obesity, Physical Activity, Diet
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| Citation velocity | historical |
|---|---|
| Highly cited | No |