The relationship between exposure to green spaces during pregnancy and low birth weight (LBW) remains understudied, particularly in low- and middle-income countries (LMICs). LBW is a significant global health concern, with approximately 90% of cases occurring in LMICs. Existing research on the greenness-LBW association is limited by a lack of large-scale studies in LMICs, insufficient national-level data, and an absence of quantitative analyses estimating the potential impact of green space improvements on LBW reduction. This study addresses these gaps by examining a nationwide cohort in Iran to establish the association between prenatal greenness exposure and LBW risk, and to quantify the potential reduction in LBW burden achievable through targeted greenspace improvements. Understanding this relationship is crucial for informing public health policies aimed at achieving the Global Nutrition Targets 2025, which aim to reduce LBW cases by 30% by 2025. The study posits that increased vegetation density could play a significant role in mitigating the LBW burden in LMICs, thereby improving maternal and child health outcomes.

Existing literature links greenness to various health benefits, including reduced mortality, improved cognitive function, and positive birth outcomes. While some population-based studies have examined the association between greenness and birth outcomes, the evidence regarding LBW is inconsistent. A major research gap is the scarcity of studies conducted in LMICs, where the majority of LBW cases occur. Most existing studies are from high-income countries (HICs), thus limiting generalizability. Furthermore, there is a lack of large-scale national studies using extensive birth records to provide robust, nationally representative evidence that would be useful for policy-making. Finally, prior research has not quantified the potential impact of increasing green space on LBW reduction in LMICs, making it difficult to assess the effectiveness of such interventions in achieving the Global Nutrition Targets 2025.

This nationwide retrospective cohort study used birth records from 2013 to 2018 covering 31 provinces in Iran, encompassing approximately 4 million mother-infant pairs. The primary outcome was LBW, defined as birth weight below 2500 grams regardless of gestational age (GA). A secondary outcome was term low birth weight (TLBW), defined as birth weight below 2500 grams with GA ≥37 weeks. Greenness exposure during pregnancy was assessed using satellite-based normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) at various buffer distances (500m, 1000m, 2000m, and 3000m) around the delivery hospitals. Multiple logistic regression models were employed to assess the association between greenness and LBW/TLBW, adjusting for maternal demographic characteristics (age, education, residence, parity, etc.), fetal variables (sex, season of birth, GA), and environmental factors (temperature, humidity, PM2.5). Counterfactual analyses were conducted to estimate the potential reduction in LBW and TLBW cases attributable to achieving specific greenness targets. The analysis incorporated restricted cubic splines to account for potential non-linear relationships between greenness and birth outcomes. Subgroup analyses were performed to explore potential effect modification by maternal age, education, and residence. Sensitivity analyses were conducted to assess the robustness of the findings by excluding records with extreme birth weights, multiple gestations, or excluding mothers with specific characteristics (age, pre-existing conditions).

The study included 4,021,741 live births after excluding ineligible records (stillbirths, neonatal deaths, etc.). Of these, 263,728 (6.6%) were LBW and 121,852 (3.0%) were TLBW. Mothers of LBW/TLBW infants consistently experienced lower greenness exposure compared to mothers of normal birth weight infants across all buffer distances. Logistic regression analyses showed consistent decreases in the risk of LBW and TLBW associated with increased greenness, even after adjusting for various confounding factors. Specifically, a 0.1-unit increase in NDVI/EVI was associated with an approximate 7-11.5% reduction in LBW odds, depending on the buffer distance. Analyses revealed approximately L-shaped exposure-response curves, suggesting greater benefit from greenness improvements at lower levels of existing greenness. Subgroup analyses indicated stronger associations between greenness and LBW/TLBW among younger, less educated, and village-dwelling mothers. Counterfactual analyses estimated that achieving mean NDVI/EVI levels could prevent 3931–5099 LBW births (4.4–5.6% of total LBW births) in 2015.

The findings of this large-scale, nationally representative study in Iran provide robust evidence supporting the association between increased prenatal greenness exposure and a reduced risk of LBW. The observed L-shaped exposure-response relationship suggests that the benefits of green space are particularly pronounced in areas with relatively low levels of existing greenness. The larger reductions in LBW risk observed among younger, less educated, and village-dwelling mothers suggest that improvements in greenspace could help reduce health inequalities. The quantitative estimations of avoidable LBW cases highlight the potential public health impact of strategic greenspace interventions. These results are particularly relevant given the high prevalence of LBW in LMICs and the global goal of reducing LBW rates. This study contributes significantly to the existing literature by providing strong evidence from a LMIC setting and offering valuable insights for public health policy.

This study provides compelling national-level evidence from Iran demonstrating a strong association between increased prenatal greenness exposure and reduced LBW risk. The L-shaped exposure-response curve and the identification of vulnerable subgroups underscore the importance of targeted greenspace interventions to improve maternal and child health outcomes, particularly in LMICs. Future research should focus on causal inference to solidify the causal link between greenness and LBW, and to investigate the underlying mechanisms responsible for this association. Further studies across multiple countries using diverse methodologies are necessary to validate these findings and to inform evidence-based policies aimed at reducing LBW globally.

Several limitations of this study should be noted. Individual maternal greenness exposures were assessed based on the location of the delivery hospital, which may not perfectly reflect residential exposure. While using multiple buffer distances mitigates this to some extent, some exposure misclassification may remain. The use of NDVI and EVI, while widely used, may not fully capture the complexity and quality of green spaces. Unmeasured confounding factors, despite adjusting for several covariates, may exist and influence the results. The counterfactual analysis is based on association analysis, and the assumption of causality may introduce some uncertainty into the estimation of avoidable LBW cases. Finally, values representing water bodies were not removed and treated as zero in the assessment of greenness exposures, which could introduce some error.