Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA.
J Glob Health. 2022 Nov 23;12:04064. doi: 10.7189/jogh.12.04064.
There is a scarcity of research that comprehensively examines programme impact from a context-specific perspective. We aimed to determine the conditions under which the Bihar Technical Support Programme led to more favourable outcomes for maternal and child health in Bihar.
We obtained block-level data on maternal and child health indicators during the state-wide scale-up of the pilot Ananya programme and data on health facility readiness, along with geographical and sociodemographic variables. We examined the associations of these factors with increases in the levels of indicators using multilevel logistic regression, and the associations with rates of change in the indicators using Bayesian Hierarchical modelling.
Frontline worker (FLW) visits between 2014-2017 were more likely to increase in blocks with better night lighting (odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.01-1.51). Birth preparedness increased in blocks with increasing FLW visits (OR = 3.43, 95% CI = 1.15-10.21), while dry cord care practice increased in blocks where satisfaction with FLW visits was increasing (OR = 1.52, 95% CI = 1.10-2.11). Age-appropriate frequency of complementary feeding increased in blocks with higher development index (OR = 1.55, 95% CI = 1.16-2.06) and a higher percentage of scheduled caste or tribe (OR = 3.21, 95% CI = 1.13-9.09). An increase in most outcomes was more likely in areas with lower baseline levels.
Contextual factors (eg, night lighting and development) not targeted by the programme and FLW visits were associated with favourable programme outcomes. Intervention design, including intervention selection for a particular geography, should be modified to fit the local context in the short term. Expanding collaborations beyond the health sector to influence modifiable contextual factors in the long term can result in a higher magnitude and more sustainable impact.
ClinicalTrials.gov: NCT02726230.
从特定背景角度全面考察方案影响的研究很少。我们旨在确定比哈尔邦技术支持方案在比哈尔邦导致孕产妇和儿童健康更有利结果的条件。
我们获得了在试点 Ananya 方案全州范围内扩大规模期间母婴健康指标的区块级数据,以及卫生机构准备情况数据以及地理和社会人口变量数据。我们使用多层逻辑回归检查了这些因素与指标水平增加的关联,并使用贝叶斯层次模型检查了这些因素与指标变化率的关联。
2014 年至 2017 年间,一线工作者(FLW)访问量更有可能增加,且区块夜间照明条件更好(比值比(OR)=1.23,95%置信区间(CI)=1.01-1.51)。在 FLW 访问量增加的区块中,生育准备度增加(OR=3.43,95%CI=1.15-10.21),而在 FLW 访问满意度增加的区块中,干脐带护理实践增加(OR=1.52,95%CI=1.10-2.11)。在发展指数较高(OR=1.55,95%CI=1.16-2.06)和较高比例在册种姓或部落(OR=3.21,95%CI=1.13-9.09)的区块中,适宜年龄的补充喂养频率增加。
方案未针对的背景因素(例如夜间照明和发展)和 FLW 访问量与有利的方案结果相关。干预设计,包括针对特定地理位置的干预措施选择,应在短期内根据当地情况进行调整。从长远来看,扩大卫生部门以外的合作以影响可改变的背景因素可以产生更大的规模和更可持续的影响。
ClinicalTrials.gov:NCT02726230。