Kinyoki Damaris K, Berkley James A, Moloney Grainne M, Odundo Elijah O, Kandala Ngianga-Bakwin, Noor Abdisalan M
INFORM Project, Spatial Health Metrics Group, Kenya Medical Research Institute/Wellcome Trust Research Programme, Nairobi, Kenya.
Kenya Medical Research Institute/Wellcome Trust Research Programme, Centre for Geographic Medicine Research (coast), Kilifi, Kenya.
BMC Public Health. 2016 Jul 28;16:654. doi: 10.1186/s12889-016-3320-6.
Stunting among children under five years old is associated with long-term effects on cognitive development, school achievement, economic productivity in adulthood and maternal reproductive outcomes. Accurate estimation of stunting and tools to forecast risk are key to planning interventions. We estimated the prevalence and distribution of stunting among children under five years in Somalia from 2007 to 2010 and explored the role of environmental covariates in its forecasting.
Data from household nutritional surveys in Somalia from 2007 to 2010 with a total of 1,066 clusters covering 73,778 children were included. We developed a Bayesian hierarchical space-time model to forecast stunting by using the relationship between observed stunting and environmental covariates in the preceding years. We then applied the model coefficients to environmental covariates in subsequent years. To determine the accuracy of the forecasting, we compared this model with a model that used data from all the years with the corresponding environmental covariates.
Rainfall (OR = 0.994, 95 % Credible interval (CrI): 0.993, 0.995) and vegetation cover (OR = 0.719, 95 % CrI: 0.603, 0.858) were significant in forecasting stunting. The difference in estimates of stunting using the two approaches was less than 3 % in all the regions for all forecast years.
Stunting in Somalia is spatially and temporally heterogeneous. Rainfall and vegetation are major drivers of these variations. The use of environmental covariates for forecasting of stunting is a potentially useful and affordable tool for planning interventions to reduce the high burden of malnutrition in Somalia.
五岁以下儿童发育迟缓与认知发展、学业成绩、成年期经济生产力及孕产妇生殖结局的长期影响相关。准确估计发育迟缓情况及预测风险的工具是规划干预措施的关键。我们估计了2007年至2010年索马里五岁以下儿童发育迟缓的患病率及分布情况,并探讨了环境协变量在其预测中的作用。
纳入了2007年至2010年索马里家庭营养调查的数据,共有1066个群组,涵盖73778名儿童。我们开发了一种贝叶斯分层时空模型,通过利用前几年观察到的发育迟缓与环境协变量之间的关系来预测发育迟缓情况。然后,我们将模型系数应用于后续年份的环境协变量。为了确定预测的准确性,我们将该模型与使用所有年份数据及相应环境协变量的模型进行了比较。
降雨量(优势比[OR]=0.994,95%可信区间[CrI]:0.993,0.995)和植被覆盖度(OR=0.719,95% CrI:0.603,0.858)在预测发育迟缓方面具有显著意义。在所有预测年份的所有地区,使用两种方法估计的发育迟缓差异均小于3%。
索马里的发育迟缓在空间和时间上具有异质性。降雨和植被是这些差异的主要驱动因素。利用环境协变量预测发育迟缓是规划干预措施以减轻索马里高营养不良负担的一种潜在有用且经济实惠的工具。