Lome-Hurtado Alejandro, Lartigue-Mendoza Jacques, Trujillo Juan C
Economics Department, Universidad Autónoma Metropolitana, Unidad Azcapotzalco, Av. San Pablo 180, Col. Reynosa Tamaulipas, Alcaldía Azcapotzalco, C.P, 02200, CDMX, Mexico.
Universidad Anáhuac México, Economics and Business School, Avenida de las Torres 131, Colonia Olivar de los Padres, C.P, 01780, Ciudad de México, Mexico.
BMC Public Health. 2021 Jan 6;21(1):29. doi: 10.1186/s12889-020-10016-9.
Globally, child mortality rate has remained high over the years, but the figure can be reduced through proper implementation of spatially-targeted public health policies. Due to its alarming rate in comparison to North American standards, child mortality is particularly a health concern in Mexico. Despite this fact, there remains a dearth of studies that address its spatio-temporal identification in the country. The aims of this study are i) to model the evolution of child mortality risk at the municipality level in Greater Mexico City, (ii) to identify municipalities with high, medium, and low risk over time, and (iii) using municipality trends, to ascertain potential high-risk municipalities.
In order to control for the space-time patterns of data, the study performs a Bayesian spatio-temporal analysis. This methodology permits the modelling of the geographical variation of child mortality risk across municipalities, within the studied time span.
The analysis shows that most of the high-risk municipalities were in the east, along with a few in the north and west areas of Greater Mexico City. In some of them, it is possible to distinguish an increasing trend in child mortality risk. The outcomes highlight municipalities currently presenting a medium risk but liable to become high risk, given their trend, after the studied period. Finally, the likelihood of child mortality risk illustrates an overall decreasing tendency throughout the 7-year studied period.
The identification of high-risk municipalities and risk trends may provide a useful input for policymakers seeking to reduce the incidence of child mortality. The results provide evidence that supports the use of geographical targeting in policy interventions.
多年来，全球儿童死亡率一直居高不下，但通过合理实施针对性的公共卫生政策，这一数字可以降低。与北美标准相比，墨西哥的儿童死亡率令人担忧，因此儿童死亡率尤其成为该国的一个卫生问题。尽管如此，该国仍缺乏针对儿童死亡率时空识别的研究。本研究的目的是：（i）对大墨西哥城各市政府层面儿童死亡风险的演变进行建模；（ii）确定不同时期高、中、低风险的市政府；（iii）利用市政府的趋势，确定潜在的高风险市政府。
为了控制数据的时空模式，本研究进行了贝叶斯时空分析。该方法允许对研究时间跨度内各市政府儿童死亡风险的地理变化进行建模。
分析表明，大多数高风险市政府位于东部，大墨西哥城的北部和西部也有一些。在其中一些地区，可以看出儿童死亡风险呈上升趋势。结果突出显示了目前处于中等风险但根据其趋势在研究期后可能成为高风险的市政府。最后，在整个7年的研究期内，儿童死亡风险的可能性总体呈下降趋势。
识别高风险市政府和风险趋势可能为寻求降低儿童死亡率的政策制定者提供有用的参考。研究结果为政策干预中使用地理定位提供了支持证据。
