@article{Puranik_Nair_VS_Biju_2017, title={Do hot-spots of maternal mortality ratio exist in india? A district-level spatial analysis}, volume={29}, url={https://iapsmupuk.org/journal/index.php/IJCH/article/view/775}, DOI={10.47203/IJCH.2017.v29i04.006}, abstractNote={<p><strong>Background</strong>: Hot-spot detection of Maternal Mortality Ratio (MMR) can assist in identifying the exact geographic location of regions that need urgent attention. <strong>Aims &Objectives</strong>: To detect hot-spots of MMR at district level in the selected nine states of India and the observed pattern was further correlated with hot-spots of certain known risk factors of MMR in the same region. <strong>Material &Methods</strong>: Data on MMR was obtained from Annual Health Survey 2012-13. Moran’s I was computed for MMR to quantify spatial autocorrelation. The hot-spot analysis of MMR and its potential risk factors were performed using Getis-Ord Gi* statistic, a measure of local indicators of spatial autocorrelation (LISA). The spatial analysis was based on queen’s contiguity weight matrix and analyses were done using ArcGIS 10.3. <strong>Results:</strong> The Moran’s I value of MMR was found to be 0.69 indicating a positive spatial autocorrelation. Districts with MMR hot-spotting was largely observed in Uttar Pradesh and Madhya Pradesh, followed by Assam, Bihar and Jharkhand. The hot-spot analysis unveiled an inverse relation of MMR with female literacy rate, mothers who received any antenatal check-up (%), mothers who utilized Janani Suraksha Yojana (%), safe delivery (%) and urbanization (%). Marriages among females below 18 years (%), total fertility rate and women with unmet need for spacing (%) had a direct relation with MMR. <strong>Conclusion:</strong> Information on hot-spots as depicted in this study can help locate the regions vulnerable to MMR and the potential risk factors, which in turn could aid in implementing targeted intervention programs.</p>}, number={4}, journal={Indian Journal of Community Health}, author={Puranik, Amitha and Nair, Suma and VS, Binu and Biju, Seena}, year={2017}, month={Dec.}, pages={369–375} }