Climate change vulnerability, and health of women and children: Evidence from India using district level data.

OBJECTIVE: To understand how climate change vulnerability is associated with women and children's health (WCH) at the district level in India. METHODS: The district-specific climate change vulnerability index was mapped to the district level NFHS-5 data (N = 674). Fractional regression and spatial analyses were performed to examine the strength of association and the presence of geographic clustering. RESULTS: Bivariate analysis revealed that the levels of WCH indicators were lower in districts with a high vulnerability index than in those with a low vulnerability index. Multivariable analyses suggested that with a 1% increase in the vulnerability index, the proportion of modern contraceptive use was reduced by 0.22, four or more prenatal care visits by 0.14, postnatal care by 0.11, and full immunization by 0.12; whereas wasting and underweight proportions increased by 0.07 and 0.10, respectively. The spatial analysis found that in about 70-118 districts, mostly in eastern India, where climate vulnerability was high the WCH outcomes were also poor. CONCLUSION: There is a macro-level association between climate change vulnerability and WCH, as districts that had high levels of climate change vulnerability also performed poorly in WCH. There is a need for an integrated approach that considers geography-specific climate change threats to develop health programs.

National guidelines for data quality in surveys: An overview.

Good quality health, nutrition and demographic survey data are vital for evidence-based decision-making. Existing literature indicates system specific, data collection and reporting gaps that affect quality of health, nutrition and demographic survey data, thereby affecting its usability and relevance. To mitigate these, the National Data Quality Forum (NDQF), under the Indian Council of Medical Research (ICMR) - National Institute of Medical Statistics (NIMS) developed the National Guidelines for Data Quality in Surveys delineating assurance mechanisms to generate standard quality data in surveys. The present article highlights the principles from the guidelines for informing survey researchers/organizations in generating good quality survey data. It describes the process of development of the national guidelines, principles for each of the survey phases listed in the document and applicability of them to data user for ensuring data quality. The guidelines may be useful to a broad-spectrum of audience such as data producers from government and non-government organizations, policy makers, research institutions, as well as individual researchers, thereby playing a vital role in improving quality of health, nutrition and demographic data ecosystem.