This article assesses the gravity of the "double burden of malnutrition" across 21 states of India, through a comparative analysis of traditional and Asian population-specific BMI categorizations for overweight and obesity. This study analyzes data on ever-married women (15-49 years) from the National Family Health Survey (NFHS-2, 1998-1999; NFHS-3, 2005-2006). Findings depict that Indian women tilt toward high BMI resulting in a co-existence of under- and overweight populations, which portray a regional pattern. With Asian population-specific cut-offs, 11 states can be classified as "double burden states"; however, following traditional categorization, only 4 states face such dual pressure.
Background
Dried blood spots (DBS) are a relatively inexpensive source of nucleic acids and are easy to collect, transport, and store in large-scale field surveys, especially in resource-limited settings. However, their performance in whole-genome sequencing (WGS) relative to that of venous blood DNA has not been analyzed for various downstream applications.
Methods
This study compares the WGS performance of DBS paired with venous blood samples collected from 12 subjects.
Results
Results of standard quality checks of coverage, base quality, and mapping quality were found to be near identical between DBS and venous blood. Concordance for single-nucleotide variants, insertions and deletions, and copy number variants was high between these two sample types. Additionally, downstream analyses typical of population-based studies were performed, such as mitochondrial heteroplasmy detection, haplotype analysis, mitochondrial copy number changes, and determination of telomere lengths. The absolute mitochondrial copy number values were higher for DBS than for venous blood, though the trend in sample-to-sample variation was similar between DBS and blood. Telomere length estimates in most DBS samples were on par with those from venous blood.
Conclusion
DBS samples can serve as a robust and feasible alternative to venous blood for studies requiring WGS analysis.
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