Understanding the Spatial Predictors of Malnutrition Among 0-2 Years Children in India Using Path Analysis.

Background: Despite several programs and policies to turn down the burden of malnutrition in the country, the rank of India in the Global Hunger Index (GHI) is 102 among 117 countries, which indicates a serious hunger situation. It is essential to design more specific interventions by focusing on the key determinants that may directly or indirectly influence malnutrition in India. Methods: Utilizing data from the National Family and Health Survey-4 (NFHS) (2015-16), we developed a structural equation model to find the direct, indirect, and total effect of various determinants on stunting, wasting, and underweight. We used spatial analysis to identify local occurrences of factors that are critical in controlling malnutrition. A p-value of 0.05 was considered to be significant throughout the study. Analysis was performed using STATA (version 15.1MP) and GeoDa software (version 1.14). Results: A final sample of 90, 842 children of 0-24 months of age was selected for the analysis. The CFI and TLI values of 0.98 and 0.93, respectively, are indicative of a good fit model. Moran's I value of global spatial autocorrelation for the widespread presence of diarrhea, poor drinking water source, exclusive breastfeeding, low birth weight, no prenatal visits, poor toilet facility was observed to be 0.446, 0.638, 0.345, 0.439, 0.620, and 0.727, respectively. Conclusion: A robust direct relation was observed for diarrhea, exclusive breastfeeding, and children born with stunting, underweight, and wasting. The variables associated indirectly with the outcome variables were the education of the mother, residence, and desired pregnancy. The identification of hotspots through spatial analysis would help revive control strategies in the affected area according to geographical needs. It is extensively addressed that interventions related to health and nutrition during the first 1, 000 days of life is crucial to seize the upshoot of growth floundering among children.

Thyroid Function Test in COVID-19 Patients: A Cross-Sectional Study in a Tertiary Care Hospital.

CONTEXT: There is scarcity of data on thyroid function abnormality in COVID-19 patients in world literature. AIMS: The objective of this study was to assess thyroid function tests in hospitalized patients of COVID-19. SETTINGS AND DESIGN: Sixty (60) patients with COVID-19 detected by RT-PCR admitted in General Medicine isolation ward and COVID block of a tertiary care teaching hospital were selected by semi-purposive sampling. MATERIALS AND METHODS: These patients were assessed for thyroid function tests, including total T3, free T3, total T4, free T4, TSH and anti-TPO antibody along with other baseline investigations. Patients with pre-existing thyroid-related ailments, those on levothyroxine or anti-thyroid drugs or other drugs known to interfere with the results were excluded. RESULTS: There were 43.3% patients in mild, 26.7% in moderate, and 30% in severe category, according to local COVID-19 severity classification protocol. 35% patients had one or more abnormality in the thyroid function, low TSH being the most common (18.33%). 9.1% patients had characteristic pattern of thyroiditis. In most of the others thyroid function did not match any typical pattern. There was no significant difference in any of the parameters of the thyroid function test between mild, moderate, and severe groups. CONCLUSION: Thyroid function may be abnormal in all categories of patients during COVID-19 infection, even in absence of pre-existing thyroid ailments. Although low TSH is the commonest abnormality and typical pattern of thyroiditis can be seen in a subsection of patients, in majority of the patients, thyroid function abnormality does not follow any characteristic pattern and likely represents a combination of thyroiditis and sick euthyroid syndrome in different points of its spectrum.