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Conditional selection of multifactor evidence for the levels of anaemia among women of reproductive age group

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  • S.T, Pavan Kumar
  • Lahiri, Biswajit

Abstract

The study aims at ascertaining the conditional selection of key indicators affecting severe, moderate, mild, and no anaemia levels for women of reproductive age in India. The secondary data for levels of anaemia and personal records of individuals collected for India from the 7th phase of District Health Survey program of the United States Agency for International Development data depository. The data was cleaned and summarised using frequency and percentages. Then the variables were tested for association with levels of anaemia using the Chi-square (χ2) test. The multinomial logistic regression model was employed to ascertain the key indicators through a conditional selection of reference categories. Results suggest that severe anaemia was significantly prevalent among women in the reproductive stage, especially among the 15–29 age groups. Secondary and higher education had a negative effect on the severity of severe, moderate, and mild anaemia. The poorest wealth index stratum had higher and more significant severe anaemia, and households with two adults of the opposite sex had a significant negative effect (β = −0.116, OR = 0.89, p < 0.001) on severe anaemia level while having a significant positive effect on moderate and mild anaemia. Rural households were associated negatively and significantly with moderate and mild anaemia, and nuclear household structures had a higher prevalence of severe anaemia. Therefore, these indicators across different levels of anaemia should be considered for a faster rate of reduction at the national level. Despite several initiatives by the public sector, the anaemia level has remained elevated among women of reproductive age. Education, wealth index, age, pregnancy, relationship structure, household structure, and place of residence were found to be key indicators for the level of anaemia. The significant variables will act as a crucial input to formulate cost-effective public interventions and finally encourage the faster reduction of anaemia levels.

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  • S.T, Pavan Kumar & Lahiri, Biswajit, 2023. "Conditional selection of multifactor evidence for the levels of anaemia among women of reproductive age group," Evaluation and Program Planning, Elsevier, vol. 100(C).
    • Handle: RePEc:eee:epplan:v:100:y:2023:i:c:s0149718923001210
    DOI: 10.1016/j.evalprogplan.2023.102344
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    1. Krishna Paudel & Mahesh Pandit & Michael Dunn, 2013. "Using spectral analysis and multinomial logit regression to explain households’ choice patterns," Empirical Economics, Springer, vol. 44(2), pages 739-760, April.
    2. Horton, S. & Ross, J., 2003. "The economics of iron deficiency," Food Policy, Elsevier, vol. 28(1), pages 51-75, February.
    3. Lee, Ryan C. & Sood, Neeraj & Deva, Sohini & Macedo, Marisol & Soto, Daniel W. & Unger, Jennifer B., 2023. "Evaluation of a COVID-19 rapid antigen testing program among student athletes in a public high school district," Evaluation and Program Planning, Elsevier, vol. 98(C).
    4. Jemal, Alexis & Caliste, Sherika, 2022. "Work-in-progress: Focus groups evaluate and inform revisions of a socio-behavioral health intervention," Evaluation and Program Planning, Elsevier, vol. 93(C).
    5. Stefan Angel & Richard Heuberger & Nadja Lamei, 2018. "Differences Between Household Income from Surveys and Registers and How These Affect the Poverty Headcount: Evidence from the Austrian SILC," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 138(2), pages 575-603, July.
    6. Glasgow, LaShawn & Clayton, Megan & Honeycutt, Amanda & Bayer, Erin M. & Plescia, Marcus & Holtgrave, Peter L. & Hacker, Karen, 2023. "Key insights on multisector community partnerships from real-world efforts to address social determinants of health," Evaluation and Program Planning, Elsevier, vol. 99(C).
    7. Edgar E. Twine & Elizaphan J. O. Rao & Isabelle Baltenweck & Amos O. Omore, 2019. "Are Technology Adoption and Collective Action Important in Accessing Credit? Evidence from Milk Producers in Tanzania," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 31(3), pages 388-412, July.
    8. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    9. Horak, Shelley & Ward, Caitlin, 2022. "Evaluating a state child care assistance program using administrative data," Evaluation and Program Planning, Elsevier, vol. 92(C).
    10. Quetsch, Lauren B. & Herschell, Amy D. & Kolko, David & Liebsack, Brittany K. & Carroll, Regina A., 2022. "Testing a community developed training protocol for an evidence-based treatment," Evaluation and Program Planning, Elsevier, vol. 92(C).
    11. Sumera Aziz Ali & Zahid Abbasi & Babar Shahid & Ghazal Moin & K Michael Hambidge & Nancy F Krebs & Jamie E Westcott & Elizabeth M McClure & Robert L Goldenberg & Sarah Saleem, 2020. "Prevalence and determinants of anemia among women of reproductive age in Thatta Pakistan: Findings from a cross-sectional study," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    12. Bleecker, Leah & Sauveplane-Stirling, Victoria & Di Ruggiero, Erica & Sellen, Daniel, 2021. "Evaluating the integration of strategic priorities within a complex research-for-development funding program," Evaluation and Program Planning, Elsevier, vol. 89(C).
    Full references (including those not matched with items on IDEAS)

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