Abstract
Objective: This research investigates the prevalence and determinants of anemia among women in Andhra Pradesh. We examined differences in anemia related to social class, urban/rural location and nutrition status body mass index (BMI). We hypothesized that rural women would have higher prevalence of anemia compared to urban women, particularly among the lower income groups, and that women with low body mass index (BMI; <18.5 kg/m2) would have a higher risk compared to normal or overweight women.
Design: The National Family Health Survey 1998/99 (NFHS-2) provides nationally representative cross-sectional survey data on women's hemoglobin status, body weight, diet, social, demographic and other household and individual level factors. Ordered logit regression analyses were applied to identify socio-economic, regional and demographic determinants of anemia.
Setting: Andhra Pradesh, a southern Indian state.
Subjects: A total of 4032 ever-married women aged 15–49 from 3872 households.
Results: Prevalence of anemia was high among all women. In all 32.4% of women had mild (100–109.99 g/l for pregnant women, 100–119.99 for non-pregnant women), 14.19% had moderate (70–99.99 g/l), and 2.2% had severe anemia (<70 g/l). Protective factors include Muslim religion, reported consumption of alcohol or pulses, and high socioeconomic status, particularly in urban areas. Poor urban women had the highest rates and odds of being anemic. Fifty-two percent of thin, 50% of normal BMI, and 41% of overweight women were anemic.
Conclusion: New program strategies are needed, particularly those that improve the overall nutrition status of women of reproductive ages. This will require tailored programs across socio-economic groups and within both rural and urban areas, but particularly among the urban and rural poor.
Sponsorship: Partial support for Margaret Bentley was provided by the Ford Foundation/India and the Carolina Population Center. Support for Paula Griffiths was provided by the Andrew W. Mellon Foundation.
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Notes
The International Institute for Population Sciences based in Mumbai, India coordinated the data collection with technical assistance from MEASURE DHS+at ORC Macro, Maryland, USA and the East–West Center, Hawaii, USA. Researchers can apply for permission to analyze the data through MEASURE DHS+, who make data collected in all of the DHS surveys available for analysis through their website; www.measuredhs.com. The survey was approved by the institutional review board at ORC, Macro, and the entire questionnaire and all of the procedures were approved by a multi-agency technical advisory committee in India, which considered human subject protections and ethical issues. Informed consent was obtained from participants both to take part in the survey and a separate, more detailed consent was obtained for hemoglobin and lead measures. The main objectives of the survey were to provide estimates of fertility, family planning practices, infant and child mortality, maternal and child health and nutrition, the utilization of maternal and child health services, the quality of these services, the status of women, women's reproductive health problems and domestic violence.
The data from NFHS 2 are being made available state by state by ORC Macro between 2000 and 2002.
All women were given the results of the hemoglobin test and had them explained to them. In addition, women with severe anemia (Hb <70 g/l) were read a statement asking whether they would give permission for the health investigator to inform a local health official about the problem.
The standard of living index is a composite index calculated by ORC Macro and the International Institute of Population Sciences and is based upon household ownership of possessions/consumer durables and land/livestock (NFHS, 1998/1999). The index was divided into low, medium and high groups based upon scores obtained. The high group contains those with a score of 25–66, the medium group scores between 15–24, and the low group 0–14.
STATA does not have a procedure for checking the proportional odds assumption. This resulted in us having to utilize SAS to test this assumption, but we were unable to test the model, which controls for survey design as SAS does not have the facility to control for survey design effects. However, by testing model 4 without survey design effects we were able to ascertain whether the proportional odds assumption was met. The results presented in Table 3 are from the models estimated in STATA which account for the survey design effects.
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Acknowledgements
The authors would like to acknowledge the individuals who contributed to the collection of the Andhra Pradesh National Family Health Survey 1998/1999; Sumati Kulkarni, Fred Arnold, TK Roy, Arvind Pandey, Robert Retherford, kamla Gupta, M Vivekananda Murty, Sunita Kishor, Vinod Mishra, Sushil Kumar, Zaheer Ahmad Khan, and Sidney, B Wesley. We thank Dr Usha Ramakrishna, Emory University, for reviewing an earlier draft of this paper and for providing analytical suggestions that greatly improved the presentation of results. Dr Anna Maria Siega-Riz of the University of North Carolina, Chapel Hill, also provided analytical guidance and support.
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Bentley, M., Griffiths, P. The burden of anemia among women in India. Eur J Clin Nutr 57, 52–60 (2003). https://doi.org/10.1038/sj.ejcn.1601504
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DOI: https://doi.org/10.1038/sj.ejcn.1601504
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