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Research ArticleDOI Number : 10.36811/ojgor.2020.110013Article Views : 21Article Downloads : 17

Rural community based study of Magnitude of Anaemia in Women of Reproductive age

Chhabra S* and Varma Shivkumar P

Obstetrics Gynaecology, Mahatma Gandhi Institute of Medical Sciences, Maharashtra, India

*Corresponding Author: Chhabra S, Emeritus Professor, Obstetrics Gynaecology, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Wardha, Maharashtra, India, Email: [email protected]; [email protected] 

Article Information

Aritcle Type: Research Article

Citation: Chhabra S, Varma Shivkumar P. 2020. Rural community based study of Magnitude of Anaemia in Women of Reproductive age. O J Gyencol Obset Res. 2: 05-10.

Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright © 2020; Chhabra S

Publication history:

Received date: 31 January, 2020
Accepted date: 12 February, 2020
Published date: 12 February, 2020

Abstract

Background: Despite several steps taken by governments, anaemia continues to be common, and affects women’s health negatively. Last demographic health survey in India revealed 27% women of 15-49 years age anaemic, so it was decided to look into present status in rural communities. Objective was to know community-based magnitude of anaemia in rural women of reproductive age.

Material and Methods: Community based study was conducted for knowing magnitude of anaemia in nonpregnant women of 15 to 49 years. In 28 villages around 75±10 km away from study institute in Central India, as per availability, 1267 women were randomly screened, keeping in mind inclusion and exclusion criteria. After information and request to permit, minimum 25 women per village, who so ever volunteered, fitted in inclusion criteria were screened.

Results: Of 1267 women randomly screened 858 (67.72%) were anaemic, 850 mildly or moderately anaemic. Eight (0.6%) severely anaemic, (Hb less than 7 gms/dl) were straight referred to hospital for work up and appropriate management. Others were also advised to get investigations, treatment, not part of study. Maximum burden of anaemia, (68.86%), was in women of 35-49 yrs age, 67.37% among 20-34 yrs old and 65.92% in adolescents, no significant difference in different age groups. Of 1267 screened, 972 (76.7%) were from lower economic status, 280(22.1%) middle economic status only 15(1.2%) from upper economic status, maximum anaemic was out of LES women. Most women with four and more births were anaemic. Parity affected maximum compared to age, economic status and education.

Conclusion: Around 70% women of reproductive age without any obvious disorders. were found to be anaemic in rural communities Parity had maximum effect.

Background

Despite several steps taken by the governments, anaemia continues to be common disorder affecting women’s health. Mostly the cause is nutritional deficiency of one or several nutrients. Main nutrients involved in the synthesis of haemoglobin are iron, folic acid, and Vit B12. Deficiency of all three or anyone can lead to various degrees of anaemia. Women become anaemic more often due to menstruation, pregnancy, or abnormal uterine bleeding in addition to nutritional deficiencies due to various social reasons and disorders like bleeding piles, worm infestations, chronic diseases such as tuberculosis, malignancy which affect men as well as women.

Despite many efforts, the demographic health survey in India revealed 27% women, of reproductive age (WRA), (15-49) years having anaemia with significant regional variations [1]. National Family Health Survey III revealed that 55.3% WRA were anaemic in the country, more of pregnant women and young [2,3]. According to World Health Organization (WHO) report, anaemia affected 1.62 billion (24.8%) people globally [4]. Reducing anaemia in WRA by 50% by 2025 is one of the six global nutrition targets that were set forth by the World Health Assembly [5]. So, anaemia remains a public health problem globally. Objective was to know the community-based magnitude of anaemia in rural WRA with mission of advocacy of prevention and therapy.

Material and Methods

Rural community-based study was conducted for knowing the magnitude of anaemia. WRA from 28 villages of Wardha district, around 75 ± 10 km away from the study institute, were screened over a period of 9 months after approval of ethics committee of the institute. Pregnant women, those with obvious disorders which could cause bleeding causing anaemia like piles, menorrhagia and known chronic diseases which could cause anaemia. A pretested tool was used. Women were explained about plans of advocacy of prevention of anaemia and help in management if found anaemic. Inclusion was after woman’s consent. No one refused. Sample size needed for screening was around 1200. Total 1267 women were randomly screened as per the availability keeping in mind inclusion and exclusion criteria. Call was sent to women to get screened at a fixed place on fixed days in 28 villages. Minimum 25 women / village were screened in each village, total 1267 women. Some villages were small other little bigger. Grade of anaemia was divided as mild, moderate, and severe. Haemoglobin >9.0–10.9g/d1 as mild, >7–8.9g/dl moderate, and <7g/dl as severe [6].

Results

Over all 858 (67.72%) women were found to be anaemic, a total of 850(67.08%) were mildly or moderately anaemic and 8 (0.6%) severely anaemic, (Hb below 7 gms/dl). Severely anaemic women were straight referred to hospital for work up and therapy though all women with anaemia were advised to get investigations and treatment which was not part of the study. Maximum burden of anaemia, 68.86%, was in women of 35-49 yrs, followed by 67.37%, amongst 20-34 yrs women, and 65.92% in adolescents. However, there was no significant difference in numbers of anaemic women in different age groups in villages. Of 1267 women who were screened, 972 (76.7%) were from lower economic class 280(22.1%) from middle economic class and only 15(1.2%) were from upper economic class [7]. As expected, highest incidence (68.50%) of anaemia was in women of low economic class, 73.70% mildly anaemic, 25.10% moderately anaemic, and 1.20% severely anaemic. Among middle economic status, 32.85% were non-anaemic and 67.14%, anaemic, 79.80% mildly anaemic and 20.20% were moderately anaemic. Among upper economic class as expected, 73.34% were non-anaemic, 26.66% anaemic equally divided in moderate and mild anaemia. (significant difference P value P=<0.000001). Of 1267 women screened 13.97% were primary school educated, 14.83% middle school pass, 55.2% high school pass, 4.5% graduates, 0.6% postgraduates and 10.9% were illiterate too. Among illiterates, 26.8% were non-anaemic and 73.20% anaemic, and 1.98% of them were severely anaemic. Of anaemic 21.78% were moderately and 76.24% mildly anaemic. As expected, highest numbers of anaemia cases were among illiterates, 73.20% and 59.74% among educated women. (significant difference P value = 0.001073). Of 1267 screened women, 336 had no pregnancy, 140 women had one birth, 431 two, 282 three, 60 had four births 15 five and 3 had six births too. On the basis of parity, division was made in group I, P0 +P1, group II, P2+P3 and group III, P4 onwards. Highest number of anaemic women were in group III, 80.76% (71.42% mild, 23.82% moderate and 4.76 % severely anaemic) followed by 67.18% in group II (74.73% mild, 24.84% moderate and severe 0.43 %) and 66.38% in group I (75.94% mild, 23.1% moderate, 0.94% severe). So as expected more of rural women with many births were anaemic. Severely anaemic were also more. Significant association was found between parity and anaemia. Most women with four and more births were anaemic. (Table I). After thorough collection of information about symptoms it was found that of 850 anaemic women 4 (0.47%) had leucorrhoea, 3 (0.35%) numbness in feet, 70 (8.23%) pain in abdomen, 60 (7.05%) dysmenorrhoea, 93 (10.94%) low backache, 18 (0.02%) irregular menstruation, not excessive, 7 (0.82%) neck pain, 35 (4.11%) generalised malaise, 2 (0.23%) body ache, 21 (2.47%) giddiness, 32 (3.76%) generalised weakness, 37 (4.35%) headache, 7 (0.82%) oligomenorrhoea and 5 (0.58%) symptoms of urinary tract infection . Overall around, 50% women were having complaints which could be linked to anaemia. These women neither knew they had anaemia nor had sought help for any of their complaints.

Discussion

Particularly in countries where the prevalence of anaemia is moderate or severe it is a public health problem, more information elucidating the etiology of anaemia is needed. Thacker 2011 [8] reported significant association of anaemia with low economic status. In the present study too on looking into the economic status there was higher incidence of anaemia in lower economic status in community (68.50%). Education is thought to be an important factor for prevention of anaemia. In the present study also, anaemia was detected in significantly more illiterate women 73.2% at community level in villages. Trinh [9] has also reported that women with lower education were more often anaemic than women who were better educated. Raghuraman et al [10] in their rural study found anaemia more often in women who were of more than four parity. Farsi [11] also found more risk of anaemia among women with high parity compared to those who had fewer pregnancies as was found in the present study also. Actually, parity affected the occurrence of anaemia maximum compared to age, education and economic status. In a cross – sectional nationally representative data from 10 surveys examining the severity of anemia and the bivariate association between anemia and factors at the country level and by infection burden [12]. Anemia prevalence was ∼40% in countries with a high infection burden and 12% and 7% in countries with moderate and low infection burdens, respectively. Iron deficiency was consistently associated with anemia in multivariate models, but the proportion of anemic women who were iron deficient was considerably lower in the high-infection group (35%) than in the moderate- and low-infection groups (65% and 71%, respectively). In the multivariate analysis, inflammation, vitamin A insufficiency, socioeconomic status, and age were also significantly associated with anemia, but malaria and vitamin B-12 and folate deficiencies were not. When anaemic women became pregnant anaemia increased with increased risk of poor birth outcomes, such as preterm birth, low birth weight, and perinatal and neonatal mortality [13]. Maternal mortality has also been associated with low haemoglobin concentrations during pregnancy with risk of maternal mortality decreasing by 25% for every 10-g/L increase in haemoglobin [14]. Anaemia resulted in reduced work productivity in nonpregnant WRA also [15-18], which is likely due to reduced oxygen-carrying capacity in an individual’s blood [19]. In the study by bivariate analysis the factors found to be significantly associated with magnitude of anaemia were age, residence, educational status, income, ethnicity, religion, marital status, delivery site, number of pregnancies , history of abortion, use of contraceptives, blood loss in the last delivery, malaria in the last one year, soil transmitted helminthes infection, HIV status, and nutritional status [20] . However, residence, family size, soil transmitted helminthes infection, history of malaria in the last one year, and nutritional status remained significantly associated with magnitude of anaemia in the multivariate logistic regression (Kenea, etal 2018 [20] In the rural community based study parity affected maximum compared to age , economic status and education. These women were screened in their own villages and were not patients and did not have any obvious disorder which could cause anaemia. The high incidence of anaemia in women of reproductive age is something to worry, needs action. 

Table I: Anaemic Women with Respect to Age, Economic status, Education and Parity.

 

Age

Women

screened

Non anaemic

Anaemic

Mild

Moderate

Severe

9-10.9 gm/dl

7-8.9 gm/dl

 

No

No

%

No

%

No

%

No

%

No

%

15-19

179

61     34.08

118    65.92

87   73.74

30    25.42

1        0.84

20-34

619

202    2.63

417    67.37

316  75.78

96     23.02

5        1.20

35-49

469

146   31.14

323   68.86

241  74.61

80     24.77

2       0.62

 

1267

409  32.28

858  67.72

644 75.07

206  24.00

8       0.93

Socio economic status

 

 

 

 

 

Low

972

306   31.50

666    68.50

491  73.70

167   25.10

8        1.20

Middle

280

92     32.85

188   67.15

150  79.80

38     20.20

0          0

Upper

15

11     73.34

4       26.66

2        50

2         50

0          0

 

1267

409  32.28

858  67.72

643 74.94

207  24.12

8       0.94

Education

 

 

 

 

 

Illiterate

138

37     26.80

101    73.20

77    76.24

22     21.78

2        1.98

I-IV

177

57     32.20

120     67.8

89    74.17

30     25.00

1        0.83

V-VII

188

52     27.65

136    72.35

95    69.84

41     30.16

0          0

VIII-XII

700

243   34.70

457    65.30

351  76.81

101   22.19

5        1.10

Graduate

57

17     29.80

40    70.20

28    70.00

12     30.00

0          0

Postgraduate

7

3       42.86

4       57.14

4       100

0           0

0          0

Total

1267

409  32.30

858  67.70

644 75.06

206  24.01

8       0.93

Parity

 

 

 

 

 

 

P0

336

115     34.2

221     65.8

164  74.21

55     24.84

2        0.95

P1

140

453     2.14

95       67.9

76    80.00

18    18.85

1       1.15

P2

431

149     34.6

282     65.4

213  75.54

67    23.75

2       0.71

P3

282

85     30.14

197     69.9

145  73.61

52     26.39

0         0

P4

60

13      21.7

47       78.3

35    74.47

11     23.40

1       2.13

P5

15

2        13.3

13       86.7

8      61.54

4        3.76

1       7.70

P6

3

0            0

3         100

2      66.67

0          0

1      33.33

Total

1267

409    32.3

858    67.7

643 74.94

207  24.12

8       0.94

Conclusion

More than two third women of reproductive age were found to be anaemic in community-based study of women of 15-49 years. These women did not have any obvious disorders which could have caused bleeding leading to anaemia or any other chronic disorders which could have made a change in haemoglobin. Parity had maximum effect.

References

1. Ethiopia Central Statistical Agency 2005. Ethiopia demographic &Health survey 2005: Preliminary report Addis Ababa Central Statistical Agency. 2006: 156-157. Ref.: https://bit.ly/2Hfb9ce 

2. McLean E, Cogswell M, Egli I, et al. 2009. Worldwide prevalence of anaemia, WHO Vitamin and Mineral Nutrition Information System, 1993-2005. Public Health Nutrition. 12: 444-454. Ref.: https://www.ncbi.nlm.nih.gov/pubmed/18498676 

3. Ma AG, Schouten Ea, Wang Y, et al. 2009. Anemia prevalence among pregnant women and birth weight in five areas in China. Medical Principles and Practice. 18: 368-372. https://bit.ly/2upzh9v 

4. WHO, Worldwide Prevalence of Anaemia 1993-2005: WHO Global Database on Anaemia, World Health Organization, Geneva. 2008. Ref.: https://bit.ly/2vqnho1

5. WHO. Global targets indicators: what is measured gets done [Internet]. Geneva (Switzerland): WHO. 2014. [cited 2016 Jun 15]. Ref.: https://bit.ly/2vp7PZm

6. Shulman CE, Levene M, Morison L, et al. 2001. Screening for severe anaemia in pregnancy in Kenya, using pallor examination and self-reported morbidity. Transactions of the Royal Society of Tropical Medicine and Hygiene. vol. 95: 250-255, Ref.: https://bit.ly/37gmof5

7. Ghosh A, Ghosh T. 2009. Modification of Kuppuswamy's socioeconomic status scale in context to Nepal. 46: 1104-1105. Ref.: https://bit.ly/2uB4cj8

8. Thacker T. 2011. Lancet study ring alarm over anaemia prevalence in India. 24: 3-11.

9. Trinh LT, Dibley M. 2007. Anaemia in Pregnant. Postpartum and Non-Pregnant Women in Lak District, DaklakProrince Of Vietnam. Asia Pac J ClinNutr. 16: 310-315. Ref.: https://bit.ly/2OGd3Xy 

10. Raghuram V, Majula A, Jayaram S. 2012. Prevalence of Anaemia Amongst Women in The Age Group in A Rural Area in South India. International Journal of Biological & Medical Research. 3: 1482-1484. Ref.: https://bit.ly/2Hha3ww 

11. Farsi Y, Brooks D, Werler M, et al, 2011. Effect of High Parity on Occurrence of Anaemia in Pregnancy: A Cohort Study. BML pregnancy & child birth. 11: 7. Ref.: https://bit.ly/2vkKIze

12. Wirth JP, Woodruff BA, Engle-Stone R, et al. 2017. Predictors of anemia in women of reproductive age: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project. Am J Clin Nutr. 106: 416-427. Ref.: https://bit.ly/37ms7Al

13. Rahman MM, Abe SK, Rahman MS, et al. 2016. Maternal anemia and risk of adverse birth and health outcomes in low- and middle-income countries: systematic review and meta-analysis. Am J Clin Nutr.103: 495-504. Ref.: https://bit.ly/2tQI9Vi

14. Stoltzfus R, Mullany L, Black R. 2004. Comparative quantification of health risks: global and regional burden of disease attributable to selected major risk factors. Geneva (Switzerland): WHO. 163-209. Ref.: https://bit.ly/2SCUJ2z

15. Untoro J, Gross R, Schultink W, et al. 1998. The association between BMI and haemoglobin and work productivity among Indonesian female factory workers. Eur J Clin Nutr. 52: 131-135. Ref.: https://go.nature.com/2H9Kyxo

16. Scholz BD, Gross R, Schultink W, et al. 1997. Anaemia is associated with reduced productivity of women workers even in less-physically-strenuous tasks. 77: 47-57. Ref.: https://bit.ly/38fAteg

17. Gilgen DD, Mascie-Taylor CGNCGN, Rosetta LL. 2001. Intestinal helminth infections, anaemia and labour productivity of female tea pluckers in Bangladesh. Trop Med Int Health. 6: 449-457. Ref.: https://bit.ly/38o6FfC

18. Selvaratnam RR, de Silva LD, Pathmeswaran A, et al. 2003. Nutritional status and productivity of Sri Lankan tea pluckers. Ceylon Med J. 48: 114-118.

19. Haas JD, Brownlie T. 2001. Iron deficiency and reduced work capacity: a critical review of the research to determine a causal relationship. 31: 676-688. Ref.: https://bit.ly/2SjA3hs

20. Adamu Kenea, Efrem Negash, Lemi Bacha, et al. 2018. Magnitude of Anemia and Associated Factors among Pregnant Women Attending Antenatal Care in Public Hospitals of Ilu Abba Bora Zone, South West Ethiopia: A Cross-Sectional Study. 7. Ref.: https://bit.ly/2vpdU88 

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