Prevalence and factors associated with anaemia among pregnant women attending reproductive and child health clinics in Mbeya region, Tanzania

Abstract

Anaemia is a global public health issue, disproportionately affecting vulnerable populations such as pregnant women. The aim of this study was to assess the prevalence of anaemia and to identify factors associated with the condition among pregnant women attending antenatal clinics in the Mbeya Region of Tanzania. A cross sectional study was conducted with 420 pregnant women (<28 weeks of gestation) attending antenatal visits in the 7 districts of the Mbeya Region. A structured questionnaire was used to collect demographic information and eating habits using a 24hours dietary recall. A blood sample was collected and tested for hemoglobin content using the HemoCue 201+. Multivariate analysis was performed using standard logistic regression to explore the association between anaemia status with socio-demographic, reproductive and nutritional factors. Overall prevalence of anaemia in pregnant women was 25.5%. Out of 107 pregnant women diagnosed with anaemia and, sixty six had mild anaemia. In a multivariate logistical regression analysis anaemic women was associated with pregnant women coming from lower socio-economic status [adjusted OR = 2.40, 95%CI (1.05, 5.48)]. Moreover, anaemia was less associated with pregnant women who were living in Mbeya district council [adjusted OR = 0.28, 95%CI (0.11, 0.72)], consume at least once a day dark green leafy vegetables [adjusted OR = 0.53, 95% CI (0.30, 0.94)], and vegetable liquid cooking oil [adjusted OR = 0.56, 95% CI (0.34, 0.98)]. The prevalence of anaemia among the pregnant women falls in the category of moderate public health problem according to the WHO classification. Low socio-economic status, consumption of green leafy vegetables and vegetable liquid cooking oil were significantly and independently associated with anaemia during pregnancy. Thus, special attention should be given to pregnant women who are in lower socio-economic status and those not consuming vegetables. Interventions that integrate health and nutrition education in reproductive and child health clinics are needed to combat anaemia.

Factors associated with anaemia among pregnant women in Rwanda: An analysis of the Rwanda Demographic and Health Survey of 2020

“…This may be because coming from wealthier households could also mean that women also access better health services and healthier, su cient food than their counterparts with less income. This agrees with results from several studies conducted in Tanzania, Sri Lanka, Nigeria, Rwanda, Uganda and Ethiopia which found women with low wealth index being more likely to be anaemic [27,[40][41][42][43][44].…”

Effect of and Interventions in Prevention and Management of Maternal Anemia in the Advent of COVID-19

“…This reason may be the contributor of the current findings showing this cluster of intervention with the highest effect on maternal anemia control Anemia intervention in African region generally recorded the highest effect as compared to other regions. This may not be due to the best practices though, as the prevalence of maternal anemia is higher in Sub-Saharan Africa [3], [49]- [51], however, this fact may be supported by the more interventions used to control anemia in Africa. Data collected from multiple center studies showed a more predictive effect (16%) of maternal anemia intervention as compared to single center studies Similar findings exist from other similar reviews although not during the COVID-19 pandemic [30], [52], [53].…”

The prevalence and risk factors associated with Iron, vitamin B12 and folate deficiencies in pregnant women: A cross-sectional study in Mbeya, Tanzania

“…This study employed a two steps sampling procedure: First, a list of all health facilities providing RCH services in the Mbeya region was obtained (n = 251) and used in a random selection of the health facilities to be involved in the study from each district. Based on the sampling frame of health facilities, a probability proportional to size was performed to allocate the number of facilities per District for inclusion in the survey [22]. Out of 251 health facilities, forty-two health facilities were randomly selected for the study.…”

“…And the addition of two reserved clusters was included in the survey. Therefore, a total of 44 health facilities offering RCH services were visited and surveyed [22].…”

“…The resulting list of pregnant mothers served as the sampling frame for the selection of participants who met the inclusion criteria. Systematic random sampling was carried out using the list of mothers to randomly select the required pregnant women for each facility to participate in the survey based on probability and proportion to size sampling for the specific facility [22].…”