Study Design and Settings
This was a hospital based cross-sectional study conducted at Janakpur Provincial Hospital, located at the Janakpurdham, the capital of Province-2, Nepal. The Province 2, one of the seven provinces consists of eight districts that extends in the south-eastern flat plains (Terai region) of Nepal. Despite its ecological richness, Province 2 fares poorly in various socio-economic and health indicators including but not limited to literacy, teenage pregnancy, nutrition, contraceptive use, immunization coverage, and exposure to domestic violence. As per the Nepal Demographic Health Survey, the prevalence of anemia among women of reproductive age was reported the highest in the Province 26. Janakpur Provincial Hospital is the largest referral level public hospitals in the Province 2 offering wide range of health care services including antenatal, maternal and newborn care. This hospital receives patients and clients largely from Dhanusha and surrounding four districts (Siraha, Mahaottari, Sarlahi and some parts of Sindhuli).
Study Population
This study was carried out among pregnant women who attended antenatal care (ANC) in the Janakpur Provincial Hospital. Women in the second and third trimester of pregnancy and belonging to the underprivileged ethnic groups were included in the study. The underprivileged groups in this study constituted of Terai Dalit, Terai Janajati, Muslim and Madhesi. These groups have historically suffered oppression, discrimination and social-segregation and are politically, economically and socially backward16, 17. They are often unable to enjoy social services and facilities and face significant inequalities in the utilization of health care7, 18. Terai dalits are ascribed the lowest position in the caste-ethnicity hierarchical structure and represent the most depressed category among all ethnic groups. They have suffered from acute landlessness, caste-based discrimination, including untouchability16, 19. Madhesi caste group grips a relatively better advantage as compared to the other three groups20.
Study Design and Sampling Procedure
The sample size was calculated using Epi Info StatCalc software assuming 95% level of confidence, 0.06 margin of error and 57.8% anemia prevalence among reproductive age women of Province-26. A minimum sample of 261 was estimated and it was increased to 287 considering the non-response rate of 10%. The study participants attending antenatal care between 10 am to 4 pm were consecutively enrolled until the planned sample size was achieved.
Data Collection
A structured questionnaire was developed based on the study objectives. Standard food and dietary recall questionnaire developed by Food and Nutrition Technical Assistance (FANTA) Project was used to assess the dietary diversity status21. The questionnaire was divided in four broad sections: socio-demographic information; preventive health practices; dietary practices; and hemoglobin level (Additional file 1). Data collection was carried out between November and December 2017 using face to face interview with the pregnant women at the antenatal care (ANC). Interviews were conducted in a separate room after the participants received their antenatal services. The interview was administered by the first author who could speak both Nepali and Maithili (local) languages. In order to determine the status of anemia, blood was drawn from each participant with the help of a certified lab technician. The blood samples were collected and tested in the laboratory of Janakpur Provincial Hospital. The collected blood samples were checked for hemoglobin level using cyanmethemoglobin method.
Measurement of Variables
Anemia
The pregnant women were considered anemic if they had a hemoglobin concentration less than 11.0 g/dl22. Anemia was further categorized as mild (hemoglobin = 10.0-10.9 g/dl), moderate (hemoglobin = 7.0-9.9 g/dl) and severe (hemoglobin < 7.0 g/dl)22.
Dietary Diversity Status
This was a dichotomous indicator of whether or not women have consumed at least five out of ten defined food groups within 24 hours. In order to determine this, we used a 24-hour dietary recall questionnaire gathering information on all foods and beverages consumed by the participants in the previous day and night. The foods consumed were aggregated into 10 recommended food groups: starchy staples, pulses (beans, peas and lentils), nuts and seeds; dairy; meat, poultry and fish; eggs, dark green leafy vegetables; vitamin A rich fruits and vegetables; other vegetables; and other fruits. For each food group the pregnant women consumed from, a score of 1 was provided and 0 otherwise. The scores from all ten food groups were added to obtain the total dietary diversity score ranging from 0 to 10. The dietary diversity score thus obtained was categorized into 2 groups to derive a dietary diversity status for pregnant women. The dietary diversity score of five or more was considered adequate (coded as 1) and the score below five was inadequate (coded as 0)21, 23.
Ethnicity
A caste/ethnicity classification used by the Health Management Information System (HMIS) of the Ministry of Health and Population, Nepal was adapted for this study. This system uses six caste-groups; Dalits, Janajati, Muslim, Madhesi, Brahmin/Chhetri and Others, of which the first four groups (Table 1) were taken as they are considered belonging to the underprivileged groups. Among Dalit and Janajati, only Terai Dalits and Terai Janajati were present during the period of data collection.
Table 1
Caste and ethnicity classification of the study population
Category of ethnic groups | Classification |
Terai Dalit | Kalar, Kori, Mandal, Chamar, Musahar, Duhad/Paswan, Dom, Dhobi |
Terai Janajati | Tharu |
Muslim | Muslim (Terai) |
Madhesi | Madhesi Brahmin, Yadav, Teli, Rajput, Kayastha, Kalwar, Sudhi, Kurmi, Haluwai, Thakur, Kewat, Mallah, Nuniya, Kanu, Nurang, Kuswaha |
Data Management and Analysis
The data was entered in EpiData Entry version 3.1 and then transferred into IBM SPSS version 23 software for analyses. In the first stage, descriptive analyses were performed. Frequency tables with percentage were generated for categorical variables, while mean and standard deviation (SD) were calculated for continuous variables. In the next stage, bivariate and multivariate analyses were performed to determine the predictors of anemia. Variables that were significant at 15% significance level in bivariate analyses using Pearson’s Chi-Square test were entered into a multiple logistic regression model24. Before performing the regression analysis, a test of multi-collinearity was done. One of the variables ‘gravida’ showed multi-collinearity [Variance inflation factor (VIF) > 5] and was excluded from the analysis. Model fit was measured with the Hosmer and Lemeshow goodness-of-fit test; the model was found to be a good fit with p > 0.05. Odds Ratios (OR) were presented with their corresponding 95% confidence intervals (CI) and a probability value (p-value) of less than 0.05 was considered statistically significant.