Dietary Diversity and its Determinants among Tribal Women of Reproductive Age in Birbhum

Introduction

Nutrition is a basic need of human beings. It is regarded as fundamental to promoting a healthy lifestyle. A balanced diet is crucial from early life for growth, development, and maintaining activity.¹ An estimated 815 million people worldwide are chronically undernourished; the majority live in low- and middle-income countries (LMICs).² Dietary diversity scores are developed based on the number of food groups consumed over a specified period. They serve as an indicator of diet quality and have been validated as predictors of micronutrient adequacy.³ In resource-poor environments worldwide, monotonous, low-quality diets that lack diversity are prevalent. Women in the reproductive age group (WRA) and children are most vulnerable to malnutrition due to low dietary intake. Studies show that a higher dietary diversity score is linked to lower maternal micronutrient deficiency and better pregnancy outcomes.⁴ A non-diversified diet can harm individuals’ health, well-being, and development by decreasing physical abilities, increasing susceptibility to infections, and hindering cognitive, reproductive, and social capacities.⁵ The tribal population in India is considered the most disadvantaged with respect to health indicators. Tribal populations are rapidly modernizing and have diverse ethnic backgrounds, cultures, diets, habitats, and behavioral habits. Various studies have been conducted to assess dietary diversity and food insecurity globally. However, the literature on India is limited. This lack of sufficient research poses a hurdle in formulating effective strategies to combat the issue. This study was conducted to evaluate the dietary diversity and household food insecurity among tribal women of reproductive age in a rural block of Birbhum, West Bengal. Additionally, it aimed to determine the association, if any, between dietary diversity scores and selected sociodemographic variables.

Materials and Methods

Study design

This study was a cross-sectional study conducted from September 2021 to December 2021 in the villages of Suri-I block of Birbhum, West Bengal.⁶ 

Study participants

The study participants were tribal women of reproductive age (15-49 years) who had been residing in tribal villages for at least 10 years. The study excluded individuals who were seriously ill, as well as those with physical disabilities and pregnant women.

Sample size

In a study conducted in Bangladesh on dietary diversity, the mean Dietary Diversity Score (DDS) and standard deviation was 4.5 ± 1.1.7 Using the formula N = 4σ² /L² (where N = sample size, σ = standard deviation, and L = allowable error), the required sample size was calculated to be 208 (with a standard deviation of 1.1, allowable error of 0.16, and a non-response rate of 10%). After applying a design effect of 1.5, the final sample size was determined to be 312. 

Sampling technique

The study participants were selected using a multistage cluster sampling technique. A list of all villages in the Suri I was prepared along with total households and individuals. Then, 10 clusters (villages) were selected. The selection was made with a probability that corresponds directly to the size of the village population, and the cluster size was determined to be 31. An updated list of Scheduled Tribe households was obtained from the local authorities to prepare the sampling frame. A total of 31 households were randomly selected from each village, and one eligible individual was chosen from each household based on their last birthday. Thus, 312 individuals were selected from 10 clusters.

Research instrument

A predesigned, prestructured standardized pro forma was used for data collection. It was divided into two sections: the first collected demographic information of participants, and the second included questions on food insecurity and dietary diversity. The 24-hour recall method was used to assess dietary diversity, and MDD-W (Minimum Dietary Diversity for Women) was computed.⁸ MDD-W was considered adequate if a woman consumed at least five different food groups; otherwise, it was deemed inadequate. Household food security was assessed using the Household Food Insecurity Access Scale (HFIAS) questionnaire.⁹ The HFIAS questions were administered with a recall period of four weeks.

In this study, the following operational definitions were considered. A household was considered food secure when its members ‘rarely’ worried about not having enough food over the previous four weeks and responded ‘no’ to questions two through nine¹⁰ (Table 4). Households were classified as mildly food insecure when members sometimes or often worried about insufficient food and were unable to eat preferred foods, or consumed a monotonous and/or undesirable items, though rarely.¹⁰ Moderately food-insecure households were those in which members sacrificed food quality and consumed a non-diversified or undesirable diet sometimes or often, and occasionally reduced meal size and frequency.¹⁰ Severe food insecurity was defined as often reducing meal size or number of meals, and/or experiencing any of the three most severe conditions, like running out of food, going to bed hungry, or going a whole day and night without eating.¹⁰ The socioeconomic status of study participants was assessed using the Modified B. G. Prasad Classification (2020).¹¹

Study techniques

Face-to-face interview and anthropometry measurements.

Ethics

Ethical clearance was obtained from the ethics committee of the institute. Confidentiality and anonymity were maintained throughout the study period.

Statistics

After data collection, the information was entered into Microsoft Excel, coded, and subsequently imported into SPSS software (Statistical Package for the Social Sciences Inc., Chicago, IL, USA), version 21.0 for analysis. The categorical data were expressed in frequency and proportions. For continuous data, normality was checked by Shapiro wilk test distribution. For continuous data, the mean with standard deviation or median with interquartile range (IQR) was used for central tendency and dispersion. Pearson’s Chi-Square test statistic was used to determine the significance of the association. To identify the sociodemographic predictors of the MDD-W score, binary multivariable logistic regression was performed. Demographic variables like age, gender, type of family, number of family members, educational status, occupation, monthly family income, and food insecurity were considered independent variables for binary logistic regression. P <0.05 was considered to be statistically significant.

Results

The study included 312 participants, with a median age of 32 years (IQR: 27-36) (Skewness -0.3 with SE 0.138). Among them, 91.7% were married, and 72.4% belonged to joint families. Most participants (88.8%) lived in katcha houses, and wood chips were the main domestic fuel for 46.3% of households. The median number of family members was 5 (IQR: 4-6). The median per capita monthly income of the families was Rs. 1666 (IQR: Rs. 1200 – Rs. 2333), and 71.2 % of participants belonged to the below middle class according to the Modified B. G. Prasad Scale (2020). About 61.9% of the study participants had no formal education.

The mean BMI of the study participants was 19.96 kg/m2 (SD ± 2.19) and 34% were undernourished. Among the participants, 67.9% were multiparous. The median age at marriage was 18 years (IQR: 18-21) and the median age at first pregnancy was 21 years ( IQR: 19-23). The median MDD-W score was 4 (IQR: 4-6), while the mean was 4.95 (SD ± 1.59). Overall, 54.2% of participants had inadequate dietary diversity, and 37.2% experienced moderate to severe food insecurity (Table 1).

The most common food groups consumed were grains, white roots, and tubers (100%), followed by pulses (88.8%) and other vegetables (62.5%). However, consumption of nuts and seeds (P <0.01), milk and milk products (P=0.01), and vitamin A-rich fruits and vegetables (P <0.01) was significantly lower among participants above thirty years of age compared to the younger age group (Table 2).

In this study, the variance inflation factor (VIF) ranged from 1.105 to 1.680, and the lowest tolerance value was 0.595, indicating minimal multicollinearity among the independent variables in the binary multivariable logistic regression analysis. The Hosmer and Lemeshow showed that the model was well fitted, with a nonsignificant result (P=0.268). After adjusting for the predictors, the model explained between 53.6% (Cox and Snell R square) and 71.6% (Nagelkarke R square) of the variance in participants' MDD-W scores.

Socioeconomic class, occupation, family members, food insecurity, parity, marital status, family type, and nutritional status demonstrated a statistically significant association with inadequate dietary diversity (MDD-W <5). Participants belonging to the below middle class and those with more than four family members had higher odds (AOR: 6.1 and 10.7, respectively) of inadequate dietary diversity. Similarly, participants aged more than 30 years (AOR: 4.1), those with multiparity (AOR: 3.4), those without paid jobs (AOR: 4.2), and those belonging to joint families (AOR: 3.9) had higher odds of inadequate dietary diversity (Table 3).

Participants were classified based on household food security using the HFIAS questionnaire.⁹ Among them, 11.5% experienced severe food insecurity, while 25.6% experienced moderate food insecurity (Table 4).

Discussion

The current study found the prevalence of inadequate dietary diversity to be 54.2%. A similar study done in Karnataka reported a prevalence of 58%.¹² In our study, the mean MDD-W score was 4.95 (SD ±1.59). A similar result was reported in a study conducted in Pakistan by Anna KL et al., where the mean MDD-W score was 4 (SD ±1). In a study done in Kolkata, the proportion of WRA attaining MDD was found to be 46.2%.^13,14 A significant association was observed between dietary diversity and smaller family size (less than four family members), belonging to the middle class and above, having formal education, and a paid job. The mean BMI of the study participants was 19.16 kg/m2 with SD ±2.19, and none were obese. According to National Family Health Survey (NFHS-5), the prevalence of obesity and overweight among WRA in Birbhum is 13.4 %.¹⁵ This may be attributed to the fact that the majority of the population belongs to the lower and lower-middle socioeconomic classes and engages in high levels of physical activity. In the present study, 11.6% of participants experienced high household food insecurity, which is comparable to the 9.2% reported in a North Indian study by Chinnakali P et al.,The most prevalent food group consumed among our participants was starchy staples.¹⁰ Similar to the findings from a study conducted in Durgapur, India, the consumption of eggs, meat, and fish was low across the study population.¹⁶

The primary objective was to assess dietary diversity and household food insecurity in low-resource settings, with the ultimate goal of ensuring access to sustainable diets.¹⁷ Achieving this requires a multidisciplinary approach, given its multiple dimensions. Strengthening the Rashtriya Krishi Vikas Yojana (RKVY) is essential for enhancing productivity, income, and innovation.¹⁸ Additionally, effective implementation of the Panchayat Extension to Scheduled Areas (PESA) Act must be reinforced.¹⁴ It is crucial to map local food systems, including production practices, food retail environments, and the factors influencing consumer purchasing patterns. The growth of industries in tribal areas poses a challenge to environmental sustainability. Pollution of water and arable land can negatively impact food security and dietary diversity. Increasing economic efficiency can boost purchasing power, and empowering women is key to achieving this goal. Strengthening national programs such as RKVY, the Public Distribution System and the National Food Security Mission (NFSM)is vital.¹⁹ This may also involve rationalizing the distribution of cultivable land, promoting aeroponics and hydroponics, diversifying crops, and enhancing livestock production. Every component is interrelated and has socio-organizational significance at the macro (national), meso- (community), and micro (individual and family) levels.

Conclusion

Dietary diversity is one of the key elements of diet quality. According to the current study, age, marital status, family structure, employment, and socioeconomic position are the main factors that determine dietary diversity, and half the population does not achieve a sufficient level of it. Among the study participants, 25.6% experienced moderate food insecurity and 11.5% experienced severe food insecurity. Therefore, in order to raise awareness of the importance of dietary diversity, campaigns should be set up. Dietary diversity is an issue that must be tackled from all angles. Eating a varied diet will enhance one's quality of life and health. A diversified diet will also help reduce micronutrient deficiencies.

Acknowledgment

We would like to express our gratitude towards the Panchayat Pradhan of the tribal community.

Financial support and sponsorship:

Nil

Conflicts of interest

There are no conflicts of interest.