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 Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 7  |  Issue : 1  |  Page : 28-35

The thin end of the trend: Nutritional status of women from marginalized communities across four states of India


Public Health Resource Network, Delhi, India

Date of Submission19-Jun-2020
Date of Decision02-Jul-2020
Date of Acceptance09-Jul-2020
Date of Web Publication23-Oct-2020

Correspondence Address:
Dr. Aditi Hegde
Aashiana Apartments, Mayur Vihar Phase-1 Extension, Delhi.
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jhrr.JHRR_20_20

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  Abstract 

Aim: Malnutrition, especially among women, has dire consequences inter-generationally and across the life cycle. Despite many efforts, the burden of malnutrition has persisted in India. The aim was (a) to identify the point prevalence of undernutrition, as well as overweight and obesity, in the described geographic areas, and (b) to compare these findings with national-level data. Materials and Methods: This cross-sectional study was conducted in select villages of Darbha (Chhattisgarh), Jhalda (West Bengal), Mohgaon and Samnapur (Madhya Pradesh), and Sonua and Kathikund (Jharkhand) between March 2016 and February 2017. Villages were selected through convenience sampling. The data were collected intra-programmatically by persons trained in health and nutrition using standard weighing scales and stadiometers. The World Health Organization classification of body mass index (BMI) for adults has been adapted for classification purposes. This study used descriptive statistics to analyze the data and used Stata 15.1 for this purpose. Results: Over 12,000 women had their BMI measured, of which 11,319 were valid. Overall, 40.64% of the participants were underweight. Upon categorizing according to severity, 8.27% of all participants were severely thin, whereas the point prevalence of moderate and mild thinness was 10.08% and 22.29%, respectively. Overweight and obese women made up almost 4.1% of the population (3.69% and 0.4%, respectively). These are in stark contrast to the NFHS-4 findings where about 23% of Indian women were underweight, whereas 21% were overweight or obese. Conclusions: Marginalized communities are disproportionately affected by severe undernutrition: the prevalence of severe thinness, a proxy for chronic hunger, is unacceptably high (8.27%) among women from these communities.

Keywords: Adult women, body mass index, malnutrition, marginalized communities, NFHS, tribal communities


How to cite this article:
Hegde A, Prasad V. The thin end of the trend: Nutritional status of women from marginalized communities across four states of India. J Health Res Rev 2020;7:28-35

How to cite this URL:
Hegde A, Prasad V. The thin end of the trend: Nutritional status of women from marginalized communities across four states of India. J Health Res Rev [serial online] 2020 [cited 2020 Nov 24];7:28-35. Available from: https://www.jhrr.org/text.asp?2020/7/1/28/298874




  Introduction Top


Malnutrition among adult women is a common occurrence, far more customary than is believed.[1] It has also received far less attention as compared to child malnutrition. Undernutrition forms one extreme of the continuum and affects the function and recovery of every organ system in the body, including muscle function, cardiorespiratory function, gastrointestinal function, immune system, and psychosocial functioning.[2] The consequences also comprise reduced work capacity and productivity, as well as decreased probability of reproductive success.[3] Obesity, which represents the other end of the continuum, is largely considered to be a preventable risk factor for chronic degenerative diseases.[4] Extensive research indicates that malnutrition often begins in-utero, and stretches throughout the life cycle. Although the nutrition of women is important for its own sake, it is imperative to acknowledge that malnutrition among women increases the risk of low birth weight babies and child malnutrition, thus creating an inter-generational effect.[5]

Routine collection of anthropometric data is a relatively simple and economical approach used for monitoring of nutritional status. In Indian public health programs, adult anthropometric measurements have mainly been used among pregnant women, to assess weight gain during pregnancy, and to correlate it with pregnancy outcomes. The identification of overweight and obese persons has also happened using these measurements, mostly in developed countries. Reduced body mass index (BMI) is an indication of thinness or underweight, and by itself can be used to identify chronic dietary energy deficiency.[6]

As per the National Family Health Survey – 4 (NFHS-4), malnutrition continues to be a prevalent problem in India; about 23% of women aged 15–49 years, and 20% of men aged 15–54 years are thin, that is with a BMI of less than 18.5kg/m2.[7] Comparing trends across years, it appears that as the proportion of malnourished adults has decreased, the proportion of overweight and obese adults has also risen drastically. The situation among marginalized tribal communities is even more alarming––more than 31% of women from scheduled tribes are categorized as thin according to NFHS-4, with 18.3% being categorized as moderately or severely thin (BMI <17.0). Meanwhile, the prevalence of overweight and obesity has increased among women from scheduled tribes over the decade (from 3.5% in NFHS-3 to 10% in NFHS-4).[7] Accounting for 8.6% of the total population of India according to the Census 2011, scheduled tribes continue to be plagued by a disproportionately high burden of undernutrition in comparison to the rest of the population.[8] The persistent burden offers an important opportunity for action on malnutrition in all its forms.

Several government programs, as well as civil society organizations are attempting to address this problem. One such innovative approach was a comprehensive strategy interlinking health and nutrition with agriculture and other livelihood practices. This intervention was implemented in nine blocks of five states––Kathikund and Sonua in Jharkhand, Darbha in Chhattisgarh, Balliguda, K.Nuagaon and Kolnara in Odisha, Samnapur and Mohgaon in Madhya Pradesh, and Jhalda in West Bengal. A community needs assessment (CNA) conducted at the beginning of the program revealed that most of the population in these areas are underserved, belong to scheduled tribes, scheduled castes or other backward classes, and suffer from poverty. The demographic picture found in the needs assessment is similar to that given by the Census, 2011 which states that the population in six of these blocks is majorly formed by scheduled tribes (ranging between 52.28% in Balliguda to 82.87% in Darbha).[8] The majority of the population in Jhalda and K.Nuagaon blocks belongs to communities other than scheduled castes and tribes. The CNA also revealed that food insufficiency was a common concern in the community. As part of the intervention, an effort was made to assess the health and nutritional status of the women in the intervention blocks using BMI as an indicator. This was done not only for assessment purposes, but also to familiarise the women with their own nutritional status.

This paper presents the nutritional status of women from six intervention blocks with the following objectives: (a) to identify the point prevalence of undernutrition, as well as overweight and obesity, in the described geographic areas, and (b) to compare these findings with data from a national survey.


  Materials and Methods Top


This descriptive cross-sectional study was conducted in villages of Darbha (Bastar district, Chhattisgarh), Jhalda (Purulia district, West Bengal), Mohgaon (Mandla district, Madhya Pradesh), Samnapur (Dindori district, Madhya Pradesh), Sonua (West Singhbhum district, Jharkhand), and Kathikund (Dumka district, Jharkhand) [Figure 1] where a health and nutrition intervention was already underway. The data were collected over 1 year between March 2016 and February 2017.
Figure 1: Data were collected from six blocks in four states of India

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Villages were selected through convenience sampling related to the intervention blocks and the presence of program personnel. Universal sampling was used for selection of participants where all women from the villages who were a part of the intervention and aged over 18 years were invited to have their BMI measured. In all, over 12,000 women had their BMI measured, of which 11,319 were considered to be valid. The data were collected intra-programmatically by persons trained in health and nutrition, known as mentors, using standard weighing scales and stadiometers. During the process, mentors were supported by change vectors: volunteers from within the local community who have been trained to conduct village-level meetings on health and nutrition. The data collection was part of an ongoing participatory health and nutrition program for which community consent was implicit. All participation was voluntary with no consequences in case of withdrawal.

The World Health Organization (WHO) classification for adults which was adapted from WHO, 1995, WHO, 2000, and WHO, 2004 has been further adapted for classification purposes.[9] The WHO classification further divides the underweight category into mild, moderate, and severe thinness. For our data, the underweight category has been similarly subdivided but overweight has been considered as an exclusive category, with no pre-obese subclassification. All three classes of the obese category were clubbed together.

Statistical analysis

Descriptive statistics, through Stata version 15.1 (India), were used to analyze the data.


  Results Top


The BMI data collected in this study gave us an opportunity to observe the nutritional status of women from marginalized communities, who are sometimes beyond the reach of conventional social interventions. It also allows us to compare the obtained data with that from NFHS – 4, a large-scale, multi-round survey conducted in a representative sample of households throughout India.[10] The NFHS provides comprehensive data on many themes, including nutritional status of adults and children. However, it is worth mentioning that the NFHS does not make a distinction between severe and moderate thinness among adults when presenting its findings.[7]

In this study, overall, 40.64% of the participants were considered to be underweight; the proportion of underweight women ranged from approximately 31%, in Sonua, to 49.5%, in Mohgaon [Figure 2]. Upon categorizing according to severity, 8.27% of all participants were severely thin, whereas the point prevalence of moderate and mild thinness was 10.08% and 22.29%, respectively [Table 1]. Overweight and obese women made up almost 4.1% of the population (3.69% and 0.4%, respectively). The highest point prevalence of obesity in this study was found in Jhalda (0.77%), whereas the lowest was in Kathikund (0.17%).
Figure 2: This graph displays the nutritional status of the study participants according to their geographical location. Overall, 8.27% of the participants were severely thin, 10.08% were moderately thin, and 22.29% were mildly thin. About 55% of the participants had normal BMI, whereas 3.69% were overweight. The prevalence of obesity was 0.4%

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Table 1: BMI status of all surveyed participants compared with NFHS – 4 data[7] (%)

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In comparison, as per NFHS – 4, about 23% of Indian women can be categorized as thin, and 21% are categorized as overweight or obese.[7] Women with normal BMI comprised about 55% in both the surveys. The NFHS-4 data for women from scheduled tribes, found the prevalence of total thinness to be 31.7% which is much lower than the proportion of total thinness in this study (40.64%). However, the combined proportion of moderate and severe thinness among women from scheduled tribes was similar in both NFHS – 4 (18.3%) and this study (18.35%).[7]

Comparing state-wise and district-wise data, the variations become even more obvious. In Jhalda, about 39% of the women were thin, with 7.07% and 10.07% being severely and moderately thin, respectively [Table 2]. The combined prevalence of severe and moderate thinness was far greater in Jhalda than in overall West Bengal (17.14% against 8.9%). Overweight and obesity was less common in Jhalda in comparison to the whole of West Bengal but was comparable to that found in Purulia district.[11]
Table 2: BMI status of women from Jhalda block compared with NFHS – 4 data[11] (%)

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Thin women made up a far greater proportion of the surveyed population in Darbha (48.70%), than in Bastar district (37.1%) and in Chhattisgarh state (26.7%) [Table 3]. The combined prevalence of severe and moderate thinness in Darbha (24.02%) was more than twice that at state level (10.1%), and almost double compared to the disaggregated data of scheduled tribes (12.7%).[12] Conversely, obese and overweight women together formed 3.26% of the surveyed population, as compared to 6.3% in Bastar district and 11.9% in Chhattisgarh overall.
Table 3: BMI status of women from Darbha block compared with NFHS – 4 data[12] (%)

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This study covered two blocks in Jharkhand––Kathikund and Sonua. Kathikund, in Dumka district, presented a greater proportion of thin women, that is, 42.19%, in comparison with the district (37.3%) and the state (31.5%) [Table 4].[13] Severe and moderate thinness was more prevalent at the block level (19.17%) relative to that at state level (12.17%). As per NFHS-4, the combined prevalence of severe and moderate thinness among scheduled tribes in the state is 13.3%, which is still lower than that found in Kathikund. When consolidated, the prevalence of overweight an obesity was at 3.55% in Kathikund (3.38% overweight and 0.17% obese), which is much lower than that found at the state-level (8.2% overweight and 2.1% obese).[13]
Table 4: BMI status of women from Kathikund and Sonua blocks compared with NFHS – 4 data[13] (%)

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Sonua, located in West Singbhum district, had a higher proportion of thin women (37.57%) in comparison with the district (32.4%) and the state (31.5%) [Table 4]. However, the combined proportion of severe and moderate thinness in Sonua (12.89%) was also comparable with that found at overall state level (12.7%) and among scheduled tribes of Jharkhand (13.3%).[13] Nevertheless, the point prevalence of severe thinness in Sonua block was found to be 6.22%. Meanwhile, the combined prevalence of overweight and obesity in Sonua (4.77% overweight and 0.27% obese) was half of that found at state level (8.22% overweight and 2.1% obese).[13]

Almost 50% of the women in Mohgaon were thin, with about 13% being in the severe thinness category [Table 5]. The combined prevalence of severe and moderate thinness in Mohgaon (24.60%) was more than twice that found at overall state level (11.5%).[14] It was also much higher than the prevalence of the same among scheduled tribes (13.6%) in Madhya Pradesh. The aggregated proportion of overweight and obese women was much lower in Mohgaon (2.59%; 2.35% overweight and 0.24% obese) than in Mandla district (7.6%) and the state (13.6%).[14]
Table 5: BMI status of women from Mohgaon and Samnapur blocks compared with NFHS – 4 data[14] (%)

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In Samnapur, close to 33% of women were categorized as thin (5.06% severely thin) [Table 5]. The comparison indicates that Samnapur had a higher proportion of thin women as compared to that at the state level (28.3%).[14] The combined proportion of severe and moderate thinness (13.4%) was also higher than that in the state (11.5%).[14] Meanwhile, the combined prevalence of overweight and obesity in Samnapur (4.19% and 0.2%, respectively) was less than one-third of that found at state level (10.5% and 3.1%, respectively).[14]


  Discussion Top


India, lauded as one of the upcoming economic powers in the world, is in the throes of an economic and nutrition transition.[15] This is especially relevant as the mentioned population is diverse, in terms of culture, economic backgrounds, and educational levels, as well as food systems. Increased access to processed foods and beverages, along with sedentary lifestyles, are considered to be characteristic of an obesogenic environment. Such an atmosphere has flourished in urban India in recent times and is progressing to rural India.[16] Simultaneously, the poor continue to show unacceptable levels of food insecurity.[17]

The differences in underweight and obesity between this study and NFHS-4 can be attributed to the coverage of each of the surveys, in terms of geography and demography. In particular, this study was conducted in some of the most marginalized communities in the states that are usually considered as “backward.” This is corroborated by the data obtained by the Census, 2011.[8]

As mentioned earlier, the NFHS does not report the sub-categories of severe and moderate thinness separately. This study makes this distinction deliberately to highlight the gravity of the situation: the level of severe underweight or thinness (BMI <16) among women from marginalized communities is unacceptably high. As compared to people with normal BMI, the mortality rates among persons with BMI <16 is significantly higher and indicates a situation of chronic hunger.[18],[19] This could be due to food intake lower than 850 Kcal for a prolonged period of time and is akin to starvation.[18] Evidence also exists to suggest that the risk of mortality from having a BMI <16 exceeds the risk of mortality from being overweight or obese.[20] According to Razak et al.[21], of 60 low- and middle-income countries, India has the greatest burden of BMI <16 among adult women (6.2%).

This study had a higher overall prevalence of severe thinness, ranging between 5.06% in Sonua and 12.93% in Mohgaon, which was striking. Other studies conducted amongst tribal populations in India have also found similarly alarming results.[22],[23],[24] What is apparent is that a mere perusal of the national-level, or even state- and district-level data can often be specious as it is inadequate to understand the “true” nutritional status of some populations, that is pockets of deprivation fail to be captured by averages and national-level data. The prevalence of overweight and obesity, although low in this study, indicates that the extremes of malnutrition are often co-located in these deprived pockets.

Some factors that would explain the observations have been studied by researchers. Kshatriya and Acharya[24] suggest that the change in food systems and rapid urbanization could be major contributors to the continued undernutrition and increased rate of obesity among tribal populations in India. With respect to food systems, the dietary diversity of these communities has become substantially restricted over time with the introduction of forest protection acts that curb the traditional practice of obtaining food from forests.[25] This loss of food sovereignty has led to high dependency on public distribution systems and shrinking of the traditional food basket, which might be a major cause of both undernutrition and obesity.[23] Kulkarni et al.[26] have postulated that apart from geographic factors, the relative food prices of food items like cereals and vegetables are significantly associated with the risk of being underweight and overweight/obese. Others propose that consumption of tobacco (especially smoked tobacco) and alcohol leads to higher odds of underweight incidence in rural communities.[27] It is also worthwhile to mention that caste, gender, economic standing, and political connectedness continue to play a role in food and nutrition security, with women from scheduled castes and scheduled tribes being the worst off in most situations.[27],[28],[29] This indicates that while some of the challenges to food and nutrition security are relatively new, others have persevered across generations. Income inequality, which is one such factor, continues to worsen across India and the World Bank estimates India’s GINI coefficient to be at 35.7% in 2011, up from 31.7% in 1993.[30],[31],[32],[33],[34] The communities covered in this study, mainly comprising of scheduled tribes and scheduled castes, suffer from the dual vulnerability of disenfranchisement and poverty. It is therefore possible that income inequality reinforces other known and unknown causal processes resulting in the high levels of malnutrition found in this study.[30] This is in line with the assertion of Neuman et al.[35] that “the poor stay thinner.”

With respect to our findings on obesity, the authors’ experience and other programmatic data suggest that the determinants in rural, tribal areas are mainly due to changing food systems, low food diversity with largely carbohydrate-rich diets, and penetration of the “junk food” market into these areas, rather than sedentary lifestyles. A recent paper which found that tribal households in eastern India consume mostly carbohydrates with little diversity supports this theory at least partly.[36]

Given the present scenario, the need of the hour is to mitigate the burden of malnutrition through effective, coherent, evidence-based policies with stringent implementation mechanisms and robust monitoring systems. Although such policies do exist in India, their implementation has been haphazard. The National Food Security Act, 2013, for example, aimed to provide legal entitlements for existing programs such as the Integrated Child Development Services, Mid-Day Meal Scheme, and the Public Distribution System. However, the apex court in the country found that even after four years the compliance to this legislation is “pathetic.”[37] Intersectoral convergence, with shared priorities and consistency of actions across all levels, is imperative for effective implementation. In addition, a system of accountability must be created.[38] However, for all of this to happen, the authors strongly recommend that national surveys such as the NFHS provide disaggregated data on the burden of severe thinness or malnutrition, especially among underserved and marginalized communities across the country.


  Conclusion Top


This paper highlights that severe malnutrition persists in pockets of the country, with unacceptably high prevalence of severe thinness among marginalized communities, as well as evidence that these communities are likely to suffer from a double burden of malnutrition. Severe malnutrition needs to be specifically tracked through the larger National survey to adequately highlight severe persistent food insecurity. With the NFHS-5 underway, it is highly recommended that severe malnutrition data, disaggregated till block-level, be made available for planning of national schemes and programs.

Future scope

There have been almost no studies in the past that cover a variety of vulnerable populations and use such a large sample size. As this data was collected as part of a program, it also offered the opportunity to tailor the intervention according to the findings. There are a few limitations to the BMI data collected in this study. Firstly, the data was not collected at the same time––therefore, seasonal variations may be present across the data. Secondly, the data were conducted as part of a field-based program rather than for research purposes. Thus, intra- as well as inter-observer differences and equipment errors are possible. A formal evaluation of the program in ongoing and will address many of these concerns. More rigorous, stand-alone research on the nutritional status of adults from vulnerable communities should be undertaken in the future and must lead to improved scope of action. Comparisons with unit-level NFHS data, which was beyond the scope of this paper, could be a potential objective in future studies.

Acknowledgement

The authors thank the women who voluntarily participated in this study and the local communities for extending their cooperation for the same. The Public Health Resource Network state team, block program officers, mentors, change vectors, and the local PRADAN teams were the implementers of the program and supported the data collection in the field. PRADAN provided financial support to the exercise.

Financial support and sponsorship

The authors did not receive financial or other support for this paper specifically. The program within which this study was undertaken was funded by Professional Assistance for Development and Action (PRADAN). Public Health Resource Network and PRADAN provided logistic support for this endeavor.

Conflicts of interest

The authors certify that they have no potential conflict of interest, financial, or otherwise, pertaining to the information discussed in this paper.

Patient consent statement

The authors certify that they have obtained all appropriate patient consent forms. In the form the patient(s) has/have given his/her/their consent for his/her/their images and other clinical information to be reported in the journal. The patients understand that their names and initials will not be published and due efforts will be made to conceal their identity, but anonymity cannot be guaranteed.



 
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    Figures

  [Figure 1], [Figure 2]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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