2. Methodology

2. METHODOLOGY

1. Theoretical Framework 1.1 Overview of Cultural Epidemiology Theoretical framework of Cultural Epidemiology as suggested by Weiss et al., (1992) was applied for the present study. The framework and methods of Cultural Epidemiology arose from efforts to achieve an effective interdisciplinary collaboration for health research by integrating the concepts and methods of anthropology and epidemiology. To make this integration possible, a framework and research instruments were developed from the insider’s perspectives known collectively as EMIC interviews (Weiss, 1997; 2001). EMIC interviews are instruments used for assessing representations of illness or specified health problems from the perspective of affected persons, their family members or community members.

Classical epidemiology concerns itself with the occurrence, distribution and determinants of disease in a population from the etic or professional point of view. This provides a way to identify priorities and to evaluate the impact of policies and programmes and these are essential in as much as findings from such research influence priorities and the allocation of resources. Such information however, is not enough to ensure that policy conforms to local needs and a different but complementary set of questions and ways to answer them are needed (Weiss, 2001). Cultural Epidemiology with its focus on the occurrence and distribution of local representation of illness experiences, meanings and behaviour (emic perspective) is positioned to play a supplementary role to basic epidemiology and anthropology. Cultural epidemiology therefore integrates these two perspectives to study locally valid illness representations and their distributions in the population to enhance local understanding and priorities for control (Weiss, 1997; 2001).

Useful guidance for local programme implementation requires consideration not only of the classical epidemiology of diseases and disorders, but also attention to the local experience of illness, its meanings, and both risk-related and help-seeking behaviours in the community (Weiss et al., 1992; Weiss, 1997; 2001). Medical

22 anthropology is especially important for identifying local concepts, categories, and context of illness, which may indicate questions about their impact on risk, vulnerability, clinical course and public health outcomes (Weiss et al., 1992). By clarifying the distributions of variables that characterise illness and how these variables affect risk, behaviour and selected outcomes, the epidemiology identifies practical implications of illness experience, meaning, and behaviour, thereby informing clinical practice and public health (Weiss et al., 1992).

1.1.1 Development of Cultural Epidemiological Framework Traditionally, medical anthropologists considered aspects of health and illness that are not addressed in the biomedical model of health and disease (Loewe, 2004). Medical anthropologists therefore distinguished illness from disease (O'Neil, 2006). Diseases and disorders are defined with reference to professional concepts, training or practice (O'Neil, 2006). These are often biomedical, but may also be psychological, based on symptom criteria in the absence of underlying theory of cause, or with reference to other professional concepts on which a medical system is based, such as humoral concepts in Ayurveda (O'Neil, 2006; Weiss et al., 1992). Illness on the other hand, refers to patients’ ways of experiencing and explaining their health problems (Weiss et al., 1992; Weiss, 1997). Professional etic and local emic concepts may overlap, and the same term may also have different professional and lay meanings, which may complicate communications between health professionals and the general population (Weiss et al., 1992; Weiss, 1997; 2001).

Elaborating this distinction between disease and illness, and recognizing that the distinction frequently created problems in the communications between patients and healers, anthropologist Arthur Kleinman formulated the concept of explanatory model to specify essential features of illness (Kleinman, 1980; 1995). As an emic elaboration of illness, the explanatory model framework was formulated to serve the interests of clinical history taking in the course of clinical consultations. The explanatory model framework takes its name from patients’ explanations of the nature of their suffering, often extending well beyond the scope of physical disease, and incorporating other non-biological features of the illness including social distress, financial disability, emotional suffering, fear and hopelessness, among others (Kleinman, 1980; 1995). The conceptual elements of the explanatory model

23 framework however were not well-suited for application in health research; cultural epidemiological categories enabled systematic investigation into patients’ explanatory models, and into the distribution of the experience, meanings and behaviours that constitute these models (Weiss et al., 1992).

Like medical anthropology, cultural epidemiology studies locally valid representations of illness-related experience, meaning, and behaviour, but it is particularly concerned with the distributions and effects of these representations in a population (Weiss et al., 1992). These representations are specified by variables and narratives that account for the experience of a designated illness or other health problem, its meaning and associated illness behaviour. Based on the explanatory model framework, cultural epidemiology addresses the primary components of the framework – illness experience, its meaning, and related behaviour and operationalizes these concepts into reliable, valid, categories suitable for comparison as patterns of distress (PD), perceived causes (PC), and help-seeking (HS), which together represent the nature of illness (Figure 3) (Weiss et al., 1992). a. Patterns of Distress (PD): PDs are reported categories of personal distress. These categories represent the total illness experience, reflecting both somatic symptoms and other troubling features such as social disruptions, financial disability, psychological burden etc. b. Perceived Causes (PC): Many people believe that multiple factors contribute to becoming ill and nearly everyone constructs some sort of story explaining why they are ill. c. Help seeking (HS): Most people take some sort of action when they fall ill, including using home remedies, consulting with family or friends, seeking advice from a traditional healer or midwife, prayer, fasting, attending a local clinic, purchasing drugs from a pharmacy, going to a private doctor etc. Help seeking is an account of patients’ help seeking behaviours, from self-help to outside help. It includes both formal and informal forms of care and advice.

Ethnographic research is an essential element of cultural epidemiology, and constitutes the first phase of cultural epidemiological research. All research occurs within an ethnographic context; in this context, illnesses are experienced, meanings

24 of illnesses are defined, and appropriate help seeking behaviours are agreed upon (Weiss et al., 1992; Weiss, 1997; 2001). Cultural epidemiological research, however, draws from this context to create a locally relevant study instrument (for the 2nd phase) capable of creating an account of what it is to be ill in that place, at a given time, under current circumstances (Weiss et al., 1992; Weiss, 1997; 2001). Thus, the integrated cultural epidemiological approach attempt to create linkages between disciplines that formerly had none and by doing so, to create a dialogue between those locally afflicted by disease, the researchers who address it, and the policy makers / clinicians etc. who implement change (Weiss et al., 1992; Weiss, 1997; 2001).

Cultural epidemiology research typically uses Explanatory Model Interview Catalogue (EMIC) interviews, which are semi-structured interviews that are locally adapted to assess representations of illness from the perspective of affected persons with a designated health problem (Weiss et al., 1992; Weiss, 1997). EMIC refers to and is based on the formulation of an illness explanatory model that systematically clarifies the experience of illness from the point of view of the people who are directly affected. Individual variations in the socio-cultural meaning of illness have been recognized as important determinants in help seeking, choice of treatment, ability to cope, use of support and the quality of life (Weiss et al., 1992; Weiss, 1997). Behind the concept of EMIC is the recognition that individuals and their families often have their own concepts and categories for illness, which may differ from those, held by clinicians / professionals (Weiss et al., 1992; Weiss, 1997). How ill health is perceived, how experiences are interpreted and how choices are made about treatment may all form part of the total picture that needs to be taken into account (Weiss, 1997).

The different views captured by EMIC can be related to the ethnographic terms ‘emic’ (ideologies of local communities) and ‘etic’ (ideology of professionals outside local communities) (Weiss et al., 1992; Weiss, 1997). Essentially, it is the dichotomy between ‘local insider’ and ‘professional outsider’ that is of interest (Kleinman, 1980; 1995). The concept and opposition represented by ‘emic’ and ‘etic’ perspectives in EMIC provide the framework for understanding the

25 relationship between biomedical models and people’s experiences (Weiss et al., 1992; Weiss, 1997).

ILLNESS (Malnutrition)

EXPERIENCE MEANING BEHAVIOUR

Operational Formulation of EMIC

PATTERNS OF PERCEIVED CAUSES HELP SEEKING DISTRESS (PD) (PC) (HS)

 Illness related problems  Foods  Family support and & concerns  Sanitation, hygiene, home remedies  Name of the illness, contamination, & health  Private practitioners and symptoms, & anticipated habits public clinics outcome  Infection, prior illness,  Western styled health  Psychological, social, & constitutional factors professionals, para- economic impact  Humoral imbalance professionals &  Stigma, disclosure, &  Magico-religious forces specialists self-esteem  Heredity  Traditional healers of  Marriage prospectus &  Retribution for previous various types marital relations deeds  Past experience and current preferences CATEGORIES, NARRATIVE, AND SOCIAL CONTEXT  Explanatory models of illness other than current problem  Focus of illnesses with a range of cultural meanings  Relationship between mind and body  Ideas about illness affecting the subject, but distinct from personal experience of presenting problems

Figure 3: Cultural Epidemiology Framework; Making the Concepts Experience, Meaning and Behaviour Operational As PD, PC, HS (Weiss; 1997)

Data sets generated from these EMIC interviews typically include quantitative variables and qualitative probes, which are cross-referenced for analysis to clarify key features and answer important questions about illness experience and its practical implications. EMIC has emerged through studies in tropical diseases (e.g. Tuberculosis, Leprosy etc.) (Maske et al., 2015; Weiss et al., 2008) and mental illness (Raguram et al, 2004). Couple of studies on childhood diarrhoea have also used EMIC framework (Morankar, 1994; Choprapawon et al., 1991).

1.2 Overview to Household Food Insecurity Access Scale (HFIAS) Food security exists when all people, at all times, have physical and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life. Food security can be examined at various levels, i.e. global, national, regional, household, and individual. Food security at the national or regional level does not necessarily indicate food security among communities, households, and individuals. Achievement of household food security does not necessarily account for the security at individual levels because of factors, such as gender discrimination.

Malnutrition is the most serious consequence of food insecurity. Adult malnutrition results in lower productivity on farms and in the labour market. In women, it results in foetal malnutrition and low birthweights of babies. Childhood nutritional deficiencies are responsible, in part, for poor school enrolment, absenteeism, early dropout, and poor classroom performance, with consequent losses in productivity during adulthood (Leiva et al., 2001; Alderman et al., 2006; Liu and Raine, 2006). Not only does food insecurity in itself have deleterious effects on households and individuals but efforts at achieving food security may also pose a heavy economic toll if households must spend most of their income on obtaining food (Alderman et al., 2006; Liu and Raine, 2006). On a household level, presence of food insecurity probably suggests a high degree of vulnerability to a broad spectrum of consequences, including psychosocial dysfunction in children, socio-familial problems, and overall poor health status. As per the State of Food Insecurity in the World (2012) India is home to more than 217 million undernourished people. The Global Hunger Index for India in the year 2018 was 31.1, which placed it in the “serious” category (ranked 103rd, out of the 119 qualifying countries) (GHI, 2018).

Various studies have been conducted to assess food insecurity at the global level; however, the literature is limited as far as India is concerned. In India around 19 published and unpublished studies have used experience-based HFIAS between January 2000 and June 2015. Lack of sufficient studies in tribal areas and amongst tribals on the burden of the food insecurity problem poses a hurdle in formulating strategies to combat this epochal issue. Taking this into consideration, the present study with the use of HFIAS documented the prevalence of food insecurity at the household level in the Warli and Thakur tribal settlements of the study area and the factors determining its existence. The HFIAS was integrated with the cultural epidemiological framework and was used along with the EMIC survey tool.

2. Study Site The state of Maharashtra being the fifth largest tribal populated state in India, has 47 tribal communities that reside in hilly regions of the state (Singh K.S, 1997; Karve, 1968). Table 3 and Table 4 show decadal growth of tribal population in Maharashtra.

Table 3: Table Showing Tribal Population in the Maharashtra Years of Total Tribal Rise in Tribal Census Population Population 1971 29,54,249 -- 1981 57,72,038 95.38% 1991 73,17,477 26.77% 2001 85,77,000 17.21% 2011 98,82,400 15.21%

The area in the state of Maharashtra where the tribal resides is divided in three parts geographically (Enthoven, 1922a; 1922b). 1. Sahyadri Region: In the topographical higher areas of Thane, Palghar, Nasik, Pune, Ahmednagar, Raigad districts, we find different tribes like Mahadev Koli, Dhore Koli, Katkare, Warali, Thakar, Kokana etc. 2. Satpura Region: Dhule, Jalgaon, Amaravati, Aurangabad districts are located in the Satpura mountain ranges in which Dhanaka, Bhilla, Yawachi, Gawit, Kokana, Koraku, Dubala, Tadavi, Pawara tribes live in majority.

3. Gondvan Region: The province around east Maharashtra, Madhya Pradesh, Andhra Pradesh, Orissa was occupied by the Gond tribe. This whole area is known as Gondvan province. In the mountainous and forest area of the Vidarbha such as Chandrapur, Bhandara, Gadchiroli, Yawatmal, Nagpur districts we find Gond, Madiya, Kolam, Thakar, Paradhi, Andha, Gavit, Malhar, Koli, Banjara, Kalkari, Pardhan tribe.

Table 4: Talukas and Their Population at 2001 and 2011 Population Population Taluka Census 2001 Census 2011 Vasai-Virar 795,863 1,343,402 Palghar 454,635 550,166 Dahanu 331,829 402,095 Talasari 121,217 154,818 Jawhar 111,039 140,187 Mokhada 67,319 83,453 Vada 142,753 178,370 Vikramgad 114,254 137,625

The fieldwork of the present study was conducted in Palghar district of Maharashtra (Figure 4). Palghar is the 36th district of Maharashtra which came into existence on 1st August 2014 and was carved out from the Thane district. It is spread between the west coast of the Arabian Sea and the rows of Sahyadri Mountains that are east of the Northern District of Palghar.

PALGHAR

Figure 4: Map of Maharashtra with District of Palghar

The district comprises 8 talukas: Palghar, Vada, Vikramgad, Jawhar, Mokhada, Dahanu, Talasari and Vasai-Virar comprising urban, rural as well as tribal population. Palghar District has 4,69,699 hectares of the total geographical area in a total 1008 villages and 3818 sub-villages as well as 477-gram panchayats. In the district, the literacy rate is 66.65% with male literacy being 72.23% and female literacy rate being 59.28% (Census, 2014a; 2014b). As per 2011 census, the district had a population of 2,990,116. The talukas with their relative populations at the 2001 and 2011 (Census, 2001; 2014b) are as follows:

Palghar is the northernmost part of Maharashtra's Konkan lowlands. It comprises the wide amphitheatre such as the Ulhas basin on the south and the hilly Vaitarna valley in the north, along with the Sahyadri plateaus and slopes. From the steep slopes of the Sahyadri in the east, the topography changes to lower elevation in the Ulhas valley through a succession of plateaus in the north and center of the district. The distance by road from the different parts to Palghar headquarters is as follows: Khodala 138 km, Mokhada 112 km, Jawhar 75 km, Vikramgad 60 km (Census, 2014a).

The main river that flows through the district is the Vaitarna. The river has many tributaries, the most important of which are Barvi and Bhatsa, Pinjal, Surya, Daherja and Tansa. Vaitarna, Konkan's largest river, originates in Tryambak hills situated in Nashik district opposite the river Godavari's source. The river flows across the talukas of Shahapur, Vada and Palghar and enters the Arabian Sea through a wide estuary off Arnala. The Vaitarna River is 154 km long and has a drainage area that covers practically the entire northern part of the district. The Ulhas river that flows to the Arabian sea is the Vasai creek, the southern border of the district. Arnala Island is located in Vasai Taluka, at the entrance to the Vaitarna estuary (Census, 2014a).

Palghar has India's first nuclear power plant in Tarapur. Boisar's industrial town is also home to one of Maharashtra's largest industrial areas at Tarapur MIDC. Maharashtra's largest fishing port is Satpati with Dahanu, Arnala, Vasai and Datiware also being major fishing ports. Dahanu is best known all over India for its chickoo production. Every year a special Chickoo festival is held at Bordi Beach in

Dahanu. The Western Railway network passes through the district's Vasai, Palghar and Dahanu talukas. Western Express Highway (NH48) passes through Manor and Chilhar to enter the district of Palghar (Census, 2014a).

There are many different ethnic tribal groups having some population in the district. However, the five major tribes are Warli, Koli Dhor, Thakur, (also known as Thakar) Katkari (also known as Kathodi, Dhor Kathodi, Dhor Kathkari, Son Kathodi, Son Katkari) and Mahadev Koli. Table 5 gives a brief description about these 5 major tribes found in the district. These five tribes together constitute 90.03% of the total Schedule Tribe (ST) population of the district.

Table 5: Brief Description of the Five Major Tribes of Palghar District

Warli: The term Warli has been derived from the word viral meaning up landers, who lived in small groups under their own headmen. The language they speak among themselves is Warli, and it belongs to the Indo-Aryan language family. They are also conversant with Gujarati and Marathi. They use Devanagari script. They are non-vegetarian but avoid beef and pork. Their staple food is rice, supplemented with jawar and wheat. Milk consumption is negligible. They are fond of alcoholic drinks prepared from molasses (Tribes of India, 2013).

Dhor Koli: A Scheduled Tribe, the Koli Dhor has derived their name from the word dhor, meaning cattle. The Koli Dhor are divided into two endogamous (marry within) occupational divisions, namely Dhor Koli and Tokra Koli, and each is divided into various clans. Their traditional vocation has been the tanning of cattle hides, but today many are involved with other agricultural pursuits. Community control is accomplished jointly by the community head and the village heads, both being hereditary positions. Their religion combines some traditional as well as Hindu elements (Tribes of India, 2013).

Thakur: They are concentrated in the Thane district of Maharashtra. They are spread over the Thane, Nasik and Ahmednagar districts of the state. They speak a corrupt from of Marathi an Indo-Aryan language and use the Devanagari script. They are basically non-vegetarians and are very fond of dry fish. The meat of wild animals is also consumed. Jowari, rice, nagli and wheat are their staple food grains, consumed with pulses and vegetables. They also consume wild roots, tubers, leaves and fruits. Some of them smoke beedis, chew loose tobacco and consume liquor, but the Ma Thakur abstains from liquor and non-vegetarian food (Tribes of India, 2013).

Katkari: They are bilingual, speaking the Katkari language, a dialect of the Marathi language with each other and speaking Marathi with the Marathi speakers who are a majority in the populace where they live. In Maharashtra the Katkari have been designated a particularly vulnerable tribal group (PVTG). The Census of India 2001 indicates that Maharashtra is home to 235,022 Katkari, mainly in Raigad, Thane and Palghar districts. Small numbers of Katkari also live in the states of Gujarat, Karnataka and Rajasthan (Tribes of India, 2013).

Mahadev Koli: Generally, 'Koli' means a fisherman but the Mahadev Koli people's primary occupation is agriculture. The Mahadev Koli derives their name from their god Mahadev (Shankar / Shiv) and lives in the Mahadev hills of Maharashtra. They speak Marathi and use the Devanagari script. Their staple food consists of rice, nagli, varai and wheat. Other than agriculture they are also involved in cattle breeding, dairy and poultry farming and wage labour as subsidiary occupations (Tribes of India, 2013).

The present study was undertaken in Mokhada taluka of Palghar district (Figure 5). The Mokhada block is listed as a Scheduled Area1 and has a population of 83,453 as per 2011 census (Census, 2014a). Mokhada has one Nagar Panchayat, 27 Gram Panchayats, 59 villages and a total of 208 padas (hamlets). Table 6 gives details of the population (total population, child population and ST population) of all villages in Mokhada taluka. Mokhada taluka was selected for the study due to the following reasons: 1. Predominance of Schedule Tribe (ST) population. The taluka constitutes more than 90% of the ST population. 2. Prevalence of malnutrition in children under the age of 5 is high for this taluka. Data for the same available from public sector / government records at www.icds.gov.in30.

Figure 5: Map of Mokhada Taluka in Palghar District

1 The criteria followed for declaring an area as Scheduled Area are preponderance of tribal population; compactness and reasonable size of the area; under-developed nature of the area; and marked disparity in economic standard of the people.

Table 6: Details of Total, Child & ST Population of All Villages in Mokhada Taluka Total Total Total ST Sr. No Villages Population Child (0-6) Population 1 Adoshi 941 166 864 2 Amale 263 51 263 3 Ase 4139 927 4087 4 Beriste 1794 286 1729 5 Botoshi 1258 268 1253 6 Brahmagaon 827 131 822 7 Charangaon 344 73 344 8 Chas 2609 501 2574 9 Dandwal 972 232 969 10 Dhamani 671 142 664 11 Dhamanshet 1536 293 1480 12 Dhondmaryachimet 534 105 534 13 Dhudgaon 828 132 752 14 Dolhare 1460 266 1299 15 Ghanval 1419 201 1401 16 Ghosali 1309 264 1306 17 Gomghar 1527 296 1512 18 Gonde Bk 2497 420 2354 19 Gonde Kh 1137 200 1046 20 Hirve 1780 261 1692 21 Jogalwadi 999 166 954 22 Kaduchiwadi 801 130 801 23 Kalamgaon 691 116 675 24 Karegaon 1048 159 961 25 Karol 945 165 932 26 Kashti 570 105 568 27 Kevanale 821 135 819 28 Khoch 1890 393 1806 29 Khodala 3178 504 1965 30 Kiniste 1303 172 1267 31 Kochale 1077 154 664 32 Koshimshet 2207 401 2168 33 Kurlod 1394 274 1368 34 Lakshminagar 582 107 581 35 Mokhada 8224 1282 5637 36 Morhande 2667 470 2512 37 Nashera 1080 227 1018 38 Nilmati 601 93 569 39 Osavira 1036 220 1002 40 Pachaghar 648 104 626 41 Palsunde 1628 256 1590 42 Pathardi 963 172 961 43 Pimpalgaon 917 154 915 44 Poshera 4417 831 4180 45 Rajivnagar 740 156 735 46 Sakhari 1462 243 1446 47 Saturly 2141 406 2098 48 Sawarde 690 128 681 49 Sayade 2083 347 2059 50 Shastrinagar 590 94 590 51 Shirasgaon 905 168 882 52 Shirson 650 146 646 53 Shivali 767 127 759 54 Suryamal 1196 194 1108 55 Swaminagar 687 111 647 56 Udhale 1267 194 1261 57 Vashind 433 57 433 58 Wakadpada 787 101 756 59 Washala 1523 201 1257 Census of India, 2011

3. Study Design and Study Tools The present study was funded by the Indian Council of Medical Research (ICMR), Department of Reproductive and Child Health (Letter No. 5/7/1087/2013/-RCH) through a grant in aid for ad-hoc research project. The study was conducted amongst Warli and Thakar communities of Mokhada taluka due to the following reasons: • National reports and studies such as NHFS, DHS etc. limits our understanding of malnutrition to just ST community. • Recent work highlights inter-tribal variation in malnutrition (MAAS, 2013). • Population wise Warli and Thakar are the pre-dominant tribal groups in Palghar region and Mokhada taluka also has high concentration of Warli and Thakar groups.

The initial plan of the study was to do conduct it in two different geographical locations to understand variations in undernutrition experiences, meanings and health seeking. Two tribal dominant settings of Nandurbar and Palghar (under Thane at that time) were considered for undertaking the study. This was based on some interesting findings from an earlier malnutrition intervention research study undertaken in these two settings (MAAS, 2013). Previous work has highlighted the inter-tribe variation in malnutrition among under-3 years’ tribal children. Though within the tribal population there was reduction in Grade III and IV malnutrition in children, this reduction was not uniform across all tribes suggesting that inter-tribal variations in malnutrition are predominantly consistent.

The current project funded by the ICMR aimed at addressing the observed inter- tribal variation in undernutrition experiences which should be one of the key strategies in the coming years. Such an integrated tribal development approach and focus would help in making the dent in the problem of undernutrition in tribal areas which is a priority tribal public health problem and should remain the focus of all future innovative interventions. The purpose of this study was to understand whether such variations about malnutrition related experiences, meaning and health seeking exist among the various tribes in Maharashtra due to their geographical and cultural differences. Accordingly, the project proposal was put up for funding to the ICMR but the grants received was not enough to undertake the study in two settings; hence

34 we had to narrow the scope down to only Palghar and among Thakar and Warli tribal groups

A study to appreciate the insiders’ perspective (emic) on topical issues of experience, meanings and behaviour was felt necessary to better understand the local undernutrition related condition in children under five years of age. To achieve this, various data collection methods were used. Figure 6 gives details of the study design and sample size achieved through the two phases of the study. Field data were collected between April 2015 and April 2016 (13 months). In all the study was conducted in 13 villages and its 26 padas (hamlets). The study is descriptive in nature and was carried out using multiple methods of data collection in two phases. The first part of the study, conducted from April to November 2015, was an ethnographic study. Various data collection techniques used for this part of the study are listed below:

STUDY PHASES

PHASE I PHASE II

ETHNOGRAPHIC EMIC SURVEY PHASE PHASE

INITIAL FIELD VISIT n=20 PILOT SURVEY

QUALITATIVE STUDY n=303 Listing MAIN SURVEY

in three rounds in two rounds

59 FGD respondents 2 sitting IDIs 1st round 2nd round

FGDs IDIs n=72 n=92 (n=07) KIIs (n=15) (n=12)

n=34 TOTAL SAMPLE n=164

Figure 6: Diagrammatic Presentation of the Study and Sample

3.1 Ethnographic Study - Phase I Phase I was an ethnographic study which was carried out from April 2015 to November 2015 (8 months) and used the following data collection tools and techniques. 3.1.1 Focus Group Discussions (FGDs): With general community members and mothers of normal and undernourished children using an FGD guide along with vignettes and pictorial depictions (Figure 7) of major sections (Annexure 1, Annexure 2, Annexure 3 and Annexure 4: Vignettes and Pictorial Depictions). FGDs were primarily used for ethnographic data and to guide construction of EMIC interview schedules for interviewing mothers of malnourished children in Phase II of the study (Annexure 5: Focus Group Discussion Guide).

Picture 1: Sanitation & Childhood Illnesses Picture 2: Notions about food during Pregnancy

Picture 3: Notions about Breastfeeding Picture 4: Perception about Child Malnutrition

Figure 7: Pictorial Depictions Used during FGDs and IDIs

3.1.2 In-depth Interviews (IDIs): Interviewing mothers of Moderately Underweight (MUW) and Severely Underweight (SUW) children using interview guide along with

vignettes and pictorial depictions of major sections. IDIs were conducted to document individual experiences of mothers of undernourished children, their knowledge and awareness about undernutrition symptoms, concerns, and causes, help seeking and preventive strategies (Annexure 5: In-Depth Interview Guide).

3.1.3 Key-Informant interviews (KIIs): Interviewing health care providers AWW, PHC- doctors etc. using KII guide. KIIs were undertaken to understand the malnutrition scenario in Mokhada, the KIIs perception of local communities and their knowledge/understanding about child malnutrition (undernutrition), its causes and treatment. The availability of different services and its utilization for malnutrition in the study taluka, information, education and communication (IEC) related activities around malnutrition etc. (Annexure 6: Key Informant Interview Guide).

Picture 1: Focus Group Discussion in Progress Picture 2: In-depth Interview in Progress

Picture 3: Key Informant Interview in Progress Picture 4: Survey Interview in Progress

Figure 8: Pictures of Various Methods of Data Collection during Study

The fieldwork during this phase was planned and carried out in three rounds (Figure 8). During this phase of data collection, there were interactions with Anganwadi

37 workers (AWW), pregnant and lactating women and mothers of children under five years of age from the ‘Warli’ and ‘Thakar’ community. During these interactions’ attempts were made to get insights into the community’s understanding about various illnesses which affect children, local terms used for various illnesses, dietary practices during pregnancy and lactation, community’s understanding about malnutrition among children and its associated problems, help-seeking, role of Anganwadi etc.

A total of six villages were selected for the three rounds of data collection. Three villages were from AUK2 intervention sites while other three were non-AUK sites. Villages with dominant presence of Warli and Thakar community were selected purposefully for this phase of data collection. In villages where the dominant community was the ‘Thakar’, FGD and IDI were conducted only with this community, while in villages which were dominated by ‘Warli’, the FGD and IDI were conducted accordingly. Some villages had a mix of both ‘Thakar’ and ‘Warli’ so selection of respondents for FGD and IDI for this village was also a mix of both these communities. This was done to address the methodological issue – whether there is any variation in the understanding and/or perception of malnutrition and related problems between these two communities.

During the three rounds of data collection, the study team interacted with pregnant and lactating women and mothers of children under five years of age with the help of AWWs. The study team first contacted the AWWs of the selected villages via phone; this was facilitated by the AUK coordinator working for Mokhada block. During the phone call, an appointment was fixed with the AWW for an interview (KII), which was conducted using an interview guide. Post the interview and explaining the purpose of the study, with the help of the AWW, a list of pregnant and lactating women and mothers of under five children was prepared from the Anganwadi records. The AWW was requested to call 6-8 respondents from the list for an FGD the following day. During the FGDs (using FGD guide), 2-3 respondents were shortlisted (who spoke and articulated well) for IDI (using IDI guide). The above-mentioned strategy was adopted for all six villages the team visited.

2 AUK = Adivasi Uttan Karyakarm is an intervention project focusing on reducing malnutrition among tribal children in tribe dominant seven districts and nine tehsils of Maharashtra covering all major tribal groups. The taluka of Mokhada is also part of AUK intervention project.

3.2 EMIC Survey - Phase II A pilot survey was conducted in Jawhar taluka3 on an overall sample of 20 mothers of nourished children through survey interviews between 9th December and 14th December 2015. The purpose of the pilot was to test the EMIC survey tool for logical flow and continuity in questions and the appropriateness of Marathi language used for interviewing tribal mothers during the survey. The 9 item questions and the 9 occurrence questions on HFIAS were translated to Marathi and were also piloted before being used for the final study. The main survey phase was carried out from January 2016 to April 2016 (4 months) in two rounds.

As stated earlier, Weiss et al., (1992) EMIC framework was the guiding principle for designing the interview schedule for interviewing mothers of undernourished children. The EMIC framework for this study refers to and was based on the formulation of an explanatory model of undernourished status that systematically clarifies the experience of illness from the point of view of the people who are directly affected (mothers of undernourished child). The EMIC framework was applied to understand malnutrition-related problems as expressed by mothers, its perceived causes, preferences for help seeking and treatment, general beliefs about malnutrition (hygiene and sanitation practices etc.) and agriculture production and consumption (access to food) and household food security. The following two tools were used during this phase: 3.2.1 Semi-Structured Interviews (SSIs): Interviews of mothers of malnourished children during the EMIC survey were carried out using an interview schedule (Annexure 7: EMIC Survey Interview Schedule). The schedule also included the Household Food Insecurity Access Scale (HFIAS). HFIAS is a 9-item scale, the method of which is based on the idea that the experience of food insecurity (access) causes predictable reactions and responses that can be captured and quantified through a survey and summarized in a scale. 3.2.2 Observation Checklist: Used to collect household related information e.g. presence of toilet, bathroom, kitchen garden, type of house, cooking area, water storage etc. (Annexure 8: Observation Checklist)

3 Jawhar taluka is adjacent to Mokhada taluka, have same geographical similarities and had the same tribal groups

3.2.3 Household Food Insecurity Access Scale (HFIAS) The Household Food Insecurity Access Scale has been used in several countries and appears to distinguish the food secure from the food insecure households across different cultural contexts (Chakraborty, 2006; Chinnakali et al., 2014). The questions in the HFIAS represent the household food insecurity experience and can be used to categorise households and populations on a continuum, from food secure to severely food insecure. The method is based on the idea that the experience of food insecurity causes predictable reactions and responses that can be quantified and summarized in a scale (FAO, 2003; Coates et al., 2007).

The HFIA prevalence indicator categorizes households into four levels of household food insecurity: food-secure, mildly food-insecure, moderately food-insecure and severely food-insecure. Households were categorized as increasingly food-insecure as these responded affirmatively to more severe conditions since they had experienced those conditions more frequently.

The questions contained in HFIAS were asked with a recall period of four weeks (30 days). The respondent was first asked an occurrence question, i.e. whether the condition in the question happened at all in the past four weeks (with the provision of ‘yes’ or ‘no’ response). If the respondent answered ‘yes’ to an occurrence question, a frequency-of-occurrence question was asked to determine whether the condition happened rarely (once or twice), sometimes (three to 10 times), or often (more than 10 times) in the past four weeks. The operational definitions used in the current study were as follows: 1. Food-secure: A household was labelled ‘food secure’ when the members ‘rarely’, in the past four weeks, worried about not having enough food and had replied ‘no’ to question number 1.2 to 1.9 (Coates et al., 2007) (Table 7) 2. Mildly food-insecure: The members of the household worried about not having enough food sometimes or often, and/or were unable to eat preferred foods, and/or ate a more monotonous diet than desired, and/or ate some foods considered undesirable but only rarely (Coates et al., 2007). 3. Moderately food-insecure: The household members sacrificed quality more frequently by eating a monotonous diet or undesirable foods sometimes or often, and/or had started to cut back on quantity by reducing the size of meals or number of meals, rarely or sometimes (Coates et al., 2007).

4. Severely food-insecure: The individuals in the household had to cut back on meal-size or number of meals often, and/or experienced any of the three most severe conditions (running out of food, going to bed hungry, or going a whole day and night without eating) (Coates et al., 2007).

Table 7: Household Food Insecurity Access Scale (HFIAS) Household Food Insecurity Access Scale (HFIAS) Coding Categories 1.1 “In the past four weeks, did you worry that your household (1. Yes 2. No) would not have enough food?”

1.1.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.2 “In the past four weeks, were you or any household members

not able to eat the kinds of foods you/they preferred because of a (1. Yes 2. No) lack of resources?”

1.2.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.3 “In the past four weeks, did you or any household members

have to eat a limited variety of foods due to a lack of (1. Yes 2. No) resources?”

1.3.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.4 “In the past four weeks, did you or any household member have

to eat some foods that you really did not want to eat because of a (1. Yes 2. No) lack of resources to obtain other types of food?”

1.4.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.5 “In the past four weeks, did you or any household member have

to eat a smaller meal than you felt you needed because there (1. Yes 2. No) was not enough food?”

1.5.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.6 “In the past four weeks, did you or any household member have

to eat fewer meals in a day because there was not enough (1. Yes 2. No) food?”

1.6.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.7 “In the past four weeks, was there ever no food to eat of any

kind in your household because of lack of resources to get (1. Yes 2. No) food?”

1.7.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.8 “In the past four weeks, did you or any household member go to sleep at night hungry because there was not enough food?” (1. Yes 2. No)

1.8.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often) 1.9 “In the past four weeks, did you or any household member go a

whole day and night without eating anything because there was (1. Yes 2. No) not enough food?”

1.9.1 “How often did this happen?” (1. Rarely 2. Sometimes 3. Often)

3.2.4 Household Hunger Scale (HHS) The HFIAS provides operational guidance for collection and tabulation of the Household Hunger Scale (HHS), a simple indicator to measure household hunger in food insecure areas. This means that the HHS produces valid and comparable results across cultures and settings so that the status of different population groups can be described in a meaningful and comparable way - to assess where resources and

41 programmatic interventions are needed and to design, implement, monitor, and evaluate policy and programmatic interventions. The HHS is most appropriate to use in areas of substantial food insecurity. In those settings, the HHS can be used for a variety of objectives, including to: 1. Monitor the prevalence of hunger over time across countries, or regions, to assess progress towards meeting international development commitments 2. Assess the food security situation in a country, or region, to provide evidence for the development and implementation of policies and programs that address food insecurity and hunger 3. Monitor and evaluate the impact of anti-hunger policies and programmes, including those that are funded by a specific donor across a number of cultures and countries  Provide information for early warning or nutrition and food security surveillance  Inform standardized food security/ humanitarian phase classifications.

4. Sample and Sampling Strategy 4.1 Strategy for Ethnographic Study - Phase I In the first phase of the study, FGDs were undertaken among general community members and mothers of malnourished children. In-depth interviews of mothers of malnourished children using an interview guide, were also undertaken during this phase. The selection of respondents was purposive and was based on the AWW’s cognizance about the respondent’s ability to interact and give information on the issues enquired. FGDs and IDIs were conducted in 6 villages. Two FGDs were conducted with only Warli members as participants and two with only Thakar members. Two FGDs had a mix of both Warli and Thakar community members. KIIs of AWWs, Child Development Project Officer (CDPO) and Primary Health Centre-Medical Officer (PHC-MO) were also undertaken during this phase. Table 8 highlights details of the study components and the samples which were covered during this phase. The findings of this phase greatly helped in designing the interview schedule and components of observation checklist for the interviews with mothers in Phase II.

Table 8: Phase I - Study Components and Sample Study Population Number Focus Group Discussions with General Community Members & Mothers 7 (6-10 respondents for each FGD) Key Informant Interviews of AWW, Mukhya Sevika, PHC-MO, etc. 12 In-depth Interviews of Mothers of MUW and SUW children 15

4.2 Strategy for EMIC study - Phase II The EMIC interviews with mothers of malnourished children were undertaken by using semi-structured survey interview tool during this phase of the study. For the main survey the Anganwadis in tribal dominant areas of the selected taluka (Mokhada) were first listed with the help of ICDS officials. The list of underweight children was collated from the data available with Anganwadis (n=26) from 13 villages of Mokhada taluka. The 13 villages predominantly had Warli and Thakar populations, so the study was restricted to these villages. Distinct lists of children who were graded as Moderate Underweight (MUW) and Severe Underweight (SUW), which was the inclusion criteria4 for selection of participants for EMIC survey, were prepared. The lists facilitated the researchers to establish contact with mothers of MUW and SUW children through the AWW.

Table 9 highlights details of the study population which was covered during this phase. A total of 303 (Warli=179 and Thakar=124) underweight children were listed. The sample size calculation was based on comparison of mean prominence of categories of distress, perceived causes and help seeking for Warli-Thakar differences. The detection of a difference of 0.5 between prominence means with equal standard deviations of 1.5 at 95% significance and 80% power required a sample size of at least 150 individuals for the study. Ten percent was added to this sample size to compensate for missing data, incomplete interviews, bad quality of interviews etc. The selection of samples within each tribe was random using online randomizer software5. A total sample of 164 was thus covered for the final study. The survey tool was piloted in Jawhar taluka on 10% sample based on the final sample size. A total of 20 pilot interviews were undertaken after which the EMIC survey tool was finalised for the final data collection.

4 Needed to record actual experiences regarding symptoms, concerns, causes and health seeking 5 Research Randomizer available at https://www.randomizer.org/

Table 9: Phase II - Study Population and Interviews Study Population Listed Interviewed Mothers of MUW children 259 137 Mothers of SUW children 44 27 Total 303 164

5. Data Management and Analysis 5.1 Analysis of Qualitative Data - FGDs, IDIs, KIIs and EMIC narratives Narrative data from FGDs, IDIs, KIIs and EMIC survey interviews were entered in a word processor in Marathi using a Unicode Devanagari font. Data were imported into MAXQDA 10 (VERBI Software, Germany). FGDs, IDIs and KIIs were manually coded while EMIC survey interviews were coded using pre-processor techniques for automatic first-level/ broad coding for narratives in response to specific questions. Thematic similarities and differences between narratives of Warli and Thakar, illiterate and educated and food insecure and food secure households were systematically analysed. Variables from the quantitative data set were imported into MAXQDA to enable selection of narratives of interest, facilitating the integrated analysis of quantitative and qualitative data.

5.2 Analysis of Household Food Insecurity Access Scale (HFIAS)6 The HFIAS yields information on food insecurity at the household level (Coates et al., 2007). Reliability analysis of the 9-item scale was done both during the pilot and the main studies. The analysis of the 9-item scale begins with anxiety related questions about food supply, which is further followed by questions about the quality and quantity of food consumed. The last three questions enquire about chronic hungry (Coates et al., 2007). Respondents were asked to answer either ‘Yes’ or ‘No’ to the nine questions, then in order to understand the frequency of the particular question ‘how often this happened’ was asked, namely: rarely (once or twice in the past four weeks), sometimes (three to ten times in the past four weeks) or often (more than ten times in the past four weeks) (Coates et al., 2007). Based on the answers to

6 Food security is defined as a state in which “all people at all times have both physical and economic access to sufficient food to meet their dietary needs for a productive and healthy life” (USAID, 1992)

44 these 9 main questions and 9 frequency questions four types of indicators were calculated to categorize households into four groups, namely: 1. Food Secure 2. Mildly Food Insecure 3. Moderately Food Insecure and 4. Severely Food Insecure.

For this study households were then grouped into two groups, namely food secure and food insecure households (Mild food insecure, moderately food insecure and severely food insecure). Three types of indicators were calculated in order to understand the characteristics of and changes in household food insecurity (access) in the surveyed population (Coates et al., 2007). The indicators provide summary information on: 1. Household Food Insecurity Access-related Conditions 2. Household Food Insecurity Access Scale Score 3. Household Food Insecurity Access Prevalence

The data on chronic hungry were used to analyse Household Hunger Scale (HHS). The data helped in constructing two types of indicators: a categorical HHS indicator and a percentage HHS score.

5.3 Analysis of EMIC Quantitative variables (PC, PD, HS and Prevention Strategies) Quantitative data were entered into and analysed in an electronic database using SPSS version 17.0 (Illinois, USA). For undernutrition, the categories related to illness experience, meaning and help-seeking behaviour were coded for their prominence with a value of 2 after a spontaneous response, a value of 1 after a probed response and a value of 0 if not considered at all to reflect the response style. An additional value of 3 was assigned to the category of response if the category was considered the most troubling category of distress, the most important perceived cause or the most helpful home remedy or outside help. The cumulative prominence by respondent (ranging from 0-5) was then used to calculate the mean prominence for each category. Through such consideration of prominence, categories were evaluated based on relative importance ascribed to them. This particular approach to comparing prominence, which has been widely used in other cultural

45 epidemiological studies, takes more information about a category into account than a simple comparison of frequencies of report without considering how they are reported. To identify significant differences for undernutrition between the two tribes, between illiterate and educated groups, and between food secure and insecure households a non-parametric statistic, the Wilcoxon rank sum test, was used when comparing prominence variables; the Pearson Chi2 and Fisher’s exact test were applied when comparing proportions7. For profile variables of age, personal, household income etc. the independent samples t-test was used.

6. Ethical Considerations The study was approved by the Savitribai Phule Pune University’s Ethics Committee (Annexure 9: Approval Letter Sr. No: Ethics/2012/16). Following precautions were taken while undertaking the study.

6.1 Protecting Identity and Integrity of Respondents All the respondents in the study were interviewed in a place which was comfortable to them. Names of the respondents while procuring lists from Anganwadi centres were codified and these codes were used in the data entry formats. All the respondents were informed that the information given by them would be reported as anonymous. Only the researcher had access to the interviews, and data collected through interviews was solely used for research purposes. Interviews were given numbers and the report, papers etc., to be published based on these data, would make mention of the individual by using pseudonyms.

6.2 Oral Consent In case of mothers of malnourished children, the first level of consent was oral and was taken by the AWW. Only those mothers who agreed at this first level were approached for interview by the investigators. Consent for health care provider for KIIs was taken at the time of interview, after explaining the purpose of the study.

7 A proportion refers to the fraction of the total that possesses a certain attribute.

6.3 Written Consent For FGDs, written consent was taken from each participant prior to the start of the FGD (Annexure 10: Consent Form for FGD). Prior to the interview, every mother of a malnourished child was explained the purpose of the study (Annexure 11: Consent Form for IDI & Survey Interview). The written consent was translated in regional language requesting the respondent’s participation on a voluntary basis. Only those who agreed to participate, were included in the study and were asked either to sign or give their left thumb impression on the consent form.