Introduction:
Women constitute almost fifty percent of our total population, and contributing to one-third of labour force significantly across all areas including fishery(1). Out of 5.4 million active fishers in our country, 29.6 percent accounts to fisherwomen (2). They contribute to small scale fisheries, excluding their family chorus(3). However, due to intake of less regular dietary requirement, the adolescent girls i.e., the future mothers, are likely to be adversely affected in terms of health and bearing children (4). India is having the largest adolescent population in the world i.e., every fifth person is between 10-19 years of age (5). These adolescents can contribute to country’s development, if benefited physically, socially, politically, and economically. But girls’ development in terms of physical and nutritional growth has been a question since many decades in India. Studies shows that it requires more energy and nutrients to cope-up development of body in terms of psychological, and physical changes (6,7). However, in different countries the growth pattern differs due to different lifestyle, food behaviours, family support system, education etc.
Many studies revealed that nutritional status of 13-14 years rural Indian girls were underweight, and they suffered from malnutrition and chronic energy deficiency (8–10). To support this fact, the NFHS-Round 4 data from India shows, at the age group of 12-17 years, 38.2 percent respondents, height for age was reported to be below -2 SD (11). Compared to this, 23.7 percent of the current study respondents for weight for age was found to be below -2SD. Indirectly this highlights the growth of the adolescent boys and girls in our country is a serious concern in terms of total number of 12- 17 years population (11). Fisherman community living in coastal areas are much more influenced by sea food and different climate. In the lack of opulent empirical data, a detail growth pattern is not recorded for the Kandra community, and much literature is not available on somatometric measurement and growth patterns of Kandra girls. Patil, (2006) in his review paper mentioned that the mean weight and height of fisherwomen was 48.5 Kilogram and 150 cm, respectively(12). In the same study it was revealed that the average BMI was reported to be 21.3 kg/m2, and 17 percent of the respondents were reported to be below normal, 10.5 percent mildly nourished, and 4.0 percent were moderately malnourished. 2.9 percent were also reported severely malnourished. Another study from five coastal states from India reported that intake of overall nutrients was less than the recommended dietary allowance (13) . However, the changes happened in the body may not corresponds with increasing age due to several reasons mentioned earlier. Considering the findings from these two studies, we may conclude that Kandra community’s girl growth pattern is a concern from their development perspective. Though there has been increasing concern over the growth and nutritional status of adolescent girls in India as raised in many literatures, but it requires further attention to bring a physical and mental development among the girls.
Kandra community, a sub-set of fishermen community from India is having a population of 5,29,717 in Odisha and many more population in India, where women play key role in socio-economic development of their family (14). Height, weight, Upper arm, calf, and chest circumference are important Somatometric measurement which is used to study the growth pattern in individuals, and the body mass index is used to assess the nutritional status. In the absence of more literature on girls’ body growth of the fisherman community, the paper tried to answer few research questions such as (i) whether the body growth of the Kandra girls is as per the national standards or not? and (ii) whether any significant difference exists between different age groups in terms of height, weight, BMI, and food behaviours. The result will help the government to design different development programs for the coastal belt residents and inculcate cultural intervention to bring sustainable development which not only address the solution of malnutrition in India, but also helps to reduce the morbidity at later stage of life.
Materials and Methods
The cross-sectional and descriptive study was chosen to conduct among Kandra community of Arjyapalli Gram Panchayat (GP) of Ganjam district of Odisha. The GP is located at 19.38°N 85.07°E of Odisha and shared its boundary with Andhra Pradesh and Indian ocean. Cochran’s formula was used to calculate the sample size with prevalence (p) of below normal BMI among women 15-49 years (23.1 percent in NFHS-4 at Ganjam district), where “q” was calculated to be 0.769. Based on the formula, sample size was calculated to be 78 at 90 percent confidence level and 0.03 percent standard error. The samples were randomly selected from two different schools i.e., Government Upper Primary and Government High School of the block from March 2019 to April 2019. All the girls’ sample were belonging to the age group of 12-16 years, and the determination of the age was confirmed by comparing exact date of birth from the school registration register. From all records, certain records were rejected which were not matched with the school registration register. Somatometric measurements such as height vertex, upper-arm circumferences, calf-circumference, chest circumference, weight, menarche, and age at marriage, were collected with the help of anthropometric instruments, and to collect exact measurement, all the measurement were taken with the minimum clothing and with proper informed consent of the subjects. However, data were analysed mainly on the nutritional aspect such as height, weight, ad BMI. Data were entered in Microsoft excel followed by test analysis in SPSS 22.0 version. Further, to understand and explore the difference of mean between two different age groups, i.e., 12-13 (early adolescent) years and above 14-16 years (Middle adolescent), Levene's Test for equality of variances and independent samples T test was tested. This paper also attempted to compare the anthropometric measurements of the studied adolescent girls with ICMR, NCHS and other local standards which may result into some policy level changes in the current ongoing programs by Central and State governments.
Results
Somatometric measurements and growth
The current study tried to understand the growth by measuring five key indicators such as height, body, upper-arm, calf, and chest circumference. Table 1 shows that increase in height, weight, Upper arm circumference, calf circumference, and chest circumference are increasing with the age as expected, however across the age, the increase was not similar. As reflects from the table for height, maximum variation i.e., Standard Deviation (SD), was reported in the age group of 12 years and lowest is in the age group of 14 years. The mean height was reported to be 144.28 ± 8.58 cm in the age of 12 years whereas the mean height for 14 years was reported to be 149.58 ± 4.39 cm. Similarly, for body weight, the average was found to be minimum i.e., 35.50±5.54 kg for the age of 12 years whereas the mean height was maximum i.e., 44.0±3.25 Kg in the age of 16 years. The analysis also shows that with increasing age, deviation in weight among the study respondent was decreasing which is a concern for the school going girls from low economic strata of the studied population. Further the other Somatometric measurements such as Upper arm circumference, calf circumference and chest circumference were also measured to measure the growth in the age groups. It depicts that deviation i.e., SD, from the mean was reported to be highest in the age group of 16 years (27.62±4.35cm) for upper arm circumferences followed by 13 years (23.58±2.10 cm), the lowest one. In the similar way, calf circumferences were with highest standard deviation in the age of 16 years (30.75±3.56 cm) and lowest in the 13 years of age (26.52±1.72 cm). Contrast to this, at the age of 12 years the chest circumference shows highest standard deviation (70.72±5.46 cm) while was lowest in the age of 15 years (78.81±2.54 cm). From the below analysis, we can say that in overall, for the studied respondents, the growth spurt was seen in the age group of 12-13 years for the studied subjects.
| Table 1: Percentage distribution of Height, Weight, Upper arm, Calf and Chest circumference in the studied population. |
| Age in years |
n |
Height in cm |
Body Weight in Kg |
Upper arm circumference in cm |
Calf circumference in cm |
Chest Circumference in cm |
x̄ |
SD |
x̄ |
SD |
x̄ |
SD |
x̄ |
SD |
x̄ |
SD |
12 + |
18 |
144.28 |
± 8.58 |
35.50 |
±5.54 |
19.72 |
±2.28 |
26.83 |
±2.64 |
70.72 |
±5.46 |
13 + |
19 |
144.05 |
± 5.57 |
39.42 |
±5.50 |
22.84 |
±3.01 |
26.52 |
±1.72 |
75.89 |
±3.33 |
14 + |
17 |
149.58 |
± 4.39 |
41.11 |
±4.43 |
23.58 |
±2.10 |
28.29 |
±2.23 |
78.58 |
±3.00 |
15 + |
16 |
147.68 |
± 6.26 |
43.31 |
±3.80 |
29.18 |
±2.57 |
31.68 |
±2.26 |
78.81 |
±2.54 |
16 + |
08 |
146.75 |
± 5.47 |
44.00 |
±3.25 |
27.62 |
±4.35 |
30.75 |
±3.56 |
79.00 |
±4.00 |
The growth curves Percentiles
Percentile is basically used to understand how many percent of the sample was reported to more than the median and percentile of the group. The percentile distribution of the studied girls is represented in the Table 2, which envisaged that at different age, 50 percent of the sampled girls were having less height than the median height (Range 130 cms to 156.10 cms). At the age of 12 years 75 percent of the girls have attained height between 130 cms to 156.10 cms, however, at 16 years of age, it was reported to be between 140 cms to 153.50 cms. It indicates maximum adolescent spurt was seen during the early age however, it was not same across the age. Comparison of 10th through 90th percentile curves indicate that 75 percent of the 12-year-old girls attained height between 130.00 cm and 156.6 cm, while 75 percent of those at 16 years of age attained height ranges between 140.00 cm and 153.50 cm. Further analysis on percentile extremes shows that increase in the 3rd percentile of height between 12 to 16 years of girls was from 130 to 140 cms. However, for 95th percentile it was reported to be 156.10 cms to 153.50 cms. Similarly, weight for the sampled girls show that in the age group of 13-, 14- and 16-years, weight was less than 50th percentile. This clearly indicates that 50 percent of the girl’s height and weight were less than average height and weight of the sample population. In the current study, it was observed that only 50 percent of the studied sample have an underweight BMI at the age group of 12 and 14 years, respectively. And it concludes that severe malnutrition is a matter of concern at the lower age group among the studied girls.
| Table 2: Percentile distribution of height, weight, and BMI of the studied population. |
| Indicator |
Age |
n |
3rd |
10th |
25th |
50th |
75th |
90th |
Height |
12 |
18 |
130.00 |
130.00 |
137.00 |
143.00 |
153.00 |
156.10 |
13 |
19 |
137.00 |
138.00 |
140.00 |
143.00 |
146.00 |
156.00 |
14 |
17 |
142.00 |
142.80 |
146.50 |
149.00 |
153.00 |
156.40 |
15 |
16 |
138.00 |
138.70 |
142.00 |
147.00 |
154.00 |
156.60 |
16 |
08 |
140.00 |
140.00 |
142.50 |
145.00 |
151.00 |
153.50 |
Weight |
12 |
18 |
25.00 |
26.80 |
30.00 |
36.50 |
39.25 |
44.20 |
13 |
19 |
30.00 |
32.00 |
35.00 |
39.00 |
44.00 |
48.00 |
14 |
17 |
35.00 |
35.80 |
37.50 |
40.00 |
44.00 |
48.60 |
15 |
16 |
38.00 |
38.00 |
40.25 |
42.50 |
46.00 |
49.60 |
16 |
08 |
38.00 |
38.00 |
40.75 |
44.50 |
45.75 |
- |
BMI |
12 |
18 |
13.20 |
14.28 |
15.10 |
16.45 |
19.12 |
20.79 |
13 |
19 |
14.20 |
14.90 |
17.80 |
19.20 |
21.20 |
22.10 |
14 |
17 |
15.60 |
15.60 |
16.55 |
18.30 |
20.15 |
21.28 |
15 |
16 |
17.30 |
17.58 |
18.40 |
18.85 |
20.90 |
22.31 |
16 |
08 |
17.80 |
17.80 |
18.40 |
20.10 |
21.45 |
- |
Body Mass Index and Nutritional Status
BMI is preferred by WHO and many other scientific institutions to measure the nutritional status of an individual. Based on the height and weight of an individual, BMI is calculated by the formulae (Weight (Kg)/Heigh2 (m2)). The current study shows that out of all the studied girls, 56.1 percent were fall with the normal BMI. However, the study shows that 21.8 percent and 5.1 percent were also affecting with mild and moderate malnutrition, respectively. The severity of the malnutrition as reflected from BMI was reported to be 17.9 percent only. Across the age of girls, the severity of malnutrition is observed more in the lower age group compared to the higher age group (Table 3). Further to understand the difference in the means of the age groups from 12 to 16, one way ANOVA was performed. The test shows that the significance value was .000 i.e., p=.000, which is below .05. In other words, it can conclude that the means of the BMIs is statistically different at least one different age groups (F77= 6.256, p <.001) (See table 3).
| Table 3: Age wise distribution of BMI in the studied population as per ICMR classification |
| Age in years |
n |
Severe [<16] |
Moderate [16-17] |
Mild [17-18.5] |
Normal [18.5-25] |
Obese [>25] |
F value in ANOVA |
Significance level |
12 |
18 |
8 (44.4) |
2 (11.1) |
3 (16.6) |
5 (27.8) |
0 |
|
|
13 |
19 |
3 (15.8) |
0 |
5 (26.3) |
11 (57.9) |
0 |
|
|
14 |
17 |
3 (17.6) |
2 (11.8) |
5 (29.4) |
7 (41.2) |
0 |
F= 6.256 |
P=0.000 |
15 |
16 |
0 |
0 |
3 (18.8) |
13 (81.3) |
0 |
|
|
16 |
08 |
0 |
0 |
1 (12.5) |
7 (87.5) |
0 |
|
|
TOTAL |
78 |
14 (17.9) |
4 (5.1) |
17 (21.8) |
43 (55.1) |
0 |
|
|
Further to explore BMI as per WHO standards, the reference group were categorized into two different age groups i.e., 12-13 years and 14-16 years, and result summarized that girl were underweight at lower age-group compared to higher age-group in the current study. However, normal BMI was reported to be attained with increasing age group. To understand the difference of means of these two groups, Levene’s test for equality of variance and independent t-test were tested. The Levene’s test results show insignificant result for equal variation in the both groups, and the independent sample t-test value (t74.350 = -2.027, p < .05) was reported to be significant which concludes that in the studied girls the difference in means was found (Table 4).
| Table 4: Percentage distribution of Body Mass Index (BMI) in the study age groups as per WHO standard |
| Body Mass Index (Kg/m2) as per WHO standards |
12-13 years,
n (%) |
14-16 years,
n (%) |
Total,
n (%) |
Levene's Test for Equality of Variances |
t-test for Equality of Means |
Underweight (<18.5) |
21 (57.8) |
14 (34.1) |
35 (44.9) |
F=2.289
P=0.134 |
t=2.032
P=0.46** |
Normal (18.5 -24.99) |
16 (43.2) |
27 (65.9) |
43 (55.1) |
Overweight (25-29.99) |
0 |
0 |
0 |
Obese (=30) |
0 |
0 |
0 |
Total |
37 (47.4) |
41 (52.6) |
78 (100.0) |
|
|
| (* p < .001, ** p<.05, *** p < .10) |
Food Habits and Nutrition
The girl’s adolescence period is a physical and psychological phase for the preparation for safe motherhood which require greater energy and nutrients. The current study tried to understand the food habit of these girls through 24 hours recall method and was summarized (Table 5). It concludes, 96.2 percent of the sampled girls eat starch-based food along with pulses (80.8 percent) irrespective of their poor economic condition. Fish as a food was ate by almost three-fourth of the girls followed by fast food (66.6 percent), vegetables (61.5 percent), milk and milk products (28.2 percent) and meat-egg (15.4 percent). Although food taken by sampled girls are rich in carbohydrates and fats, but recommended dietary allowances were not met as per some literature. The low-socioeconomic condition of the family forced them to concentrate their food pattern on the availability of sea and staple food of the area.
| Table 5: Distribution of food habit among the studied girls |
| Food items* |
n (%) |
Starch food (rice, roti, potato, bread etc.,) |
75 (96.2) |
Pulses |
63 (80.8) |
Milk and milk products |
22 (28.2) |
Chocolate/sweets |
24 (30.8) |
Green vegetables |
48 (61.5) |
Fish |
58 (74.4) |
Meat/egg |
12 (15.4) |
Fast food |
52 (66.7) |
| *Due to multiple response, the percentage was calculated from 100 percent for every category |
Patterns of growth among Kandra girls and other girls form India
The comparison of the current findings of rural girls was made with ICMR, NCHS standards, and other local studies conducted within one generation, to understand the trend. It depicts that the height and weight of the girls were much less compared to NCHS data across the age groups for both weight and height. However, when compared with ICMR data, the height was found to be less in the age of 14 and 16 years. The comparison also indicates, weight the current study findings was also reported to be high than as referred to ICMR median and reversed for the NCHS median.
To understand this variation, the paper attempts comparison with some of the local Indian studies. Which concludes that median height and weight was reported to be less than the peri-urban Bengali school going girls of the same age group. But, as per Banerjee et al., (2009) findings were showing irreversible trend for weight whereas height was more (15,16). The study conducted in Andhra Pradesh shows that the height for 12-14 years was less than the height of current study, and more for the 15 and 16 years of age group (17). Similarly, weight of the subjects was found to be more in the current study. Age group wise comparison shows that adolescent spurt was reported in 12-13 years of age however, current study result shows that adolescent growth spurt was seen in the 14-15 years of age (Table 6). It is important to mention that in the current study the menarche was also calculated to be 12.64 years and age at marriage for girls was in between 14 to 20 years.
| Table 6: Comparison of Somatometric measurement such as height and weight with ICMR, NCHS and other local studies |
| Indicators |
Age |
Present study |
ICMR (1972) |
NCHS
standards |
S.R Banerjee, et.al, (2009) |
Chakrabarty et.al, (2008) |
K. Bharathi (2017) |
IAP (2015) |
n |
x̄ |
±SD |
n |
x̄ |
±SD |
x̄ |
±SD |
x̄ |
±SD |
x̄ |
±SD |
x̄ |
±SD |
x̄ |
±SD |
Height |
12 |
18 |
144.27 |
±8.33 |
3426 |
139.20 |
na |
154.6 |
±10.7 |
146.01 |
±6.67 |
138.9 |
±4.4 |
135.72 |
±6.08 |
148.4 |
±7.0 |
13 |
19 |
144.05 |
±5.57 |
3168 |
143.90 |
na |
158.8 |
±11.7 |
148.46 |
±2.26 |
144.0 |
±6.7 |
138.75 |
±9.01 |
152.2 |
±6.9 |
14 |
17 |
149.58 |
±4.39 |
2900 |
147.50 |
na |
160.9 |
±11.2 |
150.60 |
±4.44 |
144.5 |
±5.4 |
141.24 |
±11.51 |
154.7 |
±6.6 |
15 |
16 |
147.68 |
±6.26 |
2644 |
149.60 |
na |
163.2 |
±11.6 |
150.97 |
±4.41 |
146.1 |
±4.8 |
154.90 |
±7.69 |
156.1 |
±6.6 |
16 |
8 |
146.75 |
±5.47 |
2534 |
151.00 |
na |
162.2 |
±11.7 |
151.91 |
±4.30 |
146.9 |
±5.7 |
146.85 |
±5.31 |
156.9 |
±6.1 |
Weight |
12 |
18 |
35.5 |
±5.54 |
3426 |
29.8 |
na |
47.1 |
±7.2 |
37.39 |
±7.95 |
30.3 |
±4.1 |
28.73 |
±4.33 |
39.8 |
±9.0 |
13 |
19 |
39.24 |
±5.50 |
3168 |
33.3 |
na |
51.5 |
±6.2 |
39.81 |
±8.02 |
35.0 |
±5.3 |
30.41 |
±3.83 |
43.6 |
±9.4 |
14 |
17 |
41.11 |
±4.43 |
2900 |
36.8 |
na |
54.7 |
±6.2 |
42.75 |
±5.30 |
37.2 |
±5.4 |
32.15 |
±6.40 |
46.4 |
±9.6 |
15 |
16 |
43.31 |
±3.80 |
2644 |
38.8 |
na |
56.4 |
±6.5 |
44.46 |
±6.10 |
38.4 |
±4.8 |
42.77 |
±6.64 |
48.4 |
±9.6 |
16 |
8 |
44.00 |
±3.25 |
2534 |
41.1 |
na |
58.2 |
±6.6 |
45.23 |
±8.07 |
38.5 |
±4.0 |
39.16 |
±5.39 |
49.7 |
±8.7 |
 |
Figure 1: Age wise comparison of height of different standards including NCHS, ICMR, and other local studies with current study |
 |
Figure 2: Age wise comparison of weight of different standards including NCHS, ICMR, and other local studies with current study |
Discussion
Growth of an individual should be observed at regular intervals of time to understand different dimension of growth and development. Literature depicts that along with hormonal changes, the dietary pattern also influences the growth and growth failure, and short or long height may be worrisome in many cases as it facilitates non-endocrine diseases (18). In one of the articles published in Lancet, author says that investment in adolescent health will not only bring prosperity today, but also pay dividend in future (19). Second, environmental ambience also influences the growth of the girls or any individuals that too particularly in weight and skin-fold thickness (16). It means there is an urgent need to be examined on age specific growth and the environmental factors (economic conditions of family, physical activities, mental stress etc.) in which the subjects are living.
The comparison of current study findings with similar environment was tried to capture in this discussion and concludes that, height of girls in the similar condition also varies and reasons for the same needs to be understand with respect to environment and development irrespective of low socio-economic conditions. For example, studies conducted among fisherwomen of four coastal states in India revealed that consumption of food was different across the states, and were consuming higher energy foods such as carbohydrate, proteins, and fat, but the recommended dietary allowances (RDA) was reported to be less (13). The same study also depicts that out of 1538 fisherwomen studied from four states, 2.9 percent were suffering from severe malnutrition whereas 4.1 percent from moderate and 10.5 percent from mild malnutrition (13). A review made in another research paper highlighted that majority of the children in the school from Ganjam i.e., same study area, were suffering from malnutrition. Around 2.9 percent were reported to be affected severely and the average height for women was 150 cms, weight 48.5kgs, and BMI as 21.3 (12). These worrisome figures as compared to recent median height and weight of different Indian standards and local studies, depicts undernutrition has been identified as a key problem among the school children in the age group of 12-16 years (Bhadra et al., 2011). Further compared to other international studies on the same community, findings from Indonesia revealed that median height of the current study was less compared to Indonesian fishermen girls average (21–23). This is same for the ICMR and NCHS standard too. Another study conducted in northwest Ethiopia revealed that among rural school going children, lower economic class, lack of nutritious food, lack of media exposure, and age were associated with stunting and thinness (24).
The nutritional status in terms of BMI depicts that little over 55.1 percent girls were nourished normally, while two-third belongs to undernourished group with varying proportion in different category. Age group 12, 13 and 14 years are particularly more vulnerable as 44.4 percent girls in the 12 years and 15.8 percent in 13 years, 17.6 percent girls in 14 years were severely undernourished. Moderate undernutrition was also high in age group 12 that is 16.6 percent. However, mild nutrition prevails at all age group 12 and 14 years as 11.1 percent and 11.8 percent respectively.
To understand the growth trend in terms of height and weight, current studies were compared with local standard studies, national and international standards like ICMR,1972 and NCHS. The average height in all age group was found to be lower than the findings of IAP study conducted in the year 2015 but was more than the study findings of K. Bharathi in the year 2017, except in the age 15 years. Similarly, for average weight the findings were more than K Bharthi study but less than the IAP study. In both cases, the findings are less than the NCHS standard Which implies that may be environmental factor could be one of the reasons. Hence, the reasons need to be understood more clearly and comprehensively. Further, it is also important to highlight that the undernutrition among the girls may lead to severe health consequences such as delay in growth spurt, low IQ level, failure in school, problems in Behaviour and many other (25). This also must be researched in the coming times in the Kandra community so that proper development can be addressed.
Conclusion
Lack of scientific research, particularly on certain weaker community is seen in India due to its large geographical variation and habitation. However, it is one of the prime requisites for developing different developmental programs. Nutrition with respect to Kandra community located in the coastal region is very important, because around 10 states are touching its border with Bay of Bengal. In these states, communities are residing in the coastal areas and are behaving same in the environment. Not only this, across the globes, many different cities and countries have witnessed to settled human habitation around the sea where food pattern is almost similar with respect to their dependency on sea food is also more. However, the growth pattern was reported to be different and ask for community-based intervention so that weaker section could join the mainstream of development within and outside countries. This would be possible only when the health condition of the adolescent and young would be good. The current study examined the nutritional status and growth pattern of 12-16 years school going girls who were belongs to low-socioeconomic groups. Findings were almost like the gaps reported in NFHS-4 nutritional indictors. It is a matter of concern as in future times, the girls would be the carrier of newborns and the deficiency may pull their life into different diseases. The government system in terms of School Health Program and mid-day meal is trying to address the nutritional gaps but the results were not up-to the mark since independence. Compared to the new data from ICMR, NCHS and IAP, the growth pattern observed is below the median and hence different state government should design community-based intervention program to bridge the issue of growth and nutrition and standardize the growth in context to Indian standard (Agrawal et al, 2015). Prime Minister's Overarching Scheme for Holistic Nutrition (POSHAN) program under Integrated Child Development Services (ICDS) has contributed a lot, but role of different stakeholders in the community is not contributing as it is designed and need a brainstorming to execute it properly.
Limitation of the Study: The current research was conducted on Kandra community of Ganjam, Odisha. Due to small sample size, samples were categories to early and middle adolescent so that statistical test can be conducted. This will also help to generalize the findings.
Acknowledgement: The authors express gratitude to all the adolescent school going girl respondents of K. Arjyapalli village of Ganjam district of Odisha, India for allowing to take the measurement with minimal level of clothing.
Source of Funding: The author and team did not get any kind of funding to conducting this primary research. The data were collected by one of the authors during her Master of Philosophy in Anthropology from Sambalpur University, Odisha, India.
Conflict of Interest: No conflict of interest has been reported till the paper is wrote.
Ethical Clearance: Informed consent was sought from every respondent of their voluntary participation during the study and information about their right to discontinue the interview at any point of time along with privacy, and seclusion was informed to them prior to start the interview.
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