Abstract
Background:
Any deficiency or inadequate dietary pattern can lead to poor nutrition which can further influence both growth and development throughout from infancy to adolescence. Since adolescents represent the next generation of parents, it is important to monitor their nutritional status at this crucial stage. Thus, this study aimed to explore the factors associated with nutritional status among adolescent girls belonging to these tea gardens.
Objective:
The objective of this community-based cross-sectional study was to assess the nutritional status of adolescent girls belonging to the tea garden community and the association of the sociodemographic factors with it.
Materials and Methods:
Anthropometric measurement was taken among adolescent girls in the tea estates of Nazira subdivision of Sivasagar district, Assam. The pattern of dietary intake among adolescents was also studied. The statistical analysis was done using SPSS version 15.
Results:
The prevalence of thinness and stunting across 265 adolescent girls was 49.4% and 50.6%, respectively. Calorie and protein deficits were found to be 76.60% and 65%, respectively. Majority of the respondents, i.e., 66.80% of the participants, had a poor intake of essential food constituents. Moreover, 76.21% of the respondents were anemic. The association of different sociodemographic factors with thinness, inadequate protein intake, and anemia were found during the study.
Conclusion:
Thinness and stunting along with protein–energy malnutrition and inadequate intake of important food groups were prevalent in adolescent tea community girls. Overall, the public health burden of malnutrition is still a persisting health problem in the tea gardens of Assam.
Keywords: Adolescents, anthropometry, dietary pattern, malnutrition, tea garden
INTRODUCTION
Census of India conducted in 2011 showed that 20.9% of the country's population were adolescents. Of these adolescents, 47.3% were female.[1] Adolescence is the phase of life when maximum physical growth happens necessitating maximum nutrition and health care. An adolescent gains 15%–20% of height and 25%–50% of adult weight during adolescence. Standard daily recommended allowance of an adolescent girl is 2200 kcal/day and protein requirement is 44–46 g/day.[2] In the early eighties, India attained food self-sufficiency.[3] The per capita food availability, however, has not much changed over the past few decades, the National Sample Survey Office figure of 185 g cereal per capita is actually hovering around the early eighties figure. In fact, from 1983 to 2010, rural calorie consumption has declined from 2240 kcal to 2147 kcal.[3]
As part of the Global Hunger Index, State Hunger Index currently labeled Assam as “serious” and placed at a score of 20, whereas that of Madhya Pradesh is 30 and that of Punjab 15.[4] Compared to India's average rural calorie consumption of 2147 kcal in 2010, Assam had a per capita consumption of 2120 kcal. This further reduces in the areas with a low-socioeconomic profile, where the gender-biased distribution of food is very much dominant.[5] Assam is a state belonging to the northeastern part of India consisting of 85,344 tea estates and comprising 304,400 hectares cultivated for tea.[5] Of this, 84,577 are small tea growers and 767 are big tea gardens cultivating 78,203 and 226,197 hectares, respectively.[5] Assam's economy is based on agriculture. The total area under tea cultivation of Assam is accounting for more than half of the country's total area under tea.[5] Gender discrimination in distributing and accessing food within the family not only affects their health but also affects their future children, creating an intergenerational cycle of malnutrition, making them vulnerable to various diseases, adverse reproductive outcomes, and early death.[6] This can have an impact in the form of maternal mortality ratio (MMR) which is 404 per live births in Sivasagar district with a large number of tea estates of Assam which is very much significant compared to other states in India.[7] Moreover, the Comptroller and Auditor General report reveals that districts with higher tea garden population have a higher MMR.[7] According to the Health Management Information System data, total reported maternal deaths were 709 and 13 in Assam and Sivasagar district, respectively, from April 2015 to March 2016.[8]
Since adolescents represent the next generation, it is important to monitor their nutritional status at this transition stage. Nutritional assessment of female adolescents from the tea garden community of a poor district of a poor state can be a sentinel for capturing the gains of progress made in securing good health. This study explores the factors associated with nutritional status among adolescent girls belonging to low-socioeconomic agro-based industries such as tea gardens.
MATERIALS AND METHODS
Data source
A community-based cross-sectional study was done with the main objective to measure the burden of malnutrition among adolescent girls and to find the factors influencing the same. The ethical clearance for the study was obtained from the Institutional Ethics Committee of Kasturba Medical College and Hospital, Manipal. The administrative permission for conducting the study was obtained from the Joint Director of Health Services, Sivasagar district, Assam. The estimated sample size was 265. It was calculated using the equation [(Z2 × p × q)/(d2)] ×2 (where P = prevalence; q = 1 − p; and d = relative precision). In an earlier study, the prevalence of stunting was found to be 52% among tea garden adolescents.[9] Hence, the sample size was calculated assuming 52% (0.52) prevalence (p) of stunting among them with a degree of precision (d) of 0.06 at 95% (1.96) confidence interval (Z).
Study tools and techniques
A pretested interview schedule was used to collect the data from 265 adolescent girls. Information on sociodemographic variables along with the anthropometric measurements (height and weight) using a stadiometer and a digital weighing machine were also taken. By obtaining the height and weight, the body mass index (BMI) was calculated using the formula: weight (kg)/height (m2). The BMI for age and height for age was then compared with the World Health Organization reference tables. Thinness/underweight and stunting were estimated. For the socioeconomic status, the Modified Kuppuswamy Scale for urban and peri-urban areas, updated for 2017, was used.[10]
The interview schedule also included a 24-h recall method and the National Family Health Survey (NFHS)-4 food frequency items to assess the dietary intake. A 24-h recall method was used to analyze and compare the intake of the nutrients (calorie and protein) consumed in the past 24 h. Here, the quantity of cooked food and drinks consumed in the past 24 h was measured using standard measuring cups and spoons. The domains included in the interview schedule recorded the time of consumption (early morning, breakfast, midday, lunch, evening, dinner, and bedtime), the menu, and the amount of each ingredient (spices, herbs, and oils). The data regarding the menu and ingredients were then converted into nutrients present in each food item. From each nutrient, the calorie and protein were calculated using the standard food tables recommended by the National Institute of Nutrition, Hyderabad. This was then compared with the Recommended dietary allowances (RDA) described by the Indian Council of Medical Research.
A standard food frequency questionnaire was used to study the frequency of consumption of essential food groups (milk/curd, pulses/beans, green leafy vegetables, eggs, meat/chicken, fish, fruits, and tea/coffee). This was based on the questionnaire used for NFHS-4. The frequency of each intake of each food item was categorized as daily, at least once in a week, at least once in a month, or never. According to the calorie content, food groups were scored as 3, 2, and 1, and according to the frequency of intake composition, further scorings were given as daily – 3, weekly – 2, occasionally – 1, and never – 0. Food items having high-calorie content and consumed daily were given the maximum score.
Calculation of the total scorings of each respondent was done by multiplying with the score of each food item with the score of the frequency of food intake of the participants. Scorings <25 were categorized as poor intake and scorings >25 were categorized as normal intake.
Thus, this method involves the collection of information about a list of essential food items rich in essential nutrients for which the average frequency of consumption is determined with reference to a specific period in the past.
Data analysis
For analysis, rates and proportions were calculated from the data collected using the Statistical package for social sciences (SPSS) version 15 (Chicago, SPSS Inc.). Chi-square test was performed to determine the association of the nutritional status with the sociodemographic factors of the participants. P < 0.05 was considered to be statistically significant.
RESULTS
Sociodemographic characteristics of the participants [Table 1] reveals that out of 265 adolescent girls, majority of the respondents i.e., 84.15 % belongs to an “upper lower” class(IV) in the modified Kuppuswamy scale, second lowest from the bottom, scoring between 5 and 10 in an achievable score of 29 maximum. Parents’ education was poor with mostly the absence of formal education. About 69.8% of mothers and 39.6% of fathers were illiterate. Majority of the participants’ fathers and mothers were semiskilled (laborers; 88.24% – fathers and 90.69% – mothers). The monthly income of the respondents’ families ranged from Rs. 2092 to Rs. 20,714 with a larger proportion of the families, i.e., 64.5%, coming under an income bracket of Rs. 6214–Rs. 10,356.
Table 1.
Sociodemographic characteristics of the respondents (n=265)
| Categories | n (%) |
|---|---|
| Age | |
| 10-13 | 112 (42.25) |
| 14-15 | 64 (24.15) |
| 16-19 | 89 (33.60) |
| Education of the participants | |
| Intermediate | 14 (5.3) |
| High | 112 (42.3) |
| Middle | 76 (28.7) |
| Primary | 32 (12.1) |
| Illiterate | 31 (11.7) |
| Education of the father | |
| Graduate | 1 (0.4) |
| High | 19 (7.2) |
| Middle | 63 (23.8) |
| Primary | 77 (29.1) |
| Illiterate | 105 (39.6) |
| Education of the mother | |
| High | 8 (3) |
| Middle | 28 (10.6) |
| Primary | 44 (16.6) |
| Illiterate | 185 (69.8) |
| Others | 0 |
| Family member | |
| Nuclear | 187 (70.56) |
| Joint | 78 (29.43) |
| Occupation of the participants (if >18) (n=49) | |
| Semiskilled | 13 (26.53) |
| Student | 23 (46.93) |
| Unemployed | 13 (26.53) |
| Occupation of the father (n=238) | |
| Semiskilled | 210 (88.24) |
| Unskilled | 13 (5.46) |
| Unemployed | 15 (6.30) |
| Occupation of the mother (n=258) | |
| Semiskilled | 234 (90.69) |
| Unskilled | 5 (1.95) |
| Unemployed | 19 (7.36) |
| 15,536-20,714 | 11 (4.2) |
| 10,357-15,535 | 32 (12.1) |
| 6214-10,356 | 171 (64.5) |
| >2092-6213 | 51 (19.2) |
| Socioeconomic status (Modified Kuppuswamy Scale) | |
| Lower | 32 (12.07) |
| Lower middle | 10 (3.78) |
| Upper lower | 223 (84.15) |
This study revealed that 50.6% of the adolescents were stunted, that is, suffering from long-term undernutrition and 49.4% were thin, that is, currently undernourished. The prevalence of stunting and thinness [Table 2] was seen more in uneducated ones, i.e., 58.06% and 67.74%, respectively, which was statistically significant with P = 0.038. Thinness was seen more in participants whose parents were uneducated, i.e., 57.30%. Stunting and thinness were observed most in participants whose parent (s) were unemployed which is 60%. Among those who had a socioeconomic status, scoring <5 has more prevalence of stunting and thinness, i.e., 56.25% and 65.62%, respectively.
Table 2.
Association of sociodemographic factors with the nutritional status of the respondents (n=265)
| Categories | Present, n (%) | |
|---|---|---|
| Stunting | Thinness | |
| Age group (years) | ||
| 10-15 | 87 (49.43) | 94 (53.40) |
| 16-19 | 47 (52.80) | 39 (43.82) |
| P | 0.604 | 0.140 |
| Education of the participants | ||
| Uneducated | 18 (58.06) | 21 (67.74) |
| Educated | 116 (49.57) | 112 (47.86) |
| P | 0.374 | 0.038** |
| Parents’ education | ||
| Uneducated | 42 (47.19) | 51 (57.30) |
| Educated | 92 (52.27) | 82 (46.59) |
| P | 0.435 | 0.100 |
| Parents’ occupation | ||
| Uneducated | 3 (60) | 3 (60) |
| Educated | 131 (50.38) | 130 (50) |
| P | 0.670 | 0.658 |
| Participants’ occupation (n=49) | ||
| Uneducated | 16 (32.65) | 8 (34.78) |
| Educated | 12 (24.48) | 12 (46.15) |
| P | 0.098 | 0.419 |
| Socioeconomic status (Modified Kuppuswamy Scale) | ||
| <5 | 18 (56.25) | 21 (65.62) |
| 5-15 | 116 (49.78) | 112 (48.06) |
| P | 0.493 | 0.063 |
**Statistically significant with P < 0.05
The food intake of adolescents is depicted in Table 3. Overall, 66.8% of adolescents in this study had a poor intake of essential food constituents. The prevalence of poor intake of important food constituents was observed more among uneducated participants, low-socioeconomic class, and whose parents were uneducated, i.e., 77.41%, 75%, and 71.91%, respectively. Table 3 also shows a statistically significant association between protein deficit and the respondents belonging to 16–19 years and those who were uneducated with P = 0.001 and P = 0.002, respectively. Respondents whose parents were not educated had a protein deficit, i.e., 73.03%, which was also statistically significant with P = 0.049.
Table 3.
Association of sociodemographic characteristics of the respondents across frequency of food groups intake, inadequate calorie, and protein intake (n=265)
| Categories | Present, n (%) | ||
|---|---|---|---|
| Poor intake of food groups | Inadequate calorie intake | Inadequate protein intake | |
| Age group (years) | |||
| 10-15 | 114 (64.77) | 138 (78.40) | 100 (56.81) |
| 16-19 | 63 (70.78) | 65 (73.03) | 72 (80.89) |
| P | 0.326 | 0.329 | 0.001** |
| Education of the participants | |||
| Uneducated | 24 (77.41) | 26 (83.87) | 65 (73.03) |
| Educated | 153 (65.38) | 177 (75.64) | 107 (60.79) |
| P | 0.181 | 0.309 | 0.002** |
| Parents’ education | |||
| Uneducated | 64 (71.91) | 71 (79.77) | 65 (73.03) |
| Educated | 113 (64.20) | 132 (75) | 107 (60.79) |
| P | 0.208 | 0.386 | 0.049** |
| Parents’ occupation | |||
| Uneducated | 3 (60) | 5 (100) | 3 (60) |
| Educated | 174 (66.92) | 198 (76.15) | 169 (65) |
| P | 0.745 | 0.212 | 0.817 |
| Participants’ occupation (n=49) | |||
| Uneducated | 18 (78.26) | 15 (65.21) | 17 (73.91) |
| Educated | 19 (73.07) | 19 (73.07) | 23 (88.46) |
| P | 0.674 | 0.551 | 0.189 |
| Socioeconomic status (Modified Kuppuswamy Scale) | |||
| Scoring | |||
| <5 | 24 (75) | 25 (78.125) | 23 (71.87) |
| 5-15 | 153 (65.66) | 178 (76.39) | 149 (63.94) |
| P | 0.293 | 0.828 | 0.378 |
**Statistically significant with P < 0.05
We took a subset of 56 participants for the status of anemia determination. Of the 56 participants, 42% or 75% were anemic. Among them, participants whose parents were unemployed had more anemia, i.e., 86.48%, which was statistically significant with P = 0.006. Anemia was more among the uneducated ones, i.e., 91.66%, compared to the educated ones. About 95.65% of the respondents belonging from nuclear family were anemic, and it is statistically significant with P = 0.003. The prevalence of anemia was 100% among the participants whose parents were uneducated as well as belonging to low-socioeconomic class.
DISCUSSION
This study provided insight into the areas of malnutrition among adolescent girls in tea gardens of Assam. The rising problem of food security and nutritional status of future mothers is at stake, especially in the marginalized community of the tea garden areas. The prevalence of stunting was 50.6% and of thinness was found to be 49.4%, which was similar to a study done in Dibrugarh district among adolescent girls in tea garden community which revealed 51.9% stunting and 41.3% thinness.[9] Another study among the rural adolescents in West Bengal revealed 53.57% stunting and 48.75% thinness.[11]
In this study, participants had a poor intake of adequate food constituents. A study done in rural areas of Bhopal found that 70% of adolescents had a low intake of calorie.[12] Another study done among rural adolescents in Karnal district, Haryana (2015), reported that more than half of the girls, i.e., 54.3%, had inadequate energy intake.[13] The overall prevalence of stunting and thinness was high as indicated by the anthropometric measurements. In the context of a dietary pattern, the intake of calorie and protein was low when compared to RDA. The utility of protein as protein was less because the respondents mainly had plant-produced protein, for example, cereals such as rice which was of low biological value.
CONCLUSION
To conclude, it may be said that in spite of remarkable achievements over the past two decades in ensuring overall food security, communities in agricultural sectors such as Assam tea gardens remain in the left-out islands of food insecurity and malnutrition. Counseling and periodic health checkups for adolescents could be done by health-care professionals to address the public health problem of malnutrition among adolescents and their parents. Moreover, to achieve the proposed goals as suggested by the Sustainable Development Goals charter in terms of food security and nutrition, a multisectoral approach is required.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
Acknowledgment
This research was supported by Prasanna School of Public Health and Manipal Academy of Higher Education, Manipal, Karnataka; Assam Agricultural University, Jorhat, Assam; and Symbiosis International University, Pune, India, with supplemental support from the tea estate managers. I record my profound sense of gratitude to Dr. Solomon Salve, MSc, PhD (LSHTM), for providing me his valuable time and giving instant solutions to some critical conditions in producing the manuscript.
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