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Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
26
Original Article
Adolescent Risk-taking Behaviour in India: The influence of
Socio economic Characteristics and Living Arrangement
12
Sutapa Agrawal , Praween Agrawal
1 Sutapa Agrawal, Epidemiologist, South Asia Network for Chronic Disease,
Public Health Foundation of India, New Delhi -110016, India.
2Praween Agrawal, Senior Programme Officer, Organizational Learning and Evaluation,
International Planned Parenthood Federation South Asia Regional Office, New Delhi-110003, India.
Population Council, New Delhi-110003, India.
Background: There is an increasing trend of risk-taking behaviour among adolescents
in India but little empirical evidence exists on its determinants. We examined the effect of
socio economic characteristics and living arrangement on adolescent’s risk-taking
behaviour in India.
Methods: Cross sectional population based data of 1,11,077 adolescents aged 10-19
years included in India’s second National Family Health Survey (NFHS-2,1998-99) were
analysed. Bivariate and multivariate logistic regression was used for analysis. Risk-
taking behaviour was assessed in terms of tobacco chewing, tobacco smoking, and
alcohol drinking and a combination of these three as ‘any risk behaviour’.
Results: Prevalence of chewing, smoking and drinking among adolescents was 3.3%,
1.2% and 0.9% respectively. Adolescents who were dropped out from school
(OR:6.6;95%CI:6.08-7.20) or had never been to school (OR:7.32;95%CI:6.65-8.06),
adolescent living in a female headed household (OR:1.19;95%CI:1.07-1.33), or in
household where more than three related adults stays (OR:1.52;95%CI:1.37-1.68)
were more likely to indulge in
any risk-taking behavior than their counterparts. However, female adolescents,
adolescents belonging to scheduled tribe, other backward class and other category
(ORs ranges from 0.79 to 0.89) and adolescents belonging to household with a medium
or higher standard of living (ORs ranges from 0.45 to 0.87) were less likely to indulge in
any risk-taking behavior.
Conclusion: The findings of this study calls for a comprehensive prevention and control
programs for all adolescents in general and adolescent never been to school or dropped
out from school in particular for addressing risk-taking behaviour in India.
Key words: adolescents; risk-taking behaviour; chewing; smoking; drinking; NFHS-2;
India
'or in
households where the adolescent stays with other unrelated adults (OR:1.58;95%
CI:1.32-1.89)' in the fifth line after the odds ratio brackets.
ABSTRACT
Correspondence:
Sutapa Agrawal
Epidemiologist, South Asia Network for Chronic Disease,
Public Health Foundation of India, C1/52, First floor, SDA,
New Delhi -110016.
E-mail: sutapaiips@rediffmail.com/sutapa.agrawal@phfi.org
INTRODUCTION
arly initiation of smoking, drinking and
tobacco chewing are well known to have both
E
immediate and long-term adverse health and social
consequences [1-3]. For these reasons, substance
uses during adolescence are regarded as risk-
taking behaviour. Limited studies on substance use
indicate that the prevalence of these risk-taking
behaviours among adolescents is increasing in
Asian countries [4,5] including India [6,7]. Tobacco
use poses a major public health threat particularly
for adolescents in India, with the current prevalence
of tobacco use being 36% among 15-24 years old
adolescents and youth as determined by the Global
Adult Tobacco Survey (GATS) [8]. The risk is
particularly high for adolescents belonging to the
Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
27
www.jcnh.in Agrawal & Agrawal
lower socio-economic strata (SES) and among male
adolescents [9]. Several studies in western
societies have found that multiple aetiological
factors, including individual, socio-cultural and
environmental factors [10], a range of community,
family and individual characteristics affect
substance use among adolescents [11-15]. In order
to formulate and implement effective adolescent
health policies and programmes, it is essential that
the prevalence of adolescent risk-taking behaviour
and the factors associated with them are identified.
Most of the studies on substance use among
adolescents are based on special groups of youth or
small samples of youth in limited geographic
locations [16,4]. Few studies have reported on these
behaviours at the national level in India [17,18]. This
study uses data from the second Indian National
Family Health Survey (NFHS-2) to provide
nationally representative estimates of prevalence,
and socio-economic and demographic and living
arrangement correlates of risk-taking behavior
among adolescents aged 10-19 years in India.
METHODS
We used National Family Health Survey (NFHS-2,
1998-99) data for this study. Briefly, NFHS-2 is a
nationally representative sample covering more
than 90,000 households in India and some 5,00,000
persons of all ages in those households. Full details
is provided in the basic survey report for all India
[19]. Our analysis is based on 1,11,077 adolescents
aged 10-19 years residing in the sample
households. The information about smoking,
drinking and chewing of tobacco and paan masala
for all the household members was gathered in the
household survey. The household head or some
other knowledgeable adults in the household
reported for each household member. Because the
household respondent may not be aware of
smoking and drinking behaviors of all household
members, it is possible that some of these behaviors
are underreported in the survey. The survey also
collected detailed information on household
members about their socio economic and
demographic characteristics and some indicators of
family characteristics, which gives a unique
opportunity to analyze their effect on adolescent
risk-taking behaviors.
Simple and two ways cross tabulations and
multivariate logistic regression were used for
analysis. Risk-taking behavior was assessed in
terms of tobacco chewing, tobacco smoking, and
alcohol drinking and a combination of these three as
‘any risk behaviour’. Variables included in this study
are gender, educational status (going to school,
school dropout, never been to school), marital
status (never married, ever married), religion
(Hindu, Muslim, Others), caste/tribe status
(scheduled caste, scheduled tribe, other backward
class, other, missing caste), standard of living (low,
medium, high), residence (urban, rural), gender of
the head of the household where the adolescent
live, composition of the adult in the household where
the adolescent live (two adults-opposite sex, three+
adults-related adults, others), geographic regions
(north, northeast, central, east, west, south). For a
detailed definition of variables see Table 1. Results
are presented in the form of odds ratios (ORs) with
95% confidence intervals (95% CI). In the survey,
certain states and certain categories of households
were oversampled. In all our analysis, weights are
used to restore the representativeness of the
sample [19]. All the analysis was done in SPSS
software version 19.
Ethical consideration
The survey got ethical clearance from International
Institute for Population Science’s Ethical Review
Board. The analysis presented here is based on
secondary analysis of existing survey data with all
identifying information removed. The survey
personnel obtained informed consent from each
respondent before asking questions.
Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
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RESULTS
Prevalence of chewing, smoking and drinking
among adolescents was 3.3%, 1.2% and 0.9%,
respectively, the prevalence being higher among
male, ever married, school dropout or never been to
school adolescents than their counterparts. Logistic
regression results confirms that adolescents who
were dropped out from school (OR:6.6;95%CI:6.08-
7.20) or had never been to school
(OR:7.32;95%CI:6.65-8.06) were almost seven
times more likely to indulge in any risk-taking
behavior than those who were going to school.
Adolescents residing in rural area
(OR:1.19;95%CI:1.10-1.30), ever married
adolescent (OR:2.98;95%CI:2.71-3.28),
adolescent residing in India’s northeast region
(OR:5.42;95%CI:4.67-6.28), adolescent living in a
female headed household (OR:1.19;95%CI:1.07-
1.33), or in a household where the adolescent stays
with others (not related members)
(OR:1.58;95%CI:1.32-1.89) or with more than three
related adults (OR:1.52;95%CI:1.37-1.68) were
more likely to indulge in any risk-taking behavior
than their counterparts. However, female
adolescents (OR:0.13), adolescents belonging to
scheduled tribe (OR:0.89), other backward class
(OR:0.83) and other category (OR:0.79) and
adolescents belonging to household with a medium
or higher standard of living (ORs ranges from 0.45 to
0.87) were less likely to indulge in any risk-taking
behavior. No association of adolescent risk-taking
behavior with religion was found in the adjusted
analyses.
DISCUSSION
The present study found strong evidence of
association between socio-economic
characteristics, living arrangement and
adolescent’s risk-taking behaviour in India. The
findings of the study is very useful in designing
appropriate prevention and control programs for
addressing adolescent’s risk taking behavior in
India. A few suggestions regarding adolescent
health programmes and policies can be derived
from the results. Adolescents as well as
communities as a whole need to be better informed
about the serious negative health consequences of
smoking and drinking. We found a higher proportion
of adolescents who were dropped out from school or
never been in school were chewing, smoking and
drinking than adolescents who were going to school.
Therefore school education programmes
concerning substance use should begin at an early
age, before a significant proportion of adolescents
begin to leave school. Adolescents out of school
should be approached through community-based
health education programmes, by targeting parents
and family members. Education on risk-taking
behaviour must be imparted through schools,
existing government health programmes and
community outreach programmes. For this, the
potential roles of mass media and community-
based organizations need to be explored more
vigorously. Intensive efforts started early are
needed for prevention of risk-taking behaviour in
adolescents. Community-based interventions can
be effective in preventing adolescents from initiating
tobacco use in a low-resource setting such as India.
Nevertheless, our study has some limitations. We
could not use the latest NFHS data i.e., NFHS-3,
conducted in 2005-06 for this study. The reason
being that no adolescents or household members in
NFHS-3 were interviewed for information on
tobacco chewing, smoking and drinking. Rather
these information was elicited from individual men
(aged 15-54) and women (aged 15-49) residing in
the sample households. Despite this limitation our
study is important since no cross sectional study has
looked upon this important issue among the
adolescents with a large scale nationally
representative data in India.
Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
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Table 1: Sample distribution, prevalence of tobacco chewing, tobacco smoking and alcohol drinking
and any risk taking behaviour; unadjusted and adjusted odds ratio with 95% confidence interval
(OR and 95% CI) for any risk taking behaviour among adolescents age 10-19 years (n=1,11,077)
according to selected socio-economic characteristics and living arrangement, India, 1998-99
Selected
characteristics Sample
distribution
N [%]
Tobacco
chewing
N [%]
Tobacco
smoking
N [%]
Alcohol
drinking
N [%]
Any risk
behaviour
N [%]
Any risk behaviour
Unadjusted
OR [95%CIs]
Adjusted
OR [95%CIs]
Gender p<0.0001 p<0.0001 p<0.0001 p<0.0001
Male 57593 [51.8] 2972 [5.2] 1301 [2.3] 781 [1.4] 4049 [7.0] 1.00 [ref] 1.00 [ref]
Female 53484 [48.2] 730 [1.4] 68 [0.1] 243 [0.5] 965 [1.8] 0.24[0.23-0.26] 0.13[0.12-0.15]
Educational
status <0.0001 <0.0001 <0.0001 <0.0001
Going to school 60165 [54.4] 567 [0.9] 85 [0.1] 206 [0.3] 787 [1.3] 1.00 [ref] 1.00 [ref]
School dropout 31004 [28.0] 1985 [6.4] 800 [2.6] 405 [1.3] 2605 [8.4] 6.92[6.38-7.51] 6.62[6.08-7.20]
Never been to
school 19428 [17.6] 1140 [5.9] 474 [2.4] 409 [2.1] 1602 [8.2] 6.78[6.22-7.40] 7.32[6.65-8.06]
Marital Status p<0.0001 p<0.0001 p<0.0001 p<0.0001
Never married 102311 [92.1] 3106 [3.0] 1146 [1.1] 822 [0.8] 4203 [4.1] 1.00 [ref] 1.00 [ref]
Ever Married1 8766 [7.9] 595 [6.8] 223 [2.5] 202 [2.3] 811 [9.3] 2.38[2.20-2.57] 2.98[2.71-3.28]
Religion p<0.0001 p<0.0001 p<0.0001 p=0.131
Hindu 87794 [79.0] 3028 [3.5] 1029 [1.2] 882 [1.0] 4017 [4.6] 1.00 [ref] 1.00 [ref]
Muslim 16843 [15.2] 491 [2.9] 280 [1.7] 30 [0.2] 713 [4.2] 0.92[0.85-1.00] 0.96[0.87-1.06]
Others2 6440 [5.8] 183 [2.8] 61 [0.9] 111[1.7] 283 [4.4] 0.96[0.85-1.09] 0.94[0.82 -1.09]
Caste/tribe status3 p<0.0001 p<0.0001 p<0.0001 p<0.0001
Scheduled caste 20816 [18.7] 827 [4.0] 326 [1.6] 187 [0.9] 1068 [5.1] 1.00 [ref] 1.00 [ref]
Scheduled tribe 9702 [8.7] 676 [7.0] 164 [1.7] 433 [4.5] 1034 [10.7] 2.21[2.02-2.41] 1.83[1.66-2.02]
Other backward
class 35938 [32.4] 1031 [2.9] 371 [1.0] 266 [0.7] 1373 [3.8] 0.73[0.68-0.80] 0.89[0.81-0.97]
Other 37766 [34.0] 951 [2.5] 402 [1.1] 121 [0.3] 1249 [3.3] 0.63[0.58-0.69] 0.83[0.75-0.91]
Missing caste 6856 [6.2] 216 [3.2] 106 [1.5] 17 [0.2] 291 [4.2] 0.82[0.72-0.93] 0.79[0.68-0.94]
Standard of living4 p<0.0001 p<0.0001 p<0.0001 p<0.0001
Low 35145 [32.0] 1727 [4.9] 608 [1.7] 539 [1.5] 2317 [6.6] 1.00 [ref] 1.00 [ref]
Medium 54143 [49.3] 1687 [3.1] 674 [1.2] 433 [0.8] 2331 [4.3] 0.64[0.60-0.68] 0.87[0.81-0.93]
High 20427 [18.6] 246 [1.2] 75 [0.4] 43 [0.2] 312 [1.5] 0.22[0.20-0.25] 0.45[0.39-0.51]
Residence p<0.0001 p<0.0001 p<0.0001 p<0.0001
Urban 29375 [26.4] 747 [2.5] 171 [0.6] 90 [0.3] 865 [2.9] 1.00 [ref] 1.00 [ref]
Rural 81702 [73.6] 2955 [3.6] 1198 [1.5] 934 [1.1] 4149 [5.1] 1.76[1.64-1.90] 1.19[1.10-1.30]
Gender of head of the household in
which the adolescent live p=0.027 p=0.011 p=0.342 p=0.004
Male 101958 [91.8] 3366 [3.3] 1233 [1.2] 935 [0.9] 4552 [4.5] 1.00 [ref] 1.00 [ref]
Female 9120 [8.2] 336 [3.7] 136[1.5] 88 [1.0] 462[5.1] 1.14[1.03-1.26] 1.19[1.07-1.33]
Composition of adult in the household
in which the adolescent live p<0.0001 p<0.0001 p<0.0001 p<0.0001
Two adults,
opposite sex 18631 [16.8] 346 [1.9] 108 [0.6] 114 [0.6] 478 [2.6]
1.00 [ref] 1.00 [ref]
Three+ related
adult 88249 [79.4] 3200 [3.6] 1193 [1.4] 857 [1.0] 4326 [4.9] 1.96[1.78-2.15] 1.52[1.37-1.68]
Others54197 [3.8] 155 [3.7] 67 [1.6] 53 [1.3] 210 [5.0] 2.00[1.69-2.36] 1.58[1.32-1.89]
Geographic regions6 p<0.0001 p<0.0001 p<0.0001 p<0.0001
North
14203 [12.8] 228 [1.6] 235 [1.7] 77 [0.5] 453 [3.2] 1.44[1.27-1.63] 1.79[1.57-2.05]
Northeast 4307 [3.9] 269 [6.3] 80 [1.9] 194 [4.5] 443 [10.3] 5.10[4.40-5.71] 5.42[4.67-6.28]
Central 28681 [25.8] 1095 [3.8] 424 [1.5] 193 [0.7] 1394 [4.9] 2.23[2.02-2.47] 2.23[2.01-2.48]
East 24250 [21.8] 1098 [4.5] 356 [1.5] 301 [1.2] 1367 [5.6] 2.61[2.36-2.89] 2.36[2.12-2.63]
West 15848 [14.3] 771 [4.9] 81 [0.5] 46 [0.3] 823 [5.2] 2.39[2.14-2.67] 2.63[2.34-2.97]
South 23789 [21.4] 242 [1.0] 193 [0.8] 212 [0.9] 533 [2.2] 1.00 [ref] 1.00 [ref]
Number 111077 3702 [3.3] 1370 [1.2] 1024 [0.9] 5014 [4.5]
Note: p values are from Chi square test
1Never married are those who were not married till the date of survey. Ever married includes currently married, married but gauna (a ritual after marriage) not performed, separated, divorced,
and deserted.
2Other religion includes Christian, Buddhist, Jain, Jewish, Zoroastrian, and others.
3Caste was based on the respondent's self-identification as belonging to scheduled caste, scheduled tribe, other backward class, other caste, or no caste group. Scheduled castes and
scheduled tribes are castes and tribes that the Government of India identifies as socially and economically backward and in need of special protection from social injustice and exploitation.
Scheduled tribe and scheduled caste are the most socially disadvantaged groups. Scheduled caste consists of castes that are lowest in the traditional Hindu caste hierarchy (Chitnis, 1997)
and as a consequence that experience intense social and economic segregation and disadvantage. Scheduled tribes comprise 700 tribes who tend to be geographically isolated with limited
economic and social interaction with the rest of the population. “Other backward class” is a diverse collection of intermediate castes that were considered low in the traditional caste hierarchy
but are clearly above scheduled castes. “Other caste” is thus a default residual group that enjoys higher status in the caste hierarchy.
4Standard of living was defined in terms of household assets and material possessions and these have been shown to be reliable and valid measures of household material well-being. It is an
index which is based on ownership of a number of different consumer durables and other household items. It is calculated by adding the following scores: house type: 4 for pucca, 2 for semi-
pucca, 0 for kachacha; toilet facility: 4 for own flush toilet, 2 for public or shared flush toilet or own pit toilet, 1 for shared or public pit toilet, 0 for no facility; source of lighting: 2 for electricity, 1 for
kerosene, gas or oil, 0 for other source of lighting; main fuel for cooking: 2 for electricity, liquefied natural gas, or biogas, 1 for coal, charcoal, or kerosene, 0 for other fuel; source of drinking
water: 2 for pipe, hand pump, or well in residence/yard/plot, 1 for public tap, hand pump, or well, 0 for other water source; separate room for cooking: 1 for yes, 0 for no; ownership of house: 2 for
yes, 0 for no; ownership of agricultural land: 4 for 5 acres or more, 3 for 2.04.9 acres, 2 for less than 2 acres or acreage not known, 0 for no agricultural land; ownership of irrigated land: 2 if
household owns at least some irrigated land, 0 for no irrigated land; ownership of livestock: 2 if own livestock, 0 if not own livestock; durable goods ownership: 4 for a car or tractor, 3 each for a
moped/scooter/motorcycle, telephone, refrigerator, or color television, 2 each for a bicycle, electric fan, radio/transistor, sewing machine, black and white television, water pump, bullock cart,
or thresher, 1 each for a mattress, pressure cooker, chair, cot/bed, table, or clock/watch. Index scores range from 014 for low SLI to 1524 for medium SLI to 2567 for high SLI.
5 Others include one adult/two adults of same sex or unrelated adults
6 North- Delhi, Haryana, Himachal Pradesh, Jammu & Kashmir, Punjab, Rajasthan; Northeast- Arunachal Pradesh, Assam, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim; Central-
Madhya Pradesh, Uttar Pradesh; East- Bihar, west Bengal, Orissa; West- Goa, Maharashtra, Gujarat; South-Tamil Nadu, Kerala, Andhra Pradesh, Karnataka
# Adjusted
Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
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CONCLUSION
In this large, cross sectional, population-based
study in India, we found significant risk taking
behaviour among adolescents which is determined
by their socio-economic and living arrangement
characteristics. These results add to the dearth of
evidence at the national level about determinants of
adolescent risk taking behaviour in a developing
country set up and calls for urgent governmental
prevention and control programmes.
ACKNOWLEDGEMENTS
An earlier version of this paper was presented at the
Oral session in the XXV IUSSP International
Population Conference Tours, France 18-23 July
2005; Presented as a poster at the International
Conference on ‘Emerging Population Issues in the
Asia Pacific Region: Challenges for the 21st
Century’ Mumbai, India December 10-13, 2006. SA
is supported by a welcome Trust Strategic Award
Grant No Z/041825. No other direct financial
support was available for this study. The support of
International Institute for Population Sciences
(www.iipsindia.org) and Macro International
(www.measuredhs.com) for providing access to the
1998-99 Indian National Family Health Survey data
is gratefully acknowledged.
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Conflict of interest: The authors declare no
conflict of interest.