ArticlePDF Available

Abstract

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. Risktaking 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.
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
28
www.jcnh.in Agrawal & Agrawal
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
29
www.jcnh.in Agrawal & Agrawal
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
30
www.jcnh.in Agrawal & Agrawal
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.
REFERENCES
1. Center for Disease Control (CDC): Preventing
Tobacco Use Among Young People - A Report
of the Surgeon General, Atlanta: CDC, United
States. 1994
2. Gruber E, Clemente RJ, Anderson NM, Lodico
M: Early drinking onset and its association with
alcohol use and problem behavior in late
adolescence, Preventive Medicine. 1996,
25:293-300.
3. World Health Organization (WHO): Tobacco
or Health, A Global Status Report, Geneva:
WHO. 1997
4. Tan ML: A Review of Social and Behavioral
Studies Related to HIV/AIDS in the
Philippines, Manila: Health Action Information
Network. 1994
5. Corraro MA, Guidon GE, Sharma N, Shokoohi
DF, eds: Tobacco Control Country Profiles,
Atlanta: American Cancer Society. 2000
6. Kishore J, Singh A, Grewal I, Singh SR, Roy K.
Risk behaviour in an urban and a rural male
adolescent population. Natl Med J India.
1999;12:107-10.
7. Singh SK, Schensul JJ, Gupta K, Maharana B,
Kremelberg D, Berg M. Determinants of
alcohol use, risky sexual behavior and sexual
health problems among men in low income
communities of Mumbai, India. AIDS Behav.
2010; 14:S48-60.
8.
9. Arora M, Tewari A, Tripathy V, et al.
Community-based model for preventing
tobacco use among disadvantaged
adolescents in urban slums of India. Health
Promot. Int. 2010; 25: 143-152.
10. Poland B, Frohlich K, Haines RJ,
Mykhalovskiy E, Rock M, Sparks RJ. The
social context of smoking: the next frontier in
tobacco control? Tobacco Control 2006;
15:59-63.
11. Neumark-Sztainer D: Patterns of health-
compromising behaviors among Minnesota
adolescents: socio-demographic variations,
American Journal of Public Health. 1996, 86:
1599-1606.
12. Blum RW, Rinehart PM: Reducing the Risk:
Connections that Make a Difference in the
Lives of Youth, Minneapolis: Division of
General Pediatrics and Adolescent Health,
University of Minnesota, United States, 1997.
http://www.who.int/tobacco/ surveillance/
en_tfi_india_gats_fact_sheet.pdf
Journal of Community Nutrition & Health, Vol.1, Issue 2, 2012
31
www.jcnh.in Agrawal & Agrawal
13. Resnick MD: Protecting adolescents from
harm, Journal of American Medical
Association, 1997; 278:823-832.
14. Jessor R, Turban MS, Costa FM: Protective
factors in adolescent health behavior, Journal
of Personality and Social Psychology 1998;
75:788-800.
15. Kirby D: Emerging Answers: Research
Findings on Programs to Reduce Teen
Pregnancy, Washington, D.C.: National
Campaign to Prevent Teen Pregnancy. 2001
16. Sittirai W, Praphan P, Barry J, Brown T: Thai
Sexual Behavior and Risk of HIV Infection: A
Report for the 1990 Survey of Partner
Relations and Risk of HIV Infection in
Thailand, Bangkok: Program on AIDS, Thai
Red Cross Society and Institute of Population
Studies, Chulalongkorn University. 1992.
17. Choe MK, Raymundo CM: Initiation of
smoking, drinking, and drug-use among
Filipino youth, Philippines Quarterly of Culture
and Society 2001; 29:105-132.
18. Podhisita C, Xenos P, Juntarodjana J,
Varangrat A: Drinking, Smoking, and Drug
Use among Thai Youth: Effects of Family and
Individual Factors, East-West CenterWorking
Papers Population Series, No. 108-6,
Honolulu: East-West Center, United States.
2001.
19. International Institute for Population Sciences
(IIPS) and ORC Macro. National Family
Health Survey (NFHS-2), 1998-99: India:
Volume I. Mumbai: IIPS. 2000.
Conflict of interest: The authors declare no
conflict of interest.
... Teenagers who were female, scheduled tribal, other backward class, or any other category members, as well as those who lived in homes with a medium or better quality of living, were less likely to engage in any risk-taking conduct. (Agrawal & Agrawal, 2013). ...
... There was little information available on the factors that influence alcohol consumption since alcohol use was not the primary result of many studies. One survey relied on an adult household member to provide information on teenagers, which may have led to misreporting (Agrawal & Agrawal, 2013). Despite the coexistence of smoking, drink, and drug use among teenagers, seven studies that examined all three of these behaviors were disregarded because it was challenging to isolate data specifically related to alcohol use. ...
Research Proposal
Full-text available
Drinking indecently is a severe public health issue. Sipping or tasting frequently leads to regular alcohol or worsening habits such dangerous excessive drinking or addiction, alcoholism, or even death. Social and structural factors that have an impact on adolescents' health at the individual, family, community, and societal levels have a significant impact. Violence, mental health issues, creating the risk but rather self-harm, HIV or other viral infections, poor educational performance and dropout rates, limited employment opportunities, and accidents here on road or other unintentional injuries are just a slew of negative effects of adolescent alcohol consumption. The purpose of this review is to look at the research and determine what factors lead to teen consumption in Asian countries. The study made extensive use of internet resources including Pubmed and CINHAL. The study made extensive use of internet resources including Pubmed and CINHAL. After that, databases were accessed to conduct a more extensive literature search using key phrases and chemical operator to find publications pertinent to the issue. 64 records were found. Duplicate entries and those that didn't fit the criteria were removed. A criteria for inclusion/exclusion was used to filter 8 items. Results indicated that elevated risks of teenage drinking were linked with male gender, age, melancholy, religious belief, parental/family members' drinking, lower parental attention, peer drinking/pressure/approval, and urban neighborhood. Given that they assist young people in controlling their drinking, such organizations may be crucial to consider when developing health programs for teens in the region. In order to protect south Asian young teenagers from the harmful effects of alcohol use, it is important to have a thorough knowledge of the factors that influence adolescent substance use in Asia. This will allow 11366 for the development of context-specific public health initiatives that are effective and assisted by strict regulatory guidelines.
... Teenagers who were female, scheduled tribal, other backward class, or any other category members, as well as those who lived in homes with a medium or better quality of living, were less likely to engage in any risk-taking conduct. (Agrawal & Agrawal, 2013). ...
... There was little information available on the factors that influence alcohol consumption since alcohol use was not the primary result of many studies. One survey relied on an adult household member to provide information on teenagers, which may have led to misreporting (Agrawal & Agrawal, 2013). Despite the coexistence of smoking, drink, and drug use among teenagers, seven studies that examined all three of these behaviors were disregarded because it was challenging to isolate data specifically related to alcohol use. ...
Article
Full-text available
Drinking indecently is a severe public health issue. Sipping or tasting frequently leads to regular alcohol or worsening habits such dangerous excessive drinking or addiction, alcoholism, or even death. Social and structural factors that have an impact on adolescents' health at the individual, family, community, and societal levels have a significant impact. Violence, mental health issues, creating the risk but rather self-harm, HIV or other viral infections, poor educational performance and dropout rates, limited employment opportunities, and accidents here on road or other unintentional injuries are just a slew of negative effects of adolescent alcohol consumption. The purpose of this review is to look at the research and determine what factors lead to teen consumption in Asian countries. The study made extensive use of internet resources including Pubmed and CINHAL. The study made extensive use of internet resources including Pubmed and CINHAL. After that, databases were accessed to conduct a more extensive literature search using key phrases and chemical operator to find publications pertinent to the issue. 64 records were found. Duplicate entries and those that didn't fit the criteria were removed. A criteria for inclusion/exclusion was used to filter 8 items.
Chapter
The chapter discusses the mental health problems/mental disorders faced by adolescents in the Indian as well as global context. Factors related to mental health problems in adolescents are explained. The many trends in mental health problems, such as stress, suicidal tendencies, substance use and abuse, etc., in adolescents are discussed highlighting the symptomatology, diagnostic criteria, prevalence of the disorder, causes, and treatment measures. Further, emotional and behavioural disorders, risk-taking behaviours, eating disorders, anxiety disorder, and schizophrenia are also discussed.
Article
Full-text available
This paper summarizes the main results of the survey component of a mixed methods study of alcohol and sexual risk in a general population of young men 18-29 residing in low income communities in the Greater Mumbai area. The survey included demographic variables, and scales and indices measuring work related stress, social influence, exposure to alcohol in childhood, and currently, hyper masculinity, exposure to media and pornography, risk related leisure time activities and alcohol and alcohol/sex expectancies. Measures of alcohol use included frequency/amount/contextual use of six different types of alcohol, a general estimate of frequency and amount (AUDIT), and an estimate of total ml. alcohol consumed in the past 30 days, based on estimates of alcohol content in all types of alcohol consumed, by unit of consumption (glass, peg, bottle) etc. Sexual outcome measures included types and number of partners ever and in past year with and without alcohol, and a critical event with most recent partner (with or without alcohol) and culturally specific indicators of sexual health related to sexual risk taking. A cluster sampling protocol and the use of a screener produced a sample of 1239 men, 1071 thirty day drinkers and 161 nondrinkers. Logistic regression analysis (binary and multinomial) showed relationships between predictor variables and alcohol consumption and alcohol and sexual risk indicators as well as two of the sexual health indicators associated with extramarital sex. Risk behaviors are associated with higher levels of alcohol consumption in this low risk general population of married and unmarried men. Implications for intervention include: (a) reducing or eliminating home drinking, to reduce early childhood exposure; (b) including alcohol in sexual risk and HIV prevention programs; (c) improving couples (married or unmarried) communication to reduce men's search for sexual alternatives, and (d) treating garmi as an indicator of sexual risk taking rather than STIs.
Article
Full-text available
Tobacco consumption in multiple forms presents an emerging, significant and growing threat to the health of Indian adolescents, especially those from low socio-economic communities. Research in two phases was undertaken among economically disadvantaged adolescents in two urban slums of Delhi. In phase I, qualitative research methods such as focus group discussions and in-depth interviews were used to explore and understand the determinants influencing tobacco use among these adolescents. Prevalence of tobacco use was higher among boys than girls. Adolescents reported using tobacco in multiple forms, chewing tobacco being the most popular. Peer pressure, easy availability and affordability were important reasons associated with tobacco initiation and continued use. Though they had some knowledge about the harmful effects of tobacco, this was not sufficient to motivate them to abstain or quit. The community-based intervention model developed on the basis of the results of phase I was evaluated in phase II in a demonstration study with two slum communities. One was treated as the intervention and the other as control. A significant difference in current use of tobacco was observed between the study groups (p = 0.048), with the intervention group showing a reduction in use, compared with an increase in use among the control group. Post-intervention, the intervention group reported significantly lower fresh uptake (0.3%) of tobacco use compared with the control group (1.7%). No significant change was found for quit rate (p = 0.282) in the two groups. Community-based interventions can be effective in preventing adolescents from initiating tobacco use in a low-resource setting such as India.
Article
Full-text available
The role of psychosocial protective factors in adolescent health-enhancing behaviors--healthy diet, regular exercise, adequate sleep, good dental hygiene, and seatbelt use--was investigated among 1,493 Hispanic, White, and Black high school students in a large, urban school district. Both proximal (health-related) and distal (conventionality-related) protective factors have significant positive relations with health-enhancing behavior and with the development of health-enhancing behavior. In addition, in cross-sectional analyses, protection was shown to moderate risk. Key proximal protective factors are value on health, perceived effects of health-compromising behavior, and parents who model health behavior. Key distal protective factors are positive orientation to school, friends who model conventional behavior, involvement in prosocial activities, and church attendance. The findings suggest the importance of individual differences on a dimension of conventionality-unconventionality. Strengthening both proximal and distal protective factors may help to promote healthful behaviors in adolescence.
Article
Full-text available
There is an increasing trend of risk behaviour in adolescents worldwide but very little literature is available in India on this important subject. We surveyed an urban male adolescent population and a comparable rural population to determine the difference in their risk behaviour. A comparative cross-sectional study was conducted among 199 and 152 male adolescents from an urban village of south Delhi and a rural village in Uttar Pradesh. A pretested semi-structured interview schedule with 36 items was applied on all subjects by trained interviewers. Consuming alcohol, smoking, pre-marital sexual intercourse and consuming bhang (cannabis) were present in 32.2%, 25.1%, 12.5% and 11.5% of the urban village adolescents and in 1.3%, 48.7%, 11.2%, and 16.5% of those residing in the rural village, respectively. About 66.8% of urban and 51.3% of rural adolescents had indulged in physical fights and 12.5% of urban and 6.6% of rural adolescents were in possession of assault weapons such as iron rods, chains or knives sometime in the 30 days prior to the interview. The results of our study indicate that there is a high prevalence of risk behaviour in both urban and rural adolescents. However, except for smoking which was more common amongst rural adolescents all the other risk behaviours were more in those residing in urban areas. The reasons for this need to be ascertained, taking the geographical and socio-cultural factors into account, prior to considering the introduction of behaviour modification programmes.
Article
Full-text available
A better understanding of the social context of smoking may help to enhance tobacco control research and practice.
Article
This report summarizes three bodies of research on teenage pregnancy and programs to reduce the risk of teenage pregnancy. Studies included in this report were completed in 1980 or later, conducted in the United States or Canada, targeted adolescents, employed an experimental or quasi-experimental design, had a sample size of at least 100 in the combined treatment and control group, and measured the impact on sexual or contraceptive behavior, pregnancy, or childbearing. Six chapters focus on: (1) "Making the Case for Prevention Efforts: Adolescent Risk-Taking Behavior and Its Consequences"; (2) "Looking for Reasons Why: The Antecedents of Adolescent Sexual Behavior"; (3) "Assessing the Evidence: Factors Affecting the Strength of Research Results"; (4) "Emerging Answers: The Behavioral Impact of Programs To Reduce Adolescent Sexual Risk-Taking"; (5) "Looking Forward: Conclusions about the State of Research and the Effectiveness of Programs"; and (6) "Bringing It Home: Applying These Research Results in Communities." (Chapters contain references.) (SM)
Article
To examine the relationship between age of drinking onset and patterns of use, abuse of other substances, and the prevalence of other alcohol-related problems in a population of midwestern high school seniors. We analyzed self-report survey data on public school students' history of alcohol and other drug use and related problems from the Minnesota Student Survey conducted in 1989. The sample consisted of 2,650 male and female seniors, representing a 10% random sample of all white seniors in the study. The findings suggest that early onset of alcohol use (by age 12) is associated with subsequent abuse of alcohol and related problem behaviors in later adolescence, including alcohol-related violence, injuries, drinking and driving, and absenteeism from school or work, as well as increased risks for using other drugs. This paper identifies the preadolescent years from age 10 to 12 as a particularly vulnerable period for the development of early alcohol dependence and abuse. Delaying alcohol use onset to age 13 may significantly reduce the risk of severe alcohol abuse in later adolescence.
Article
This study compared prevalence rates of health-compromising behaviors among boys and girls from different ethnic backgrounds in early, middle, and late adolescence and compared co-occurrences of such behaviors across gender and ethnic groups. The study population included 123 132 adolescents in grades 6, 9, and 12. Adolescents completed a classroom-administered statewide survey focusing on high-risk behaviors, including unhealthy weight loss, substance abuse, suicide risk, delinquency, and sexual activity. Prevalence rates of most health-compromising behaviors differed by gender, increased with age, and tended to be highest among American Indian youth and lowest among Asian Americans. Strong associations were found between substance abuse and delinquency across all ethnic groups. Substance abuse and delinquency were associated with suicide risk across most ethnic groups. Covariations with sexual activity and unhealthy weight loss behaviors showed more ethnic variation. Prevention interventions should take into account the tendency for health-compromising behaviors to co-occur and should be sensitive to demographic and socioeconomic differences in behavior patterns.