Indian journal of pediatrics · 2013
ADad 6: the predictive factors for Anxiety Disorders among adolescents in a rural community population in India.
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Nair M K C, Russell Paul Swamidhas Sudhakar, Subramaniam Vinod Shanmukham, Nazeema Suma, Sequeira Anupama Zeena, Chembagam Neethu, George Babu
Аннотация
OBJECTIVE: Development of Anxiety Disorders (AD) among adolescents is the interplay of risk and protective factors that have a biological and environmental basis. This study documents the predictive factors associated with the presence of AD among adolescents in India.
METHODS: The authors prospectively collected data for 500 adolescents in a community with independent, trained raters. Data on the dependent variable of AD and its subtypes was collected with Screen for Child Anxiety Related Emotional Disorders (SCARED), Socio-economic status with Modified Kuppuswamy Scale, depression with Beck Depression Inventory and the other independent variables with a specially designed proforma. The predictive factors for the presence of AD were analyzed with univariate and multivariate regression analyses appropriately, and a parsimonious predictive model was built.
RESULTS: Gender (adjusted OR = 1.96), and presence of Depressive Disorder (adjusted OR = 24.14) emerged as independent risk factors. Level of education came-out as a protective factor (adjusted OR = 0.66). Adolescent girls were at risk of developing Separation Anxiety Disorder (SeAD) (adjusted OR = 3.51) and Social Anxiety Disorder (SoAD) (adjusted OR = 1.69). Level of education had a protective influence on SeAD (adjusted OR = 0.39) and SoAD (adjusted OR = 0.59) among those doing high school. This protective effect increased if they were in higher-secondary school for SeAD (adjusted OR = 0.21) and SoAD (adjusted OR = 0.22). In the multivariate model age of the adolescent also gained significance and the 3-factor model had a good model fit. Panic Disorder and Generalized Anxiety Disorder were not related to any specific variable.
CONCLUSIONS: Identifying the factors associated with AD and the subtypes can be used to predict, prevent or treat these disorders in this population. Educating adolescent girls to higher-secondary school level seem to be an important step in this direction.
METHODS: The authors prospectively collected data for 500 adolescents in a community with independent, trained raters. Data on the dependent variable of AD and its subtypes was collected with Screen for Child Anxiety Related Emotional Disorders (SCARED), Socio-economic status with Modified Kuppuswamy Scale, depression with Beck Depression Inventory and the other independent variables with a specially designed proforma. The predictive factors for the presence of AD were analyzed with univariate and multivariate regression analyses appropriately, and a parsimonious predictive model was built.
RESULTS: Gender (adjusted OR = 1.96), and presence of Depressive Disorder (adjusted OR = 24.14) emerged as independent risk factors. Level of education came-out as a protective factor (adjusted OR = 0.66). Adolescent girls were at risk of developing Separation Anxiety Disorder (SeAD) (adjusted OR = 3.51) and Social Anxiety Disorder (SoAD) (adjusted OR = 1.69). Level of education had a protective influence on SeAD (adjusted OR = 0.39) and SoAD (adjusted OR = 0.59) among those doing high school. This protective effect increased if they were in higher-secondary school for SeAD (adjusted OR = 0.21) and SoAD (adjusted OR = 0.22). In the multivariate model age of the adolescent also gained significance and the 3-factor model had a good model fit. Panic Disorder and Generalized Anxiety Disorder were not related to any specific variable.
CONCLUSIONS: Identifying the factors associated with AD and the subtypes can be used to predict, prevent or treat these disorders in this population. Educating adolescent girls to higher-secondary school level seem to be an important step in this direction.