Review of Economics and Development Studies Vol. I, No 1, June 2015 1 Volume and Issues Obtainable at Center for Sustainability Research and Consultancy Review of Economics and Development Studies ISSN:2519-9692 ISSN (E): 2519-9706 Volume 1: Issue 1 June 2015 Journal homepage: www.publishing.globalcsrc.org/reads Psychosocial Health of Adolescent living in Urban Slum Nigeria 1 Adenike E. Idowu, 2 Emmanuel O. Amoo, 3 Idowu I. Chiazor, 4 Olujide Adekeye 1 University of Witwatersrand, Johannesburg, South Africa.esther.idowu@covenantuniversity.edu.ng 2 University of Witwatersrand, Johannesburg, South Africa.emme.amoo@covenantuniversity.edu.ng 3 South Africa.idowu.chiazor@covenantuniversity.edu.ng 4 Covenant University, Ota, Ogun State Nigeria.jide.adekeye@covenantuniversity.edu.ng ARTICLEDETAILS ABSTRACT History Revised format: May 2015 Available online: June 2015 The paper examines association of neighborhood characteristics with psychosocial statues of adolescent living in urban slums. Data for the study were obtained from a cross sectional survey among adolescent age 15-19, living in urban slums in Lagos State. Adopted a measuring scale for adverse environment and psychosocial attributes, data were analyzed using univariate and binary logistic regression analysis. Results revealed that neighborhood characteristics were associated with low self-academic performance rating. Both parental process and neighborhood factors such social disorganization was able to predict psychosocial wellbeing such subjective academic performance rating. The findings revealed among others that adverse neighborhood characteristics in urban slum were associated with unhealthy subjective wellbeing which reflects wide personal and social contexts and have implications for public health and social wellbeing. This paper calls for programmes that are tailor to addressing rapidly developing slum settlements in low income area, to secure the future generation. © 2015 The authors, under a Creative Commons Attribution- NonCommercial 4.0 Keywords Urbanization Psychological wellbeing Urban slums JEL Classification I15, R20 Corresponding author’s email address: esther.idowu@covenantuniversity.edu.ng Recommended citation:Idowu, A. E., Amoo, E. O.,Chiazor, I. I., AdekeyeO. (2015).Psychosocial Health of Adolescent living in Urban Slum Nigeria.Review of Economics and Development Studies, 1 (1) 1-10 DOI:https://doi.org/10.26710/reads.v1i1.111 1. Introduction Adolescence is viewed as a period when adult personal and social identities begin to take shape through the process of social interaction and are thus vulnerable to several risk behavior and adverse health effects, intensified by poverty and unstable social context such as living in slum (Ndugwa, Kabiru, Cleland, Beguy, Egondi, Zulu, and Jesor, (2011; Clarke, 2010 ). Living in slums, which are characterized by lack of basic services, substandard housing, overcrowding and high density, unhealthy living condition and hazardous locations, insecure tenure, informal settlements, poverty and social http://www.publishing.globalcsrc.org/reads mailto:esther.idowu@covenantuniversity.edu.ng mailto:emme.amoo@covenantuniversity.edu.ng mailto:idowu.chiazor@covenantuniversity.edu.ng mailto:jide.adekeye@covenantuniversity.edu.ng mailto:esther.idowu@covenantuniversity.edu.ng Review of Economics and Development Studies Vol. I, No 1, June 2015 2 exclusion, can be linked to increases related to negative social behaviors, child abuse and can directly affect children education (Sheuya, 2008). Other risk factors of adolescent health are due to many pressures and challenges they are facing from growing academic expectations, changing social relationships with family and peers and the physical and emotional changes associated with maturation (World Health Organization, 2012: Omigbodun, Dogra, Esan and Adedokun, 2008). They face issues of puberty, first exposure to relationship, drugs, alcohol, or sex, embracing life career and so on (McNeely, and Blanchard, 2009). Their behaviors therefore are products of social, economic and cultural forces of and within the communities where they live. According to classification of social determinant of health by WHO (2005), health can be approach intermediate factors such as living and working conditions, social and political exclusion, social capital, access to quality health care, violence and crime, transportation, and the physical environment. These identified factors continue to affect adolescent on issues such as mental health, the development of health complaints, tobacco use, diet, physical activity level and alcohol use (WHO, 2012; Thomas, Torrone, and Browing, 2010; Omigbodunet al, 2008; Saluja, Lachan, Scheidt, Overpeck, Sun, and Giedd, 2004 ). All these factors have been investigated almost completely at an individual and family level (Salujaet al, 2004; Park, 2004; Li, Feigelman, and Stanton, 2000). Few studies have accessed the influence of the environment on adolescent behaviour, academic performance and subjective wellbeing (Oshodi, Aina and Onajole, 2010, Adedimaji, Omololu, and Odutolu, 2007). In the their study, Adedimajiet al, (2007) investigated the relationship between HIV/AIDS risk perception and protective behaviour among sexually-active urban young slum dwellers in Ibadan and found that structural and environmental constraints were identified as barriers to adopting protective behaviour. This study explored the influence of environment on psychosocial health of the adolescent living in urban slums in Nigeria. 2. Literature review Writer such as Jessor, (1991) assert that large segments of our young people are growing up in circumstances of limited resources and pervasive adversity that, for many of them, their health, their development, indeed their lives as a whole, are certain to be severely and perhaps irretrievably compromised. Both family and neighborhood socioeconomics predicted occurrence and perception of stressors in adolescent (Chen and Paterson, 2006). Family contexts are associated with health and risky behaviours in adolescents: family economic circumstances and personal traits of parents can affect the characteristics of the peers, schools, and neighborhoods to which parents and children are exposed and, in turn, the psychological well-being of family members (Conger, Conger, and Martin, 2010; Das, 2000). Consequently, living in a neighbourhood with low socioeconomic status confers risk to adolescents in terms of a host of behavioural, social, and emotional problems (The National Academies, 2011), and may be more vulnerable to negative psychosocial health effect from distress and adverse urban slum characterized by congestion, high levels of unemployment, inadequate social services, extreme poverty, insecurity, crime, and hopelessness. Gonzales, Cauce, Friedman, and mason (1996) highlighted the influence of neighbourhood on the problem of academic underachievement, relating neighbourhood risk to lower grades in school. As reported in Columbia University TeenScreen National center for Mental Health Checkups (2009), adolescent with a lifetime occurrence of social phobia are almost twice as likely to fail a grade of not finish high school. In a state like Lagos, one of the most populous states in Nigeria, that has undergone an unprecedented rate of urbanization in the few years (Odufuwa, Fransen, Bongwa, &Gianoli, 2009; Ilesanmi, 2010). Consequent movement of people to the state has put pressure on government and individuals as the demand for housing continue to rise far and above what the state can offer. Rapid social, economic and environmental challenges is evident in poor services delivery, lack of adequate and affordable housing, Review of Economics and Development Studies Vol. I, No 1, June 2015 3 proliferation of slums, chaotic conditions, poverty, social polarization, crime, violence, unemployment and dwindling job opportunities (Celik, Zyman, and Mahdi 2009; Ilesanmi, 2010). This is evidence in the occurences of slums/ghettos and squalor in Maroko, Ajegunle, Orile/Amuwo, ipori-Olaleye, and Agegeetc (Fadairo&taiwo, 2009). Therefore, slum settlements are formed mainly because of the inability of the city governments to plan and provide affordable housing for the low-income segments of the urban population (UN Habitat, 2016). Hence, squatter and slum housing is the housing solution for this low-income urban population. (LingOoi, and HougPhua, 2007; Akunnaya, and Adedapo,2014). These changes and associated declines in social, economic and environmental standard will have serious consequences on individual standard of living. It is known that neighbourhoods with good physical and social structures and services that help maintain the wellbeing and productivity of its inhabitants foster community cohesion (World Health organization, 2007). In the context of social, economical and environmental insecurity, life-style change, although obviously a challenge has the promise of more pervasive and more enduring impact on the repertoire of risk and health behaviours in adolescents (Jessor, 1991). Therefore, the health of adolescents may be jeopardize in a slum that characterized by urban decay, high rates of poverty and unemployment, where many slum dwellers employs themselves in the informal economy usually with low incomes. These including street vending, drug dealing, domestic work and other form of home based economic activities. As a result, slums are identified as breeding grounds for social problems such as crime, drug addiction, alcoholism, high rates of mental illness and suicide. They are also characterized by high rates of diseases due to insanitary conditions, malnutrition, and lack of basic health care services (Njoku, andOkoro, 2014). Stephens 2012, explores the impact of the process of urban social, environmental, and health inequality and inequity on urban children and young people and found that mental disability, or mental illness, is a global problem of current generation of urban children and may be particularly difficult in very inequitable urban settings where children may grow up in a very stressful, threatening, and disorienting environment with impacts on social coping, self-esteem, anxiety, and aggression (Stephens, 2012; Stewart-Brown, 2003). In essence, all children growing up in cities with great inequalities may be vulnerable to problems of emotional and psychosocial well-being. Therefore, the shift towards social morbidity among young people means that the major threats to their health wellbeing are increasingly rooted in the organization, economics, opportunities and expectations of everyday life. This means that the search for protective factors against a variety of adverse outcomes must include an understanding of adolescents’ social relationships and feelings of connections to others as they experience and live the developmental changes of their physical, social and psychological selves. (Resnick, Harris, and Blum, 1993). In Sampson (1986) model, social disorganization may have an effect on youth through its effects on family structures and stability. Social disorganization variables may influence community crime rates when taking into account the effects of levels of family disruption; that may occur by removing an important set of control structures over youths’ behaviours and creating greater opportunities for criminal victimization. Sampson, Raudenbush and Earls’s (1997) model of social disorganization argued that socially disorganized neighbourhoods are likely to be low on collective efficacy, unlikely to intervene in a neighbourhood context in which the rules are unclear and people mistrust or fear one another. In their causal model on direct and moderating effects of community context on the psychological well- being, Cutrona, Russell, Hessling, Brown and Murry (2007) identified certain neighbourhood-related domains that could affect the outcome of the interaction between subjects and environment. For Review of Economics and Development Studies Vol. I, No 1, June 2015 4 instance, when personal bounds are absent, people do not work together to garner needed resources for their community, such as adequate police protection, high quality schools, and access to needed services, the absence of such resources can lead to demoralization. And neighbourhood that present threats to safety, inadequate public transportation, poor quality housing, high traffic density, and undesirable commercial operations impose a high level of daily strain on residents, such strains are consistently associated with psychological distress (Cutronaet al, 2007). In this study we explore the association of neighbourhood characteristics and psychosocial health among young adolescent living in urban slum in Lagos state, Nigeria. We take into account that neighbourhood is an environment within which people live and conduct their daily activities, its features may be measured based on the perception of the individuals therein and achieving a balance between personal preferences or needs and environmental pressures fosters satisfaction with the neighbourhood and psychological well-being (Ferreira, César, Camargos, Lima-costa, and Proietti, ( 2009). The objective is to examine the effect of neighbourhood characteristics on psychosocial well-being of the young adult living in urban slums. 3. Methods Data for the study were extracted from a cross sectional survey among 220 young adults age15-19 selected in equal proportion from one of the urban slum area of Agege Local Government area of Lagos State, Nigeria. The study adopted a multi-stage sampling technique, to select a representative sample from the study population drawn from the households. The first stage of the sampling process involved stratification of Agege into selection of two (2) enumeration areas from the selected LGA while 2 streets from a listing of all major streets in each of the enumeration area were also made. Systematic random sampling procedure was then used to select housing units from a listing of all houses in each major street in the sample. Finally, within each selected housing unit, a household comprising one young adult age was selected. Where there was a household that did not fulfill the criteria, the next household was chosen for replacement. Also, any household where there was more than one eligible for selection, a simple random sampling was used to select a respondent. Verbal consent was obtained from each respondent. The LGA was selected for being a representative of tribe and culture, urban poor setting. The study adopted a measuring scale for both neighbourhood characteristics and psychosocial health. The young boys and girls completed a 30 minutes interview and administered questionnaire with questions on demographic information, about the family, peer and neighbourhood characteristics. 4. Measures Psychosocial health-was defined by Clarke, (2006) as the presence of positive psychosocial traits, or absence of negative traits, which was measure by focusing on four categories of functioning: externalizing behaviour problems, internalizing behaviour problems, social competence, and academic performance. This study adopted just one of the four categories of functioning: self-rated academic performance. At individual level-the dependent variable is self-rated academic performance. The respondents were asked to evaluate their academic performance as poor, fair, good, or excellent. We dichotomized responses into poor/fair and good/excellent, coded as 0 and 1respectively. Demographic characteristic were predictor variables and were all self-reported by the participants. Age was treated as a continuous variable and gender was treated as a dichotomous variable with males coded 1 and females coded 0. Socioeconomic was captured in relations to parent and guardian employment status, educational attainment. The main goal of this dichotomization was to analyze possible neighbourhood factors in Review of Economics and Development Studies Vol. I, No 1, June 2015 5 relation to the presence or absence of psychosocial health problems. At neighbourhood Level- we utilized variables that capture neighbourhood social environment. The respondents were interviewed about the perception of their neighbourhood and social ties with their neighbors. Using scale adapted from Dahlberg, Toal, Swahn, Behrens (2005) Compendium of Assessment Tools: environmental assessment scale with indices to measure social capital, social cohesion, social control and social disorder and violence. The survey questions comprising each measure using a likert scale type. The questionnaire was designed in a way that both attitude and neighbourhood factors responses to were captured. The Model was computed to identify neighbourhood correlates of subjective academic performance. Respondents were asked to respond to statement related to neighbourhood factors defined as the following: “When I am not at home, one of my parents knows where I am and who I am with”. Very true, somewhat true, somewhat false, and very false. ‘Hiding because of shootings in neighborhood? Very true, somewhat true, and somewhat false. ‘If a group of neighborhood children were skipping school and hanging out on a street corner, how likely is it that your neighbors would do something about it? Very likely, likely, neither likely, unlikely and very likely. ‘I have seen drug deals’: Never, once or twice, a few times and constant The reliability and validity of this scale have been tested and reported in Macklem, (2014); Eriquez, Kelly, Cheng, Hunter & Mendez (2012). The instrument was divided into three sections, A-C, which helped to measure the variables of study. Section A covered the socio-demographic characteristics of the respondents. Section B contained scale on attitude, while section C was on the neighbourhood factors of the respondents. The responses generated from these sections helped to establish the foundation upon which the study could be situated in its context. 5. Analysis The quantitative data gathered from the field were analyzed descriptive and inferential statistical methods methods. Copies of the questionnaire returned were edited, coded and data entry was done. The data were analyzed using the Statistical Package for Social Sciences (SPSS 16) software. First, characteristics of the study sample were described using univariate analysis (frequency distribution and simple percentages). In addition, Multi-variate logistic regression analyses were performed in order to estimate the relative influence of the independent variables on attitude schooling. In the context of logistic regression model, π in the conditional probability of the form ρ{Y=1}. That is, poor/fair and good/excellent indicator is more or less likely dependent on combinations of values of the predictor variables. Therefore, the general the model: Logistic Regression estimating the influence of neighbourhood characteristics on the odds of poor/fair performance Ln= {p/(1-p)}=αo+β1X1 + β2X2+β3X3+…βnXn + e Ln= {ρ/(1-ρ)}=log-odds of good/excellent performance to log-odds of poor/fair performance Hence, parameters in the model are denoted as: αo that represents the intercept, β1= change in log-odds of poor/fair performance with parental control, β2= change in log-odds of poor/fair performance with stressful urban effects, β3= change in log-odds of poor/fair performance with social control, β4= change in log-odds of poor/fair performance with social cohesion, β5= change in log-odds of poor/fair performance with community involvement, β6= change in log-odds of poor/fair performance with exposure, β7= change in log-odds of poor/fair performance with neighbourhood disorganization Review of Economics and Development Studies Vol. I, No 1, June 2015 6 6. Results Table 1 displays the descriptive statistics for all respondents. The mean age is 14, and 177 and 43 were from public and private secondary schools respectively. While 53% of the respondents were female, only 15% reported excellent academic performance. The distribution by level of parental education qualifications shows that 10% had primary school certificate, 24% had secondary school certificate, 66% educated up to tertiary level. The distribution by parent’s occupation revealed that 49.5% were self- employed, and 50.5% work as an employee. Table 1: Distribution of Respondents by Demographic Characteristics Variables Frequency Percent% 1. School Type Public 177 80 Private 43 20 Total 220 100 2. Sex Male 104 47 Female 116 53 Total 220 100 3. Academic Performance Excellent 33 15 Good 88 40 Fair 79 36 Poor 20 9 Total 220 100 4. Parent Educational Qualification Primary 22 10 Secondary school 53 24 Tertiary 145 66 Total 220 100 5. Parents’ Occupation Self Employed 109 49.5 Employee 111 50.5 Total 220 100 Source: Field survey, 2014 Model The Model was computed to identify neighbourhood correlates of subjective wellbeing. Respondents were asked to respond to neighbourhood factors defined as the following: Parental control- “When I am not at home, one of my parents knows where I am and who I am with”. Stressful urban effect- ‘Hiding because of shootings in neighborhood? Social control- ‘If a group of neighborhood children were skipping school and hanging out on a street corner, how likely is it that your neighbors would do something about it? Exposure- I have seen drug deals Review of Economics and Development Studies Vol. I, No 1, June 2015 7 The results from table 2 revealed that the more the parental control and monitoring the probability of better performance in school, see Exp(B) 0.001, and 0.050 respectively, more likely to perform poorly. The same observation goes for stressful urban effects, lack of social control and social cohesion in the neighbourhood, exposure and neighbourhood disorganization are more likely to have negative attitude and perform badly in schooling. Table: 2 Binary logistic regression estimates of the influence neighbourhood on academic performance Selected Variables B Sig. Exp(B ) Parents knows where I am and who I am with. Very true Somewhat true RC 1.211 - 0.621 - 3.329 Somewhat false 1.745 0.001 5.728 Very false 1.001 0.050 2.722 Hiding because of shootings in neighborhood Very True RC - - Somewhat True -.310 0.042 .734 Somewhat False -.099 0.019 .906 Social control in Neighbourhood Very likely RC - - Likely .249 0.590 1.335 Neither likely -.508 0.025 .602 Unlikely -.793 0.010 .418 Very unlikely -.552 0.004 .576 Exposure to Drug Deals Never Once or twice RC -.374 - 0.028 - .754 A few times -.121 0.059 .776 Constant -.027 0.646 .622 2 Log likelihood = 1631.602(a) Cox & Snell R Square =.045 Nagelkerke R Square = .063 Overall Percentage = 68.9 Source: Field Survey 2013-2014 RC=Reference Category 7. Discussion This study extends upon previous assertions concerning the impact of urban social environment on psychosocial health problems among urban youth living in slums. Consistent with conclusions from Columbia University TeenScreen National center for Mental Health Checkups (2009 students reporting high levels of psychosocial stress are more likely to perceive themselves as less academically competent; and neighbourhood risk was related to lower grades in findings from Gonzales, et al (1996). According to WHO 2012, Neighbourhood that engender high levels of social capital create better mental health. Lack of social control, social cohesion, and stressful urban effect, exposure to anti-social/illegal activities and neighborhood disorganization that we observed in poor neighbourhood may reflect an absence of some level of encouragement needed to pursue academic achievement. This is not strange, as Review of Economics and Development Studies Vol. I, No 1, June 2015 8 Thomas, Torrone, and Browing (2010) found, for example, neighbourhood characteristic such as social capital, social disorder can be associated with rates of infections in neighbourhoods. Also neighbourhood poverty, disorder, deterioration of the built environment, and have been associated with biological indicators of stress and depression. Therefore, exposure in disadvantaged neighbourhood can be a major distraction and setback in academic achievement. Adolescent health and behaviours are often considered as a factor that has to do with parenting. Parental control and monitoring is also a factor in academic performance. Adolescent in slums lack of strong parental control, because there is greater degree of individual freedom, every member in the family is more or less free from any restriction due to his or her being economically productive, the parents have relatively lost their control over them (Das, 2000). This study is in line with report from Li, Feigelman, and Stanton, (2000) that observed strong inverse correlation between perceived parental monitoring and adolescent risk behaviour. This may suggest that parental monitoring initiative may be an affective intervention tool in academic performance. This find is consistent with result from (Ndugwa et al, 2011) which says parental monitoring is to be associated with lower levels of delinquent behaviuor, greater schooling performance, and lower levels of sexual behaviour. This study is limited in ability to access the variation in age, religion parental background and the inherent issues in self reporting academic performance. Despite the limitations, this research is important for the understanding of how neighbourhood disadvantaged features is related to attitude and academic performance among the youth. The indices can be use to evaluate new area for educational policy and performance interventions for secondary school students in Nigeria. 8. Conclusion and policy recommendations In conclusion, this study affirms that neighbourhood characteristics are very important in adolescent psychosocial wellbeing, which has implication for academic performance. This paper calls for programmes that are tailor to addressing rapidly developing slum settlements in low income area, to secure the future generation. Therefore, the need to focus attention on improving the state of infrastructure, security and social work activities in slums areas. This will give the young adults hope for the future and live a quality life which is important for public health. Acknowledgement: The authors acknowledged field work support from Covenant University, Nigeria. References Adedimaji, A. A., Omololu, F. O. and Odutolu, O. (2007) HIV Risk Perception and Constraints to Protective Behaviour among Young Slum Dwellers in Ibadan, Nigeria.Journal of Health, population and Nutrition; 25(2): 146-157. Akunnaya, P. 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