La repercusion de las condiciones sociodemograficas sobre la calidad de vida de los adolescentes en una cohorte de nacimiento en el Brasil: un estudio longitudinal.
The terms "quality of life" (QoL) and "well-being" are often used to measure different realms of an individual's satisfaction with existence and experience in an attempt to understand how social, individual, and emotional factors influence behavior and lifestyle. The World Health Organization's QoL assessment (WHO-QoL) defines QoL as "the individuals' perception of their position in life in the context of the culture in which they live and in relation to their goals, expectations, standards, and concerns" (1).
Nevertheless, QoL has many differing definitions (2-4), reflecting the theoretical divergences in this area. As a result, various standardized and validated instruments have been proposed for evaluating QoL, most of which include a wide range of variables for measuring the social, emotional, health-related, and other dimensions of QoL (5). Most of these instruments provide a rating score for classifying the subject as having or not having QoL. Regardless, the different dimensions of QoL can be evaluated individually for a better understanding of the causal pathways and relationships with various independent variables (6).
Most studies that evaluate QoL are cross-sectional because they are based on the assumption that short-term experiences are the major determinants (7, 8). Nevertheless, certain early life events can also have long-term effects on various aspects of QoL. Over the last 20 years, as the hypothesis of the early origins of adult diseases (9) has emerged, a number of longitudinal studies have attempted to determine to what extent adverse events that occur during gestation and/or in the first years of life may predispose individuals to various diseases (10, 11). However, studies on how such determinant events influence QoL are scarce and limited to high-income countries (HIC) (12-14). Recognizing the impact of these early adverse events on health conditions--including chronic diseases, biological variables, and different aspects of human capital (height, school achievement, economic productivity, and birth-weight of offspring)--special attention has been given to the effects of life-course socioeconomic trajectories and racial and gender inequities on these outcomes (15). In addition, some of these effects can even be transmitted to offspring (intergenerational effects), reinforcing inequities in the next generation (16, 17). Nevertheless, even in HIC there is a lack of information about the impact of early poverty, skin color, and gender on QoL in adolescence and adulthood.
Considering that QoL is a multidimensional construct that includes physical, emotional, mental, social, and behavioral components (17), the present study investigated early sociodemographic variables (socioeconomic position, skin color, and gender) as risk factors associated with family and social outcomes in adolescence. The main hypotheses to be tested was that these objective and subjective aspects--reflecting the QoL social domain--are especially influential among males, black/brown individuals, offspring of mothers who had little education at the time of birth, and in those who are and always have been poor (at birth and in adolescence). To achieve these objectives, the present study evaluated the 1993 Pelotas Birth Cohort Study (Brazil), which used one of the few cohorts in low- and middle-income countries, and included data on sociodemographic, nutritional, and health-related variables collected directly through several follow-ups from shortly after birth to 11 years of age (18).
MATERIALS AND METHODS
Pelotas is a city in southern part of Brazil with a population of approximately 340 000. In 2002, the city had a per-capita Gross Domestic Product of US$ 1 958 (national mean, US$ 2 604). All children born in 1993 whose mothers lived in the municipality's urban area at the time of birth were eligible for participation in the study (n = 5 249), covering approximately 99% of births in the city that year. This is one of the largest and longest-standing birth cohorts in middle-income countries (19). With the exception of 16 mothers that either could not be interviewed or refused to participate in the study, all others were interviewed and had their children examined shortly after birth. Children were subsequently followed-up on numerous occasions from infancy to 11 years of age (20). One of the last follow-up studies was carried out from July 2004-March 2005 and included 4 482 adolescents who were known to be living and could be located. After 30 refusals (0.7%), a total of 4 452 adolescents were interviewed. Considering those who were known to have died (n = 141), the follow-up rate was 87.5%. Information on socioeconomic, demographic, and health variables was collected at each visit. Details regarding follow-up visits are described in another study (20).
During the 2004-2005 follow-up, three questionnaires were administered: two to the adolescents (one face-to-face and one confidential) and one to the parent/ guardian. The face-to-face instrument investigated academic achievement, behavioral variables, nutritional status, health conditions, and discrimination. The confidential questionnaire investigated alcohol and drug use, family relationships, and sexual behavior. A guardian (preferably the subject's mother) provided information on socioeconomic, demographic, and maternal health conditions.
One of the aims in this follow-up was to evaluate family and social relationships in adolescence through self-reporting. This information was not collected according to any specific, previously available QoL questionnaire. Self-reported questions were considered as a proxy for evaluation of the social domain of QoL. The topics included were:
(a) family relationships (perceived relationship with mother and father, family conflicts, and physical punishment); (b) educational achievement; (c) perception of neighborhood safety; and, (d) perception of discrimination. Given that QoL is based on individual perception, some questions were selected from among other variables collected at 11 years of age because they were considered good indicators due to some subjectivity (i.e., dissatisfaction with frequent physical punishment).
The family aspects of QoL were evaluated using four variables: (a) relationship with mother, collected as ordinal variables (excellent, very good, good, regular, and very poor relationship--subjects that defined their relationship as regular or very bad were classified as having a "poor relationship with their mother"); (b) relationship with father, collected and categorized as above; (c) frequent family conflicts compared with other families, collected as a dichotomous variable; and, (d) physical punishment by parents in the last 6 months, collected as a continuous variable. Frequent punishment was defined as occurring six or more times. In addition, an outcome variable was generated that combined responses for all of the above variables to obtain a comprehensive assessment of the family aspects of QoL. Different cutoff points were tested and individuals with two or more adversely-affected family aspects were classified as having family relationship problems since these were more closely related to the independent variables.
The social aspects of QoL were evaluated using three variables: (a) fear of the neighborhood of residence, collected as a dichotomous variable; (b) suffering discrimination for any reason (race, religion, socioeconomic position, physical disability, or other), analyzed as a dichotomous variable; and, (c) academic failure, collected as a numeric variable and analyzed as a dichotomous variable (failure > 1 time in life).
The independent variables were collected at different follow-up visits. The subject's gender was collected in 1993. Self-reported skin color was collected in 2004-2005 and categorized as white, black, mixed, yellow, and indigenous according to the classification of the Brazilian Institute of Geography and Statistics (21). All the results for the last four groups were very similar, and for this reason skin color was classified as white or nonwhite.
The main socioeconomic position (SEP) indicator at birth used in the analyses was maternal education. This exposure has been more strongly related to different components of an offspring's health than other socioeconomic variables, especially in the first years of life (22). Maternal education level was collected in 1993 as a numeric variable and analyzed as a categorical variable (0-4 years of education; 5-8 years; 9-11 years; and [greater than or equal to] 12 years).
To evaluate socioeconomic trajectories, two variables were considered: family income at birth (based on income of all family members) and family possession of consumer goods. To ensure comparability between both periods, the variables were divided into quintiles. SEP change between birth and 11 years of age was classified as: (a) always poor (lowest quintile at birth and at 11 years); (b) never poor (quintiles 2-5 at birth and 11 years); (c) poor-non-poor (lowest quintile at birth and quintiles 2-5 at 11 years); and (d) non-poor-poor (quintiles 2-5 at birth and lowest quintile at 11 years).
Multivariable analysis was carried out by Poisson regression based on a conceptual model taking into account a proposed hierarchy of causal relationships. The most distal level included skin color, sex, and maternal education, which may influence SEP change. The last variable was included in a second level. Prevalences were estimated for all variables. For crude analysis, the Chi-square test was used. For adjusted analyses, the Poisson regression with robust variance was used to estimate prevalence ratios (PR) and their respective Confidence Intervals (95%CI). Tests for heterogeneity or for trend were performed according to the nature of the exposures. Variables whose significance level after adjustment for variables in the same or higher levels was [less than or equal to] 0.2 were kept in the model. Stata 9.0 software (StataCorp LP, College Station, Texas, United States of America) was used for data analysis.
The approval of the Federal University of Pelotas Research Ethics Committee was obtained for each of the follow-ups. For the latest follow-ups, written consent was obtained from all subjects. In accordance with the guidelines of the local ethics committees, all adolescents whose parents signed an informed consent were included in the study.
In 2004-2005, a total of 4 452 cohort members were interviewed. Including known deaths, the follow-up rate was 87.5% of live births in 1993. Follow-up rates were similar for both sexes and across different birth weight categories. There were fewer losses among those with lower and middle family income at birth and among offspring of mothers with 9-11 years of schooling. In spite of these differences, at least 80% of adolescents in each category were traced.
The proportion of males and females was equally distributed throughout the sample; two-thirds of subjects classified themselves as white (Table 1). Approximately 75% of mothers had less than 9 years of schooling. SEP between 1993 and 2004 improved for almost 11% of subjects, and a similar proportion moved in the opposite direction. Only 8% of subjects remained in the lowest SEP quintile in both periods.
Family and social aspects of QoL are also described in Table 1. Poor relationship with fathers was three times more frequent than with mothers. Physical punishment by parents ([greater than or equal to] 6 times in the last 6 months) was twice as prevalent as family conflicts. Family relationship problems (> 1 altercation) affected 6% of the cohort members. Prevalence of academic failure, fear of neighborhood, and discrimination were close to 15% for each variable.
Tables 2a and 2b show the results of crude and adjusted analyses for family aspects of QoL: poor relationship with mothers, poor relationship with fathers, family conflicts, frequent physical punishment by parents, and family relationship problems. Skin color was associated with almost all the outcomes in crude and adjusted analyses (30%-40% higher risk among non-whites compared to whites), with the exception of family conflicts. Conversely, sex was only associated with physical punishment by parents in crude and adjusted analyses, which was 30% less common among girls. Maternal education was inversely associated with poor relationship with fathers and mothers, physical punishment, and family relationship problems. The association with family conflicts was U-shaped and the intermediate level of maternal education (9-11 years) showed a protective effect. Current poverty (always poor and non-poor/poor) was adversely associated with all family aspects of QoL, with the exception of family conflicts, which were more frequent only among those always poor.
Crude and adjusted analyses for social aspects of QoL--fear of the neighborhood of residence, discrimination, and academic failure--are shown in Table 3. Fear of the neighborhood and discrimination were 20%-30% more frequent among women and nonwhites when compared to their respective reference groups. Nonwhite adolescents also showed higher risk of academic failure and, conversely, being female provided a protective effect. Maternal education was inversely associated with discrimination in crude and adjusted analyses, but not with fear of the neighborhood. Academic failure was 20 times more frequent among adolescents with lower maternal education at birth (0-4 years) than those with higher education, even after controlling for potential confounders. Likewise, SEP change was not associated with fear of neighborhood, but was associated with discrimination, which was more frequent among those currently poor (always poor and non-poor-poor). Academic failure was also 2.5 times more frequent among subjects who were always poor when compared to those who were never poor, with intermediate risk for the other two categories.
Additional analyses were carried out to explore possible pathways between skin color and the outcomes. After adjustment for SEP change, only the associations with maternal relationship and family relationship problems were reduced, these being no longer statistically significant.
Effect modification by sex or skin color was also analyzed, but no evidence of interactions was found (P-value for interaction > 0.2 in all the cases).
A summary of findings is included in Table 4.
This study sought to examine the effects of sex, skin color, maternal education at birth, and SEP change on some family and social aspects of QoL among adolescents (11-12 years of age) in the 1993 Pelotas Birth Cohort. In accordance with the initial hypothesis, the results (Table 4) showed that: (a) except for family conflicts, all the family and social aspects of QoL were worse among nonwhites adolescents; (b) among boys, physical punishment by parents and academic failure were more frequent, whereas among girls discrimination and fear of neighborhood were more prevalent; (c) individuals with lower maternal education at birth and who were always poor (SEP) had most of the family and social aspects of QoL affected, except for fear of neighborhood; and (d) the strongest association was found between lower maternal education and academic failure.
The association between self-reported skin color and the family and social aspects of QoL reflects a range of social conditions that are unfavorable to nonwhites. In Brazil, skin color has been more widely used in the epidemiological context to measure social differences in health outcomes and treatment, but is not an accurate predictor of ancestry in this population (23). The results of the present study concur with those of other studies that show that in adolescents, skin color/ethnicity is related to well being and aspects of QoL (7, 24-27). According to Brazilian surveys (1993-2007), inequities related to skin color have been attributed to black/brown individuals having lower income, lower education, worse household conditions (healthiness and security), and being more susceptible to socioeconomic and racial discrimination than whites (28). Compared to other regional cities in the state, Pelotas has a higher proportion of black/brown individuals (16.1%), and this could potentially attenuate social inequities related to skin color (29). However, this study's findings showed consistently that skin color affected almost all aspects of QoL, even in early adolescence, and that these effects were not explained by SEP.
Early poverty and lower maternal education were related to academic failure, principally affecting males. Concurring with this study's results, other studies (30-33) have found the same relationships: boys have worse academic performance and are more predisposed to poor academic habits than girls. The mechanisms related to this finding are complex and not well understood, and include individual, familiar, educational, and social characteristics. In Brazil, socioeconomic and cultural factors among poor families are such that boys are taught to develop responsibility for the family's financial situation at an early age (34). A study carried out in Pelotas in 1998 showed that children and adolescent boys contribute, on average, up to 18% of the family income. Moreover, the higher the contribution, the higher the school dropout rate for these adolescents (35). The present results raise questions regarding the quality and structure of the educational system in Brazil, and the importance of remaining in school for the poorest.
Physical punishment was more frequent among males, black/brown individuals with lower maternal education, and among those always poor. Some Brazilian studies also showed that poverty, parental stress, and other family characteristics--such as domestic violence--are related to physical punishment by parents, and this practice can affect mental health and behavioral outcomes in children (36, 37). Additionally, physical punishment may represent either an exposure or an outcome for other variables in adolescence, such as academic failure and/or attempts at independence from parental control (both more frequent among males) (38); however, this specific pathway was not examined, and further study may be necessary.
Fear of neighborhood was more frequent among females, probably because they are considered to be more susceptible to urban violence, shown by prior study of the same cohort (39). Leisure time among girls is more tightly controlled by the family, thereby reducing the amount of time spent engaging in social interactions outside the home environment. This leads to differences in how males and females perceive their social surroundings, and according to the results of this present study, is not mediated by SEP.
Additionally, fear of neighborhood affected all socioeconomic groups in a similar way, probably because this outcome is more related to the spatial distribution of specific dangerous places inside the neighborhood than to the size or socioeconomic characteristics of the locality (40).
Discrimination was also more frequent among females. In adolescence, various discriminatory practices, such as teasing, bullying, and assigning nicknames (related to physical appearance) are common at school (38, 41, 42). In this study's cohort, most forms of discrimination--skin color, poverty, and physical appearance--were more frequent among females (data not shown). However, male Brazilian adults are more affected by discriminatory practices related to skin color and SEP (33, 38). There are no other population based studies in Brazil evaluating discrimination in early adolescence, and further studies evaluating the interactions between gender, stage of life, and discrimination are necessary.
Maternal education is an important social marker for health outcomes (43-45), and in this study it was related to family and social aspects of QoL, particularly regarding academic failure. This variable reflects a mother's knowledge, practices, and life aspirations, which can be directly or indirectly transmitted to offspring. For example, maternal education has been related to quality of care of children, which in turn can affect physical and mental well-being in offspring. Maternal education also represents a more stable indicator of SEP than does family income. However, due to the longitudinal design of this study, we were able to evaluate socioeconomic trajectories from birth to early adolescence. Consistent with the results for maternal education, the cumulative effect of poverty increased the risk of alteration in most of the family and social aspects of QoL.
The prospective design of this study reduces the possibility of reversal causality in the findings. However, there are several possible limitations in the present study. Losses at follow-up are an important limitation of prospective studies, but only 12.5% of the original cohort was missed at 11 years of age. The application of a confidential questionnaire resulted in a high response rate for family relationship questions (~95% for all of them), reducing the probability of information bias. Another limitation is that the study did not employ a specific questionnaire to evaluate QoL in adolescence. Nevertheless, all the results consistently pointed out the relevance of sociodemographic conditions on the outcomes. To confirm the results, the 1993 Pelotas Birth Cohort Study is planning to evaluate QoL with a standardized questionnaire administered at 18 years of age. In addition, QoL can be affected across the life-course and may vary for different exposures, such as age and sociopolitical context (46). Therefore, the present findings may not be extrapolated to other population groups and/or other ages, even for the same city. However, inequities associated with gender, skin color, and SEP have been related to different health outcomes at different ages and in different populations (20).
In conclusion, adolescents belonging to lower socioeconomic groups showed worse QoL than the wealthiest groups. The underlying mechanisms are not well known, but probably involve the effects of lower parental education on physical and psychological health of offspring. This study also showed than lower SEP across the life-course has a cumulative effect on QoL, principally for academic failure and family relationships. Skin color was related to family and social aspects of QoL, independent of SEP. In spite of this, other social and cultural characteristics may be involved and new studies are necessary. Gender was also important for QoL in adolescence: in girls, social aspects were particularly affected, while in boys academic failure and physical punishment by parents were affected.
These results suggest that policies should be directed principally to improving access to high quality education, especially in the lower SEP groups, for both parents and children. This would help to minimize inequities at birth, across the life-course, and in the next generation.
Acknowledgements. The authors wish to thank Fernando Barros, Cesar Victora, Maria de Fatima Vieira, Marilda Neutzling, Pedro R. C. Hallal, and Neiva Valle for their important collaboration in the different stages and levels of the Pelotas 1993 Birth Cohort Study.
The present study was supported by the Wellcome Trust (United Kingdom). The initial stages of the cohort were supported by the European Union, the Programa Nacional para Centros de Excelencia (PRONEX) of the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq), and by the Ministry of Health of Brazil.
Manuscript received on 11 January 2010. Revised version accepted for publication on 21 June 2010.
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Helen Goncalves,  David A. Gonzalez,  Cora Luiza Araujo,  Luciana Anselmi,  and Ana M. B. Menezes 
 Post-graduate Program in Epidemiology, Federal University of Pelotas, Brazil. Send correspondence to Helen Goncalves, firstname.lastname@example.org
TABLE 1. Descriptive analysis of conditions at birth (sociodemographic variables) and at 11 years of age (family and social aspects of quality of life) among the 1993 Pelotas Birth Cohort Study and the 2004-2005 follow-up study Variable (a) No. % Skin color White 2 953 66.8 Black/mixed 1 259 28.5 Yellow/indigenous 208 4.7 Sex Male 2 606 49.7 Female 2 642 50.3 Maternal education in 1993 (b) 0-4 years 1 468 28.0 5-8 2 424 46.2 9-11 923 17.6 [greater than or equal to] 12 427 8.2 Change in socioeconomic status (1993-2004) (c) Always poor 330 7.9 Poor-non-poor 473 11.3 Non-poor-poor 511 12.2 Never poor 2 888 68.7 Relationship with father Excellent-very good 3 092 72.3 Good 665 15.5 Bad-very bad 522 12.2 Relationship with mother Excellent-very good 3 650 84.1 Good 499 11.5 Bad-very bad 190 4.4 Physically punished by parents ([greater than or equal to] 6 times in the last 6 months) No 3 742 86.3 Yes 593 13.7 Frequent family conflicts No 3 918 93.6 Yes 268 6.4 Family relationship problems (> 1 altercation) No 3 785 94.0 Yes 241 6.0 Fear of neighborhood No 3 724 84.0 Yes 709 16.0 Victim of discrimination No 3 711 83.6 Yes 726 16.4 Academic failure (> once) No 3 707 85.6 Yes 624 14.4 (a) Some variables contain missing values. (b) Maternal education in completed years of study. (c) Poor: lowest quintile; Non-poor: other quintiles. TABLE 2a. Crude and adjusted analysis (prevalence ratios (PR) and confidence interval (95% CI)) for family aspects of quality of life (bad relation-ship with parent and frequent family conflicts) at 11 years of age according to sociodemographic variables, Pelotas, Brazil Bad relationship with mother Crude Adjusted No. % analysis analysis PR (95%CI) PR (95%CI) Skin color P = 0.01 (a) P = 0.06 (a) White 2 903 3.8 1.0 1.0 (b,c) Nonwhite 1 425 5.5 1.5 (1.1-1.9) 1.3 (1.0-1.7) Sex P = 0.5 (a) P = 0.4 (a) Male 2 126 4.6 1.0 1.0 (b,d) Female 2 213 4.2 0.9 (0.7-1.2) 0.9 (0.7-1.2) Maternal education (in 1993) P < 0.001 (e) P < 0.001 (e) 0-4 1 184 5.4 3.5 (1.4-8.6) 3.2 (1.3-8.0) 5-8 2 079 5.1 3.3 (1.4-8.0) 3.1 (1.3-7.6) 9-11 745 1.9 1.2 (0.4-3.4) 1.2 (0.4-3.3) [greater than or equal to] 12 324 1.5 1.0 1.0 (b,d) Change in socioeconomic status (1993-2004) P < 0.001 (a) P < 0.001 (a) Always poor 319 8.5 2.9 (1.9-4.3) 2.5 (1.6-3.9) Poor-non-poor 457 5.0 1.7 (1.1-2.7) 1.5 (1.0-2.4) Non-poor-poor 490 7.4 2.5 (1.7-3.6) 2.1 (1.4-3.2) Never poor 2 835 3.0 1.0 1.0 (c,d) Bad relationship with father Crude Adjusted No. % analysis analysis PR (95%CI) PR (95%CI) Skin color P < 0.001 (a) P = 0.001 (a) White 2 867 10.7 1.0 1.0 (b,c) Nonwhite 1 401 15.2 1.4 (1.2-1.7) 1.3 (1.1-1.6) Sex P = 0.03 (a) P = 0.07 (a) Male 2 093 11.1 1.0 1.0 (b,d) Female 2 186 13.3 1.2 (1.1-1.4) 1.2 (1.0-1.4) Maternal education (in 1993) P < 0.001 (e) P < 0.001 (e) 0-4 1 162 14.9 2.7 (1.7-4.3) 2.4 (1.5-3.9) 5-8 2 052 12.3 2.2 (1.4-3.5) 2.1 (1.3-3.3) 9-11 736 10.2 1.8 (1.1-3.0) 1.8 (1.1-2.9) [greater than or equal to] 12 322 5.6 1.0 1.0 (b,d) Change in socioeconomic status (1993-2004) P < 0.001 (a) P < 0.001 (a) Always poor 307 18.9 1.9 (1.5-2.5) 1.7 (1.3-2.3) Poor-non-poor 454 11.9 1.2 (0.9-1.6) 1.1 (0.8-1.5) Non-poor-poor 482 17.6 1.8 (1.4-2.2) 1.6 (1.3-2.1) Never poor 2 807 9.9 1.0 1.0 (c,d) Frequent family conflicts Crude Adjusted analysis analysis No. % PR (95%CI) PR (95%CI) Skin color P = 0.3 (a) P = 0.4 (a) White 2 773 6.1 1.0 1.0 (b,c) Nonwhite 1 402 6.9 1.1 (0.9-1.4) 1.1 (0.9-1.4) Sex P = 0.09 (a) P = 0.08 (a) Male 2 037 7.1 1.0 1.0 (b,d) Female 2 149 5.8 0.8 (0.7-1.0) 0.8 (0.6-1.0) Maternal education (in 1993) P = 0.006 (a) P = 0.006 (a) 0-4 1 139 7.6 1.0 (0.7-1.6) 1.1 (0.7-1.6) 5-8 2 011 6.6 0.9 (0.6-1.4) 0.9 (0.6-1.4) 9-11 714 3.5 0.5 (0.3-0.8) 0.5 (0.3-0.8) [greater than or equal to] 12 315 7.3 1.0 1.0 (b,d) Change in socioeconomic status (1993-2004) P = 0.005 (a) P = 0.05 (a) Always poor 308 10.4 1.9 (1.3-2.7) 1.7 (1.2-2.5) Poor-non-poor 504 7.7 1.4 (1.0-1.9) 1.3 (0.9-1.9) Non-poor-poor 491 7.1 1.3 (0.9-1.8) 1.2 (0.8-1.7) Never poor 2 883 5.6 1.0 1.0 (c,d) (a) Wald's test for heterogeneity. (b) Adjusted for sex. (c) Adjusted for maternal education in 1993. (d) Adjusted for skin color. (e) Wald's test for trend. TABLE 2b. Crude and adjusted analysis (prevalence ratios (PR) and confidence interval (95% CI)) for family aspects of quality of life (physical punishment and family relationship problems) at 11 years of age according to sociodemographic variables, Pelotas, Brazil Physically punished by parents ([greater than or equal to] 6 times in the last 6 months) Crude analysis Adjusted analysis No. % PR (95%CI) PR (95%CI) Skin color P < 0.001 (a) P< 0.001 (a) White 2 892 11.8 1.0 1.0 (b,c) Nonwhite 1 430 17.5 1.5 (1.3-1.7) 1.4 (1.2-1.6) Sex P < 0.001 (a) P< 0.001 (a) Male 2 123 16.5 1.0 1.0 (b,d) Female 2 212 11.0 0.7 (0.6-0.8) 0.7 (0.6-0.8) Maternal education (in 1993) P < 0.001 (e) P< 0.001 (e) 0-4 1 187 17.1 2.1 (1.4-3.0) 2.0 (1.3-2.9) 5-8 2 074 13.9 1.7 (1.2-2.4) 1.6 (1.1-2.4) 9-11 742 9.7 1.2 (0.8-1.8) 1.2 (0.8-1.8) [greater than or equal to] 12 325 8.3 1.0 1.0 (b,c) Change in socioeconomic status (1993-2004) P < 0.001 (a) P = 0.01 (a) Always poor 318 19.5 1.7 (1.3-2.1) 1.4 (1.1-1.7) Poor-non-poor 526 15.6 1.3 (1.1-1.7) 1.2 (0.9-1.4) Non-poor-poor 508 19.1 1.6 (1.3-2.0) 1.4 (1.1-1.7) Never poor 2 983 11.8 1.0 1.0 (b,d) Family relationship problems (> 1 altercation) Crude analysis Adjusted analysis No. % PR (95%CI) PR (95%CI) Skin color P = 0.001 (a) P = 0.02 (a) White 2 687 5.1 1.0 1.0 (b,c) Nonwhite 1 328 7.8 1.5 (1.2-1.9) 1.4 (1.1-1.7) Sex P = 0.2 (a) P = 0.4 (a) Male 1 955 6.5 1.0 1.0 (b,d) Female 2 071 5.5 0.8 (0.7-1.1) 0.9 (0.7-1.2) Maternal education (in 1993) P < 0.001 (e) P < 0.001 (e) 0-4 1 086 8.0 3.5 (1.7-7.6) 3.2 (1.5-6.9) 5-8 1 937 6.7 3.0 (1.4-6.3) 2.8 (1.3-5.9) 9-11 687 2.3 1.0 (0.4-2.5) 1.0 (0.4-2.4) [greater than or equal to] 12 309 2.3 1.0 1.0 (b,c) Change in socioeconomic status (1993-2004) P < 0.001 (a) P < 0.001 (a) Always poor 287 12.2 3.0 (2.1-4.3) 2.5 (1.7-3.6) Poor-non-poor 426 8.7 2.1 (1.5-3.1) 1.8 (1.3-2.6) Non-poor-poor 448 8.3 2.0 (1.4-2.9) 1.7 (1.2-2.5) Never poor 2 646 4.0 1.0 1.0 (b,d) (a) Wald's test for heterogeneity. (b) Adjusted for skin color. (c) Adjusted for sex. (d) Adjusted for maternal education in 1993. (e) Wald's test for trend. TABLE 3. Crude and adjusted analysis (prevalence ratios (PR) and confidence interval (95% CI)) for social aspects of quality of life at 11 years of age according to sociodemographic variables, Pelotas, Brazil Fear of neighborhood of residence Crude Adjusted No. % analysis analysis PR (95%CI) PR (95%CI) Skin color P = 0.006 (a) P = 0.008 (a) White 2 951 15.0 1.0 1.0 (b,c) Nonwhite 1 467 18.2 1.2 (1.1-1.4) 1.2 (1.1-1.4) Sex P < 0.001 (a) P < 0.001 (a) Male 2 177 14.0 1.0 1.0 (b,d) Female 2 256 18.0 1.3 (1.1-1.5) 1.3 (1.1-1.5) Maternal education (in 1993) P = 0.6 (e) P = 1.0 (e) 0-4 1 225 16.0 1.0 (0.7-1.3) 0.9 (0.7-1.2) 5-8 2 121 16.6 1.0 (0.8-1.3) 0.9 (0.7-1.2) 9-11 752 14.0 0.8 (0.6-1.1) 0.8 (0.6-1.1) [greater than or equal to] 12 328 16.8 1.0 1.0 (b,c) Change in socioeconomic status (1993-2004) P = 0.6 (a) P = 0.8 (a) Always poor 329 18.2 1.2 (0.9-1.5) 1.1 (0.9-1.5) Poor-non-poor 471 15.7 1.0 (0.8-1.3) 1.0 (0.8-1.3) Non-poor-poor 509 16.3 1.1 (0.9-1.3) 1.0 (0.8-1.3) Never poor 2 876 15.4 1.0 1.0b,d Victim of discrimination Crude Adjusted No. % analysis analysis PR (95%CI) PR (95%CI) Skin color P < 0.001 (a) P< 0.001 (a) White 2 952 14.6 1.0 1.0 (b,c) Nonwhite 1 467 19.8 1.4 (1.2-1.6) 1.3 (1.1-1.5) Sex P = 0.006 (a) P = 0.01 (a) Male 2 093 14.8 1.0 1.0 (b,d) Female 2 186 17.9 1.2 (1.1-1.4) 1.2 (1.1-1.4) Maternal education (in 1993) P< 0.001 (e) P< 0.001 (e) 0-4 1 227 20.1 1.7 (1.2-2.3) 1.5 (1.1-2.1) 5-8 2 120 15.9 1.3 (1.0-1.8) 1.3 (0.9-1.7) 9-11 755 13.6 1.2 (0.8-1.6) 1.1 (0.8-1.5) [greater than or equal to] 12 328 11.9 1.0 1.0 (b,c) Change in socioeconomic status (1993-2004) P< 0.001 (a) P< 0.001 (a) Always poor 329 23.4 1.7 (1.4-2.1) 1.6 (1.3-2.0) Poor-non-poor 473 18.0 1.3 (1.1-1.6) 1.3 (1.0-1.6) Non-poor-poor 509 22.2 1.6 (1.4-2.0) 1.5 (1.3-1.9) Never poor 2 878 13.6 1.0 1.0 (b,d) Academic failure (> once) Crude Adjusted analysis analysis No. % PR (95%CI) PR (95%CI) Skin color P < 0.001 (a) P< 0.001 (a) White 2 883 10.9 1.0 1.0 (b,c) Nonwhite 1 425 21.1 1.9 (1.7-2.2) 1.6 (1.4-1.8) Sex P < 0.001 (a) P = 0.01 (a) Male 2 125 18.4 1.0 1.0 (b,d) Female 2 206 10.6 0.6 (0.5-0.7) 0.6 (0.5-0.7) Maternal education (in 1993) P< 0.001 (e) P< 0.001 (e) 0-4 1 196 27.7 22.3 (8.4-59.4) 19.5 (7.3-51.9) 5-8 2 026 12.6 10.2 (3.8-27.1) 9.2 (3.4-24.5) 9-11 738 3.7 3.0 (1.0-8.4) 2.7 (1.0-7.8) [greater than or equal to] 12 323 1.2 1.0 1.0 (b,c) Change in socioeconomic status (1993-2004) P< 0.001 (a) P< 0.001 (a) Always poor 319 35.7 4.3 (3.6-5.3) 2.5 (2.0-3.1) Poor-non-poor 464 20.0 2.4 (3.0-3.0) 1.7 (1.3-2.1) Non-poor-poor 494 22.9 2.8 (2.3-3.4) 1.7 (1.4-2.1) Never poor 2 839 8.2 1.0 1.0 (b,d) (a) Wald's test for heterogeneity. (b) Adjusted for skin color. (c) Adjusted for sex. (d) Adjusted for maternal education in 1993. (e) Wald's test for trend. TABLE 4. Higher risk groups in the association between sociodemographic variables and quality of life among adolescents (summary of adjusted analyses), 1993 Pelotas Birth Cohort Studies and 2004 followup, Pelotas, Brazil Skin color Sex (2004-2005) (1993) Poor relationship with mother Nonwhite -- (a) Poor relationship with father Nonwhite -- Frequent family conflicts -- -- Physical punishment by parents ([greater than or equal to] 6 in the last 6 months) Nonwhite Male Family relationship problems Nonwhite -- Fear of neighborhood Nonwhite Female Discrimination Nonwhite Female Academic failure Nonwhite Male Maternal education at birth (1993) Poor relationship with mother Low Poor relationship with father Low Frequent family conflicts Low and high Physical punishment by parents ([greater than or equal to] 6 in the last 6 months) Low Family relationship problems Low Fear of neighborhood -- Discrimination Low Academic failure Low Change in socioeconomic position (1993-2004) Poor relationship with mother Always poor and non-poor/poor Poor relationship with father Always poor and non-poor/poor Frequent family conflicts Always poor Physical punishment by parents ([greater than or equal to] 6 in the last 6 months) Always poor and non-poor/poor Family relationship problems Always poor and non-poor/poor Fear of neighborhood -- Discrimination Always poor and non-poor/poor Academic failure Always poor (a) Not associated.
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|Title Annotation:||Investigacion original|
|Author:||Goncalves, Helen; Gonzalez, David A.; Araujo, Cora Luiza; Anselmi, Luciana; Menezes, Ana M.B.|
|Publication:||Revista Panamericana de Salud Publica|
|Date:||Aug 1, 2010|
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