Perceptual & Motor Skills: Perception 2014, 118, 2, 548-562. © Perceptual & Motor Skills 2014
BRAZILIAN ADOLESCENTS' BODY WEIGHT MISPERCEPTION AND THE HUMAN DEVELOPMENT INDEX OF THE CITIES WHERE THEY LIVE1, 2, 3 DIEGO A. S. SILVA AND ELIANE C. A. GONÇALVES Universidade Federal de Santa Catarina, Brazil Summary.—This study investigated the relationship between adolescents' body weight misperception and the Human Development Index (HDI) of the cities in which they live in Brazil. Data from a large national survey that included 60,973 boys and girls between 13 and 15 yr. (M = 14.2, SD = 1.1; 47.5% boys, 52.5% girls) were analyzed. Regression analyses were adjusted for potential confounding factors such as population density, income inequality, nutritional status (BMI), and mothers’ education. In both sexes, the relationship between perceived underweight showed an inverse relationship with HDI. The highest prevalences of participants who perceived themselves as overweight for girls were found in cities with high HDI.
Body weight self-perception is one of the most important body image components because it is associated with feelings and attitudes about one's own body (Pauline, Selvam, Swaminathan, & Vaz, 2012). Excessive concern with body weight may influence behaviors that adolescents adopt in their daily lives, such as the use of laxatives and non-prescription drugs, excessive practice of physical exercise, inadequate diets, and even suicidal ideation (Cheung, Ip, Lam, & Bibby, 2007; Seo & Lee, 2013). Sociocultural factors affect how adolescents perceive their body weight (Fidelix, Silva, Pelegrini, Silva, & Petroski, 2011). Studies have shown that body weight misperception in adolescents and its associated behaviors differ from one country and culture to another (Xie, Chou, Spruijt-Metz, Reynolds, Clark, Palmer, et al., 2006; Cheung, et al., 2007; Ursoniu, Putnoky, & Vlaicu, 2011; Pauline, et al., 2012). In China, for example, it was found that among adolescents, 37.7% of boys and 18.8% of girls perceived themselves to be thin, while 26.5% of young boys and 5.8% of girls perceived themselves to be overweight. Furthermore, factors such as media exposure Address correspondence to Diego Augusto Santos Silva, Departamento de Educação Física, Universidade Federal de Santa Catarina, Centro de Desportos, Campus Universitário– Trindade–Caixa Postal 476, CEP 88040-900–Florianópolis, Santa Catarina, Brazil or e-mail ([email protected]). 2 Both authors acknowledge ethical responsibility for the content of the manuscript and will accept the consequences of any ethical violation. This is an ecological-design study that used data on the prevalence of body weight perception and nutritional status of the report from the National Adolescent School-based Health Survey (PeNSE), which is a partnership between the Ministry of Health and the Brazilian Institute of Geography and Statistics. 3 The authors declare no conflict of interest. 1
DOI 10.2466/27.10.PMS.118k22w7
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ISSN 0031-5125
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time, attitudes toward physical appearance, and adoption of health-risking behaviors were associated with body weight misperception in girls (Xie, et al., 2006). Research conducted with adolescents in Romania reported that 22.6% of normal-weight adolescents perceived themselves as overweight (Ursoniu, et al., 2011). Moreover, in both sexes, a body weight misperception was associated with the excessive practice of physical exercise, low amount of calories in foods, ingestion of diet pills, frequent vomiting, and use of laxatives (Ursoniu, et al., 2011). The difference in the frequency of thin or overweight body perception and its associated behaviors from one country to another may result from several factors, such as media influence, lack of parental education, cultural prejudice, and low self-esteem (Silva, Pereira, & Cabral de Oliveira, 2012). Media presentations, for instance, play an important role in the lives of adolescents, and they are a powerful factor in disseminating the ideals of perfect body, in which underweight for girls and developed muscles for boys symbolize competence, success, and sex appeal, while obesity represents laziness, self-pity, lack of decision-making power, and a lower quality of life (Araújo, Dumith, Menezes, & Hallal, 2010). There is sufficient evidence indicating that populations with higher material deprivation and lower access to psychosocial support have a higher incidence of diseases and mortality, more often at earlier ages due to preventable conditions (Di Cesare, Khang, Asaria, Blakely, Cowan, Farzadfar, et al., 2013). Nevertheless, little is known about the relationships between such socio-economic conditions and body weight misperception. Thus, the aim of this study was to investigate the relationship between body weight perception of adolescents and the Human Development Index of the cities where they live in Brazil. This study predicted that populations with better living conditions have more adolescents with body weight misperception, since they have more access to electronic media that impose ideal beauty standards (Xie, et al., 2006). Hypothesis. The Human Development Index in Brazilian cities and a healthy body weight perception will be significantly correlated. METHOD Sample This is an ecological-design study that used data on the frequency of body weight perception issues from the report of the National Adolescent School-based Health Survey (PeNSE), which is a partnership between the Ministry of Health and the Brazilian Institute of Geography and Statistics (IBGE, 2009). The PeNSE's overall aim was to investigate the risk factors for health protection among Brazilian adolescents. The target population
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included the 9th-yr. students of public and private elementary schools in all 26 state capitals and the Federal District. The ninth year of the Brazilian educational system is equivalent to Grade 9 of North American high schools. Among the 1,453 schools surveyed by PeNSE, 2,175 classes which included 68,735 students attending schools were selected. Of these, 63,411 (92.3%) were present on the day of data collection, totaling 7.7% loss at this stage. Students (n = 501) were excluded from the sample due to refusal to participate, and 1,937 students did not fill the variable “sex.” Thus, the sample included 60,973 students whose data were analyzed. This sample size corresponded to an overall non-response rate of 11.3%. In the sample studied, 89% of students ages 13 to 15 yr. (M = 14.2, SD = 1.1), 47.5% were boys and 52.5% girls. The PeNSE was approved by the National Research Ethics Board (Brazilian Institute of Geography and Statistics, 2009). Measures Body weight perception.—The variable concerning body weight perception was constructed based on the following question: “How do you describe your weight?” The response options were “too thin,” “thin,” “normal,” “fat,” and “too fat.” For the present study, the responses “too thin” and “thin” were considered together as underweight perception, the responses “fat” and “too fat” were considered together as overweight perception, and the responses “normal“ were considered as normal body weight perception. This classification was adopted by the PeNSE in its reports (Castro, Levy, Cardoso, Passos, Sardinha, Tavares, et al., 2010). Nutritional status.—Information about the nutritional status of students was analyzed based on data from PeNSE, which showed information on the prevalence of underweight, normal weight, overweight, and obesity for boys and girls in each of the 27 locations analyzed (Brazilian Institute of Geography and Statistics, 2009). For body weight measurement, adolescents were asked to wear light clothes, to remain barefoot, and to stand on an electronic scale with a capacity of 150 kg and 100 g sensitivity. Height was measured using a stadiometer with a scale in millimeters and a maximum capacity of 200 cm. In this measurement, the adolescents remained barefoot with feet together, heels touching the wall in an upright posture and eyes fixed on the horizon, without flexing or extending the head. Body Mass Index (BMI) and BMI Z scores were calculated, and for the classification of adolescents regarding their nutritional status, literature recommendations were adopted (De Onis, Onyango, Borghi, Siyam, Nishida, & Siekmann, 2007; Z < − 2, underweight; + 1 < Z > − 2, normal weight; Z > + 1, overweight; Z > + 2, obese). For the inferential analysis, overweight and obesity categories were grouped into a single category.
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Body weight misperception.—Body weight misperception was calculated as the difference between body perception and nutritional status categories (body perception – BMI). This procedure resulted in two scores used in data analysis. The underweight misperception score (people who declared themselves thinner than they really were) was the difference between underweight perception and underweight status as assessed by BMI. The overweight misperception score (people who declared themselves heavier than they really were) was the difference between overweight perception and actual overweight as assessed by BMI. Positive values of both scores indicated that perception was higher than the actual weight. Negative values indicated that perception was lower than the actual weight. Human development.—The level of human development of each city was analyzed using the Human Development Index (HDI), a composite index that measures the average achievements of a given city in three basic dimensions: (a) long and healthy life, as measured by life expectancy at birth; (b) knowledge, as measured by the adult literacy rate and the ratio of combined gross enrollment in primary, secondary, and higher schools; and (c) standard of living, as measured by gross domestic product (GDP) per capita in purchasing power parity in U.S. dollars (United Nations Development Programme, 2005). According to this index (ranging from 0 to 1), a city is rated as low in human development for HDI < 0.500, middle for HDI between 0.500 and 0.799, and high for HDI ≥ 0.800. Information about the HDI of Brazilian cities were extracted from the 2013 Atlas of Human Development in Brazil, a survey coordinated by the United Nations Development Programme (2013). Although the information was published in 2013, the HDI was constructed based on data collected from the 2010 Brazilian Demographic Census. Thus, information regarding body weight perception and HDI were collected 1 yr. apart. Some potential confounding factors in the ecological relationship between body weight perception and HDI were also included in analyses: population density, the Gini index, and education level of the students' mothers. The population density of a city is measured by the ratio of the city population divided by its surface area, e.g., the number of people per square kilometer. The Gini index, which is expressed in percentage points, is a measure commonly used to calculate income distribution inequalities (United Nations Development Programme, 2013). It consists of a number between 0 and 100, where 0 corresponds to complete income equality and 100 corresponds to complete inequality (United Nations Development Programme, 2013). The data on population density and the Gini index were collected from the 2013 Atlas of Human Development in Brazil (United Nations Development Programme, 2013). Although the information was published in 2013, the Gini
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index and the population density were built based on data collected from the 2010 Brazilian Demographic Census. Thus, information on body weight perception, the Gini index, and population density were collected 1 yr. apart. Information regarding the education level of the students' mothers was based on data from the PeNSE, which showed the frequency of mothers with the following education levels: no education or incomplete elementary school, completed elementary school or incomplete high school, completed high school or incomplete higher education, and completed higher education (Brazilian Institute of Geography and Statistics, 2009). Analysis Descriptive statistics were calculated: means, standard deviations (SD), and relative frequencies. Initially, the data normality was tested by the Shapiro–Wilks test and distribution histograms. The variables were normally distributed, so parametric statistics were used. The correlations among body weight perception, nutritional status, body weight misperception, and HDI were assessed by the Pearson correlation coefficient (r). Simple and multiple linear regression was used to assess how much the HDI explained the variation in the prevalence of body weight perception, nutritional status, and body weight misperception. Then, multiple linearregression analysis was run, adjusted by potential confounding factors (population density, Gini index, and maternal education). For all analyses, a significance level of 5% was adopted. The analyses were stratified by sex using Stata Version 11. Six adjusted models were constructed: (1) In the adjusted thinness perception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, underweight prevalence, and body weight misperception score. (2) In the adjusted overweight perception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, overweight prevalence, and body weight misperception score. (3) In the adjusted underweight model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, body weight perception, and body weight misperception score. (4) In the adjusted overweight (overweight + obesity) model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, body weight perception, and body weight misperception score. (5) In the adjusted thinness misperception model, the variables included in the adjusted analysis were HDI, population density, Gini
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index, maternal education, underweight prevalence, and body weight perception score. (6) In the adjusted overweight misperception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, overweight prevalence, and body weight perception score. RESULTS Table 1 shows that the prevalence of individuals who perceived themselves as underweight was 22.1%. The prevalence of adolescents who perceived themselves as overweight and obese was 17.7%. The body weight misperception score indicated that girls and boys actually perceived themselves to be thinner than they really were. For girls who reported being overweight, the misperception score showed that they perceived themselves to be heavier than they really were (M difference = 0.4, SD = 2.4). On the other hand, the body weight misperception score indicated that boys perceived themselves to be lighter than they actually were (M difference = −8.9, SD = 2.6). Table 2 shows the correlation of body perception, nutritional status, and body weight misperception with the HDI of Brazilian cities. Both for girls and for boys, the thinness perception decreased with increasing HDI of cities. In relation to nutritional status, significant correlation only for boys was detected, in which overweight increased with increasing HDI of cities. Thinness misperception (declaring themselves thinner than they really were) was more evident in cities with lower HDI both for girls and boys. The variance inflation factor was acceptable for all variables (VIF range = 1.02 to 1.64), so there were no problems with multicollinearity. For girls in the unadjusted regressions, significant correlations were found only for thinness and overweight perception, with HDI of Brazilian cities. By adjusting for socioeconomic variables, it was found that the association with HDI remained for the overweight perception, and the model explained 37% of the variance. Furthermore, each one-unit increase of HDI (0.001) resulted in an increase of 33.97% in the prevalence of overweight perception. Still for girls, no association was found between nutritional status and HDI. However, for girls who perceived themselves to be heavier than they really were, there was an association between body weight misperception score and HDI of Brazilian cities, indicating that each oneunit increase in HDI resulted in an average increase of 28.19% in the body weight misperception score. Furthermore, the model adjusted for potential confounding factors explained 35% of the body weight misperception variation (Adj R2 = .35; Table 3).
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 1 PREVALENCE AND MEAN VALUES OF VARIABLES Variable
%
95%CI
Girls Thinness perception
21.4
20.6, 22.1
Overweight perception
21.3
20.5, 22.1
Boys Thinness perception
23.0
22.1, 23.8
Overweight perception
13.8
13.1, 14.5
Girls (Nutritional status = BMI category) Underweight
2.2
1.9, 2.5
Normal weight
75.6
74.8, 76.4
Overweight
16.4
15.7, 17.1
5.8
5.4, 6.2
Obesity Boys (Nutritional status = BMI category) Underweight
3.6
3.2, 4.0
Normal weight
72.2
70.9, 73.5
Overweight
15.5
14.6, 16.4
8.7
8.0, 9.3
No education or incomplete elementary school
25.9
25.3, 26.5
Completed elementary school or incomplete high school
13.7
13.3, 14.2
Completed high school or incomplete higher education
25.7
25.1, 26.3
16.1
15.7, 16.6
Obesity Maternal education
Completed higher education
M Gini index
0.60
Population density (people/km )
SD 0.03
2,797.9
2,785.9
19.2
1.8
0.4
2.4
% Thinness perception – % Underweight
19.5
2.8
% Overweight perception – % Overweight and obesity
−8.9
2.6
2
Body weight misperception score in girls % Thinness perception – % Underweight % Overweight perception – % Overweight and obesity Body weight misperception score in boys
Human Development Index
0.776
0.035
Note.—CI = confidence interval.
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TABLE 2 PEARSON CORRELATION COEFFICIENTS (95% CONFIDENCE INTERVALS) AMONG BODY WEIGHT PERCEPTION, NUTRITIONAL STATUS, BODY WEIGHT MISPERCEPTION, AND HUMAN DEVELOPMENT INDEX Girls
Variable
r (95%CI)
Boys p
r (95%CI)
p
Body weight perception Thinness Overweight
−.40 (−.77, −.02) .54 (.19, .88)
.04 < .01
−.51 (−.86, −.15) .58 (.24, .91)
< .01 < .01
Nutritional status Underweight Overweight
−.31
.11
.23
.25
−.34
.08
.13 .42 (.05, .79)
.50 .02
Body weight misperception Lighter than actual
−.55 (−.89, −.21)
< .01
Heavier than actual .31 .11 −.18 .34 Note.—r = Pearson correlation coefficient; CI = confidence interval (shown only for statistically significant correlations).
For boys in the unadjusted regressions, it was observed that the prevalence of thinness perception decreased with increasing HDI, and the prevalence of overweight perception increased with increasing HDI. This association remained significant after adjustment for sociodemographic variables, and the explanatory power of socioeconomic variables for the variation in the prevalence of underweight perception was 41% (Adj R2 = .41) and for the variation in the prevalence of overweight perception was 29%. Also for boys, no association was found in the adjusted regression between nutritional status and HDI. However, for boys who perceived themselves thinner than they actually are, there was an association in the unadjusted and adjusted regressions between body weight misperception score and HDI of Brazilian cities, indicating that after adjustment for socioeconomic variables, increasing the HDI reflected in a decrease of 40.85% in the body weight misperception scores. Moreover, the explanatory power of the model adjusted for variation in the body weight misperception was 32% (Table 4). DISCUSSION The main finding of this study was that in both genders, thinness misperception (adolescents who perceived themselves to be thinner than they actually were) had an inverse relationship with the HDI of cities, indicating that the highest thinness misperception prevalence was in cities with low HDI. For girls, adjusting analyses for other socioeconomic variables showed that the overweight misperception (adolescents who perceived
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 3 LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN GIRLS Model
Variable
Unstandardized Coefficients B
Standardized Coefficients
SE
t
p
Adj R2
0.13
β
Body weight perception Thinness Model 1
(Constant) HDI
Model 2
(Constant) HDI
39.44
8.30
−23.19
10.68
−5.00
14.08
6.25
13.07
4.74
< .01
−2.17
.04
−0.35
.72
.10
0.47
.63
−.39
Population density
0.00
0.00
−.17
−0.92
.36
Gini index
44.27
13.36
.62
3.31
.01
Maternal education
−0.28
0.12
−.46
−2.29
.03
−10.96
10.07
41.53
12.96
0.43
Body weight perception Overweight Model 1
(Constant) HDI
Model 2
(Constant)
11.73
18.69
HDI
33.97
13.46
−1.08
.28
.53
3.20
< .01
0.62
.53
.44
2.52
.01
Population density
2.55
0.00
.02
0.13
.89
Gini index
−35.68
18.52
−.38
−1.92
.06
0.33
0.26
.19
1.25
.22
2.43
.02
−.30
−1.61
.11
0.01
.98
−.21
−1.07
.29
Maternal education
0.26 0.37
Nutritional status Underweight Model 1
(Constant) HDI
Model 2
(Constant) HDI
6.49
2.66
−5.54
3.43
0.09
5.04
−3.89
3.63
Population density
1.09
0.00
.04
0.21
.83
Gini index
9.16
5.00
.42
1.83
.08
−0.03
0.07
−.07
−0.43
.67
Maternal education
0.05 0.16
(continued on next page)
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BODY WEIGHT MISPERCEPTION TABLE 3 (CONT’D) LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN GIRLS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
0.01
β
Nutritional status Overweight Model 1 Model 2
4.99
13.70
HDI
(Constant)
20.45
17.70
(Constant)
31.77
27.29
5.78
19.66
HDI
0.36
.72
.22
1.15
.25
1.16
.25
.06
0.29
.77
Population density
0.00
0.00
.44
1.83
.08
Gini index
−30.51
27.04
−.27
−1.12
.27
0.11
0.38
.05
0.28
.77
32.94
7.53
Maternal education
0.04
Body weight misperception Lighter than actual Model 1
(Constant) HDI
Model 2
(Constant) HDI
−17.64
9.69
0.45
13.31
−8.58
9.59
4.37 < .01 −.34
−1.82
.08
0.03
.97
−.16
−0.89
.38
Population density
0.00
0.00
−.19
−0.93
.35
Gini index
34.11
13.19
.54
2.58
.02
0.38
0.18
.34
2.06
.05
−15.96
10.12
−1.57
.12
21.07
13.03
1.61
.11
−20.03
16.89
−1.18
.24
28.19
12.16
.41
2.31
.03
Maternal education
0.08 0.29
Body weight misperception Heavier than actual Model 1
(Constant) HDI
Model 2
(Constant) HDI
.30
Population density
0.00
0.00
−.56
−2.81
.01
Gini index
−5.16
16.73
−.06
−0.30
.76
0.22
0.23
.14
0.92
.36
Maternal education
0.05 0.35
themselves heavier than they really were) was greater in cities with higher HDI. Moreover, the HDI of cities along with other macro-structural indicators explained 35% of the variance in the overweight misperception in girls and 32% in the underweight misperception in boys.
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 4 LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN BOYS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
.23
β
Body weight perception Thinness Model 1
(Constant) HDI
Model 2
(Constant) HDI
54.32
10.53
−40.30
13.55
21.71
18.58
−34.35
13.38
−.51 −.43
5.15
< .01
−2.97
< .01
1.16
.25
−2.56
.01
Population density
0.00
0.00
.09
0.51
.61
Gini index
37.40
18.41
.39
2.03
.05
0.38
0.26
.22
1.45
.16
−13.50
7.66
34.81
9.85
−21.03
15.56
35.15
11.21
Maternal education
.41
Body weight perception Overweight Model 1
(Constant) HDI
Model 2
(Constant) HDI
.57 .58
−1.76
.28
3.53
< .01
−1.35
.19
3.13
< .01
Population density
3.96
0.01
.05
0.24
.80
Gini index
4.73
15.42
.06
0.30
.76
Maternal education
0.31
0.22
.24
1.43
.16
0.02
.97
.13
0.67
.50
−1.02
.31
0.90
.37
.31 .29
Nutritional status Underweight Model 1 Model 2
(Constant)
0.13
4.96
HDI
4.32
6.38
−10.27
9.97
6.50
7.18
(Constant) HDI Population density
6.32
3.23
.01
0.06
.95
Gini index
11.23
9.88
.28
1.13
.26
0.14 0.13 .20 (continued on next page)
1.01
.32
Maternal education
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.22
.02 .02
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559
BODY WEIGHT MISPERCEPTION TABLE 4 (CONT’D) LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN BOYS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
−0.96
.34
.14
2.34
.03
−0.21
.83
1.65
.11
β
Nutritional status Overweight Model 1 Model 2
−15.69
16.33
HDI
(Constant)
49.17
21.01
(Constant)
−6.80
31.72
HDI
37.81
22.85
.42 .32
Population density
0.01
0.00
.34
1.55
.13
Gini index
−14.85
31.43
−.10
−0.47
.64
0.55
0.44
.21
1.21
.23
5.19
BRAZILIAN ADOLESCENTS' BODY WEIGHT MISPERCEPTION AND THE HUMAN DEVELOPMENT INDEX OF THE CITIES WHERE THEY LIVE1, 2, 3 DIEGO A. S. SILVA AND ELIANE C. A. GONÇALVES Universidade Federal de Santa Catarina, Brazil Summary.—This study investigated the relationship between adolescents' body weight misperception and the Human Development Index (HDI) of the cities in which they live in Brazil. Data from a large national survey that included 60,973 boys and girls between 13 and 15 yr. (M = 14.2, SD = 1.1; 47.5% boys, 52.5% girls) were analyzed. Regression analyses were adjusted for potential confounding factors such as population density, income inequality, nutritional status (BMI), and mothers’ education. In both sexes, the relationship between perceived underweight showed an inverse relationship with HDI. The highest prevalences of participants who perceived themselves as overweight for girls were found in cities with high HDI.
Body weight self-perception is one of the most important body image components because it is associated with feelings and attitudes about one's own body (Pauline, Selvam, Swaminathan, & Vaz, 2012). Excessive concern with body weight may influence behaviors that adolescents adopt in their daily lives, such as the use of laxatives and non-prescription drugs, excessive practice of physical exercise, inadequate diets, and even suicidal ideation (Cheung, Ip, Lam, & Bibby, 2007; Seo & Lee, 2013). Sociocultural factors affect how adolescents perceive their body weight (Fidelix, Silva, Pelegrini, Silva, & Petroski, 2011). Studies have shown that body weight misperception in adolescents and its associated behaviors differ from one country and culture to another (Xie, Chou, Spruijt-Metz, Reynolds, Clark, Palmer, et al., 2006; Cheung, et al., 2007; Ursoniu, Putnoky, & Vlaicu, 2011; Pauline, et al., 2012). In China, for example, it was found that among adolescents, 37.7% of boys and 18.8% of girls perceived themselves to be thin, while 26.5% of young boys and 5.8% of girls perceived themselves to be overweight. Furthermore, factors such as media exposure Address correspondence to Diego Augusto Santos Silva, Departamento de Educação Física, Universidade Federal de Santa Catarina, Centro de Desportos, Campus Universitário– Trindade–Caixa Postal 476, CEP 88040-900–Florianópolis, Santa Catarina, Brazil or e-mail ([email protected]). 2 Both authors acknowledge ethical responsibility for the content of the manuscript and will accept the consequences of any ethical violation. This is an ecological-design study that used data on the prevalence of body weight perception and nutritional status of the report from the National Adolescent School-based Health Survey (PeNSE), which is a partnership between the Ministry of Health and the Brazilian Institute of Geography and Statistics. 3 The authors declare no conflict of interest. 1
DOI 10.2466/27.10.PMS.118k22w7
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ISSN 0031-5125
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time, attitudes toward physical appearance, and adoption of health-risking behaviors were associated with body weight misperception in girls (Xie, et al., 2006). Research conducted with adolescents in Romania reported that 22.6% of normal-weight adolescents perceived themselves as overweight (Ursoniu, et al., 2011). Moreover, in both sexes, a body weight misperception was associated with the excessive practice of physical exercise, low amount of calories in foods, ingestion of diet pills, frequent vomiting, and use of laxatives (Ursoniu, et al., 2011). The difference in the frequency of thin or overweight body perception and its associated behaviors from one country to another may result from several factors, such as media influence, lack of parental education, cultural prejudice, and low self-esteem (Silva, Pereira, & Cabral de Oliveira, 2012). Media presentations, for instance, play an important role in the lives of adolescents, and they are a powerful factor in disseminating the ideals of perfect body, in which underweight for girls and developed muscles for boys symbolize competence, success, and sex appeal, while obesity represents laziness, self-pity, lack of decision-making power, and a lower quality of life (Araújo, Dumith, Menezes, & Hallal, 2010). There is sufficient evidence indicating that populations with higher material deprivation and lower access to psychosocial support have a higher incidence of diseases and mortality, more often at earlier ages due to preventable conditions (Di Cesare, Khang, Asaria, Blakely, Cowan, Farzadfar, et al., 2013). Nevertheless, little is known about the relationships between such socio-economic conditions and body weight misperception. Thus, the aim of this study was to investigate the relationship between body weight perception of adolescents and the Human Development Index of the cities where they live in Brazil. This study predicted that populations with better living conditions have more adolescents with body weight misperception, since they have more access to electronic media that impose ideal beauty standards (Xie, et al., 2006). Hypothesis. The Human Development Index in Brazilian cities and a healthy body weight perception will be significantly correlated. METHOD Sample This is an ecological-design study that used data on the frequency of body weight perception issues from the report of the National Adolescent School-based Health Survey (PeNSE), which is a partnership between the Ministry of Health and the Brazilian Institute of Geography and Statistics (IBGE, 2009). The PeNSE's overall aim was to investigate the risk factors for health protection among Brazilian adolescents. The target population
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included the 9th-yr. students of public and private elementary schools in all 26 state capitals and the Federal District. The ninth year of the Brazilian educational system is equivalent to Grade 9 of North American high schools. Among the 1,453 schools surveyed by PeNSE, 2,175 classes which included 68,735 students attending schools were selected. Of these, 63,411 (92.3%) were present on the day of data collection, totaling 7.7% loss at this stage. Students (n = 501) were excluded from the sample due to refusal to participate, and 1,937 students did not fill the variable “sex.” Thus, the sample included 60,973 students whose data were analyzed. This sample size corresponded to an overall non-response rate of 11.3%. In the sample studied, 89% of students ages 13 to 15 yr. (M = 14.2, SD = 1.1), 47.5% were boys and 52.5% girls. The PeNSE was approved by the National Research Ethics Board (Brazilian Institute of Geography and Statistics, 2009). Measures Body weight perception.—The variable concerning body weight perception was constructed based on the following question: “How do you describe your weight?” The response options were “too thin,” “thin,” “normal,” “fat,” and “too fat.” For the present study, the responses “too thin” and “thin” were considered together as underweight perception, the responses “fat” and “too fat” were considered together as overweight perception, and the responses “normal“ were considered as normal body weight perception. This classification was adopted by the PeNSE in its reports (Castro, Levy, Cardoso, Passos, Sardinha, Tavares, et al., 2010). Nutritional status.—Information about the nutritional status of students was analyzed based on data from PeNSE, which showed information on the prevalence of underweight, normal weight, overweight, and obesity for boys and girls in each of the 27 locations analyzed (Brazilian Institute of Geography and Statistics, 2009). For body weight measurement, adolescents were asked to wear light clothes, to remain barefoot, and to stand on an electronic scale with a capacity of 150 kg and 100 g sensitivity. Height was measured using a stadiometer with a scale in millimeters and a maximum capacity of 200 cm. In this measurement, the adolescents remained barefoot with feet together, heels touching the wall in an upright posture and eyes fixed on the horizon, without flexing or extending the head. Body Mass Index (BMI) and BMI Z scores were calculated, and for the classification of adolescents regarding their nutritional status, literature recommendations were adopted (De Onis, Onyango, Borghi, Siyam, Nishida, & Siekmann, 2007; Z < − 2, underweight; + 1 < Z > − 2, normal weight; Z > + 1, overweight; Z > + 2, obese). For the inferential analysis, overweight and obesity categories were grouped into a single category.
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Body weight misperception.—Body weight misperception was calculated as the difference between body perception and nutritional status categories (body perception – BMI). This procedure resulted in two scores used in data analysis. The underweight misperception score (people who declared themselves thinner than they really were) was the difference between underweight perception and underweight status as assessed by BMI. The overweight misperception score (people who declared themselves heavier than they really were) was the difference between overweight perception and actual overweight as assessed by BMI. Positive values of both scores indicated that perception was higher than the actual weight. Negative values indicated that perception was lower than the actual weight. Human development.—The level of human development of each city was analyzed using the Human Development Index (HDI), a composite index that measures the average achievements of a given city in three basic dimensions: (a) long and healthy life, as measured by life expectancy at birth; (b) knowledge, as measured by the adult literacy rate and the ratio of combined gross enrollment in primary, secondary, and higher schools; and (c) standard of living, as measured by gross domestic product (GDP) per capita in purchasing power parity in U.S. dollars (United Nations Development Programme, 2005). According to this index (ranging from 0 to 1), a city is rated as low in human development for HDI < 0.500, middle for HDI between 0.500 and 0.799, and high for HDI ≥ 0.800. Information about the HDI of Brazilian cities were extracted from the 2013 Atlas of Human Development in Brazil, a survey coordinated by the United Nations Development Programme (2013). Although the information was published in 2013, the HDI was constructed based on data collected from the 2010 Brazilian Demographic Census. Thus, information regarding body weight perception and HDI were collected 1 yr. apart. Some potential confounding factors in the ecological relationship between body weight perception and HDI were also included in analyses: population density, the Gini index, and education level of the students' mothers. The population density of a city is measured by the ratio of the city population divided by its surface area, e.g., the number of people per square kilometer. The Gini index, which is expressed in percentage points, is a measure commonly used to calculate income distribution inequalities (United Nations Development Programme, 2013). It consists of a number between 0 and 100, where 0 corresponds to complete income equality and 100 corresponds to complete inequality (United Nations Development Programme, 2013). The data on population density and the Gini index were collected from the 2013 Atlas of Human Development in Brazil (United Nations Development Programme, 2013). Although the information was published in 2013, the Gini
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index and the population density were built based on data collected from the 2010 Brazilian Demographic Census. Thus, information on body weight perception, the Gini index, and population density were collected 1 yr. apart. Information regarding the education level of the students' mothers was based on data from the PeNSE, which showed the frequency of mothers with the following education levels: no education or incomplete elementary school, completed elementary school or incomplete high school, completed high school or incomplete higher education, and completed higher education (Brazilian Institute of Geography and Statistics, 2009). Analysis Descriptive statistics were calculated: means, standard deviations (SD), and relative frequencies. Initially, the data normality was tested by the Shapiro–Wilks test and distribution histograms. The variables were normally distributed, so parametric statistics were used. The correlations among body weight perception, nutritional status, body weight misperception, and HDI were assessed by the Pearson correlation coefficient (r). Simple and multiple linear regression was used to assess how much the HDI explained the variation in the prevalence of body weight perception, nutritional status, and body weight misperception. Then, multiple linearregression analysis was run, adjusted by potential confounding factors (population density, Gini index, and maternal education). For all analyses, a significance level of 5% was adopted. The analyses were stratified by sex using Stata Version 11. Six adjusted models were constructed: (1) In the adjusted thinness perception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, underweight prevalence, and body weight misperception score. (2) In the adjusted overweight perception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, overweight prevalence, and body weight misperception score. (3) In the adjusted underweight model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, body weight perception, and body weight misperception score. (4) In the adjusted overweight (overweight + obesity) model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, body weight perception, and body weight misperception score. (5) In the adjusted thinness misperception model, the variables included in the adjusted analysis were HDI, population density, Gini
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index, maternal education, underweight prevalence, and body weight perception score. (6) In the adjusted overweight misperception model, the variables included in the adjusted analysis were HDI, population density, Gini index, maternal education, overweight prevalence, and body weight perception score. RESULTS Table 1 shows that the prevalence of individuals who perceived themselves as underweight was 22.1%. The prevalence of adolescents who perceived themselves as overweight and obese was 17.7%. The body weight misperception score indicated that girls and boys actually perceived themselves to be thinner than they really were. For girls who reported being overweight, the misperception score showed that they perceived themselves to be heavier than they really were (M difference = 0.4, SD = 2.4). On the other hand, the body weight misperception score indicated that boys perceived themselves to be lighter than they actually were (M difference = −8.9, SD = 2.6). Table 2 shows the correlation of body perception, nutritional status, and body weight misperception with the HDI of Brazilian cities. Both for girls and for boys, the thinness perception decreased with increasing HDI of cities. In relation to nutritional status, significant correlation only for boys was detected, in which overweight increased with increasing HDI of cities. Thinness misperception (declaring themselves thinner than they really were) was more evident in cities with lower HDI both for girls and boys. The variance inflation factor was acceptable for all variables (VIF range = 1.02 to 1.64), so there were no problems with multicollinearity. For girls in the unadjusted regressions, significant correlations were found only for thinness and overweight perception, with HDI of Brazilian cities. By adjusting for socioeconomic variables, it was found that the association with HDI remained for the overweight perception, and the model explained 37% of the variance. Furthermore, each one-unit increase of HDI (0.001) resulted in an increase of 33.97% in the prevalence of overweight perception. Still for girls, no association was found between nutritional status and HDI. However, for girls who perceived themselves to be heavier than they really were, there was an association between body weight misperception score and HDI of Brazilian cities, indicating that each oneunit increase in HDI resulted in an average increase of 28.19% in the body weight misperception score. Furthermore, the model adjusted for potential confounding factors explained 35% of the body weight misperception variation (Adj R2 = .35; Table 3).
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 1 PREVALENCE AND MEAN VALUES OF VARIABLES Variable
%
95%CI
Girls Thinness perception
21.4
20.6, 22.1
Overweight perception
21.3
20.5, 22.1
Boys Thinness perception
23.0
22.1, 23.8
Overweight perception
13.8
13.1, 14.5
Girls (Nutritional status = BMI category) Underweight
2.2
1.9, 2.5
Normal weight
75.6
74.8, 76.4
Overweight
16.4
15.7, 17.1
5.8
5.4, 6.2
Obesity Boys (Nutritional status = BMI category) Underweight
3.6
3.2, 4.0
Normal weight
72.2
70.9, 73.5
Overweight
15.5
14.6, 16.4
8.7
8.0, 9.3
No education or incomplete elementary school
25.9
25.3, 26.5
Completed elementary school or incomplete high school
13.7
13.3, 14.2
Completed high school or incomplete higher education
25.7
25.1, 26.3
16.1
15.7, 16.6
Obesity Maternal education
Completed higher education
M Gini index
0.60
Population density (people/km )
SD 0.03
2,797.9
2,785.9
19.2
1.8
0.4
2.4
% Thinness perception – % Underweight
19.5
2.8
% Overweight perception – % Overweight and obesity
−8.9
2.6
2
Body weight misperception score in girls % Thinness perception – % Underweight % Overweight perception – % Overweight and obesity Body weight misperception score in boys
Human Development Index
0.776
0.035
Note.—CI = confidence interval.
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TABLE 2 PEARSON CORRELATION COEFFICIENTS (95% CONFIDENCE INTERVALS) AMONG BODY WEIGHT PERCEPTION, NUTRITIONAL STATUS, BODY WEIGHT MISPERCEPTION, AND HUMAN DEVELOPMENT INDEX Girls
Variable
r (95%CI)
Boys p
r (95%CI)
p
Body weight perception Thinness Overweight
−.40 (−.77, −.02) .54 (.19, .88)
.04 < .01
−.51 (−.86, −.15) .58 (.24, .91)
< .01 < .01
Nutritional status Underweight Overweight
−.31
.11
.23
.25
−.34
.08
.13 .42 (.05, .79)
.50 .02
Body weight misperception Lighter than actual
−.55 (−.89, −.21)
< .01
Heavier than actual .31 .11 −.18 .34 Note.—r = Pearson correlation coefficient; CI = confidence interval (shown only for statistically significant correlations).
For boys in the unadjusted regressions, it was observed that the prevalence of thinness perception decreased with increasing HDI, and the prevalence of overweight perception increased with increasing HDI. This association remained significant after adjustment for sociodemographic variables, and the explanatory power of socioeconomic variables for the variation in the prevalence of underweight perception was 41% (Adj R2 = .41) and for the variation in the prevalence of overweight perception was 29%. Also for boys, no association was found in the adjusted regression between nutritional status and HDI. However, for boys who perceived themselves thinner than they actually are, there was an association in the unadjusted and adjusted regressions between body weight misperception score and HDI of Brazilian cities, indicating that after adjustment for socioeconomic variables, increasing the HDI reflected in a decrease of 40.85% in the body weight misperception scores. Moreover, the explanatory power of the model adjusted for variation in the body weight misperception was 32% (Table 4). DISCUSSION The main finding of this study was that in both genders, thinness misperception (adolescents who perceived themselves to be thinner than they actually were) had an inverse relationship with the HDI of cities, indicating that the highest thinness misperception prevalence was in cities with low HDI. For girls, adjusting analyses for other socioeconomic variables showed that the overweight misperception (adolescents who perceived
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 3 LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN GIRLS Model
Variable
Unstandardized Coefficients B
Standardized Coefficients
SE
t
p
Adj R2
0.13
β
Body weight perception Thinness Model 1
(Constant) HDI
Model 2
(Constant) HDI
39.44
8.30
−23.19
10.68
−5.00
14.08
6.25
13.07
4.74
< .01
−2.17
.04
−0.35
.72
.10
0.47
.63
−.39
Population density
0.00
0.00
−.17
−0.92
.36
Gini index
44.27
13.36
.62
3.31
.01
Maternal education
−0.28
0.12
−.46
−2.29
.03
−10.96
10.07
41.53
12.96
0.43
Body weight perception Overweight Model 1
(Constant) HDI
Model 2
(Constant)
11.73
18.69
HDI
33.97
13.46
−1.08
.28
.53
3.20
< .01
0.62
.53
.44
2.52
.01
Population density
2.55
0.00
.02
0.13
.89
Gini index
−35.68
18.52
−.38
−1.92
.06
0.33
0.26
.19
1.25
.22
2.43
.02
−.30
−1.61
.11
0.01
.98
−.21
−1.07
.29
Maternal education
0.26 0.37
Nutritional status Underweight Model 1
(Constant) HDI
Model 2
(Constant) HDI
6.49
2.66
−5.54
3.43
0.09
5.04
−3.89
3.63
Population density
1.09
0.00
.04
0.21
.83
Gini index
9.16
5.00
.42
1.83
.08
−0.03
0.07
−.07
−0.43
.67
Maternal education
0.05 0.16
(continued on next page)
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BODY WEIGHT MISPERCEPTION TABLE 3 (CONT’D) LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN GIRLS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
0.01
β
Nutritional status Overweight Model 1 Model 2
4.99
13.70
HDI
(Constant)
20.45
17.70
(Constant)
31.77
27.29
5.78
19.66
HDI
0.36
.72
.22
1.15
.25
1.16
.25
.06
0.29
.77
Population density
0.00
0.00
.44
1.83
.08
Gini index
−30.51
27.04
−.27
−1.12
.27
0.11
0.38
.05
0.28
.77
32.94
7.53
Maternal education
0.04
Body weight misperception Lighter than actual Model 1
(Constant) HDI
Model 2
(Constant) HDI
−17.64
9.69
0.45
13.31
−8.58
9.59
4.37 < .01 −.34
−1.82
.08
0.03
.97
−.16
−0.89
.38
Population density
0.00
0.00
−.19
−0.93
.35
Gini index
34.11
13.19
.54
2.58
.02
0.38
0.18
.34
2.06
.05
−15.96
10.12
−1.57
.12
21.07
13.03
1.61
.11
−20.03
16.89
−1.18
.24
28.19
12.16
.41
2.31
.03
Maternal education
0.08 0.29
Body weight misperception Heavier than actual Model 1
(Constant) HDI
Model 2
(Constant) HDI
.30
Population density
0.00
0.00
−.56
−2.81
.01
Gini index
−5.16
16.73
−.06
−0.30
.76
0.22
0.23
.14
0.92
.36
Maternal education
0.05 0.35
themselves heavier than they really were) was greater in cities with higher HDI. Moreover, the HDI of cities along with other macro-structural indicators explained 35% of the variance in the overweight misperception in girls and 32% in the underweight misperception in boys.
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D. A. S. SILVA & E. C. A. GONÇALVES TABLE 4 LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN BOYS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
.23
β
Body weight perception Thinness Model 1
(Constant) HDI
Model 2
(Constant) HDI
54.32
10.53
−40.30
13.55
21.71
18.58
−34.35
13.38
−.51 −.43
5.15
< .01
−2.97
< .01
1.16
.25
−2.56
.01
Population density
0.00
0.00
.09
0.51
.61
Gini index
37.40
18.41
.39
2.03
.05
0.38
0.26
.22
1.45
.16
−13.50
7.66
34.81
9.85
−21.03
15.56
35.15
11.21
Maternal education
.41
Body weight perception Overweight Model 1
(Constant) HDI
Model 2
(Constant) HDI
.57 .58
−1.76
.28
3.53
< .01
−1.35
.19
3.13
< .01
Population density
3.96
0.01
.05
0.24
.80
Gini index
4.73
15.42
.06
0.30
.76
Maternal education
0.31
0.22
.24
1.43
.16
0.02
.97
.13
0.67
.50
−1.02
.31
0.90
.37
.31 .29
Nutritional status Underweight Model 1 Model 2
(Constant)
0.13
4.96
HDI
4.32
6.38
−10.27
9.97
6.50
7.18
(Constant) HDI Population density
6.32
3.23
.01
0.06
.95
Gini index
11.23
9.88
.28
1.13
.26
0.14 0.13 .20 (continued on next page)
1.01
.32
Maternal education
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.22
.02 .02
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559
BODY WEIGHT MISPERCEPTION TABLE 4 (CONT’D) LINEAR REGRESSIONS OF HUMAN DEVELOPMENT INDEX FROM WEIGHT PERCEPTION, NUTRITIONAL STATUS, AND WEIGHT MISPERCEPTION IN BOYS Model
Variable
Unstandardized Coefficients B
SE
Standardized Coefficients
t
p
Adj R2
−0.96
.34
.14
2.34
.03
−0.21
.83
1.65
.11
β
Nutritional status Overweight Model 1 Model 2
−15.69
16.33
HDI
(Constant)
49.17
21.01
(Constant)
−6.80
31.72
HDI
37.81
22.85
.42 .32
Population density
0.01
0.00
.34
1.55
.13
Gini index
−14.85
31.43
−.10
−0.47
.64
0.55
0.44
.21
1.21
.23
5.19
