Millennium development goals and oral health in cities in southern Brazil

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Community Dent Oral Epidemiol 2010; 38: 197–205                                                  2010 John Wiley & Sons A/S
All rights reserved

                                                                                    Roberto Eduardo Bueno*, Samuel Jorge
Millennium development goals                                                        Moysés and Simone Tetu Moysés
                                                                                    Pontifı́cia Universidade Católica do Paraná,

and oral health in cities in                                                        Curitiba, Paraná, Brasil

southern Brazil
Bueno RE, Moysés SJ, Moysés ST. Millennium development goals and oral
health in cities in southern Brazil. Community Dent Oral Epidemiol 2010; 38:
197–205.  2010 John Wiley & Sons A ⁄ S.

Abstract – Objectives: To investigate social determinants of oral health,
analysing the occurrence of associations between millennium development
goals (MDG) indicators and oral health (OH) indicators. Methods: An
ecological study was performed in two distinct phases. In Phase 1, MDG
indicators and related covariates were obtained from the demographic census
of the Brazilian Institute of Geography and Statistics, the Ministry of Health
database and the 2000 Human Development Atlas, making up the whole set of
independent variables. Principal component analysis was carried out for the
independent variables showing the correlations among the variables
comprising the main components, and generating a synthetic index allowing
the performance of the cities to be known with regard to the MDG (MDG
index). In Phase 2, the DMFT index (mean number of decay, missing or filled
permanent teeth) and the CF index (prevalence of caries-free individuals), in
12 years old were obtained from the epidemiological survey undertaken in
2002–2003, in 49 cities in southern Brazil, and were analysed in relation to the    Key words: dental caries; epidemiology;
MDG index using Spearman’s correlation. Results: A statistically significant        health promotion; oral health; social
correlation was found for the DMFT and CF indices, respectively, with: the          determinants of health
MDG index (R2 = 0.49 and 0.48; P = 0.00); the socioeconomic status of the           Roberto Eduardo Bueno, Alameda Butantã,
population (R2 = 0.12 and 0.12; P = 0.02); the socioenvironmental characteristics   300, Zaniolo, São José dos Pinhais, PR 83025-
                                                                                    745, Brazil
(R2 = 0.41 and 0.46; P = 0.00). Conclusions: The MDG synthetic index of the
                                                                                    Tel.: 55 41 33835552
cities analysed and the respective components relating to their socioeconomic       e-mail:
and socioenvironmental status demonstrated a positive correlation with OH           *Grant Holder: CAPES–Coordenação de
indicators. As such, intersectoral public policies based on population strategies   Aperfeiçoamento de Pessoal de Nı́vel Superior.
that act on social determinants of general and oral health need to be integrated    Submitted 6 November 2009;
so as to impact on the MDG and OH outcomes.                                         accepted 21 December 2009

                                                                Development (1994), the World Summit for Social
Introduction                                                    Development in Copenhagen (1995) and the World
At the Millennium Summit, held in September                     Conference on Women in Peking (1995).
2000, 191 countries committed to making efforts to                The MDG are addressed to improving living
meet the millennium development goals (MDG) by                  conditions and promoting social equity. The eight
the year 2015 (1). The MDG were the result of                   goals are monitored by means of 18 targets with 48
complex negotiations that converged in the                      indicators. The goals include: (i) eradicating pov-
principal commitments of a series of international              erty and hunger; (ii) achieving universal quality
meetings held during the 1990s, such as the                     primary education; (iii) promoting gender equality
Environmental Conferences in Rio de Janeiro                     and empowering women; (iv) reducing child
(1992), the Vienna Human Rights Conference                      mortality; (v) improving maternal health; (vi)
(1993), the Cairo Conference on Population and                  combating HIV ⁄ AIDS, malaria and other diseases;

doi: 10.1111/j.1600-0528.2010.00531.x                                                                                       197
Bueno et al.

(vii) improving quality of life and ensuring envi-         The interconnection between health and devel-
ronmental sustainability; and (viii) encouraging a      opment, as thoroughly reflected by the MDG
global partnership for development. The goals can       statements, was reaffirmed in the document
also serve as a link between the agendas of             prepared by the Commission on Social Determi-
governments, companies and civil society. They          nants of Health which criticised the utilitarian view
are extensive references for the formulation of         that health is just a resource for economic devel-
intersectoral public policies, aimed at social inclu-   opment, arguing instead that socioeconomic con-
sion, reduction of inequities, promotion of health      ditions can, also, determine the health of a
and quality of life of more vulnerable populations,     population (2). More specifically, and having rele-
with protection of the environment and sustainable      vant implications for this study, it is acknowledged
development.                                            at large that socioeconomic influences play a
   In Chile in March 2005, the World Health             relevant role in the changes observed in health
Organization (WHO) launched the Commission              indicators, including oral health. A study based on
on Social Determinants of Health, providing sup-        data from 18 industrialized countries showed that
port to governments with theoretical and strategic      dental services, measured in terms of the dentist–
inputs for improving the health conditions and          population ratio, accounted for 3% of the reduction
well-being of their populations, having equity as a     observed in the 12 years old mean caries preva-
fundamental principle (2).                              lence, through the 1970s and mid 1980s, whereas
   The participants of the Commission defined the       social factors accounted for 65% of the observed
theory of Dahlgren and Whitehead as one of the          reduction (9). These findings undoubtedly may
references used to explain equity in health (3).        challenge the still dominant biomedical paradigm
According to this far-reaching theoretical model,       in dentistry, because they made it explicit that
equity in health is determined at different levels,     socioeconomic factors, such as education levels, the
ranging from the individual to the collective,          percentage of economically active highly educated
involving public health policies aimed at equality      women and the level of social inequality were able
and the strengthening of individuals and com-           to explain 65% of the observed reduction of dental
munities, improved access to essential services         caries. These results also confirm that socioeco-
and macro-economic and cultural change.                 nomic status is strongly related to dental caries
   The Division of Equity at the World Health           (9–11).
Organization defines health equity as the absence          Emphasis has been clearly made in recent liter-
of unfair, avoidable or unnecessary differences in      ature on social determinants and their impact on
relation to the health of a given population or         health as a whole and on oral health in particular
several groups, within or between countries,            (8, 12–17). Political and sectorial agendas working
defined by social, economic, demographic or             on social determinants of health can encourage the
geographic criteria (2, 4).Social disadvantages,        effective fulfilment of the MDG in nations, states
mainly when accumulated during childhood and            and cities. It is therefore important to further
analysed throughout the life course of a person,        analyse social determinants of health through the
can exacerbate health inequities (5–7). Inequity        associations between MDG indicators and oral
implies failure to avoid or overcome health             health indicators.
differences that breach human rights, and are
deeply rooted as unfair social stratification.
Health inequity can therefore be defined as a
moral category engrained in political reality and
in the negotiation of social relations of power         This is an ecological study, involving the use of
(2, 4).                                                 aggregated data suitable for measuring the health
   Widespread poor oral health is one of the most       situation of human groups taken globally, and how
evident expressions of inequity with regard to          their health is influenced by social, environmental
poverty and social and health exclusion (8). In this    and behavioural conditions (18).
sense, the MDG indicators are also considered to be        The study was divided into two distinct phases.
important measures of inequities, therefore any         In Phase 1, MDG indicators were obtained from the
existing progresses of MDG among populations            2000 demographic census undertaken by the
can be used to guide the analysis of their health       Brazilian Institute of Geography and Statistics
dynamics, including oral health.                        (IBGE) (19), the Ministry of Health database

Millennium development goals and oral health

(DATASUS) (20) and the UNDP Human Develop-                  to evaluate assumptions and limitations and to
ment Atlas (21) for the year 2000. Nine MDG                 estimate the number of principal components from
variables were selected, based on the theoretical           eigenvalues. An eigenvalue can be thought of as
input obtained from the review of the literature            an index of variance. In principal components
and also based on the availability of information           analysis, each principal component yields an
about 49 cities in Southern Brazil, namely: (i) the         eigenvalue, which is the amount of the total
percentage of people below the poverty line,                variance explained by the component. The
corresponding to the family per capita income of            adopted criterion was what is used usually in
less than ½ a minimum wage (Source: UNDP) (21);             the specialized literature of the area, the test of
(ii) percentage of functionally illiterate people (less     larger eigenvalue than 1 (23).
than 4 years of education); (iii) the ratio of illiterate      The final stage in the development of an index
men and women (Source: IBGE) (19); (iv) the                 was to integrate the set of indicators into a single
mortality rate in children aged under 5 years old           measure, after weighting them consistently as to
(per 1000 live births); (v) the percentage of children      their relative importance in explaining the features
born to adolescent mothers aged in the range of             of the synthetic MDG index. The index so obtained
10–19 years old (Source: DATASUS) (20); (vi) the            facilitated further analysis, when the research
percentage of people living in homes with access to         objectives aimed at ranking the study cities. Based
mains water supply and a bathroom; (vii) the                on this analysis, synthetic MDG index (final scores)
percentage of people having their litter collected;         were calculated, per city, using the weighted
(viii) the percentage of people with access to a            average of the scores obtained from the factor
telephone; (ix) the percentage of people with a             analysis of principal components of the 15 vari-
computer (Source: IBGE) (19).                               ables ⁄ covariates and the total variance explained
   In addition, six covariates associated with oral         by the 3 components, using the following equation:
health outcomes according to the literature on this         SYNTHETIC MDG INDEX = [(score of the 1st
area were also obtained and analysed, namely: (i)           Component · variance of the 1st Compo-
length of time, in years, the water supply has been         nent) + (score of the 2nd Component · variance
fluoridated (Source: Oral Health Brazil) (22); (ii) the     of the 2nd Component) + (score of the 3rd Com-
1991 Municipal Human Development Index (HDI-                ponent · variance of the 3rd Component)] ⁄ total
M 1991); (iii) the 2000 Municipal Human Develop-            variance. The synthetic MDG indices described
ment Index (HDI-M 2000); (iv) Per-Capita Income             performance towards achieving the MDG, in terms
(Source: UNDP) (21); (v) Population; and (vi) Rate          of the observational units (cities), using the regres-
of Urbanization (Source: IBGE 2000 census) (19). As         sion method, combining information on those
they showed significant associations by bivariate           dimensions of city structure which were likely to
analysis, they were subsequently included in the            be most important for the study hypothesis and
whole analysis.                                             developed a typology of cities based on these
   Factor analysis of principal components was              dimensions which could be used as a basis for
performed to find evidence of possible correlations         assessing social determinants of health (23).
between the MDG variables and to simplify the                  In Phase 2 of the study, the oral health indicators
data by reducing the number of variables aiming at          (outcome variables), the DMFT index (mean num-
statistical parsimony. This analysis assumes that a         ber of decay, missing or filled permanent teeth) and
smaller number of variables exist subjacent to the          the prevalence of 12 years old caries-free children
data (components), which express what the origi-            were obtained from the national epidemiological
nal variables have in common. This analysis also            survey undertaken in 2002–2003 (22). These
enabled the validity of the variables that made up          secondary data were aggregated by city. The
the components to be evaluated, by informing                population of the study was originally intended
whether or not they load the concepts they aim to           to be comprised of 50 cities located in the southern
express (23). This analysis was the chosen tech-            region of Brazil, which had been part of the
nique for weighting and reducing various indica-            probabilistic sample of the national survey, but
tors to a single index of cities in this study. Also        one city was excluded because of the data lacking
was used to confirm the theory with regard to               for the 12 years old, which is the target age of this
social determinants of health.                              study. The final sample was therefore comprised of
   Principal components extraction with Varimax             49 cities, providing total for 7119 individuals aged
(orthogonal) rotation through SPSS 14.0 was used            12 years old.

Bueno et al.

  A descriptive analysis was conducted to explore                 interquartile range of 1.9. The percentage preva-
association between the oral health outcome vari-                 lence rate of caries-free children presented mean of
ables and exposure variables.                                     30.7 (95% CI: 25.79–35.54); median of 31.8; standard
  Finally, Spearman’s correlation was applied to                  deviation of 17.0; and variation interquartile range
the three principal components of the factor                      of 26.3.
analysis and their synthetic MDG indices in                          The six included covariates demonstrated signif-
relation to the 49 cities and the respective oral                 icant association (P = 0.00) with oral health out-
health outcomes, namely the DMFT index and                        comes variables when bivariate analysis was
the prevalence of caries-free children at 12 years                performed. The principal components analysis
old.                                                              explained 82.16% of the total variance of the
                                                                  distribution of the 15 variables ⁄ covariates in the
                                                                  three principal components identified (Table 1).
                                                                  The rotated loadings matrix (Table 2) determined
Results                                                           how many and which of the 15 variables ⁄ covari-
The asymmetrical distribution for the 49 cities in                ables covariates were loaded in each principal
Southern Brazil in 2003 of the index CPO-D to the                 component.
12 years presented mean of 2.8 (95% CI: 2.37–3.20);                  Based on the principal components analysis, the
median of 2.3; standard deviation of 1.4; and                     components obtained were combined into a

Table 1. Total variance explained by the final rotated solution, for the 15 variables ⁄ covariates of 49 cities in the southern
region of Brazil, 2000
                                                                   Rotation sums of squared loadings
Component                                                          Total               % Variation               Cumulative %
Socioeconomic condition                                            4.328               28.85                     28.85
Human development and mother and child health                      4.175               27.84                     56.69
Socioenvironmental condition                                       3.822               25.47                     82.16
Extraction method: principal component analysis.

Table 2. Matrix of rotated components, loadings and component labels, for 49 cities of the southern region of Brazil, 2000
                                                          Principal components
                                                                              Human development
                                                          Socioeconomic       and mother                 Socioenvironmental
                                                          condition           and child health           condition
Population (city size)                                    0.862
Proportion of people having a computer                    0.818
Per capita income                                         0.817
Ratio of literate women and men                           0.696
Proportion of people having a telephone                   0.671
Mortality rate among children aged under 5 years                              )0.864
Proportion of teenage mothers (10–19 years)                                   )0.800
HDI-M 2000                                                                     0.769
Proportion of people below the poverty line                                   )0.736
HDI-M 1991                                                                     0.685
Functional illiteracy rate                                                    )0.628
Urbanization rate                                                                                        0.833
Proportion of households having rubbish                                                                  0.814
Length of time water supply has been                                                                     0.774
 fluoridated (years)
Proportion of households with mains                                                                      0.703
 water and a bathroom
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Rotation
converged in 4 iterations. Component Scoring.

Millennium development goals and oral health

synthetic MDG index (final score), and this made it          separately, of the ‘Socioeconomic condition’ and
possible to classify the cities according to an              ‘Socioenvironmental condition’ components, with
ordinal scale (Table 3), ranging from 1.14 (best             the DMFT index and prevalence of caries-free
performance) to )1.50 (worst performance) (23).              children. On the other hand, no association was
   Spearman’s correlation (Table 4) showed a                 observed between these outcomes and the compo-
statistically significant association of the synthetic       nent relating to ‘Human development and mother
MDG index of the performance of the cities and,              and child health’. A statistically significant

Table 3. Case summaries of oral health outcomes, principal components and synthetic MDG index (decreasing order of
performance profile) in 49 cities in Southern Brazil, 2000 ⁄ 2003
                                   Socioeconomic     Human development ⁄        Socioenvironmental    Synthetic
Cities   DMFT     % Caries-free    condition         mother and child health    condition             MDG Index
 1       1.06     53.48             3.76             )0.28                      )0.26                  1.14
 2       1.39     47.15             3.72             )0.94                       0.36                  1.10
 3       1.30     50.37             2.31              0.53                       0.24                  1.07
 4       1.30     52.02             1.40              0.70                       0.49                  0.88
 5       1.12     58.85             1.05              1.05                       0.35                  0.83
 6       2.20     33.99             0.34              1.46                       0.61                  0.80
 7       1.19     60.45             0.65              1.13                       0.18                  0.67
 8       1.82     41.52             0.33              0.16                       0.91                  0.45
 9       1.63     53.85             0.48             )0.09                       0.97                  0.44
10       2.35     34.01            )0.41              0.91                       0.83                  0.42
11       1.54     43.75            )0.20              0.28                       1.03                  0.35
12       1.41     45.45            )0.33              0.31                       1.11                  0.33
13       1.61     41.50            )0.35              0.17                       1.22                  0.31
14       1.82     40.10             0.41              0.46                       0.01                  0.30
15       3.33     24.08            )0.08              0.30                       0.50                  0.23
16       1.83     35.35            )0.84              0.35                       1.22                  0.20
17       1.63     42.70            )0.17             )0.22                       1.05                  0.19
18       0.80     62.02            )1.11              0.42                       1.38                  0.18
19       3.47     25.14            )0.25              0.50                       0.31                  0.18
20       1.34     48.10            )0.69             )0.17                       1.40                  0.14
21       5.81      8.51            )0.43              0.67                      )0.02                  0.07
22       2.55     20.78            )0.12              1.49                      )1.28                  0.07
23       3.00     20.00            )0.51              1.68                      )1.14                  0.04
24       2.85     23.60            )0.04              1.18                      )1.15                  0.03
25       2.11     39.81             0.14             )0.94                       0.92                  0.02
26       2.29     31.85            )0.35             )0.30                       0.75                  0.01
27       3.48     17.72            )0.48              1.46                      )1.05                  0.00
28       1.63     41.40            )0.27             )0.74                       1.09                 )0.01
29       2.98     24.66            )0.20             )0.62                       0.74                 )0.05
30       4.54      5.00            )0.35              0.19                       0.01                 )0.05
31       3.27     29.09            )1.37              0.14                       1.21                 )0.06
32       3.12     18.60            )0.59              0.53                      )0.25                 )0.10
33       4.70     13.04            )0.34              0.55                      )0.59                 )0.12
34       3.80     20.53            )0.04             )0.06                      )0.56                 )0.21
35       3.49     18.45             0.32             )0.66                      )0.33                 )0.22
36       2.22     34.87            )0.42              0.09                      )0.52                 )0.28
37       4.01      7.69            )0.51              0.43                      )0.88                 )0.30
38       1.36     52.66            )0.71             )1.29                       1.02                 )0.37
39       3.39     19.16             0.00             )1.53                       0.34                 )0.41
40       7.21      4.65            )0.45              0.42                      )1.50                 )0.48
41       4.38      4.76            )0.93              1.01                      )1.71                 )0.51
42       2.30     45.39            )0.74             )0.57                      )0.20                 )0.52
43       2.14     32.50            )0.41             )1.14                      )0.03                 )0.54
44       6.28      6.98             0.30             )0.80                      )1.68                 )0.69
45       2.43     27.50             0.37             )0.33                      )2.61                 )0.79
46       5.00      0.00            )0.46             )0.34                      )1.86                 )0.85
47       4.08     10.59            )0.29             )1.82                      )1.13                 )1.07
48       4.42     10.75            )0.87             )2.60                      )0.43                 )1.32
49       3.44     18.18            )0.30             )3.13                      )1.08                 )1.50

Bueno et al.

Table 4. Spearman’s correlation between cities MDG performance and oral health outcomes
                                                 Human development
                    Socioeconomic                and mother and          Socioenvironmental          Synthetic MDG
                    condition                    child health            condition                   Index
                    Coefficient       P          Coefficient   P         Coefficient      P          Coefficient      P
DMFT                )0.340*           0.017      )0.057        0.698     )0.644**         0.000      )0.699**         0.000
% Caries-free        0.342*           0.016       0.022        0.882      0.680**         0.000       0.692**         0.000
*Correlation is significant at the 0.05 level (2-tailed).
**Correlation is significant at the 0.01 level (2-tailed).

correlation was found of the DMFT and CF                        the DMFT index at 12 years old, as shown in
indices, respectively, with: the MDG index                      Fig. 2.
(R2 = 0.49 and 0.48; P = 0.00); the socioeconomic
status of the population (R2 = 0.12 and 0.12;
P = 0.02) and the socioenvironmental characteris-
tics (R2 = 0.41 and 0.46; P = 0.00). Even consider-
ing the exclusion of the years of water supply                  The limitations inherent to an ecological study,
fluoridation covariate, the factor related to socio-            whereby observations made at the aggregate level
environmental characteristic maintained the                     of analysis cannot be inferred in relation to
significant correlation with the oral health out-               individuals, as well as the risk of cross-classifica-
comes (R2 = 0.37 and 0.43; P = 0.00).                           tion and migration between population strata
   A strong correlation was observed between the                must be considered when interpreting the results
outcomes mentioned and the Component relating                   (18). Nevertheless, one of the likely limitations
to ‘socioenvironmental condition’ which ex-                     of studies with such approach, which is the
plained 41% of the variance of the DMFT index                   collinearity of the independent (contextual) vari-
and 46% of the variance in the prevalence of                    ables ⁄ covariates, has been addressed and mini-
12 years old children free from caries (Fig. 1). The            mized through the use of principal component
synthetic MDG index explained 48% of the                        analysis (23).
variance in the prevalence of 12 years old free                    The principal component analysis used in this
from caries and explained 49% of the variance in                study demonstrated a correlation between the

Fig. 1. Correlation between socioenvironmental condi-           Fig. 2. Correlation between the Final Score (municipal
tion and the prevalence of 12-year-old caries-free chil-        performance profile: synthetic MDG index) and DMFT
dren, in 49 cities in southern Brazil, 2003.                    index in 12-year olds in 49 cities in southern Brazil, 2003.

Millennium development goals and oral health

components relating to the cities’ MDG perfor-           environmental, curricular and social attributes,
mance, as well as covariates of interest, and the oral   among others, had an oral health profile superior
health outcomes. Both the overall performance of         to those attending ‘unsupportive’ schools, thus
the cities analysed, as measured by the synthetic        resulting in a higher percentage of caries-free
MDG index, and the components relating to                schoolchildren.
socioeconomic and socioenvironmental conditions             Peres et al. (40) performed an evaluation in the
demonstrated themselves to be correlated with the        cities of the state of Santa Catarina on the factors
oral health indicators analysed, namely the DMFT         that influence the addition of fluoride to the water
index and the prevalence of 12 years old caries-free     supply system, this being a measure indicated by
children.                                                the literature as being predominant in caries
   In cities in the state of Paraná and also in         prevention and the reduction of the negative
Brazil, better Municipal Human Development               impact of social inequalities on caries prevalence.
Indices (HDI-M) have been associated with a              The results indicate that municipalities with larger
longer period of fluoridation of the public water        populations, higher indices of child development
supply and lower average dental caries experi-           and lower rates of illiteracy are associated with a
ence (24, 25).                                           longer period of implementation of water
   A tendency of lower DMFT indices was observed         fluoridation.
in larger cities. The effectiveness of water fluorida-      General socioeconomic and socioenvironmental
tion on caries reduction is a widely accepted fact,      factors have played an expressive role in explain-
both by public health specialists and by the dental      ing oral health outcomes (24–43). These studies
community, in Brazil and internationally (26). The       corroborate the findings of the present study, in
reduction in DMFT rates has been attributed,             that the synthetic MDG index of 49 cities in
besides other important factors, to the scaling up       southern Brazil explained 49% of the DMFT index
of the fluoridation of the public water supply,          variance in 12 years old. This is a significant
especially in southern and south-eastern Brazil          epidemiological result, because oral health out-
(27).                                                    comes are predominantly explained by biological
   Baldani et al. (28) found that access of house-       factors and are rarely associated with social factors.
holds to treated and fluoridated water is an             In the case of dental caries, a disease of multifac-
important benefit, not only as a means of reducing       torial aetiology and usually explained by individ-
caries levels but also for alleviating the impact of     ual determinants, the evidences found through this
socioeconomic inequalities on caries prevalence.         study can contribute towards more in-depth
These authors also used education indicators such        analyses of the social determinants indicated by
as the illiteracy coefficient, the average number of     the MDG with regard to caries experience in
years of schooling and repeated school years and         populations.
the percentages of children aged 7–14 years not
attending school, among others to show the higher
prevalence of caries in cities in the state of Paraná
with the worst education indicators.
   Social class and degrees of hardship have been        MDG indicators have significant associations with
associated with dental caries, periodontal diseases,     oral health indicators. Both the overall perfor-
tooth loss and toothlessness in adults and children      mance of the cities analysed, measured by the
in the United Kingdom, Australia, New Zealand            use of the synthetic MDG index, and their
and Chile (16, 17, 29–34).                               principal factorial components in relation to
   In Brazil, there has been an increase in the          socioeconomic and socioenvironmental conditions
evidence that average caries experience follows the      demonstrate themselves to be correlated to oral
same international tendency in relation to social        health indicators. As such, intersectoral public
and health inequities faced by the population            policies based on population strategies that act on
(35–40).                                                 the social determinants of general and oral health
   Moysés et al. (38) in an evaluation of state         need to be integrated. However, longitudinal
schools in poor outlying districts of Curitiba           studies are needed to evaluate in greater depth
benefited by health promotion policies, observed         the performance and the impact of the public
that students attending better schools, referred to      healthy policies monitored in this study using the
as ‘supportive’ schools based on their physical,         MDG.

Bueno et al.

                                                                   gradient: implications for theoretical explanations.
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