4. Soares DS, Mello LM, Silva AS, Martinez EZ, Nunes AA. Femoral ...

SOCIOECONOMIC AND DEMOGRAPHIC DETERMINANTS IN THE PROVISION OF ASSISTANCE
TO ELDERLY PEOPLE WITH A FRACTURED FEMUR Ms Joselene Gomes Madeiras1
Dr. Eraldo Schunk da Silva2
Dr. Mirian Ueda Yamaguchi3
Dr. Sônia Maria Marques Gomes Bertolini3
Dr. Cassia Kely Favoretto Costa4
Marcelo Picinin Bernuci3
Helen Katharine Christofel5
Dr. Ely Mitie Massuda6
RESUMO A fratura de fêmur é um problema de saúde pública que afeta os idosos
apresentando alta morbimortalidade. O objetivo do presente estudo foi
analisar o perfil da assistência à fratura de fêmur em idosos, relacionando
às condições socioeconômicas e demográficas, no estado do Paraná entre os
anos 2008 a 2013. As relações foram obtidas por meio de análise fatorial e
construção dos índices: PAI - potencial de atenção ao idoso, cuja variável
foi representada pelo PIB municipal idoso; PAP - potencial de atenção à
população, representado pelo PIB per capta; e ET - eficiência do tratamento
representado pela taxa anual de fraturas e taxa anual de óbitos por
residência. Os municípios foram classificados de acordo com a faixa de
variação por índice. Em relação ao PAI, 10 municípios foram classificados
com baixo potencial de atenção ao idoso; 357 com moderado potencial; e 32
com baixo potencial. Em relação ao PAP, 12 municípios foram classificados
com alto potencial de atenção à população; 303 com moderado potencial; e 84
com baixo potencial. Em relação ao ET, 109 municípios apresentaram alta
eficiência do tratamento; 110 com moderada eficiência; e 180 com baixa
eficiência. Conclui-se que o desempenho da economia exerce significativa
influência na assistência à fratura de fêmur em idosos. Palavras-chave: fraturas femorais, envelhecimento, condições
socioeconômicas. SOCIOECONOMIC AND DEMOGRAPHIC DERTERMINANTS IN THE PROVISION OF ASSISTANCE
TO ELDERLY PEOPLE WITH A FRACTURED FEMUR ABSTRACT Femur fracture is a public health problem that affects the elderly with
high morbidity and mortality. The purpose of the present study was to
analyze the profile of the assistance given to the elderly who have femoral
fractures, relating to their socioeconomic and demographic conditions, in
the state of Paraná between the years 2008 to 2013. These relationships
were obtained through factor analysis and the development and analysis of
the following rates: PAE - the potential of primary health care to the
elderly, whose variable was represented by the contribution of the elderly
to the municipal GDP, PAP - the potential of the primary health care to the
population, represented by GDP per capita and TE - treatment efficiency
represented by the annual rate of fractures and annual rate of death per
residence. The municipalities were classified according to the rate
variation range. In relation to PAE, 10 municipalities were classified with
low potential of care for the elderly, 357 with moderate potential and 32
had low potential. In relation to PAE, 12 municipalities were classified
with low potential of primary care for the elderly, 303 with moderate
potential and 84 had low potential. In relation to TE, 109 municipalities
showed high treatment efficiency, 110 with moderate efficiency and 180 had
low efficiency. Our conclusion was that the performance of the economy
exerts significant influence on femoral fracture morbidity in the elderly. Keywords: femoral fractures, aging, socioeconomic conditions. INTRODUCTION Brazil has been undergoing important demographic changes and there has
been an acceleration in the aging of the population. In 2000, 5.61% of the
population in the country was made up of people who were 65 years old or
older and this number increased in 2010. The prediction is that it will
reach 11.3% in 20251. The southern region has the most amount of elderly
people (14.4%) in the country and in the state of Paraná this number
represents 11.21% of the population2. This new scenery has raised concerns
and as a result, it has been the focus of public policies due to the
related morbidities for this age group, which is proving costly for the
health system3.
Femoral fractures have immerged as one of the main health problems
associated with an aging population4-6. It is responsible for the high
rates of morbidity and mortality. It has a negative effect on the quality
of life of the elderly9-11. Although changes in the bone density due to
osteoporosis have been associated with incidents of fractures of the femur
for the older people, little is known about the profile of morbidity during
the different conditions.
Amongst the studies that have associated ethnic and demographic
factors to fractures, particularly for older people, only a few have
analyzed aspects connected to social and economic issues and even fewer
have evaluated the influence of income19,20. Evidence of the positive
effects of wealth on the offer of services and the availability of
infrastructure in health, reinforces the idea of the interference of
socioeconomic development in the profile of morbidities.
In this way, we understood that health care outcomes are determined by
different life cycles and constructed by one's social, economic and
environment conditions impacting on a person's quality of life particularly
when the individual reaches senescence24-27. Therefore, the purpose of this
study was to analyze the profile of morbidity for femoral fractures
affecting the elderly and its relationship with socioeconomic and
demographic conditions in the state of Paraná between the years 2008 to
2013. METHODS This was a quantitative study that was also retrospective and inter-
disciplinary. The population in the study was made up of data on older
people being 60 years old or older who were the victims of femoral
fractures resulting in a hospital admission between January 2008 and
December 2013 on the Brazilian National Health System (SUS) in the
municipalities of the state of Paraná. We obtained approval from the
ethics committee on research at the Centro Universitário de Maringá under
the opinion reference number 1.359.807.
The information was collected from the a public database through the
program TabNet (version 3.6 of TAB for Windows), available from the SUS
Information Technology Department - DATASUS28
(http://www2.datasus.gov.br/DATASUS/index.php), which refers to hospital
admissions (SIH) of elderly people on SUS. The following data was
collected: age of the elderly people, year of hospital admission,
classification of the femoral fracture in accordance with the code for the
International Classification of Disease (ICD 10)28, the number of deaths
per residence and the number of femoral fractures per area of residence. The data referring to the Human Development Index (HDI), the Municipal
Human Development Index, the Gross Domestic Product (GDP) and the GDP per
capita, were obtained from the Instituto Paranaense de Desenvolvimento
Econômico e Social - IPARDES29 (http://www.ipardes.gov.br/) and the
Instituto Brasileiro de Geografia e Estatística - IBGE30 -
(http://www.ibge.gov.br/home/) from 399 municipalities in the state of
Paraná. For this study, the GDP of the municipalities was divided by the
number of elderly people resident in each one of them in order to fully
understand the effect of the differences in the proportion of the elderly.
In this way, the level of wealth in the municipalities represented by their
GDP was obtained in such a way that so as to take into account the elderly
population.
Typology of the municipalities do state do Paraná For the construction of the typology of the homogenous groups in the
municipalities, the multivariate Factor Analysis technique was primarily
used (AF). The main purpose of this step was to obtain the factor scores.
AF identifies the relatively small factor number that can be used to
represent the relationships between many variables that are inter-related.
The mathematical model is similar to the multiple regression equation;
where every variable is expressed as a linear combination of non-observed
factors: X1 - µ1 = a11 F1 + a12 F2 + ... + a1m Fm + ?1
X2 - µ2 = a21 F1 + a22 F2 + ... + a2m Fm + ?2
X3 - µ3 = a31 F1 + a32 F2 + ... + a3m Fm + ?3
...
Xp - µp = ap1 F1 + ap2 F2 + ... + apm Fm + ?p
Where:
Aij = factor load;
F1, F2,..., Fm = common factors;
?1, ?1,..., ?p = mistakes or specific factors.
Although it is possible that all of the variables contribute to a
determined factor, only a sub-group from them will actually characterize
it. Thus the factor model assumes that the variables can be grouped by
their correlations to which they belong, being the same group that is
highly co-related to each other. Subsequently and based of the factor
scores, we calculated the three rates: the potential of primary health care
to elderly people (PAE), the potential of primary health care to the
population (PAP) and th