290
Internacional Journal of Cardiovascular Sciences. 2015;28(4):290-297
ORIGINAL MANUSCRIPT
Influence of Exercise on Anthropometric Indicators of Cardiovascular
Risk in Elderly Women
Gabriel Espinosa1, Flávia Porto2, Jonas Lírio Gurgel1
Universidade Federal Fluminense – Programa de Pós-graduação em Ciências Cardiovasculares (Doutorado) – Niterói, RJ – Brazil
Universidade do Estado do Rio de Janeiro – Instituto de Educação Física e Desportos – Rio de Janeiro, RJ – Brazil
1
2
Abstract
Background: Although there is evidence of the benefits of physical exercise on cardiovascular health (CV), only a few
studies evaluate the effectiveness of community exercise programs in reducing CV risk indicators.
Objective: To compare anthropometric indicators of CV risk among elderly women who do not exercise.
Methods: In this cross-sectional study, the sample consisted of two groups: EMIPOA composed of 305 women
(68.19±2.82 years; 69.31±13.88 kg, 1.54±0.07 m; body mass index (BMI) 29.30±5.54 kg/m2) coming from the Porto Alegre
Multidimensional Study on Elderly Individuals; and PEG, consisting of 50 elderly women (68.28±4.68 years;
66.08±9.48 kg, 1.56±0.06 m; and BMI 27.29±3.62 kg/m2) participating in an exercise program. There following items
were assessed: body mass (BM), BMI, abdominal circumference (AC), waist circumference (WC), abdomen/hip ratio
(AHR), waist/hip ratio (WHR), body shape index (BSI) and body fat. The groups were stratified (60-69 years and
70-79 years). Normality of data was tested (Shapiro-Wilk and Kolmogorov-Smirnov) and the groups were compared
(Student’s t test for independent samples or Mann-Whitney), considering p≤0.05 as significance level.
Results: The PEG (60-69 years) presented lower values than EMIPOA (60-69 years) for: BM, BMI, AC, WC, AHR, WHR
and BSI. Height, the sum of skinfold thickness and body fat did not differ. For the 70-79 years stratum, only height
difference was found (PEG>EMIPOA).
Conclusions: Participation in a physical exercise program influenced the levels of anthropometric indicators of CV risk
and this influence was attenuated in older individuals.
Keywords: Health of the elderly; Exercise; Anthropometry; Risk factors
Introduction
The Brazilian population follows an international trend
of increased aging rate driven by a decline in fertility and
mortality, in addition to increased life expectancy. In
Brazil alone, there are more than 15 million elderly
people1. Porto Alegre is the second Brazilian capital with
the highest proportion of elderly people, second only to
Rio de Janeiro2. This demographic transition brings
increased prevalence of non-transmissible chronic
diseases (NTCDs) and, consequently, an increase in
mortality from these diseases3.
In Brazil and in other countries, cardiovascular (CV)
diseases are the leading cause of morbidity and
mortality4. These include ischemic heart disease, acute
myocardial infarction, coronary artery disease and
systemic hypertension5. In Brazil, morbidity of CVD is
even greater in people with low income6.
Corresponding author: Gabriel Espinosa
Rua Prof. Marcus Waldemar de Frias Rei, s/n – São Domingos – 24210-201 – Niterói, RJ – Brazil
E-mail: [email protected]
DOI: 10.5935/2359-4802.20150042
Manuscript received on June 20, 2015; approved on September 1, 2015; revised on September 16, 2015.
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
The rapid increase in the prevalence of CVD in the end
of the last century caused an alarming socio-economic
scenario to be administered by governments and the
private sector, significantly increasing expenses to cover
treatment for these diseases7. Mitigation of this problem
depends on the development of global strategies for the
prevention of CVD and health promotion8. Evaluation
of cardiovascular (CV) risk is of great importance for the
early detection and timely treatment of CVD and also
9
to provide support for more effective planning of public
policies aimed at population health.
Traditional models for CV risk prediction consider the
main risk factors: age, sex, blood pressure, smoking,
history of diabetes mellitus and lipid profile9. However,
in primary care, this evaluation is not often feasible
because of the difficulty in determining blood markers,
whether because of delays in having the tests done or
lack of resources to have the tests done. The use of
anthropometric variables associated with other
indicators available, routinely evaluated by primary
care professionals10.
For elderly adults, it is recommended
generally to perform moderate physical
activity for at least 30 minutes daily, as
well as intense physical activities two to
three times per week 23. Community
programs of physical exercise are
important for maintaining the health
and quality of life of older people.
However, in most cases, these programs
only focus on socialization, not
considering any biological aspects
associated with the individual’s
functional capacity. Furthermore,
regular control of exercise intensity and
volume as well as individualization of
overload are typically neglected. Ideally,
global physical exercise programs
should focus on different motor qualities
in the same session of exercises24.
ABBREVIATIONS AND
ACRONYMS
•AC – abdominal
circumference
•AHR — abdomen/hip ratio
•BM — body mass
•BMI — body mass index
•BSI — body shape index
•CV – cardiovascular
•CVD — cardiovascular
disease
•EMIPOA – Porto Alegre
Multidimensional Study on
Elderly Individuals
•NTCD — non-transmissible
chronic diseases
•PEG — physical exercise
group
•WC — waist circumference
•WHR — waist/hip ratio
There is a lack of studies evaluating the
effectiveness of community exercise
programs in reducing CVD risk indicators. Deeper
The measurement of skin folds is commonly used to
estimate body fat percentage11. Body mass index (BMI)
is the most studied and affordable variable. Although
it is a general measure of obesity, BMI is considered
strong indicator of mortality12. Measures related to
abdominal fat, waist circumference (WC) and abdominal
circumference (AC), waist/hip ratios (WHR) and
abdomen/hip ratio (AHR) have presented stronger
associations with CVD than BMI, especially in
understanding of possible morphological changes,
resulting from a regular program of exercise can, above
all, serve as a basis for more effective training
structuring.
The objective of this study was to compare the levels of
anthropometric CV health indicators (BMI, body fat,
AHR, WHR and BSI) of older practitioners and nonpractitioners of physical exercises.
women 13-15 . More recently, a new mortality risk
indicator developed, the body shape index (BSI), which
considers waist circumference, BMI and height16. This
Methods
indicator was more accurate than the other ones in the
The sample in this study was composed of two groups
prediction of cardiovascular risk in older people
of elderly women aged ≥60, all living in Porto Alegre,
(55-79 years)17.
RS. The first group comprised the elderly women selected
for the Porto Alegre Multidimensional Study on Elderly
The main form of intervention in health promotion and
Women (EMIPOA), a population-based survey conducted
CVD prevention is based on changes in people’s
by the Institute of Geriatrics and Gerontology from
lifestyle. Increase in physical activity at leisure time is
Pontifícia Universidade Católica do Rio Grande do Sul
among the priorities in the strategic action plans on the
(IGG-PUCRS). The second group (PEG) comprised
global and nacionais levels to face NTCD. High levels
elderly women engaged in physical exercises in a
of physical fitness are associated with decreased
community exercise program developed as an extension
incidence of CVD
project by PUCRS.
18
19
20-22
.
291
292
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
The EMIPOA sample selection was organized in two
umbilical line) and hip circumference (at the level of
steps. Initially, 1 164 elderly individuals were randomly
the greatest prominence of the greatest trochanters)
selected and interviewed in their homes using a
were measured using anthropometric tape (Sanny®,
multidimensional investigation questionnaire. These
Standard, São Bernardo do Campo, Brazil) with 0.1 cm
elderly individuals were invited to participate in the
precision.
second stage, which included a set of assessments by
a multidisciplinary team. The samples were matched
for housing area. Only women living in the same
regions presented by the PEG elderly women were
included in this study. Of the 472 elderly men and
women who participated in the second stage and lived
BSI was calculated by waist circumference divided by
BMI raised to 2/3 times height raised to ½ [waist
circumference/(IMC2/3 x Height1/2)]16.
in the same regions, 305 women were included
Statistical treatment
(68.19±2.82 years; 69.31±13.88 kg; 1.54±0.07 m; BMI
For the statistical treatment of the data, the groups
29.30±5.54 kg/m2).
were initially stratified by age groups (60 to 69 and
The PEG group consisted of 50 women (68.28±4.68 years;
66.08±9.48 kg; 1.56±0.06 m; BMI 27.29±3.62 kg/m2). The
program offered exercise and volleyball classes for
50 minutes, twice a week. Only the elderly women who
have done exercise classes for at least three years were
only included.
This study has been approved by the Research Ethics
Commission of PUCRS under no. 1066/05-CEP. All
participants signed an Informed Consent Form.
70 to 79 years). Data normality was tested from the
Shapiro-Wilk test when the sample size ≤50, and the
Kolmogorov-Smirnov test when >50. Then, descriptive
statistics was used: mean and standard deviation or
median and interquartile range. To compare the
anthropometric indicators of CV risk among the
groups, Student’s t test was used for independent
samples when the data distribution was parametric
and Mann-Whitney in cases of non-parametric
distribution. In all statistical tests, the significance level
was α≤0.05.
Data collection took place at the Research and Physical
Activity Laboratory, PUCRS. All procedures were
conducted by trained researchers with experience in
physical evaluations.
Results
Table 1 shows the results of anthropometric indicators
Body mass was measured by digital scale (Plenna®,
of CV risk among EMIPOA and PEG groups. In the
Snow, Bom Retiro, Brazil) with a precision of 100 g.
60-69 years stratum, PEG presented significantly lower
Height was obtained with the help of a professional wall
values ​​than EMIPOA for: body mass, BMI, abdominal
stadiometer (Sanny®, Standard, São Bernardo do Campo,
Brazil) with precision of 0.1 cm. BMI was calculated
(kg/m2). To estimate fat percentage, the protocol for
women was used, based on the sum of three skinfolds
(triceps, suprailiac and thighs) to calculate body density
and the Siri25 equation to calculate fat percentage. The
skinfolds were measured using a scientific caliper with
precision of 0.1 mm (Sanny®, Standard, São Bernardo do
Campo, Brazil).
circumference, waist circumference, AHR, WHR and BSI.
There was no difference for the following variables:
height, sum of skinfolds and body fat percentage. As for
the stratum 70-79, a significant difference was only found
for height. PEG was, on average, 4 cm higher than
EMIPOA.
Except for fat percentage and sum of skinfolds, the other
variables showed a statistically significant difference, at
To calculate WHR and AWR, waist (midpoint between
least in one of the strata, the largest number of differences
the last rib and the iliac crest), abdomen (transversal
was found in the stratum 60-69 years.
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
Table 1
Anthropometric indicators of cardiovascular risk among elderly women practitioners (PEG) and non-practitioners of
exercise (EMIPOA)
Body mass (kg)
Height (m)
BMI (kg/m )
2
Σ Skinfolds (mm)
Body fat (%)
Abdominal circumference
(cm)
Waist circumference (cm)
AHR
WHR
BSI (m11/6/kg2/3)
EMIPOA
PEG
p
β
62.51±13.95
0.021*
0.999
19
67.25±10.23
0.782
0.06
69.31±13.88
50
66.08±9.48
--
--
184
1.55±0.06
31
1.55±0.06
0.684
0.05
70-79
121
1.53±0.07
19
1.57±0.06
0.012*
0.69
Total
305
1.54±0.07
50
1.56±0.06
--
--
60-69
184
29.6±5.56
31
27.01±3.69
0.013*
0.8
§
70-79
121
28.72±7.66
19
27.38±3.77
0.403
0.155
Total
305
29.3±5.54
50
27.29±3.62
--
--
60-69
184
93.45±25.23
31
84.49±23.19
0.066
0.474
70-79§
121
87.36±27.63
19
81.53±21.49
0.288
0.152
Total
305
91.03±27.63
50
83.37±22.38
--
--
60-69
184
40.0±9.51
31
36.68±8.95
0.071
0.453
70-79
121
38.37±10.6
19
36.06±8.3
0.366
0.163
Total
305
39.35±10.6
50
36.44±8.62
--
--
60-69
184
96.46±12.44
26
87.25±9.5
0.001*
0.989
70-79
121
97.01 ± 13.39
12
97.43 ± 7.37
0.916
0.052
Total
305
96.68 ± 13.39
38
90.47 ± 10.01
--
--
60-69
184
90.57 ± 12.4
31
83.14 ± 9.23
0.020*
0.936
70-79
121
89.84 ± 11.69
19
86.55 ± 8.75
0.243
0.249
Total
305
90.28 ± 11.69
50
84.44 ± 9.12
--
--
60-69
184
0.94 ± 0.08
26
0.91 ± 0.06
0.013*
0.826
70-79
121
0.96 ± 0.08
12
0.97 ± 0.08
0.552
0.103
Total
305
0.95 ± 0.08
38
0.92 ± 0.08
--
--
60-69§
184
0.89 ± 0.11
31
0.84 ± 0.09
0.009*
0.565
§
70-79
121
0.87 ± 0.12
19
0.86 ± 0.12
0.445
0.199
Total
305
0.89 ± 0.08
50
0.85 ± 0.06
--
--
60-69
184
0.077 ± 0.005
31
0.073 ± 0.003
0.034*
0.641
70-79
121
0.078 ± 0.005
19
0.075 ± 0.004
0.093
0.488
Total
305
0.077 ± 0.005
50
0.074 ± 0.004
--
--
Age group
n
Mean±SD
n
Mean±SD
60-69§
184
69.19±19.03
31
§
70-79
121
67.22±17.8
Total
305
60-69
EMIPOA — group deriving from the Porto Alegre Multidimensional Study on Elderly Women; PEG — group of elderly women from
a physical exercise program; BMI — body mass index; AHR — abdomen/hip ratio; WHR — waist/hip ratio; BSI — body shape index;
§
nonparametric variable; SD — standard deviation; β — statistical power; *significant difference (Student’s t test or Mann-Whitney).
293
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Discussion
In order to compare the levels of anthropometric CV
health indicators of elderly female practitioners and nonpractitioners of physical exercise, it was found that not
all variables analyzed showed the expected behavior.
PEG in the stratum 60-69 years presented lower body
mass values, consistent with the findings of other
studies26. Literature shows that elderly practitioners of
physical exercises should have body mass lower than
non-practitioners, or at least an attenuation of its increase
related to aging27.
As for height, no significant differences among the
groups was expected, because it is a genetically
influenced variable. However, PEG (70-79 years)
presented significantly higher values ​​than EMIPOA.
Although the actual influence of lifestyle in reducing
the height of elderly individuals is not yet known,
Sagiv et al.28 found that the regular practice of moderate
to intense resistance exercise over life is associated with
attenuation of loss of height resulting from aging. This
attenuation appears to be due to the maintenance of
bone density and intervertebral spaces28 or potentially
greater trunk flexibility in the elderly individuals who
do physical exercises, thus giving them a more
verticalized29 posture.
As for BMI, it was found that physical exercise may
apparently have contributed to a slight decrease of this
variable, but this is only significant for elderly women
aged 60-69 years. Koster et al.26 have reported an inverse
relationship between the level of physical fitness and BMI
in elderly women.
Aging produces changes in body composition, even when
there is no concomitant changes in body mass and/or
BMI30. Accumulation of body fat (% fat and sum of
skinfolds) related to aging is more associated with
lifestyle and level of physical activity than aging itself31,32.
Several authors argue that physically active people have
lower amounts of body fat26,30. However, the fact that no
significant differences have been found suggests a
potential inadequacy of the exercise program conducted.
It would be necessary that the program generated a
higher weekly calorie expenditure to achieve effective
impact on variables related to body fat.
The evaluation method may also have influenced the
results related to body fat. The skinfolds may not have
been sensitive enough to detect differences between
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
groups, which is related to body fat redistribution11. With
aging, there is a significant redistribution of subcutaneous
fat to ectopic deposits33.
Redistribution of body fat directly influences the values​​
of some CV health indicators, from AHR to WHR, as
they are related to fat accumulation in the central intraabdominal region11. Both for abdominal and waist
circumferences and for AHR and WHR, the PEG
presented lower values. As for these variables, the
literature lacks cross-sectional studies that have
evaluated the association between them and the level of
physical activity or regular exercising. However, some
studies have shown reduction in ​​waist circumference
values, WHR and intra-abdominal fat after physical
training30.
Reflecting the results for waist circumference and BMI,
BSI presented the same behavior. Significantly lower
values ​​for the PEG compared to EMIPOA. This is an
important finding, since this variable has been more
specific than the other anthropometric variables in CV
risk stratification in elderly women17.
The significant difference in cardiovascular risk indicators
found between the groups in the stratum of 60-69 years,
pointed to some possible hypotheses. The first is related
to potential reduction of trainability with aging. Older
individuals would have a lower trainability, i.e., it would
be more difficult to improve fitness or functionality for
the same relative stimulus of training. This hypothesis
seems consistent with the fact that there is a reduction in
the adaptive capacity of the tissues and systems to stimuli
with aging. Evidence is still lacking, and this issue is still
controversial in the literature. Few studies have
demonstrated a reduction in trainability34,35, while others
showed no significant differences between old and young
individuals in relation to trainability36.
In describing the general adaptation theory, Selye37 points
to the need for stimulus to be given in an optimal intensity
range for promoting adaptation, because, being too below
standard, stimulus would be weak and would not
promote adaptation. Being suboptimal, some stimulus
could, at the most, promote the maintenance of capacity,
but without any significant improvement in performance.
If stimulus is very strong, above this optimal range, it
could lead to injury or adverse effects. It is believed that
this optimal range should decrease with age and with
other limiting factors of performance, such as pathological
conditions38, in which there would be a relative increase
of this threshold to promote adaptation, and a reduction
of this maximum threshold to avoid injury or adverse
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
effects. In addition, elderly individuals would require a
longer time to undergo adaptation to physical exercise
compared to younger individuals, that is, the results
would take longer to be noticed36,39. The elderly would
require higher relative intensities30 and higher frequency
of training39 than younger individuals.
A second hypothesis is that added to this scenario,
physical education teachers usually tend to be too careful
with older people, who are usually more debilitated,
mainly due to fear of the risk of complications arising
from exercising loads. This behavior would reduce more
significantly the relative intensity of training, making it
even harder to obtain some positive physiological effect
arising from exercising. Based on these assumptions, it
is suggested, in this case, that older individuals have an
even stronger training control, considering the greater
difficulty of promoting positive adaptations on these
individuals.
These population-based studies often establish
comparisons between a sample and populations with
different biopsychosocial characteristics40. This may
generate bias in the interpretation of parameters for the
classification of the population. From this perspective,
this study brings a difference when comparing a group
(PEG) with data from a local population living in the
same region (EMIPOA).
It is important to consider that this study presents a
cross-sectional design rather than a quasi-experimental
design with a control group and an intervention group,
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
which limits the conclusions and potential inference of
the results obtained. The assumptions made to try to
explain the lack of differences in the stratum 70-79 years
between the groups still need more evidence. This fact
should be considered as a gap in the corpus of knowledge
of exercise prescription, but the hypotheses presented
serve as a starting point to new studies that seek to give
scientific support to these theories, which must provide
appropriate experimental designs and study the influence
of aging and senescence on trainability.
Conclusions
The findings suggest that a structured exercise program
can improve the CV health indicators of participants, but
the elderly of this study showed no fully satisfactory
results. A review of the program is needed so they can
achieve the desired results, especially with regard to the
effectiveness of physical exercises for individuals older
than 69. Greater care in controlling training intensity and
volume of the elderly is suggested, especially with
advancing age.
Potential Conflicts of Interest
This study has no relevant conflicts of interest.
Sources of Funding
This study had no external funding sources.
Academic Association
This study is not associated with any graduate programs.
References
1. Instituto Brasileiro de Geografia e Estatística. [Internet]. Atlas
do censo demográfico 2010. [acesso em 2015 ago. 5]. Disponível
em: <http://www.ibge.gov.br/home/estatistica/populacao/
censo2010/default_atlas.shtm>
2. Instituto Brasileiro de Geografia e Estatística. Estudos e
Pesquisas. Diretoria de Pesquisas. Informação Demográfica e
Socioeconômica nº 9. Perfil dos idosos responsáveis pelos
domicílios no Brasil 2000. Rio de Janeiro: IBGE; 2002.
3. Duncan BB, Chor D, Aquino EML, Bensenor IM, Mill JG,
Schmidt MI, et al. Doenças crônicas não transmissíveis no Brasil:
prioridade para enfrentamento e investigação. Rev Saude
Publica. 2012;46(supl.):126-34.
4. Schmidt MI, Duncan BB, Azevedo e Silva G, Menezes AM,
Monteiro CA, Barreto SM, et al. Chronic non-communicable
diseases in Brazil: burden and current challenges. Lancet.
2011;377(9781):1949-61.
5. World Health Organization. [Internet]. The top 10 causes of
death. 2012. Fact sheet nº 310. [cited 2015 Aug 5]. Available from:
<http://www.who.int/mediacentre/factsheets/fs310/en>
6. Schramm JMA, Oliveira AF, Leite IC, Valente JG, Gadelha AMJ,
Portela MC, et al. Transição epidemiológica e o estudo de carga
de doença no Brasil. Cienc Saúde Coletiva. 2004;9(4):897-908.
7. W orld Health Organization. Global status report on
noncommunicable diseases 2010. Geneva: WHO; 2011.
8. W orld Health Organization. Global status report on
noncommunicable diseases 2014. Geneva: WHO; 2014.
9. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB,
Gibbons R, et al; American College of Cardiology/American Heart
Association Task Force on Practice Guidelines. 2013 ACC/AHA
guideline on the assessment of cardiovascular risk: a report of the
American College of Cardiology/American Heart Association Task
Force on Practice Guidelines. Circulation. 2014;129(25 Suppl 2):S49-73.
Erratum in: Circulation. 2014;129(25 Suppl 2):S74-5.
295
296
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
10. D’Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M,
Massaro JM, et al. General cardiovascular risk profile for use in
primary care: the Framingham Heart Study. Circulation.
2008;117(6):743-53.
11. Cornier MA, Després JP, Davis N, Grossniklaus DA, Klein S,
Lamarche B, et al; American Heart Association Obesity
Committee of the Council on Nutrition; Physical Activity and
Metabolism; Council on Arteriosclerosis; Thrombosis and
Vascular Biology; Council on Cardiovascular Disease in the
Young; Council on Cardiovascular Radiology and Intervention;
Council on Cardiovascular Nursing, Council on Epidemiology
and Prevention; Council on the Kidney in Cardiovascular
Disease, and Stroke Council. Assessing adiposity: a scientific
statement from the American Heart Association. Circulation.
2011;124(18):1996-2019.
12. Prospective Studies Collaboration, Whitlock G, Lewington S,
Sherliker P, Clarke R, Emberson J, Halsey J, et al. Body-mass
index and cause-specific mortality in 900 000 adults:
collaborative analyses of 57 prospective studies. Lancet.
2009;373(9669):1083-96.
13. Li C, Engström G, Hedblad B, Calling S, Berglund G, Janzon L.
Sex differences in the relationships between BMI, WHR and
incidence of cardiovascular disease: a population-based cohort
study. Int J Obes (Lond). 2006;30(12):1775-81.
14. Freiberg MS, Pencina MJ, D’Agostino RB, Lanier K, Wilson PW,
Vasan RS. BMI vs. waist circumference for identifying vascular
risk. Obesity (Silver Spring). 2008;16(2):463-9.
15. G oh LG, Dhaliwal SS, Welborn TA, Lee AH, Della PR.
Anthropometric measurements of general and central obesity
and the prediction of cardiovascular disease risk in women: a
cross-sectional study. BMJ Open. 2014;4(2):e004138.
16. Krakauer NY, Krakauer JC. A new body shape index predicts
mortality hazard independently of body mass index. PLoS One.
2012;7(7):e39504.
17. Dhana K, Ikram MA, Hofman A, Franco OH, Kavousi M.
Anthropometric measures in cardiovascular disease prediction:
comparison of laboratory-based versus non-laboratory-based
model. Heart. 2015;101(5):377-83.
18. W orld Health Organization. Global action plan for the
prevention and control of noncommunicable diseases 2013-2020.
Geneva: WHO; 2013.
19. M inistério da Saúde. Secretaria de Vigilância em Saúde.
Departamento de Análise de Situação de Saúde. Plano de ações
estratégicas para o enfrentamento das doenças crônicas não
transmissíveis (DCNT) no Brasil. 2011-2022. Brasília: Ministério
da Saúde; 2011. Série B. Textos Básicos de Saúde.
20. Blair SN, Kampert JB, Kohl HW 3rd, Barlow CE, Macera CA,
Paffenbarger RS Jr, et al. Influences of cardiorespiratory fitness
and other precursors on cardiovascular disease and all-cause
mortality in men and women. JAMA. 1996;276(3):205-10.
21. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, et al.
Cardiorespiratory fitness as a quantitative predictor of all-cause
mortality and cardiovascular events in healthy men and women:
a meta-analysis. JAMA. 2009;301(19):2024-35.
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
22. M yers J, Prakash M, Froelicher V, Do D, Partington S,
Atwood JE. Exercise capacity and mortality among men referred
for exercise testing. N Engl J Med. 2002;346(11):793-801.
23. Nelson ME, Rejeski WJ, Blair SN, Duncan PW, Judge JO,
King AC, et al. Physical activity and public health in older
adults: recommendation from the American College of Sports
Medicine and the American Heart Association. Med Sci Sports
Exerc. 2007;39(8):1435-45.
24. American College of Sports Medicine; Chodzko-Zajko WJ,
Proctor DN, Fiatarone Singh MA, Minson CT, Nigg CR,
Salem GJ, et al. American College of Sports Medicine position
stand. Exercise and physical activity for older adults. Med Sci
Sports Exerc. 2009;41(7):1510-30.
25. Jackson AS, Pollock ML, Ward A. Generalized equations for
predicting body density of women. Med Sci Sports Exerc.
1980;12(3):175-81.
26. K oster A, Visser M, Simonsick EM, Yu B, Allison DB,
Newman AB, et al; Health, Aging and Body Composition Study.
Association between fitness and changes in body composition
and muscle strength. J Am Geriatr Soc. 2010;58(2):219-26.
27. Stewart KJ, Bacher AC, Turner K, Lim JG, Hees PS, Shapiro EP,
et al. Exercise and risk factors associated with metabolic
syndrome in older adults. Am J Prev Med. 2005;28(1):9-18.
28. Sagiv M, Vogelaere PP, Soudry M, Ehrsam R. Role of physical
activity training in attenuation of height loss through aging.
Gerontology. 2000;46(5):266-70.
29. Hinman MR. Comparison of thoracic kyphosis and postural
stiffness in younger and older women. Spine J. 2004;4(4):413-7.
30. Kay SJ, Fiatarone Singh MA. The influence of physical activity
on abdominal fat: a systematic review of the literature. Obes
Rev. 2006;7(2):183-200.
31. St-Onge MP, Gallagher D. Body composition changes with
aging: the cause or the result of alterations in metabolic rate
and macronutrient oxidation? Nutrition. 2010;26(2):152-5.
32. Aoyagi Y, Shephard RJ. Habitual physical activity and health
in the elderly: the Nakanojo Study. Geriatr Gerontol Int.
2010;10(Suppl 1):S236-43.
33. Kuk JL, Saunders TJ, Davidson LE, Ross R. Age-related changes
in total and regional fat distribution. Ageing Res Rev.
2009;8(4):339-48.
34. Gilbert MJ, Zerulla TC, Tierney KB. Zebrafish (Danio rerio) as
a model for the study of aging and exercise: physical ability and
trainability decrease with age. Exp Gerontol. 2014;50:106-13.
35. Kumar V, Selby A, Rankin D, Patel R, Atherton P, Hildebrandt W,
et al. Age-related differences in the dose-response relationship
of muscle protein synthesis to resistance exercise in young and
old men. J Physiol. 2009;587(Pt 1):211-7.
36. Okazaki K, Iwasaki K, Prasad A, Palmer MD, Martini ER,
Fu Q, et al. Dose-response relationship of endurance training
for autonomic circulatory control in healthy seniors. J Appl
Physiol (1985). 2005;99(3):1041-9.
37. Selye H. Stress and the general adaptation syndrome. Br Med
J. 1950;1(4667):1383-92.
38. U emura K, Shimada H, Makizako H, Doi T, Yoshida D,
Tsutsumimoto K, et al. Cognitive function affects trainability
for physical performance in exercise intervention among older
adults with mild cognitive impairment. Clin Interv Aging.
2013;8:97-102.
Int J Cardiovasc Sci. 2015;28(4):290-297
Original Manuscript
39. Brown RE, Riddell MC, Macpherson AK, Canning KL, Kuk JL.
The association between frequency of physical activity and
mortality risk across the adult age span. J Aging Health.
2013;25(5):803-14.
Espinosa et al.
Physical Exercise and Cardiovascular Risk in Elderly Women
40. Gurgel JL. Avaliação do perfil antropométrico dos idosos de
Porto Alegre-RS: a influência da metodologia na determinação
da composição corporal. [Tese de doutorado]. Porto Alegre:
Pontifícia Universidade Católica do Rio Grande do Sul; 2008.
297