Abstract
Objective
Few data are available on population level regarding domain-specific correlates of physical activity (PA) in Latin America. The aim of this study was to examine the relationships among PA patterns and their main sociodemographic determinants and cardiovascular risk factors in the Southern Cone of Latin America.
Methods
CESCAS I is a population-based prospective cohort study with a 4-stage stratified sampling of a general population of 7,524 adults aged 35–74 years from four mid-sized cities in Argentina, Chile and Uruguay. PA was assessed using the transcultural adaptation of the International Physical Activity Questionnaire long form (IPAQ). The questionnaire asked about frequency (days/week) and duration (minutes/day) of moderate and vigorous intensity activities in three different domains: work, leisure time and active transportation (walking and bicycling). PA levels ≥ 600 metabolic equivalent tasks (MET) minutes/week was considered sufficiently active (SA). Odds ratios for associations of SA status with sociodemographic determinants and cardiovascular risk factors were obtained using multivariable-adjusted logistic regression models.
Results
Almost sixty five percent (64.8%) of the participants reported ≥ 600 MET minutes/week. The lowest prevalence of sufficiently active individuals was seen in Temuco, Chile (58.0 %), among women (58.7%), older individuals (55.4%), those with higher educational level (61.6%) and homemakers (53.4%). Approximately 22.8% of the population reported no PA. In multivariable analysis, PA levels were lower among women, individuals who were older, obese, university educated, with clerical work, retired/unemployed or homemakers, and those with physical limitations.
Conclusions
Future interventions to increase PA levels in the Southern Cone of Latin America must take into account disparities by gender and socioeconomic status. The promotion of PA during leisure time in women –unemployed and homemakers– and of active transportation for those performing office or clerical work should be a priority in this population.
Keywords: Exercise, Motor Activity, Developing Countries, Cross-Sectional Studies, Physical Activity, Prevalence
INTRODUCTION
The incidence of cardiovascular diseases (CVD) is increasing throughout the developing world and causes almost 16.7 million deaths each year, 80% of which occur in low and middle-income countries.1 There is substantial evidence from epidemiological studies that physical activity (PA) is associated with a lower risk of morbidity and mortality from CVD.2 The most active men and women have a 30% to 35% lower risk of CVD compared with the least active men and women.3 These benefits may be due to improved lipid profiles, blood pressure, weight control, endothelial function and insulin sensitivity.4,5 Current PA guidelines recommend a minimum of 150 minutes of moderate to vigorous intensity activities or 75 minutes of vigorous intensity activities PA per week, or some combination with equivalent energy expenditure to achieve such health benefits.6 Despite these recommendations, worldwide physical inactivity (energy expenditure < 600 MET-min/week6) contributes 6% to the burden of coronary heart disease, 7% to type 2 diabetes, 10% to breast cancer, and 10% to colon cancer. Every year more than 533,000 deaths could potentially be avoided by decreasing physical inactivity by 10%. The total elimination of physical inactivity would increase the global population life expectancy by 0.68 years.7
The prevalence of physical inactivity in Latin America was the highest reported worldwide8 and ranked fifth as a risk factor for mortality in the Southern Cone of Latin America (SCLA).9 It is known that sociodemographic characteristics such as gender, age, level of income and education vary across different PA domains (occupation, household, active transportation and leisure time).10
Few data on PA by domain is available from the Southern Cone of Latin America. Most reports are from Brazil11,12 and Colombia13,14 Data regarding domain-specific correlates of PA is essential for tailoring health promotion strategies.
The CESCAS I study is a population-based cohort study designed to examine CVD risk factor prevalence and associations with the incidence of CVD events in the SCLA. Using baseline data from this study, we examined the relationships between sociodemographic determinants, prevalence of cardiovascular risk factors and PA patterns by domain in a cross sectional sample of the adult population from four mid-sized cities in Argentina, Chile and Uruguay.
METHODS
Study design and sampling
CESCAS I is a population-based prospective cohort study initiated in February 2011. Baseline data on risk factors and prevalence of CVD were collected between 2011 and 2013. A detailed description of the study population and design has been presented elsewhere.15 Briefly, the CESCAS I study used a 4-stage multistage random sample of a general population of 7,524 adults aged 35–74 years from four mid-sized cities in Argentina (Bariloche and Marcos Paz), Chile (Temuco) and Uruguay (Canelones-Barros Blancos). In the first stage, census radii were randomly selected from each of the four locations, stratified by socio-economic level. In the second stage, a number of blocks proportional to the radius size were randomly selected. In the third stage, households within each block were selected by systematic random sampling. All members between 35–74 years in the selected households were listed to create the study sampling frame. In the final stage of sampling, one listed member per household was randomly selected to be included in the study. The overall response rate was 73.4% and the response rates were similar in men and women and across different locations. The present analysis was restricted to the 7,524 adults who responded to the PA questionnaire in the first phase. All participants provided an informed consent form and the study was approved by independent Institutional review boards in Argentina, Chile, Uruguay and the US as well as by the National Heart, Lung and Blood Institute of the National Institutes of Health.
Data collection
Baseline data was collected in participant´s household by trained interviewers regarding exposure to risk factors and prevalence of CVD. Data was collected using cross-culturally adapted questionnaires from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).16 Once the survey was completed, each participant was scheduled for a clinical exam to obtain physical measurements (blood pressure, weight, height and waist circumference), electrocardiogram and overnight fasting blood samples.
Physical activity assessment
PA was assessed using the transcultural adaptation of the International Physical Activity Questionnaire long form (IPAQ) used in the HCHS/SOL study.17 IPAQ had an acceptable reliability (Spearman correlation coefficients around 0.8), however the validity was moderate at best (correlation coefficients around 0.3) but comparable to most other self-report validation studies. 18
The questionnaire asked about frequency (days/week) and duration (minutes/day) of moderate and vigorous intensity activities in the last 7 days in three different domains: work, leisure time and active transportation (walking and bicycling). In addition, one question assessed the total time spent in sedentary activities (for example, watching television and playing video/board games).
We estimated energy expended on the assessed PA in metabolic equivalents (MET). One MET is defined as the energy it takes to sit quietly, which is about one calorie per every kilogram (2.2 pounds) of body weight per hour for an average adult (e.g. 1 MET = 1 kcal/kg/hour). The corresponding METs for the three physical activity intensities are the following: light intensity activities <3.0 METs, moderate intensity activities 3.0–6.0 METs and vigorous intensity activities >6 METs. The values used in this study were 8 METs for vigorous intensity activities, 4 METs for moderate intensity activities and 3.3 METs for walking or biking following the IPAQ´s guidelines for data processing and analysis.19 We expressed the total PA score per week as total MET-minutes/week calculated as the sum of energy expended in walking or biking, and moderate to vigorous intensity activities. Only activities performed for 10 or more minutes were included in the calculation of the PA scores. If a subject reported participating in any activity for more than 180 minutes, we truncated this at 180 minutes.19 We defined sufficiently active as 600 MET-minutes/week or more, according to the current World Health Organization (WHO) guidelines for PA.6
Covariate measurement
The present study analyzed nine independent variables: four sociodemographic variables (age, sex, level of educational attainment, and occupation), four CVD risk factors (body weight, hypertension, diabetes, and current smoking status) and self-reported physical limitation (asking to participants about their ability to climb stairs or walk more than an hour). Educational level was classified as primary school or lower, middle or high school, university. Occupation was classified as manual labor, office or clerical work, retired, unemployed and homemaker. Hypertension was defined as a mean systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥ 90 mm Hg, and/or self-report of current use of antihypertensive medications.20 Body mass index (BMI) was calculated as body weight divided by the square of height (kg/m2), and participants were categorized into normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2) and obese (≥ 30.0 kg/m2) groups according to the WHO guidelines.21. Hypercholesterolemia was defined as total cholesterol ≥240 mg/dL and/or use of lipid-lowering medication.22 Diabetes was defined as fasting glucose ≥126 mg/dl or self-reported history of diabetes.23 Current smoking was defined as smoking at least one cigarette per week at the time of the survey.24 Central obesity was defined as waist circumference ≥102 for men and ≥88 cm for women.22
Statistical analysis
This study was designed to provide precise estimates of the prevalence of PA by gender, age groups (35–44 years, 45–54 years, 55–64 years, and 65–74 years), and location. Prevalence estimates were weighted on the basis of the age and gender distribution of the population according to 2010 census data. Age standardized estimates of prevalence were calculated by the direct method, based on the World Standard Population as recommended by the WHO.25 Gender-stratified analyses were performed to explore behavioral differences between men and women. To describe the general characteristics of the study population we used the absolute and relative frequencies for categorical variables. To describe energy expenditure PA scores we used median, 25th, and 75th percentiles because the data were positively skewed. PA scores were also dichotomized as “sufficiently active” or “inactive” as previously described based on WHO guidelines. Estimates of prevalence were reported as proportions with 95% confidence intervals (CI). The prevalence of PA by domain was calculated as the percentage of the total population who spent ≥ 600 MET-minutes/week in that domain.
Odds ratios (OR) and 95% CI for the association between PA status and independent variables of interest were obtained using multivariable-adjusted logistic regression models. The inclusion of independent variables in the regression model was conducted in the following order: 1- demographic variables (age and sex); 2- socioeconomic factors (education level and occupation); 3- medical and health conditions (body weight, hypertension, diabetes and smoking status) and finally we included physical limitation for performing moderate intensity activities. Independent variables with p-value less than 0.05 from two-tailed tests were considered significantly associated with the outcome of interest. All analyses were conducted in STATA 10.0 (Stata Corp, College Station, TX, USA) and took into account the complex sampling strategy using survey commands.
RESULTS
Of the 10,254 individuals randomly selected from the sampling frame, 550 were never found at their homes and 1,394 refused to participate. Of the 8,310 who completed home surveys, 855 did not attend the clinical examination. Thus, the final sample for this analysis includes 7,524 participants (3,165 men and 4,359 women). The overall response rate was 73.4%, and the response rates were similar in men and women and across locations. The general characteristics of the population are shown in Table 1. We found a high prevalence of overweight and obesity affecting 87% of the overall population (41.3% overweight and 35.7% obese). Thirty-four percent of the population had only primary school or less education; 43.1% were not currently working and 22.9% described their work activities as highly sedentary. Only 12.9% of women reported performing vigorous intensity activity and the most frequent leisure activities were brisk walking and going to the gym. Conversely, 39.9% of men reported performing vigorous intensity activity and the most frequent activities was team sports (soccer and basketball) followed by brisk walking. Men more often reported ≥6 hours seated per day as compared to women (15.1% vs. 10.5% respectively) but less often reported physical limitations in performing moderate intensity PA (6.7% vs. 13.7%, respectively).
Table 1.
Characteristics of the study population
| Characteristics | Overall (n=7,524) |
Men (n=3,165) |
Women (n=4,359) |
|---|---|---|---|
| Age Group (Years), n (%) | |||
| 35–44 | 1,716 (22.8) | 706 (22.3) | 1,010 (23.2) |
| 45–54 | 2,072 (27.5) | 832 (26.3) | 1,240 (28.5) |
| 55–64 | 2,114 (28.1) | 935 (29.5) | 1,179 (27.1) |
| 65–74 | 1,622 (21.6) | 692 (21.9) | 930 (21.3) |
| Educational level, % (95% CI) | |||
| Primary school or lower | 34.1 (32.8, 35.3) | 32.9(31.0, 34.7) | 35.1(33.5, 36.8) |
| Middle or high school | 42.1 (40.7, 43.5) | 42.7(40.6, 44.7) | 41.7(39.8, 43.5) |
| University | 23.8 (22.5, 25.1) | 24.5(22.5, 26.4) | 23.2(21.5, 24.9) |
| Occupation status, % (95% CI) | |||
| Manual labor | 34.0 (32.6, 35.4) | 43.7(41.5, 45.8) | 25.6(24.0, 27.3) |
| Office or clerical work | 22.9 (21.6, 24.1) | 28.4(26.4, 30.5) | 18.0(16.4, 19.7) |
| Retired | 20.2 (19.3, 21.2) | 19.1(17.7, 20.5) | 21.2(19.9, 22.6) |
| Unemployed | 8.6 (7.7, 9.4) | 8.4(7.1, 9.6) | 8.7(7.5, 10.0) |
| Homemaker | 14.3 (13.3, 15.3) | 0.5(0.2, 0.7) | 26.3(24.6, 28.1) |
| Risk Factorsa, % (95% CI) | |||
| Overweight | 41.3 (39.9, 42.7) | 47.7 (45.6, 49.8) | 35.5 (33.7, 37.3) |
| Obesity | 35.7 (34.4, 37.0) | 31.9 (30.0, 33.8) | 39.1 (37.3, 40.9) |
| Hypertension | 40.8 (39.4, 42.1) | 44.7 (42.6, 46.7) | 37.3 (35.5, 39.0) |
| Hypercholesterolemia | 24.4 (23.3, 25.6) | 23.1 (21.4, 24.9) | 25.6 (24.0, 27.1) |
| Diabetes | 12.4 (11.5, 13.3) | 10.6 ( 9.4, 11.7) | 14.0 (12.8, 15.3) |
| Current smoker | 29.7 (28.4, 31.0) | 33.3 (31.3, 35.3) | 26.5 (24.8, 28.3) |
| Intensity Level of PAa | |||
| Vigorous, % (95% CI) | 25.6 (24.4, 26.9) | 39.9 (37.9, 42.0) | 12.9 (11.5, 14.2) |
| Active days/week | 4.2 (1.9, 5.7) | 4.3 (1.9, 5.7) | 3.4 (2, 5.6) |
| Daily duration (min/day) | 160 (59, 173) | 163 (90, 174) | 93 (50, 158) |
| Moderate, % (95% CI) | 39.7 (38.3, 41.0) | 42.2 (40.2, 44.3) | 37.4 (35.6, 39.2) |
| Active days/week | 4.9 (2.8, 6.3) | 5.1 (3.4, 6.4) | 4.7 (2.5, 6.3) |
| Daily duration (min/day) | 171 (59, 177) | 156 (81, 172) | 170 (56, 176) |
| Walking or biking, % (95% CI) | 61.1 (59.7, 62.5) | 58.7 (56.6, 60.7) | 63.3 (61.5, 65.1) |
| Active days/weeka | 5.3 (3.8, 6.4) | 5.7 (4.2, 6.5) | 5 (3.3, 6.4) |
| Daily duration (min/day) | 59 (27, 108) | 55 (28, 101) | 59 (27, 106) |
| Type of exerciseb, % (95% CI) | |||
| Brisk walking | 12 (11.1, 12.9) | 12.5 (11.2, 13.9) | 11.5 (10.4, 12.7) |
| Team sports: soccer, basketball | 6.5 (5.7, 7.3) | 13.1 (11.6, 14.7) | 0.6 (0.3, 1) |
| Gym-Moderate intensity activities | 4.6 (4.1, 5.2) | 2.8 (2.1, 3.5) | 6.3 (5.4, 7.2) |
| Jogging | 3.9 (3.3, 4.4) | 6 (4.9, 7) | 2 (1.4, 2.6) |
| Biking <20 km/hour | 3.7 (3.1, 4.2) | 4.2 (3.3, 5.1) | 3.2 (2.5, 3.9) |
| Physical limitations, % (95% CI) | |||
| To moderate intensity activities | 10.4 ( 9.6, 11.2) | 6.7 ( 5.8, 7.6) | 13.7 (12.4, 14.9) |
Weighted Prevalence of overweight: body-mass index ≥25 and <30 kg/m2; Obesity: body-mass index ≥30 kg/m2; Hypertension: systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or use of antihypertensive medication; Hypercholesterolemia: total cholesterol ≥240 mg/dL and/or use of lipid-lowering medication; Diabetes: fasting glucose ≥126 mg/dL or self- reported history of diabetes.
Features of each physical activity intensity level, expressed in weighted medians and 25th, 75th percentiles calculated in adults who reported activities of that intensity. CI: confidence interval. Km: kilometers.
In leisure time.
Almost two-thirds of the population (64.8%) reported meeting the recommended level of PA and were classified as sufficiently active according to WHO guidelines6 (Table 2). The lowest prevalence of sufficiently active individuals was seen in Temuco, Chile (58.0%), in women (58.7%). Sufficient activity was less often seen among older individuals (55.4%), those with a higher educational level (61.6%), and homemakers (53.4%). Overall, 22.8% (95% CI: 21.6, 24.0%) reported not performing any PA (19.5%; 95% CI: 17.8, 21.2% among men and 25.7%; 95% CI: 24.0, 27.4% among women).
Table 2.
Prevalence of sufficiently active statusa by sex
| Population group | Overall % (95% CI) |
Men % (95% CI) |
Women % (95% CI) |
|---|---|---|---|
| Overall | 64.8 (63.5, 66.2) | 71.7 (69.8, 73.6) | 58.7 (56.9, 60.6) |
| Age (years) | |||
| 35–44 | 67.7 (65.1, 70.4) | 74.1 (70.4, 77.7) | 61.8 (58.0, 65.5) |
| 45–54 | 65.5 (63.2, 67.9) | 73.4 (70.1, 76.7) | 58.5 (55.2, 61.8) |
| 55–64 | 64.4 (62.1, 66.7) | 69.0 (65.7, 72.2) | 60.3 (57.0, 63.6) |
| 65–74 | 55.4 (52.7, 58.1) | 64.2 (60.3, 68.0) | 48.8 (45.1, 52.4) |
| Location | |||
| Marcos Paz, Argentina | 75.7 (73.7, 77.6) | 79.5 (76.5, 82.5) | 71.9 (69.3, 74.5) |
| Bariloche, Argentina | 72.2 (70.2, 74.3) | 77.0 (74.1, 80.0) | 67.8 (65.1, 70.6) |
| Temuco, Chile | 58.0 (55.6, 60.4) | 66.9 (63.5, 70.2) | 50.5 (47.2, 53.8) |
| Barros Blancos, Uruguay | 65.7 (63.2, 68.1) | 71.2 (67.5, 74.8) | 60.5 (57.3, 63.8) |
| Educational level | |||
| Primary school or lower | 66.7 (64.8, 68.6) | 74.0 (71.3, 76.8) | 60.6 (57.9, 63.2) |
| Middle or high school | 65.1 (63.0, 67.3) | 71.6 (68.6, 74.5) | 59.2 (56.2, 62.2) |
| University | 61.6 (58.4, 64.7) | 68.6 (64.3, 73.0) | 54.9 (50.5, 59.3) |
| Occupation status | |||
| Manual labor | 77.9 (75.8, 80.1) | 80.2 (77.4, 83.0) | 74.6 (71.2, 78.1) |
| Office or clerical work | 62.1 (58.9, 65.4) | 67.5 (63.4, 71.6) | 54.8 (49.7, 59.9) |
| Retired | 56.8 (54.4, 59.3) | 63.7 (60.2, 67.3) | 51.5 (48.2, 54.8) |
| Unemployed | 56.2 (50.8, 61.5) | 59.5 (52.0, 66.9) | 53.4 (46.0, 60.9) |
| Homemaker | 53.4 (49.6, 57.1) | 80.3 (61.4, 99.2) | 53.0 (49.1, 56.8) |
Inactive defined as < 600 MET-minutes/week from work, leisure-time activities, and active transport; CI: confidence interval
Men had significantly higher PA scores than women among currently working individuals (median 2,763 vs. 989 MET-minutes/week, for men and women respectively), as well as among the retired, unemployed and homemakers (median 1,188 vs. 692 MET-minutes/week, for men and women respectively). (Supplementary table)
The prevalence of sufficiently active status by domain is shown in table 3. Overall, subjects tended to meet the recommended level of PA more frequently through transportation and occupation; a lower proportion met PA levels in their leisure time (38.8%, 34.1%, and 19%, for each domain respectively). Subjects who met the sufficiently active status at work were more likely to be younger, male, less educated and performing manual labor. Those who met PA levels through transportation were older and less educated. Those who met the recommended level of PA in their leisure time were younger, male, more educated and currently working in manual, office, or clerical work. In the multivariable analysis, PA levels decreased with older age (OR 0.77; 95% CI: 0.61, 0.98), and was lower among women (OR 0.62; 95% CI: 0.54, 0.72), the obese (OR 0.68; 95% CI: 0.58, 0.81), those with university education (OR 0.78; 95% CI: 0.65, 0.94), engaged in office or clerical work (OR 0.60; 95% CI: 0.49, 0.73), retired/unemployed or homemakers (OR 0.45; 95% CI: 0.36, 0.56), subjects with physical limitations (OR 0.67; 95% CI: 0.56, 0.81) and those who spent ≥6 hours/day seated (OR 0.40; 95% CI: 0.33, 0.49) (Table 4).
Table 3.
Prevalence of sufficiently active status by domaina
| Population group | Occupation % (95% CI) |
Transportation % (95% CI) |
Leisure time % (95% CI) |
|---|---|---|---|
| Overall | 34.1 (32.8, 35.4) | 38.8 (37.5, 40.2) | 19.0 (17.9, 20.1) |
| Age (years) | |||
| 35–44 | 38.6 (35.9, 41.3) | 38.1 (35.5, 40.8) | 22.6 (20.3, 24.9) |
| 45–54 | 37.9 (35.6, 40.3) | 37.3 (35.0, 39.7) | 18.5 (16.6, 20.5) |
| 55–64 | 31.5 (29.3, 33.8) | 40.4 (38.0, 42.8) | 15.4 (13.6, 17.1) |
| 65–74 | 16.4 (14.4, 18.4) | 42.0 (39.3, 44.6) | 15.3 (13.4, 17.2) |
| Sex | |||
| Men | 43.3 (41.2, 45.4) | 39.5 (37.4, 41.5) | 24.2 (22.4, 26.1) |
| Women | 25.9 (24.2, 27.6) | 38.3 (36.5, 40.1) | 14.3 (13.1, 15.6) |
| Location | |||
| Marcos Paz, Argentina | 27.0 (24.7, 29.3) | 62.6 (60.2, 64.9) | 15.7 (13.8, 17.6) |
| Bariloche, Argentina | 43.1 (40.7, 45.5) | 33.8 (31.6, 36.0) | 26.1 (23.9, 28.2) |
| Temuco, Chile | 29.5 (27.3, 31.7) | 38.1 (35.7, 40.4) | 16.7 (14.9, 18.6) |
| Barros Blancos, Uruguay | 36.7 (34.1, 39.2) | 35.2 (32.8, 37.7) | 15.4 (13.5, 17.3) |
| Educational level | |||
| Primary school or lower | 36.0 (34.0, 38.0) | 42.2 (40.2, 44.2) | 12.3 (10.9, 13.6) |
| Middle or high school | 35.6 (33.4, 37.7) | 38.4 (36.3, 40.6) | 21.1 (19.3, 22.9) |
| University | 28.6 (25.7, 31.5) | 34.7 (31.7, 37.7) | 25.0 (22.3, 27.7) |
| Occupation status | |||
| Manual labor | 56.6 (54.1, 59.1) | 41.4 (38.9, 43.9) | 20.0 (17.9, 22.0) |
| Office or clerical work | 28.5 (25.6, 31.5) | 32.6 (29.6, 35.7) | 25.6 (22.7, 28.4) |
| Retired | NA | 40.6 (38.2, 42.9) | 15.7 (14.0, 17.5) |
| Unemployed | NA | 41.5 (36.3, 46.7) | 15.5 (11.5, 19.5) |
| Homemaker | NA | 39.8 (36.1, 43.5) | 12.3 ( 9.9, 14.8) |
Proportion of population who spent ≥ 600 MET-minutes/week in each domain. NA: Not applicable
Table 4.
Odds ratios (95% confidence intervals) for being sufficiently active associated with selected sociodemographic and clinical variablesa
| Risk Factors | Univariate OR (95%CI) |
Multivariate OR (95%CI) |
|---|---|---|
| Age (years) | ||
| 35–44 | 1.00 | 1.00 |
| 45–54 | 0.91 (0.77, 1.06) | 0.97 (0.81, 1.16) |
| 55–64 | 0.86 (0.74, 1.01) | 0.95 (0.79, 1.15) |
| 65–74 | 0.59 (0.50, 0.70) | 0.77 (0.60, 0.98) |
| Sex | ||
| Men | 1.00 | 1.00 |
| Women | 0.56 (0.50, 0.63) | 0.63 (0.54, 0.72) |
| Hypertension | ||
| No | 1.00 | 1.00 |
| Yes | 0.88 (0.78, 0.99) | 1.05 (0.91, 1.21) |
| Body weight | ||
| Normal weight | 1.00 | 1.00 |
| Overweight | 0.91 (0.78, 1.07) | 0.86 (0.72, 1.03) |
| Obese | 0.66 (0.56, 0.77) | 0.69 (0.57, 0.82) |
| Diabetes | ||
| No | 1.00 | 1.00 |
| Yes | 0.67 (0.57, 0.79) | 0.84 (0.70, 1.01) |
| Smoking status | ||
| Never/former | 1.00 | 1.00 |
| Current | 1.04 (0.91, 1.19) | 0.96 (0.82, 1.12) |
| Educational level | ||
| Primary school or lower | 1.00 | 1.00 |
| Middle or high school | 0.93 (0.82, 1.06) | 0.86 (0.75, 0.99) |
| University | 0.80 (0.68, 0.94) | 0.78 (0.65, 0.94) |
| Occupation | ||
| Manual labor | 1.00 | 1.00 |
| Office or clerical work | 0.46 (0.39, 0.56) | 0.60 (0.49, 0.73) |
| Retired | 0.37 (0.32, 0.44) | 0.50 (0.40, 0.62) |
| Unemployed | 0.36 (0.28, 0.47) | 0.41 (0.32, 0.54) |
| Homemaker | 0.32 (0.27, 0.39) | 0.45 (0.37, 0.56) |
| Physical limitations | ||
| No | 1.00 | 1.00 |
| Yes | 0.51 (0.43, 0.60) | 0.68 (0.56, 0.83) |
Adjusted for all variables in table. Sufficiently active: ≥600 MET-minutes/week. Normal weight: body-mass index ≥18.5 and <25; Overweight: body-mass index ≥25 and <30 kg/m2; Obese: body-mass index ≥30 kg/m2; Hypertension: systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg and/or use of antihypertensive medication; Diabetes: fasting glucose ≥126 mg/dL or self- reported history of diabetes.
DISCUSSION
The results of the present study provide valuable insights into patterns and correlates of PA among the urban population in four cities of Argentina, Chile and Uruguay. Out of the total population, 64.8% met current PA recommendations and were more likely to be younger than 65 years old, male, with lower education, performing manual laborers, with normal weight, and without physical limitations. When the level of PA by domain was analyzed, active transportation through walking or biking was the main contributor to total daily energy expenditure, followed by occupation and leisure time. Active transportation correlated with variables that are usually associated with a lower income population, such us lower education, retired, unemployed, homemaker, manual laborers and older population. As regards occupation, those who reported to perform moderate and vigorous intensity activities (The IPAQ doesn’t ask about light intensity activities) were also more likely to be less educated manual laborers, but mostly younger men.
By contrast, those who achieved the recommended levels of PA in leisure time were more likely to be men with university education and those performing office or clerical work. Similarly to previous reports, indicators of higher education were positively associated with higher participation in exercise/sports in leisure time and lower moderate or vigorous intensity activities in occupation.26,27,28 This might suggest a better understanding of information regarding the health benefits of PA. It should be noted that the energy spent in active transportation and occupation was somewhat inversely correlated with energy expenditure during leisure time (exercise/sports), reflecting time constraints and different determinants for these domains of PA.
We found a large disparity in PA levels between women and men: women spent a third of the total energy expended by men (989 vs. 2763 MET-minutes/week, respectively). A large proportion of women were retired, unemployed or homemakers, who showed the lowest energy expenditure in our study. In addition, only 12.9% of women reported to perform any vigorous intensity activities and a low proportion participated in leisure time exercise/sports (21.3%). Previous research conducted in Latin America showed similar results, women were less likely to participate in leisure time PA but spent more time in household activities.29,30 We found no evidence of disparity participation in PA and sports related to traditional gender roles from Argentina, Chile or Uruguay. In occupation, women also showed a lower PA score compared to men (770 vs. 4810 MET-minutes/week, respectively) mainly at the expense of reducing manual labor activities. Finally, 13.5% reported some limitation for walking or climbing stairs which reduced the possibility to achieve a sufficiently active status, reflected in lower energy expenditure in comparison with women with no physical limitations (492 vs. 1,088 MET-minutes/week, respectively).
Among the four cities, Temuco (Chile) was the location with the lowest prevalence of sufficiently active (58%) population, followed by Barros Blancos in Uruguay (65.7%). This difference might be explained by differences in built environment (parks, road safety or bike paths), however there is no published data in relation to this topic. A previous report from Temuco described higher levels of PA (sufficiently active 81.6%31). The discrepancy could be partially explained by the inclusion of the energy expended in the household domain, which was not included in our study.
This is the first study reporting prevalence and PA patterns from Marcos Paz, Bariloche (Argentina) and Barros Blancos (Uruguay); therefore the only possible comparison was against previous reports describing PA at regional level. The prevalence of sufficiently active status found in Marcos Paz and Bariloche was higher than that reported in 2009 at a regional level (75.7 vs. 44.6% and 72.2 vs. 44.9%, respectively).32 These discrepancies could be related to the fact that regional reports considered the sufficiently active status if achieved ≥ 600 MET-min-week at least 5 days a week (IPAQ definition)33. Therefore, those subjects who spent ≥ 600 MET-min-week but in less than 5 days a week were classified as inactive, resulting in underestimation of the prevalence of sufficient activity. The prevalence found Barros Blancos (65.7%) was similar to that reported at a national level in Uruguay in 2006 (64.9%).34
The prevalence of sufficiently active status in our study was slightly higher than the levels reported for the Americas and upper-middle income countries (56.7% and 58% respectively).8 Other individual reports of PA from Latin America, mostly from Brazil, showed in general lower prevalences of subjects achieving recommended levels of PA (58.9%8, 19.3%35, 27.5%36, 43.1%37, 19.4%38 and 33.4%39 ). Reports from Colombia (53.5%14 and 21.2%40) and Peru (44.4%41) showed similar results.
Strengths of the current report include the multistage sampling process used in CESCAS I study, which allowed a direct estimation of the prevalence of PA levels in adults and also minimized selection bias. The PA questionnaire was administered by trained interviewers providing a comprehensive picture of participants’ PA patterns by collecting extensive and detailed information on the type, duration, and length of various domains of PA. The response rate in our study was high (73.4%).
A few limitations of the present study must be underscored. First, although validation studies in Latin America42 suggested that the IPAQ had acceptable validity and reliability in comparison with accelerometers; responses to the IPAQ tend to overestimate occupation and household physical activities. In this context, the lack of validation of self-report using activity monitors is a major limitation of the current study.
Nevertheless, this questionnaire is the most frequent tool used for assessing PA at population level because it is intended to quantify PA behaviors over a longer duration of time and thus incorporates elements of psychosocial and environmental context.43 Second, we used the same questionnaire employed in the HCHS/SOL study which did not include the household domain. This omission might result in a slight underestimation of the prevalence of sufficient PA; however our results were similar to other previous reports from Latin America. Third, METs are not an equivalent of fitness; thus a moderate intensity physical activity based on MET may actually be vigorous for some people. Finally, these results are representative of the selected cities included in the study, and therefore do not necessarily represent the general adult population of Argentina, Chile and Uruguay.
In conclusion, the proportion of sufficiently active subjects in the four cities of the Southern Cone is low compared with the worldwide prevalence, but higher than that reported for Latin America.8 Results from the present study are important to understand the patterns of PA in different domains in accordance with sociodemographic characteristics and CVD risk factors. Interventions to increase PA level in women, the unemployed and people with low education should focus on promoting PA in leisure time, in contrast to people performing office or clerical work or higher education where the intervention should be focused on promoting active transportation. Follow-up of this population-based cohort study will allow the identification of trends in PA in the Southern Cone and their prospective association various health outcomes, particularly CVD and risk factors.
Supplementary Material
Highlights.
Physical inactivity in the Southern Cone was lower than that reported for Latin America
Women, the unemployed, and the less educated population were more physically inactive
Physical activity varied across domains according to sociodemographic characteristics
Higher educated population should increase active transportation
Women and the less educated population should increase physical activity in leisure time
Acknowledgments
FUNDING
This work was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health under contract #268200900029C.
Footnotes
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