This study offers insight into the social patterning of chronic disease risk factors in a major Latin American city. We found evidence that BMI and obesity are inversely associated with education and income in women but not men. In addition, among all adults, having a high blood pressure diagnosis was inversely associated with income and education (although trends by education were not statistically significant) and having a diabetes diagnosis was inversely associated with education. The diabetes results were particularly striking: adults who had complete secondary education but incomplete tertiary or university education had more than two times the odds of reporting a diabetes diagnosis when compared to those with complete tertiary or university education, and those with less than a secondary school education had more than four times the odds of reporting a diabetes diagnosis when compared to the same group. Considering that, in many countries (including Latin America), people of lower socioeconomic status may be less likely to have access to a medical professional13–15
to diagnose either high blood pressure or diabetes, it is likely that the associations between low social position and higher odds of diabetes and hypertension are underestimated. In contrast to results for BMI, high blood pressure, and diabetes, the behavioral risk factors of diet, physical activity, and smoking were not consistently patterned by education or income, except for a positive association of fruit and vegetable intake with income.
Most studies of socioeconomic status and chronic disease risk factors have been conducted in high-income economies, and most show inverse social gradients.9
However, evidence suggests that the social patterning may vary depending on the social and economic context of the country. In lower-income countries, higher levels of socioeconomic resources may be associated with lifestyle characteristics conducive to higher levels of chronic disease risk factors. However, a reversal of this social gradient may occur over time as those of higher social classes recognize that their lifestyles are not conducive to a healthy life and have the resources to change their behaviors and potentially their environments.16–18
A limited number of studies have investigated social gradients in chronic disease risk factors in developing countries. Most work has focused on BMI and obesity. A recent review of the socioeconomic patterning of obesity19
reported that, for women, stronger inverse associations between BMI and indicators of education, occupation, income, or material resources emerged as country-level development increased. In men, results were more mixed: associations of socioeconomic factors were often not statistically significant and were sometimes curvilinear.19
Likewise, a cross-national study of obesity among women from 27 developing countries found that SES, measured by education, was positively associated with obesity in low-income economies, but negatively associated with obesity in upper- to middle-income developing countries.20
A recent review on SES and obesity in developing countries supports these findings, noting that, as economies develop, obesity becomes more prominent among lower SES groups with this shift occurring earlier for women than men.21
Our findings are consistent with prior work: we found an inverse social gradient in BMI and obesity for women, but not for men, using both education and income. These results would be expected given that Argentina is a middle-income country, and urban areas are often the first to undergo these transitions to inverse social gradients. The reasons for the stronger social patterning in women than in men (which has been consistently reported also in developed countries19
) remain to be determined.
Studies investigating the social patterning of hypertension and diabetes have reported both positive and inverse associations with socioeconomic position. For example, hypertension and diabetes have been found to be both inversely and positively associated with socioeconomic factors in countries of Asia and Africa.22–30
In Latin America and the Caribbean, hypertension was inversely associated with SES in a major city in Chile31
and systolic blood pressure was inversely associated with income and education in Trinidad and Tobago.32
However, in other areas, the association depended on gender. Studies in urban areas of Cuba and Peru found that hypertension was inversely associated with socioeconomic factors in women, but positively associated with socioeconomic factors in men.33,34
Diabetes was inversely associated with socioeconomic factors in urban Bolivia,35
In a study of elderly in seven cities in Latin America and the Caribbean, diabetes mellitus was inversely associated with education in Buenos Aires and Montevideo, but showed no patterning in Bridgetown, São Paulo, Santiago, Havana, or Mexico City.37
Diabetes also showed no association with SES in Valparaiso, Chile.31
We found inverse associations of income and education with hypertension and of education with diabetes in a large urban area in Argentina. These results suggest that the social patterning of hypertension and diabetes may vary substantially across developing countries by level of development and level of urbanization. However, given the emerging associations between BMI and social position as countries develop and the fact that BMI is a strong risk factor for both diabetes and hypertension, it is to be expected that strong inverse social gradients in diabetes and hypertension are likely to emerge, especially in women.
With the exception of smoking, few studies have examined the social patterning of health behaviors in developing countries. Like hypertension and diabetes, the social patterning of smoking is not invariant. Both inverse and positive associations of socioeconomic factors with smoking have been reported in countries of Asia and Africa.23,24,27,38
The direction of the association between smoking and SES depended on urban/rural status among older adults in Mexico, exhibiting a positive association with income in urban areas but a negative association with wealth in less-urban areas.39
In a Chilean city, current smoking was not associated with SES, but being sedentary in leisure time was inversely associated with SES.31
A recent study in Rio de Janeiro found that a composite measure of cardiovascular disease risk (based on BMI, fat location, smoking, hypertension, sedentary lifestyle, and alcohol consumption) was inversely associated with education in men and women and with income in men.40
We found some evidence of a positive association between income and eating fruit and vegetables, but no evidence of strong social gradients in physical activity or smoking in the city of Buenos Aires. Behaviors such as diet and physical activity are notoriously difficult to measure and the questions available to asses these behaviors were very limited. Physical activity, for example, includes both occupational and leisure-time activity (which likely vary by gender), and fruit and vegetable intake is measured by days consumed rather than the amounts consumed on each of those days. Detailed assessment of physical activity and diet was not available in this survey. This could have affected our ability to detect stronger or more consistent social patterning of these behaviors. We did detect some social patterning of diet, and it is plausible that, in developing countries, low socioeconomic position is still associated with greater occupational physical activity, resulting in no gradient in physical activity. Our questionnaire did not allow us to distinguish between these different types of activity. On the other hand, it is possible that, in developing countries, behaviors such as being sedentary and smoking are still as common in the higher as in the lower socioeconomic groups for a variety of social and cultural reasons. For example, price may be a deterrent to smoking among low SES groups in some developing countries, although transnational tobacco companies are increasing marketing and availability to larger sections of the population.1,5
It is plausible that inverse gradients will emerge over time as they have in other countries.9
Despite the limitations of the self-reported measures, the outcomes of physician-diagnosed diabetes and hypertension and self-reported BMI may be better markers of the cumulative effects of a variety of difficult-to-measure behaviors and exposures that are patterned by SES, hence the stronger associations of SES with these factors that we observed in our data. The fact that hypertension and diabetes were inversely associated with socioeconomic position in both genders despite the absence of BMI differences in men suggests that BMI is not the only factor driving these differences.
We also found that lower area-level education was associated with higher BMI after controlling for individual-level education and income. Area-level was correlated with other area-level measures, such as inadequate housing and percentage of the population with unmet basic needs, and was used as a proxy for a variety of socioeconomic conditions. Although area effects have received much attention in industrialized countries,41,42
they have been rarely investigated in nonindustrialized countries. One multilevel study in rural China found inverse associations of community socioeconomic characteristics with smoking, waist-to-hip ratio, systolic blood pressure and BMI.43
Our results for BMI are consistent with those reported in China, but we did not find area-level effects for other risk factors. Interestingly, area effects were present for both women and men despite the absence of social gradients in BMI in men at the individual level. It has been argued that a variety of area features including access to walkable environments, healthy foods, and sources of chronic stress could contribute to area differences in BMI.44,45
It is plausible that limitations in our measures of physical activity and diet make it difficult to detect area effects on these behaviors. Moreover, the extent of which area characteristics relevant to health behaviors covary with area SES in developing countries requires further research.
A limitation of our analyses is the use of self-reported measures of risk factors which undoubtedly introduced measurement error. For instance, the assessment of diabetes and hypertension was based on self-reports; height and weight were also self-reported possibly resulting in misclassification.46–51
Nevertheless, many population surveys, including surveys in high-income countries such as the Behavioral Risk Factor Surveillance System11
in the US, rely on self-reported measures for the surveillance of risk factors. In addition, these data from a large urban area may not be generalizable to less-urban or rural areas. The cross-sectional nature of our analyses obviously does not allow us to examine trends over time in the social patterning of risk factors. Limitations in the measures used also do not allow us to draw firm conclusions regarding the relative importance of income and education. Also, we did not assess the impact of other individual and area socioeconomic variables, such as occupation, wealth, and area-level poverty, which may also yield important insights into the burden of these risk factors by social factors.
Our study adds to the paucity of data on the individual and area-level social patterning of chronic disease risk in developing countries. We found that BMI was clearly inversely associated with SES in women and that diabetes and hypertension were inversely associated with SES in women than in men. In addition, lower area-level education was associated with higher BMI in both genders. Stronger inverse social patterning is likely to emerge over time in urban areas like the one we investigated. The presence of these inequalities needs to be considered by policy makers and public health workers both in terms of understanding the causes of chronic diseases and designing appropriate interventions.