Limits...
Surprising SES Gradients in mortality, health, and biomarkers in a Latin American population of adults.

Rosero-Bixby L, Dow WH - J Gerontol B Psychol Sci Soc Sci (2009)

Bottom Line: The ultimate health indicator, mortality, as well as the metabolic syndrome, reveals that better educated and wealthier individuals are worse off.Traditional cardiovascular risk factors such as diabetes and cholesterol are not significantly related to SES, but hypertension and obesity are worse among high-SES individuals.But negative SES gradients in healthy years of life persist.

View Article: PubMed Central - PubMed

Affiliation: Central American Population Center and Institute for Health Research, University of Costa Rica, San Pedro, San José, Costa Rica. lrosero@ccp.ucr.ac.cr

ABSTRACT

Background: To determine socioeconomic status (SES) gradients in the different dimensions of health among elderly Costa Ricans.

Hypothesis: SES disparities in adult health are minimal in Costa Rican society.

Methods: Data from the Costa Rican Study on Longevity and Healthy Aging study: 8,000 elderly Costa Ricans to determine mortality in the period 2000-2007 and a subsample of 3,000 to determine prevalence of several health conditions and biomarkers from anthropometry and blood and urine specimens.

Results: The ultimate health indicator, mortality, as well as the metabolic syndrome, reveals that better educated and wealthier individuals are worse off. In contrast, quality of life-related measures such as functional and cognitive disabilities, physical frailty, and depression all clearly worsen with lower SES. Overall self-reported health (SRH) also shows a strong positive SES gradient. Traditional cardiovascular risk factors such as diabetes and cholesterol are not significantly related to SES, but hypertension and obesity are worse among high-SES individuals. Reflecting mixed SES gradients in behaviors, smoking and lack of exercise are more common among low SES, but high calorie diets are more common among high SES.

Conclusions: Negative modern behaviors among high-SES groups may be reversing cardiovascular risks across SES groups, hence reversing mortality risks. But negative SES gradients in healthy years of life persist.

Show MeSH

Related in: MedlinePlus

Poor-health indicators odds ratio prevalence in high-socioeconomic status (SES) and low-SES individuals. See text for method to calculate odds ratios from models controlling for age, sex, and marital status with logistic regression. High SES are wealthy metro San Jose residents with postprimary education; low SES are poor lowland residents with no education. SRH = self-rated health; CRP = C-reactive protein; DHEA-S = Dehydroepiandrosterone sulfate
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC2654981&req=5

fig4: Poor-health indicators odds ratio prevalence in high-socioeconomic status (SES) and low-SES individuals. See text for method to calculate odds ratios from models controlling for age, sex, and marital status with logistic regression. High SES are wealthy metro San Jose residents with postprimary education; low SES are poor lowland residents with no education. SRH = self-rated health; CRP = C-reactive protein; DHEA-S = Dehydroepiandrosterone sulfate

Mentions: Figure 4 summarizes the large amount of information presented in Tables 3 and 4. With a logistic regression model for each health condition, the net effect of the three high-SES characteristics (metro San Jose, high school education, and rich wealth). We then summarized the three odds ratios by computing the one that would correspond to an individual with simultaneously the three high-SES characteristics; that is, by multiplication of the three odds ratios, and (except in six cases as described subsequently) we report this product in Figure 4. Given that this procedure presumes no interactions among the three SES variables, we also tested models with the triple interaction of the three low-SES indicators and with the triple interaction of the three high-SES indicators (these extreme groups of all low SES and all high SES each represent only 4% of the sample). In the six (out of 54) regression models where these interactions proved significant, we instead report in Figure 4 an odds ratio that includes this triple interaction, rather than the previously described product of the odds ratios in the uninteracted model. In five of the six significant triple-interacted models, results were insensitive to the choice of method. Figure 4 shows these hypothetical odds ratios, sorted descending by the low-SES effect, which conversely results in approximately ascending sorting by the high-SES effects. Figures below 1 (dots at the left) denote good health; that is, the risk of suffering the condition is lower in the group with respect to the rest of the population.


Surprising SES Gradients in mortality, health, and biomarkers in a Latin American population of adults.

Rosero-Bixby L, Dow WH - J Gerontol B Psychol Sci Soc Sci (2009)

Poor-health indicators odds ratio prevalence in high-socioeconomic status (SES) and low-SES individuals. See text for method to calculate odds ratios from models controlling for age, sex, and marital status with logistic regression. High SES are wealthy metro San Jose residents with postprimary education; low SES are poor lowland residents with no education. SRH = self-rated health; CRP = C-reactive protein; DHEA-S = Dehydroepiandrosterone sulfate
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2654981&req=5

fig4: Poor-health indicators odds ratio prevalence in high-socioeconomic status (SES) and low-SES individuals. See text for method to calculate odds ratios from models controlling for age, sex, and marital status with logistic regression. High SES are wealthy metro San Jose residents with postprimary education; low SES are poor lowland residents with no education. SRH = self-rated health; CRP = C-reactive protein; DHEA-S = Dehydroepiandrosterone sulfate
Mentions: Figure 4 summarizes the large amount of information presented in Tables 3 and 4. With a logistic regression model for each health condition, the net effect of the three high-SES characteristics (metro San Jose, high school education, and rich wealth). We then summarized the three odds ratios by computing the one that would correspond to an individual with simultaneously the three high-SES characteristics; that is, by multiplication of the three odds ratios, and (except in six cases as described subsequently) we report this product in Figure 4. Given that this procedure presumes no interactions among the three SES variables, we also tested models with the triple interaction of the three low-SES indicators and with the triple interaction of the three high-SES indicators (these extreme groups of all low SES and all high SES each represent only 4% of the sample). In the six (out of 54) regression models where these interactions proved significant, we instead report in Figure 4 an odds ratio that includes this triple interaction, rather than the previously described product of the odds ratios in the uninteracted model. In five of the six significant triple-interacted models, results were insensitive to the choice of method. Figure 4 shows these hypothetical odds ratios, sorted descending by the low-SES effect, which conversely results in approximately ascending sorting by the high-SES effects. Figures below 1 (dots at the left) denote good health; that is, the risk of suffering the condition is lower in the group with respect to the rest of the population.

Bottom Line: The ultimate health indicator, mortality, as well as the metabolic syndrome, reveals that better educated and wealthier individuals are worse off.Traditional cardiovascular risk factors such as diabetes and cholesterol are not significantly related to SES, but hypertension and obesity are worse among high-SES individuals.But negative SES gradients in healthy years of life persist.

View Article: PubMed Central - PubMed

Affiliation: Central American Population Center and Institute for Health Research, University of Costa Rica, San Pedro, San José, Costa Rica. lrosero@ccp.ucr.ac.cr

ABSTRACT

Background: To determine socioeconomic status (SES) gradients in the different dimensions of health among elderly Costa Ricans.

Hypothesis: SES disparities in adult health are minimal in Costa Rican society.

Methods: Data from the Costa Rican Study on Longevity and Healthy Aging study: 8,000 elderly Costa Ricans to determine mortality in the period 2000-2007 and a subsample of 3,000 to determine prevalence of several health conditions and biomarkers from anthropometry and blood and urine specimens.

Results: The ultimate health indicator, mortality, as well as the metabolic syndrome, reveals that better educated and wealthier individuals are worse off. In contrast, quality of life-related measures such as functional and cognitive disabilities, physical frailty, and depression all clearly worsen with lower SES. Overall self-reported health (SRH) also shows a strong positive SES gradient. Traditional cardiovascular risk factors such as diabetes and cholesterol are not significantly related to SES, but hypertension and obesity are worse among high-SES individuals. Reflecting mixed SES gradients in behaviors, smoking and lack of exercise are more common among low SES, but high calorie diets are more common among high SES.

Conclusions: Negative modern behaviors among high-SES groups may be reversing cardiovascular risks across SES groups, hence reversing mortality risks. But negative SES gradients in healthy years of life persist.

Show MeSH
Related in: MedlinePlus