1 Carolina Population Center, University of North Carolina at Chapel Hill, NC, USA.
2 Department of Preventive Medicine and Epidemiology, Loyola University, Chicago, IL, USA.
3 Tropical Metabolism Research Institute, University of the West Indies, Jamaica.
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Abstract |
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Methods Hypertension (systolic BP 140 mmHg, diastolic BP
90 mmHg or current hypertensive medication use) was estimated based on self-reported medication use and the mean of the second and third of three manual BP measurements. Income and education were self-reported. Linear or logistic regressions were used to estimate multivariate associations between BP or hypertension and SES.
Results Hypertension prevalence was 20% in men and 28% in women. In both men and women, the income distributions of BP and hypertension were non-linear, indicating elevated levels in low as well as in high-income groups. In contrast to the negative relationships typical for industrialized countries, multivariate-adjusted BP and hypertension were highest in the wealthiest women. In men with some high school education, income was positively associated with BP, while there were negative associations in men with lesser education. Unlike women, mean BP were highest in poor men with limited education. Low SES men were also least likely to receive diagnosis and treatment.
Conclusions Socioeconomic status is related to BP and hypertension in Jamaica, although relationships are non-linear. Behavioural and environmental factors that explain elevated BP among both low and high SES adults in developing countries must be identified to develop effective prevention strategies.
Accepted 6 December 2002
Social and cultural transitions during the process of economic development are thought to influence the pace at which hypertension and other risk factors for cardiovascular disease (CVD) emerge in developing countries.1 Little is currently known about how socioeconomic factors may influence the distribution of blood pressure (BP) and hypertension in these societies, asfew studies have been published, and results have been heterogeneous.25 In contrast, there is a fairly consistent negative association between socioeconomic status (SES) and BP in industrialized countries.2,6 This negative association is thought to have emerged between 1940 and 1960; earlier studies in the US and UK found that high SES groups were at greater risk.6
The basis for the inconsistent associations between SES and BP in developing country studies is unclear. One explanation may be heterogeneity in stages of modernization and economic development. It has been hypothesized that there may be a transition in the relationship between SES and CVD risk, with the direction and magnitude of the associations changing from positive to negative with Westernization and economic development.7,8 While there is limitedand conflictingempirical evidence of such a transition, plausible mechanisms have been put forth.8,9 In the least developed countries, high SES sub-groups may be early adopters of atherogenic and hypertensive lifestylescharacterized by smoking, sedentarism, and diets high in energy and fats. In more industrialized countries, high SES groups may be the first to adopt lifestyles that help to lower CVD risk, or to receive better treatment, while changes in the low SES environment may increasingly promote lifestyles adverse for health. Under this hypothesis, we would expect associations between SES and BP to be strong and positive in low-income countries, but variable in more industrialized, middle-income countries.
The relationship between SES and BP in the developing world may also be influenced by the emergence of new risk factorsfor hypertension and CVD. Though little is known about the distribution of potential risk factors such as fetal undernutrition and psychosocial stress, they may disproportionately affect the poor.1,10 The coexistence of emerging and traditional risk factors may lead to elevated risk in both the poorest and relatively well-off subgroups.
Using income and education as socioeconomic indicators, this paper examines the association between SES and BP in Jamaica, a middle-income Caribbean country. Jamaica provides an opportunity to explore how SES is related to BP in a country where epidemiological and nutrition transitions are well underway, but coexist with problems related to undernutrition. Cardiovascular diseases are the leading cause of death, along with diabetes and cancer.11 Obesity and hypertension are highly prevalent.12 Nonetheless, nutritional deficiencies remain widespread, and nutrition-related disorders are also in the top five causes of death.11
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Materials and Methods |
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Data collection methods
Trained staff measured BP using a standardized protocol.13 Arm circumference was measured and appropriate cuff sizes selected. After participants emptied their bladders and sat quietly for 510 minutes, three manual BP measurements were taken, with intervals of 1 minute between measures. The mean of the second and third measurements was used in all analyses. Hypertension was defined as self-reported current use of hypertensive medication, mean systolic blood pressure (SBP) 140 mmHg or diastolic blood pressure (DBP)
90 mmHg.14 Moderate/severe hypertension was defined as medication use or BP
160/95 mmHg.
Trained field staff also collected anthropometric data. Digital scales were calibrated daily. Height and weight were measured without shoes and with light clothing. Body mass index (BMI, calculated as weight in kg/height in metres2) was used to classify participants as normal (<25), overweight (25<30), and obese (30).15 Underweight (BMI<18) was omitted as there were few such subjects (5% of men, 6% of women) and this adjustment did not influence results.
Questionnaires were used to collect information on self-reported income, education, and other relevant social and biological factors, including family history of hypertension, occupation, marital status, oral contraceptive use (women), and lifestyle changes being used in attempts to lower BP (less salt, more exercise, dietary change, reduced alcohol use). Individual monthly income was reported in six categories: 600 Jamaican dollars (J$), J$6011000, J$10013000, J$30016000, J$600112 000, and
J$12 000. Using category midpoints, income was deflated to J$1993 using consumer price index data from the Statistical Institute of Jamaica.16 As categories were fairly wide, only 2% of subjects were reclassified after deflation. The highest and lowest income groups were collapsed with neighbouring categories because of small numbers. Income was also dichotomized at J$3000/month (US$91.5 in 1993), approximately the national poverty line.17,18 Family income, reported by 997 subjects as part of an earlier sub-study, was used in supplementary models to validate results based on individual income.19 The Spearman correlation between individual and family income was 0.78 (0.65 for estimated per capita income); rank ordering was preserved for 73% of the sample using individual versus family income.
Statistical analysis
All analyses used Stata version 6.0 (College Station, TX). Age was strongly associated with income and education as well as with BP. Therefore, in descriptive analysis, mean BP and hypertension prevalence were age-adjusted by the direct method, using the total sample age distribution as the standard. Age-adjusted means and prevalences were calculated by sex, as well as by income and education level. The SES distribution of mean BP and hypertension was examined both for the entire sample and after excluding those on medication, as any influence of SES on access to care may have affected these distributions.
Multivariate-adjusted associations between mean BP and SES were estimated using linear regression; logistic regression was used to estimate associations between hypertension and SES. Models were fitted including and excluding treated subjects with similar results. Dummy variables were used for income and education to minimize assumptions about linearity. Based on the distributions observed, polynomials were used to test for quadratic trends; variables were centred to avoid collinearity. We evaluated confounding (15% change-in-estimate for parameters of interest) by the following variables: pulse rate, marital status, overweight status, fasting glucose level, household size, family history of hypertension, ambient temperature, alcohol and smoking use (past or current), and oral contraceptive use among women. Associations were significant at P < 0.05. We also assessed whether SES variables were modified by each other, or by overweight status; effect modification was deemed significant if P < 0.05 in linear and P < 0.20 in logistic models. Final models included only age groups, income terms, education, overweight status, and year of exam. Predicted BP from model equations were estimated to describe distributions after multivariate adjustment.
Overall, 18% of women and 17% of men declined to report income. There were no differences in age, BP, hypertension prevalence, education level, or obesity among participants with versus without income data. To further assess bias, supplementary linear models were fitted using estimated income values based on multivariate imputation, with age, sex, education level, marital status, interview date, employment status, and occupation category as predictors. Results (not shown) were very similar to main findings based only on subjects with reported income; coefficients for imputed and reported income were not significantly different. Other diagnostics included collinearity assessment, and confirming similar results after substituting log transformed BP or excluding multivariate outliers.20,21 To assess any influence of temporal changes, we also confirmed that findings were similar using samples limited to 19931996 and 19941998 data.
Finally, we estimated associations between SES and hypertension awareness, treatment, and control. Numbers available for this analysis were limited as there were few hypertensive men and women in each income and education category. Hypertensive participants who reported being told by a doctor or nurse that they had hypertension were defined as aware; one participant who reported pregnancy-related hypertension only and one who was uncertain about prior diagnosis were excluded. Control was defined as SBP<140 mmHg and DBP<90 mmHg among all hypertensives. In addition to age-adjusted prevalence estimates, logistic regression was used to estimate associations between SES and awareness, treatment and control, adjusted for age.
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Results |
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Multivariate associationsmain effects
Multivariate associations using dummy variables indicated that the wealthiest women had significantly higher mean DBP and hypertension than women in intermediate income groups (Table 2). Differences between the highest and lowest income levels were non-significant, reflecting the J-shaped distributions described above (Table 2
). Because of the non-linear pattern, substitution of the cruder income variable dichotomized at the poverty line obscured these relationships (e.g. DBP coefficient for poverty 0.51 P = 0.56). Systolic blood pressure model results were similar, but did not reach significance, nor did associations with education. All main effect associations were insignificant in men.
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Joint effects of income and education
As illustrated in Figure 2, SES effects on BP in men were significant only after including an interaction between income and education level. Including this interaction showed that income was positively associated with BP only among men with >6th grade schooling (DBP coefficients for increasing versus lowest income group: 1.84 P = 0.62; 7.05 P = 0.02; 6.55 P = 0.03). In men with limited (
6th grade) schooling, higher income was associated with reduced BP (DBP coefficients: 2.59 P = 0.17; 4.78 P = 0.01; 1.34 P = 0.51). Similarly, >6th grade education was negatively associated with BP among low-income (DBP coefficient 6.36 P = 0.01), but not higher-income men (coefficient 2.35 P = 0.10). Associations were similar for SBP, and similar but non-significant for hypertension. Povertyeducation interactions remained at least marginally significant (P < 0.10) among normal weight as well as overweight men. Findings did not change when retirees and/or college-educated men were excluded (not shown). Interactions were not significant among women. As in women, mean BP were elevated in the wealthiest men. However, stratified results and interactions showed that while mean BP were highest among wealthiest women regardless of education level, BP were highest among the poorest men if they also had limited education (Figure 2
).
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Discussion |
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In contrast to generally positive associations with income, associations with education were generally negative or insignificant. Non-significant negative associations were observed in women. Similarly, 6th grade education was associated with significant reductions in BP among poor men. In non-poor men, though, there was a non-significant positive association.
Furthermore, disparities in BP across SES groups were substantial. Age-adjusted differences in BP across SES groups were in the order of 25 mmHg for SBP and 45 mmHg for DBP; multivariate-adjusted differences were at times higher. Differences of 5 mmHg in DBP have been estimated to predict a 21% lower rate of CHD and 34% lower rate of stroke.22 We also found substantial differencesof the order of 10%in the prevalence of hypertension across SES groups.
A better understanding of pathways linking the socioeconomic environment to BP is essential for designing and targeting interventions to reduce hypertension in rapidly developing countries where levels of CVD and hypertension are increasing.1 Hypertension prevalence in this study (20.1% in men, 28.7% in women) was similar to recent estimates for the US (22.8% for men and 18.0% for women).23 Environmental factors that contribute to the high prevalence of hypertension, the substantial disparities in BP across some SES groups, and differences in the magnitude and direction of relationships with income versus education, are not well understood. To our knowledge, the interaction between income and education observed in men has not been described in previous studies on BP. The interaction may well be a statistical artefact. Alternatively, it may be that in men with very limited educationand thus limited economic prospectsincreased income may act as a buffer against psychosocial stress. Income may be associated with greater stress, or other adverse lifestyle practices, in more educated men. It is not certain why this interaction was not found in women. Studies in other contexts are needed to examine these relationships in men and women, and to explore underlying factors that might explain this phenomenon.
Income and education may be markers of a diverse range of community and individual factors associated with CVD risk. Studies in developed countries have found relationships between SES indicators and factors such as access to care, availability of healthy foods, individual dietary patterns, and physical activity.2426 Similar factors may explain the SES gradient in BP in highly westernized, middle-income developing countries.
Most studies in developing countries have reported direct (positive) or no associations between SES and blood pressure, although a number of studies have reported negative relationships.2,5,27 Few studies, if any, have explicitly examined whether relationships are non-linear, or examined joint effects of income and education. The non-linear associations observed in this study may reflect widespread adoption of lifestyles characterized by factors such as sedentarism and high-fat diets across diverse SES groups. Relatively high BP among low SES groups may also reflect alternative risk factors such as early undernutrition or psychosocial stress. Indeed, previous studies in Jamaica found that growth retardation in infancy was associated with higher BP in late childhood.28 Further study of SES and BP in countries at different stages of development may provide insights on how socioeconomic transitions are linked to the emergence of hypertension.
As reported previously, treatment rates in this sample were high.29 In this study, we also showed that low income was associated with reduced awareness, treatment, and control of hypertension in men. Income was also weakly related to lower treatment rates in women. Given the high prevalence in low SES groups, ensuring adequate diagnosis and treatment of hypertension regardless of SES is essential. Disparities in diagnosis and effective treatment of early markers of CVD risk could create disparities in progression to more advanced disease. Indeed the observation of greater declines in CVD mortality among high versus low SES groups suggests such disparities have been problematic in industrialized countries.6
Although 18% of the sample did not report income, we found consistent results for men and women, and similar results based on imputed or family income, suggesting that the income distributions observed are credible. The observation of a similar pattern for education also reduces the likelihood that the income distribution in men might be attributable to reverse causality, such as adverse effects on current earnings as a consequence of health-related changes in employment. Despite a moderate response rate (61%), comparisons of mean income and unemployment against national data indicated that the sample was similar to Jamaica as a whole, suggesting our results are generalizable. The sample poverty level (45%) was similar to national estimates of 4060% during 19901998.17
In spite of the higher prevalence in industrialized countries, developing countries contribute nearly twice as much as industrialized nations to the global CVD burden because of their larger population size.1,2 The prevalence of hypertension in these countries has risen dramatically in recent decades; further increases are anticipated with improvements in life expectancy and continued development.1,30 Effective primordial prevention is needed to mitigate this epidemic.
KEY MESSAGES
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Acknowledgments |
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References |
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