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However, because ethnic minority women are disproportionately poor, socioeconomic status SES may substantially explain these risk factor differences. Main Outcome Measures.
The striking differences by both ethnicity and SES underscore the critical need to improve screening, early detection, and treatment of CVD-related conditions for black and Mexican American women, as well as for women of lower SES in all ethnic groups.
Ethnic minority women exhibit CVD risk factors to a greater extent than do white women. Many studies have documented greater prevalences of high blood pressure, physical inactivity, excess weight, and diabetes in African American women than in white women. As one of the fastest-growing ethnic minority groups, the Hispanic share of the population is projected to increase to Some ethnic variations in CVD risk factors may be genetically based. Numerous empirical studies in the United States have shown strong associations among CVD risk factors and a broad array of SES indicators, including education, income, and occupational status.
Therefore, erroneous findings can result, overestimating the effects of ethnicity without considering the effects of SES. We hypothesized that black and Mexican American women would exhibit CVD risk factors to a greater extent than white women but that the differences would be explained substantially by SES. To test this hypothesis, we evaluated the independent relationships of ethnicity and SES with 6 primary CVD risk factors: systolic blood pressure, cigarette smoking, body mass index BMIphysical inactivity, non—high-density lipoprotein cholesterol non—HDL-Cand non—insulin-dependent diabetes mellitus NIDDM, chosen because of its relationship to lifestyle factors and its disproportionately high rates in ethnic minority groups.
We also addressed 2 important measurement and analytic issues that contribute to understanding ethnic differences in CVD. First, we examined whether 2 indicators of SES, educational attainment an individual-level marker of SES and poverty-income ratio a family-level markerproduced similar findings. Second, we examined whether 2 analytic procedures, a multivariate linear model and a matched-pairs analysis, produced similar findings.
Phase I was conducted from to and phase II from to It included a total sample of persons aged 2 months or older. The household surveys included demographic, socioeconomic, dietary, and health history questions; the medical examinations included measurements of blood pressure, lipid levels, and glucose levels.
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The sample for our analyses included black, Mexican American, and white women aged 25 to 64 years who completed both the home questionnaire and medical examination. We used the lower age cut point of 25 years to ensure that most individuals had completed their highest level of education our primary indicator of SES and the upper age cut point of 64 years to avoid problems of selection effects due to non—CVD-caused morbidity and mortality.
The women who completed only the home questionnaire were similar to the women who completed both the home questionnaire and medical examination in age Women who chose 1 of the first 3 were included in our analyses. We used educational attainment as our primary indicator of SES because education level, unlike income level and occupation, is available regardless of employment status, a more constant measure of lifelong SES, and not affected by the CVD outcomes we analyzed.
Poverty-income ratio, our secondary indicator of SES, is calculated from family income and family size and is based on US Bureau of the Census tables. We used the following 6 CVD risk factors as outcome variables: 1 Systolic blood pressure, measured in millimeters of mercury.
We report the mean of the second and third of 3 readings, measured on the right arm by a physician while the participant was seated during the medical examination. Participants reported whether they had smoked at least cigarettes during their lifetimes and whether they were currently smoking cigarettes.
The calculations provide a measure of relative weight. Questions on leisure-time physical activity were adapted from the National Health Interview Survey, 50 which asked participants whether they had engaged in any leisure-time physical activity in the past month, including exercises, sports, or physically active hobbies. Women who reported no leisure-time activities were considered physically inactive.
Measurements were taken from serum specimens, analyzed by standardized protocols, and calculated as the difference between total cholesterol and HDL-C. We used multiple linear regression models for continuous outcomes and logistic regression models for binary outcomes.
The outcome variables in our models were the 6 risk factors described herein. The predictor variables were age in years, centered at the sample mean to aid in the interpretation of the regression coefficientsrace or ethnicity black and Mexican American women compared separately with white women; each comparison used white women as the reference groupand years of education continuous and centered at 12 years.
We included all first-order interactions between predictor variables age and ethnicity, age and education, ethnicity and education. In a secondary analysis, we substituted poverty-income ratio continuous, centered at the sample mean for years of education to examine the extent to which this indicator of SES might produce different. We used a matched-pairs analysis to confirm findings from the linear models because matching can overcome potential limitations such as unmet linear model assumptions, problems of collinearity eg, a strong correlation between ethnicity and SESand exclusion of higher-order interaction terms.
To test for overall differences in CVD risk factors between the matched pairs, we used paired t tests for continuous risk factor variables and the McNemar test for binary variables. Less educated women were older, less likely to live in urban areas especially white womenand poorer than women who were more highly educated.
Mexican American women were younger, had completed less education, and were less likely to be born in the United States and to speak English at home than black or white women. As expected, age was ificantly associated with all risk factors.
The magnitude of the ethnic and SES differences was large for many comparisons. Each BMI unit is equivalent to about 2.
When poverty-income ratio was substituted for years of education in the linear models, were almost identical; all risk factors that were ificantly related to years of education were also ificantly related to the poverty-income ratio. Table 3 presents descriptive statistics, displaying means with SDs and percentages.
As confirmed by the linear models Table 2black and Mexican American women had ificantly higher levels of BMI and blood pressure and higher prevalences of diabetes and physical inactivity than did white women of comparable SES. The main exceptions were for smoking prevalences and non—HDL-C levels; Mexican American women had lower smoking prevalences and black women had lower non—HDL-C levels than did white women.
Two important and ificant interactions emerged in the linear models, between ethnicity and age for both blood pressure and smoking Figure 1. Black and Mexican American women had steeper increases in blood pressure than white women across age groups, resulting in ificantly greater ethnic differences for the older than younger age groups eg, the black-white difference of 4 mm Hg at age years increased to 11 mm Hg at age years. The matched-pairs analysis confirmed the from the linear models. were almost identical for all risk factors, indicating no bias in applying the linear model to the full sample.
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The only result not confirmed was for non—HDL-C; the black-white comparison was ificant in the linear model but not ificant in the matched-pairs analysis. This difference raises some doubts about the validity of the finding of ificantly higher non—HDL-C values for black vs white women in the unmatched sample. To our knowledge, this article is one of the first to document higher levels of CVD risk factors among black and Mexican American women than among white women of comparable age and SES. We hypothesized that ethnic minority status would be associated with higher levels of CVD risk factors, but that the associations would be explained substantially by SES.
Our hypothesis was not confirmed. After adjustment for age and SES, highly ificant differences in BMI, blood pressure, diabetes, and physical inactivity remained between white women and both black and Mexican American women.
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In addition, we found large differences in CVD risk factors by SES, a finding that illustrates the high-risk status of both ethnic minority women as well as white women with low SES. Shea and colleagues 11 examined the independent associations of educational attainment and ethnicity white, black, and Hispanic with the primary CVD risk factors.
The survey included an oversampling of black and Mexican American women, the 2 largest groups of ethnic minority women in the United States. It also included large s of women at the extremes of educational attainment. Extensive and complete data are available from both the home survey and medical examination, including individual-level and family-level indicators of SES and standardized measures of blood pressure, lipid levels, and glucose levels.
Despite these strengths, our should be interpreted with caution because of several de and measurement limitations.
For example, the onset of smoking, excess weight gain, and physical inactivity usually occurs at early ages, often before the completion of formal education. Although we could not determine from the data the temporal association between level of education and these CVD risk factors, it is more likely that SES influences risk of disease than that risk of disease influences SES.
To verify self-reported smoking, we used a biochemical measure, serum cotinine, that was available for all women from phase I of the survey. Among women who reported being nonsmokers, the following percentages had positive for cotinine: 8.
Thus, the minimal underreporting of smoking by Mexican American women and women with higher SES lends credence to our finding of their low smoking rates. Few studies have assessed reporting bias by ethnicity for physical activity measures; however, we have seen no indications of differential underreporting or overreporting by black, Mexican American, or white women. It is not surprising that black and Mexican American women, who often have fewer resources and less time to engage in leisure-time physical activity than white women, reported lower levels of activity.
The few questions available in NHANES III to assess physical activity highlight the need for future surveys to include measures such as total activity recall or energy expenditure that better reflect overall activity levels of women, regardless of ethnic and income status. Last, our primary measure of SES educational attainment did not measure core beliefs and practices in relation to specific CVD risk factors or medical conditions.
Furthermore, it did not provide the same economic benefits to black and Mexican American women as to white women. The striking ethnic and SES differences in CVD risk factors highlight the need for reform in public health policies, health care systems, and intervention programs. The challenge for public health professionals is to identify and understand groups of women with high prevalences of risk factors and disease, and to de effective interventions at the individual and societal levels that will benefit these women.
Public policies need to ensure that ethnic minority women and women with low SES from all ethnic groups have heart-healthy food choices, smoke-free environments at the workplace, and safe and convenient places to exercise.
Health care systems need effective protocols to reach ethnic minority women and women with low SES who often experience differential access to health care services 177879 because of cost barriers, unavailability of health insurance, and discrimination in health care. Intervention programs, based on targeted subgroup approaches, need to identify high-risk populations, develop strong and enduring partnerships with communities, and tailor strategies to the language and literacy needs, values, and cultures of the populations.
Our findings are especially relevant in light of the global rise of CVD and other chronic diseases that are influenced by increasing prevalences of hypertension, cigarette smoking, hypercholesterolemia, obesity, physical inactivity, and diabetes. Our work builds on studies that have documented disproportionate suffering, disability, and premature death from CVD among ethnic minority women and those with low SES.
Fortunately, CVD risk factors are well established and their occurrence can be largely prevented.