ABSTRACT:

Introduction:

In high-income countries, persons of high socioeconomic status (SES) have a lower cardiovascular risk. However, in middle and low-income countries, the results are controversial.

Objective:

To evaluate the association between family income and cardiovascular risk factors in young adults.

Methods:

A total of 2,063 individuals of a birth cohort initiated in 1978/79 in the city of Ribeirão Preto, Brazil, were evaluated at age of 23/25 years. Cardiovascular risk factors (hypertension, sedentary lifestyle, smoking, low high-density lipoprotein (HDL)-cholesterol, high low-density lipoprotein (LDL)-cholesterol, high fibrinogen, insulin resistance, diabetes, abdominal and total obesity, and metabolic syndrome) were evaluated according to family income. Income was assessed in multiples of the minimum wage. Simple Poisson regression models were used to estimate the prevalence ratios (PR) with robust estimation of the variance.

Results:

High-income women showed lower prevalences of low HDL-cholesterol (PR = 0.47), total obesity (PR = 0.22), abdominal obesity (PR = 0.28), high blood pressure (PR = 0.28), insulin resistance (PR = 0.57), sedentary lifestyle (PR = 0.47), metabolic syndrome (PR = 0.24), and high caloric intake (PR = 0.71) (p < 0.05). High-income men showed lower prevalences of low HDL-cholesterol (PR = 0.73) and sedentarism (PR = 0.81) (p < 0.05). These results may be explained by the fact that high-income women pay more attention to healthy habits and those with the lowest family income are least likely to access health services resources and treatments.

Conclusion:

Women were in the final phase of the epidemiologic transition, whereas men were in the middle phase.

Keywords:
Risk factors; Cardiovascular diseases; Young adult; Income

RESUMO:

Introdução:

Em países de alta renda, indivíduos de situação socioeconômica elevada apresentam menor risco cardiovascular. Em países de média e baixa rendas, os resultados são controversos.

Objetivo:

Avaliar a associação entre renda familiar e fatores de risco cardiovascular em adultos jovens.

Metodologia:

Estudo seccional em que foram avaliados 2.063 indivíduos aos 23/25 anos de uma coorte de nascimento iniciada em 1978/79 na cidade de Ribeirão Preto, Brasil. Avaliaram-se fatores de risco cardiovascular (hipertensão arterial, sedentarismo, tabagismo, HDL - colesterol baixo, LDL - colesterol elevado, fibrinogênio alto, resistência insulínica, diabetes, obesidade abdominal e total e síndrome metabólica) de acordo com renda familiar. A renda foi avaliada em múltiplos do salário mínimo. As razões de prevalências (RP) foram estimadas em modelos de regressão de Poisson simples, com estimativa robusta da variância.

Resultados:

Mulheres de maior renda apresentaram menores prevalências de HDL - colesterol baixo (RP = 0,47), obesidade total (RP = 0,22) e abdominal (RP = 0,28), resistência insulínica (RP = 0,57), pressão arterial elevada (RP = 0,28), sedentarismo (RP = 0,47), síndrome metabólica (RP = 0,24) e alta ingestão calórica (RP = 0,71) (p < 0,05). Os homens de maior renda apresentaram menores prevalências de HDL - colesterol baixo (RP = 0,73) e sedentarismo (RP = 0,81) (p < 0,05). Pode ser que mulheres de alta renda prestem mais atenção aos hábitos saudáveis e aquelas com menor renda têm menor probabilidade de acessar recursos e tratamentos de serviços de saúde.

Conclusão:

As mulheres encontravam-se na fase final da transição epidemiológica, enquanto os homens, na fase intermediária.

Palavras-chave:
Fatores de risco; Doenças cardiovasculares; Adulto jovem; Renda

INTRODUCTION

Cardiovascular diseases currently represent a serious public health problem worldwide, being the main cause of morbidity and premature mortality. By 2025, more than 80% of all cases of cardiovascular diseases and diabetes are expected to occur in middle and low-income countries¹1. Alwan A, Maclean DR, Riley LM, d’Espaignet ET, Mathers CD, Stevens GA, et al. Monitoring and surveillance of chronic noncommunicable diseases: progress and capacity in high-burden countries. Lancet 2010; 376(9755): 1861-8. https://doi.org/10.1016/S0140-6736(10)61853-3
https://doi.org/https://doi.org/10.1016/... . Cardiovascular risk factors (CRF) are conditions associated with early onset cardiovascular disease. Some of these risks are not amenable to change, such as sex, age and heredity; others may be changed, such as smoking, hypertension, dyslipidemia, obesity, diabetes mellitus/carbohydrate intolerance, sedentarism, psychosocial stress and some factors related to hemostasis, inflammation and thrombosis, recently considered to be CRF²2. Piepoli MS, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, et al. European Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J 2016; 37(29): 2315-81. https://doi.org/10.1093/eurheartj/ehw106
https://doi.org/https://doi.org/10.1093/... .

Socioeconomic status (SES) is defined as the position a person occupies in the society to which he/she belongs, measured according to income, occupation and/or education. Some studies have demonstrated an association between SES and CRF³3. Albert MA, Glynn RJ, Buring J, Ridker PM. Impact of traditional and novel risk factors on the relationship between socioeconomic status and the incident cardiovascular events. Circulation 2006; 114(24): 2619-26. http://doi.org/10.1161/CIRCULATIONAHA.106.660043
https://doi.org/http://doi.org/10.1161/C... ^,44. Johnson-Lawrence M, Kaplan G, Galea S. Socioeconomic mobility in adulthood and cardiovascular disease mortality. Ann Epidemiol 2013; 23(4): 167-71. http://doi.org/10.1016/j.annepidem.2013.02.004
https://doi.org/http://doi.org/10.1016/j... . Researches conducted in high-income countries have demonstrated that high-income persons have a lower cardiovascular risk, whereas low-income ones present a higher cardiovascular risk. These differences in cardiovascular risk factors between the wealthy and the poor are attributed to the epidemiologic transition⁴4. Johnson-Lawrence M, Kaplan G, Galea S. Socioeconomic mobility in adulthood and cardiovascular disease mortality. Ann Epidemiol 2013; 23(4): 167-71. http://doi.org/10.1016/j.annepidem.2013.02.004
https://doi.org/http://doi.org/10.1016/j... ^,55. Mishra GD, Chiesa F, Goodman A, De Stavola B, Koupil I. Socio-economic position over the life course and all-cause, and circulatory disease mortality at age 50-87 years: results from the Swedish birth cohort. Eur J Epidemiol 2013; 28(2): 139-47. http://doi.org/10.1007/s10654-013-9777-z
https://doi.org/http://doi.org/10.1007/s... ^,66. Stringhini S, Spencer B, Marques-Vidal P, Waeber G, Vollenweider P, Paccaud F, et al. Age and gender differences in the social patterning of cardiovascular risk factors in Switzerland: the CoLaus study. Plos One 2012; 7(11): e49443. http://doi.org/10.1371/journal.pone.0049443
https://doi.org/http://doi.org/10.1371/j... .

The epidemiologic transition that started in the past century in high-income countries seems to be characterized, in its initial phase, by a worse cardiovascular risk in the high-income groups of the population. In its intermediate phase, this difference seems to disappear due to a worsening of cardiovascular risk in poorer persons, while wealthier persons would continue to have an unchanged and unfavorable cardiovascular risk. In the final phase of this transition, there seems to be an inversion in the relation between income and cardiovascular risk that would lead to a lower cardiovascular risk in the wealthier population and a higher one in the poorer population⁷7. Dong C, Rundek T, Wright CB, Anwar Z, Elkind MS, Sacco RL. Ideal cardiovascular health predicts lower risks of myocardial infarction, stroke, and vascular death across whites, blacks, and Hispanics: the northern Manhattan study. Circulation 2012; 125(24): 2975-84. http://doi.org/10.1161/CIRCULATIONAHA.111.081083
https://doi.org/http://doi.org/10.1161/C... ^,88. Popkin BM. The nutrition and obesity in the developing world. J Nutr 2001; 131(3): 871S-3S. https://doi.org/10.1093/jn/131.3.871S
https://doi.org/https://doi.org/10.1093/... .

Studies conducted in middle-income countries, in addition to being scarce, have reported controversial results. One research demonstrated a higher cardiovascular risk among high-income persons⁹9. Samuel P, Antonisamy B, Raghupathy P, Richard J, Fall C. Socio-economic status and cardiovascular risk factors in rural and urban áreas of Velorre, Talminadu. South India. Int J Epidemio 2012; 41(5): 1315-27. http://doi.org/10.1093/ije/dys001
https://doi.org/http://doi.org/10.1093/i... , while another concluded that the cardiovascular risk was lower among wealthier people¹⁰10. Pisa P, Behanan R, Vorster H, Kruger A. Social drift of cardiovascular disease risk factors in Africans from the Noorth West Province of South Africa, the PURE study. Cardiovascular J Afr 2012; 23(7): 371-8. https://dx.doi.org/10.5830%2FCVJA-2012-018
https://doi.org/https://dx.doi.org/10.58... . It is still unknown whether the inversion of the association between SES and CRF observed in high-income countries has already occurred in middle-income countries¹¹11. Popkin BM. The shift in stages of the nutrition transition in the developing world differs from past experiences. Public Health Nutr 2002; 5(1a): 205-14. http://doi.org/10.1079/PHN2001295
https://doi.org/http://doi.org/10.1079/P... .

The objective of the present study was to determine whether high-income persons have a lower cardiovascular risk than low-income ones from a birth cohort re-assessed at 23 to 25 years of age in Ribeirão Preto, Brazil. The question was: had the epidemiologic transition been concluded or was it still in its intermediate phase in the city of Ribeirão Preto, in 2002-04?

METHODS

STUDY DESIGN

The present investigation was a cross-sectional study based on data from a birth cohort started in Ribeirão Preto, Brazil, in 1978/79. This cohort is entitled “Perinatal Health in Ribeirão Preto, São Paulo, Brazil”, and included liveborn singletons delivered at hospitals by mothers residing in the municipality, from June 1^st, 1978 to May 31^st, 1979. The persons who participated in the first phase of the research were evaluated at other times, i.e., at school age when they were 8 to 11 years old, at the time of the military draft, and at the age of 23 to 25 years. This study used data collected at young adult age from April 2, 2002 to May 12, 2004.

SAMPLE

A total of 9,067 mothers of liveborns were first interviewed in 1978/79, representing 98% of the total number of liveborns in Ribeirão Preto during the study period. Children whose mothers did not reside in the city (2,094) and twins (146) were excluded. Thus, 6,827 liveborns were included in the first phase. A new evaluation was performed from 2002 to 2004 when the subjects were 23 to 25 years old. The following procedures were used to locate the cohort subjects: search of the addresses in the original birth charts, enrollment in schools, inscriptions in health plans and in the Unified Health system, military service, and search in the telephone list.

The survey revealed that 343 subjects had died and 819 were not identified, with 5,665 subjects thus having been located. This group was submitted to systematic selection, with the first of each three names being selected according to birth date and geographic region of the city. If the selected subject was not available, the next name down on the list was chosen. 705 subjects were lost to follow-up, due to the following reasons: refusal to participate (209), detention (31), death after 20 years of age (34), or failure to attend the interview (431). The losses were replaced using the same systematic selection, resulting in 2,063 subjects. In addition, 151 young adults were excluded because no information was available about their family income. Thus, the final sample for the present study consisted of 1,912 young adults.

POWER ANALYSIS

For this study, the power was 86.9% to detect a 10% difference in the prevalences between the compared groups for prevalences that were around 50%. The study power was 82.8% to detect a 5% difference between the groups for prevalences around 10%, assuming a 0.05 significance level.

STUDY VARIABLES

The family income of the young adults was determined using a question about this topic during the month preceding data collection. All sources of family income were considered: salaries, investment money, property income, donations by relatives, and any others. The variable family income did not consider the number of family members. The absolute values of this income were calculated as multiples of the Brazilian minimum wage (MW) for each period (R$ 260.00 in 2004), and income groups were categorized as less than 5 MW, 5 to 9.9 MW, 10 to 19.9 MW, and 20 MW or more.

The participants were submitted to physical examination and to blood collection performed by a doctor and a trained practical nurse. A 40 mL blood sample was obtained aseptically from the cubital vein after a fast of at least 12 hours for the determination of fasting glycemia and total cholesterol and fractions. University Hospital, Faculty of Medicine of Ribeirão Preto, Universidade de São Paulo The samples were processed and analyzed in the laboratories of the HCFMRP-USP, by the enzymatic colorimetric method using a Dade Behring Xpand instrument (Dade Behring^®, Liederbach, Germany) and Dade Behring Dimension (Liederbach, Germany) chemical reagents.Fasting plasma insulin and glucose were used to estimate insulin resistance (HOMA 1 - insulin resistance = fasting plasma glycemia x fasting plasma insulin/22.5, available at http://www.dtu.ox.ac.uk/index.php?maindoc=/homa/)¹²12. Wallace TM, Levy JC, Matthews DR. Use and abuse of HOMA modeling. Diabetes Care 2004; 27(6): 1487-95. http://doi.org/10.2337/diacare.27.6.1487
https://doi.org/http://doi.org/10.2337/d... .

Blood pressure was measured three times¹³13. Hense HW, Koivisto AM, Kuulasmaa K, Zaborskis A, Kupsc W, Tuomilehto J. Assessment of blood pressure measurement quality in the baseline surveys of the WHO MONICA project. J Hum Hypertens 1995; 9(12): 935-46. using a digital sphignomanometer adjusted to arm circumference The same evaluator made the measurements at 15-minute intervals, with the subject sitting and holding his left arm at the height of the heart. The mean value of the last two measurements was considered for analysis.

For the physical examination, the participants wore light clothing and were barefoot. Weight was measured with a mechanical scale (Filizola^®, Brazil) calibrated before each weighing, with 50 g precision. Height was measured with a Harpenden model wood stadiometer with 0.1 cm precision, with the subject standing up.

Body mass index (BMI) was calculated as weight divided by height squared (kg/m²). Waist circumference (WC) was measured with an inextensible metric tape positioned on the smallest circumference between the iliac crest and the last rib. This measurement was performed at the end of a normal expiration, with the subject standing up with a relaxed abdomen.

Total daily caloric intake (in kcal) and percent ingested fat (%) were calculated with the DietSys software, version 4.0 (National Cancer Institute, Bethesda, MD, USA), based on information obtained with a food frequency questionnaire validated for the Brazilian population¹⁴14. Ribeiro AB, Cardoso MA. Construção de um questionário de frequência alimentar como subsídio para programas de prevenção de doenças crônicas não transmissíveis. Rev Nutr 2002; 15(2): 239-45. http://dx.doi.org/10.1590/S1415-52732002000200012
https://doi.org/http://dx.doi.org/10.159... . Physical activity was determined using the short version of the International Physical Activity Questionnaire¹⁵15. Haskell WL, Lee IM, Pate RR, Powell KE, Blair SN, Franklin BA, et al. Physical activity and public health: update recommendations for the American College of Sports Medicine and the American Heart Association. Circulation 2007; 116(9): 1081-93. https://doi.org/10.1161/CIRCULATIONAHA.107.185649
https://doi.org/https://doi.org/10.1161/... . Smoking habit during the last 30 days was also obtained with a questionnaire.

The following variables were determined: Homeostatic Model Assessment of Insulin Resistance (HOMA IR - ≤ 2.15, normal or > 2.15, high¹⁶16. Yun K-J, Han K, Kim MK, Park Y-M, Baek K-H, Song K-H, et al. Insulin resistance distribuition and cut-off value in koreans from the 2008-2010 Korean National Health and Nutrition Examination Survey. Plos One 2016; 11(4): e0154593. http://doi.org/10.1371/journal.pone.0154593
https://doi.org/http://doi.org/10.1371/j... ), total cholesterol (< 240 mg/dL, normal or ≥ 240 mg/dL, high), low-density lipoprotein (LDL)-cholesterol (< 160 mg/dL, normal or ≥ 160 mg/dL, high), high-density lipoprotein (HDL)-cholesterol (< 50 mg/dL, low or ≥ 50 mg/dL, normal for women, < 40 mg/dL, low or ≥ 40 mg/dL, normal for men), triglycerides (< 150 mg/dL, normal or ≥ 150 mg/dL, high), fibrinogen (≤ 3.7 mg/dL, normal or > 3,7 mg/dL, high), diabetes (fasting glycemia > 126 mg/dL or use of a glycemia-lowering drug, or medical diagnosis), high blood pressure (systolic blood pressure ≥ 130 mm Hg, or diastolic blood pressure ≥ 85 mmHg), waist circumference (high when ≥ 90 cm for men or ≥ 85 cm for women), excessive caloric intake (> 2,900 kcal for men or > 2200 kcal for women)¹⁷17. Institute of Medicine/Food and Nutrition Board. Dietary reference intake for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and aminoacids (macronutrients). Washington, D.C.: National Academy Press, 2002. p. 697-736., smoking (no or yes), practicing physical activity (sedentary or non-sedentary), and total obesity when BMI was ≥ 30 kg/m².

The criteria of the Joint Interim Statement (JIS) were used to classify the metabolic syndrome (MS)¹⁸18. Alberti KG, Eckel RH, Grundy MW, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009; 120(16): 1640-5. https://doi.org/10.1161/CIRCULATIONAHA.109.192644
https://doi.org/https://doi.org/10.1161/... . The JIS considers MS to be present when three or more of the following five factors were detected: abdominal obesity when WC is ≥ 90 cm for men and ≥ 80 cm for women, hypertriglyceridemia (≥ 150 mg/dL), low HDL-cholesterol levels (< 40 mg/dL for men and < 50 mg/dL for women), systemic arterial hypertension (blood pressure ≥ 130/85 mmHg or the use of an antihypertensive drug), and high fasting glycemia (≥ 100 mg/dL).

The Framingham score was applied in order to determine the risk of death due to coronary disease. The Framingham risk equation was computed as the probability of developing a coronary event within 10 years according to sex, based on the following parameters: age, total cholesterol, HDL-cholesterol, smoking, systolic arterial pressure, diastolic arterial pressure, and diabetes. The risk of death due to coronary disease is low when less than 10%, moderate from 10 to 20% and high when more than 20%¹⁹19. D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care the Framingham Heart Study. Circulation 2008; 117(6): 743-53. http://doi.org/10.1161/CIRCULATIONAHA.107.699579
https://doi.org/http://doi.org/10.1161/C... . This score was used as a continuous variable.

STATISTICAL ANALYSIS

The data were weighted because of differential sampling losses at 23 to 25 years. Inverse probability of selection weighting was estimated by logistic regression based on birth weight, parity, preterm birth, marital status, maternal smoking, maternal age, maternal schooling, family income, and maternal occupation. Groups with lower follow-up rates were given greater weights, whereas the ones with higher participation rates were given smaller weights trying to recreate the original composition of the cohort at birth.

The independent variable was family income and the dependent ones were the cardiovascular risk factors. To determine the associations between family income and the cardiovascular risk factors, the χ² test was applied to the categorical variables and analysis of variance (ANOVA) or the Kruskal-Wallis test was applied to the numerical variables. P value for trend was also calculated for all cardiovascular risk factors.

Simple Poisson regressions with robust estimation of standard errors were performed to determine the association between family income and cardiovascular risk factors, with the level of significance set at 0.05. No adjustment for confounding was performed, since socioeconomic factors are distal factors in the theoretical model. Because we wanted to estimate the total effect, it would not make sense to adjust for mediators. We also did not adjust for age because the subjects were in a narrow age range (23 to 25 years). All analyses were stratified by sex, giving that a previous study conducted on the same sample had indicated that the associations between family income and adiposity varied between sexes²⁰20. Aitsi-Selmi A, Batty GD, Barbieri MA, Silva AAM, Cardoso VC, Goldani MZ, et al. Childhood socioeconomic position, adult socioeconomic position and social mobility in relation markers of adiposity in early adulthood: evidence of differential effects by gender in the 1978/79 Ribeirão Preto cohort study. Int J Obes 2012; 37: 439-47. http://doi.org/10.1038/ijo.2012.64
https://doi.org/http://doi.org/10.1038/i... . The STATA^® 14.0 software (College Station, TX, USA) was used for the analyses.

ETHICAL AND LEGAL ASPECTS

The study was approved by the Research Ethics committee of HCFMRP-USP (protocol No. 7606/99, on February 7, 2000), and all subjects gave written informed consent to participate.

RESULTS

When comparing the cardiovascular risk factors according to sex, women showed higher prevalences of diabetes (2.5%), low HDL-cholesterol (45.1%), high fibrinogen (15.5%), high caloric intake (25.3%), smoking (20.9%), and sedentarism (54.3%), whereas men presented higher prevalences of high HOMA IR (22.5%), high triglycerides (16.3%), high blood pressure (40.8%), and metabolic syndrome (17.8%). In addition, the Framingham score was higher among men (1.03%) compared to women (0.53) (Table 1).

The young adult women belonging to the low family income group had higher prevalences of insulin resistance (HOMA IR index - 19.8%; p = 0.039), low HDL-cholesterol (52.6%; p < 0.001), total obesity (14.6%; p = 0.003), abdominal obesity (18.5%; p < 0.001), MS (7.7%, p = 0.021), and high caloric intake (27.4%; p = 0.023), as well as a higher prevalence of sedentarism (58.5%; p < 0.001). The median cardiovascular risk measured by the Framingham score was low (0.46%), but higher (0.47%; p = 0.002) among low-income women compared to all others (Table 2).

Low-income young adult men had a higher prevalence of low HDL-cholesterol (40.3%; p = 0.023) and sedentarism (32.6%; p = 0.044) (Table 2). The Framingham score was very low for all groups (median: 0.86%) (Table 3).

In the Poisson regression models, the young adult women and men belonging to the low-income group were used as reference. High-income women had lower prevalences of insulin resistance (HOMA IR, PR = 0.57; p = 0.009), low HDL-cholesterol (PR = 0.47; p < 0.001), high blood pressure (PR = 0.28; p = 0.011), total obesity (PR = 0.22; p < 0.001), abdominal obesity (PR = 0.28; p < 0.001 MS (PR = 0.24; p = 0.001), high caloric intake (PR = 0.71; p = 0.008), and sedentarism (PR = 0.47; p < 0.001) (Table 4).

High-income young adult men had lower prevalences of low HDL-cholesterol (PR = .73; p = 0.026) and sedentarism (PR = 0.81; p = 0.029) (Table 5).

DISCUSSION

The present study investigated the associations between family income and cardiovascular risk factors among young adults participating in a cohort study in the city of Ribeirão Preto, São Paulo, Brazil. High-income women showed a lower prevalence of insulin resistance, low HDL-cholesterol, abdominal obesity, total obesity, high blood pressure, metabolic syndrome, high caloric intake, and sedentarism. High-income men presented a lower prevalence of low HDL-cholesterol and sedentarism.

The strong points of the study were the large sample size and the use of various cardiovascular risk factors: blood pressure, lipid profile, obesity, metabolic syndrome, dietary consumption, physical activity, smoking, diabetes, and insulin resistance using the HOMA-IR model, currently accepted for the identification of insulin resistance among young people. In addition, few studies about these aspects are available in low and middle-income countries.

Among the limitations of the study is the fact that, even though this is a birth cohort study, in this analysis, only cross-sectional data were used. Another limitation was the use of family income as the only indicator of the socioeconomic status of the subjects, without considering education. However, schooling did not have a discriminatory power since most subjects had a similar educational level (84.5% had more than 12 years of study).

Additional possible limitation could be selection bias, since subjects with a lower income at birth (25.9%) had lower participation rates (p < 0.001) in the follow-up than subjects with a higher income at birth (35.4%). This greater loss of data regarding income among poorer subjects may have prevented the detection of some differences or may have underestimated the associations presented here. In addition, some data about family income were missing (151 observations). In the statistical analysis, inverse probability of selection weighting was performed trying to mitigate selection bias.

The present results showed that low-income women had a worse cardiovascular profile than high-income women. Seven of the 15 cardiovascular risk factors investigated were more prevalent among low-income women, who also had a worse Framingham cardiovascular risk score. For men, only two of the 15 factors investigated were more prevalent among low-income subjects. In addition, there was no difference in the Framingham cardiovascular risk score among men.

Thus, it can be seen that the epidemiologic transition observed in Ribeirão Preto, a city in a middle-income country, occurred in a different manner according to sex: for women, the socioeconomic gradient of cardiovascular risk had already become inverted for almost the greatest part of the risk factors studied, suggesting that these women are already in the final phase of the epidemiologic transition. And for men, the socioeconomic gradient of cardiovascular risk became inverted only regarding two of the risk factors studied, suggesting that men are in the intermediate phase of the epidemiologic transition.

In this transition, the cardiovascular risk factors are first concentrated among high-income persons in high-income countries since these persons come in earlier contact with the “modern lifestyle”. Later, some factors such as behavioral, nutritional and educational changes, access to health services and a greater practice of physical exercise lead to a reduction of these cardiovascular risk factors in the high-income population, and finally start to affect low-income persons by leading them to a worsening of their cardiovascular risk factors⁷7. Dong C, Rundek T, Wright CB, Anwar Z, Elkind MS, Sacco RL. Ideal cardiovascular health predicts lower risks of myocardial infarction, stroke, and vascular death across whites, blacks, and Hispanics: the northern Manhattan study. Circulation 2012; 125(24): 2975-84. http://doi.org/10.1161/CIRCULATIONAHA.111.081083
https://doi.org/http://doi.org/10.1161/C... ^,88. Popkin BM. The nutrition and obesity in the developing world. J Nutr 2001; 131(3): 871S-3S. https://doi.org/10.1093/jn/131.3.871S
https://doi.org/https://doi.org/10.1093/... ^,2121. Lawlor DA, Harro M, Wadderkopp N, Andersen LB, Sardinha LB, Riddoch CJ, et al. Association of socioeconomic position with insulin resistance among children from Denmark, Estonia and Portugal: cross sectional study. BMJ 2005; 331(7510): 183. http://doi.org/10.1136/bmj.331.7510.183
https://doi.org/http://doi.org/10.1136/b... ^,2222. Elovainio M, Ferrie JE, Singh-Manoux A, Shipley M, Batty GD, Head J, et al. Socioeconomic differences in cardiometabolic factors: social causation or health related selection? Evidence from the Whitehall II Cohort Study, 1991-2004. Am J Epidemiol 2011; 174(7); 779-89. http://doi.org/10.1093/aje/kwr149
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In middle-income countries, the process of epidemiologic transition started at a later time than in high-income countries. In addition, there is the fact that this transition may occur in a different manner at each location in middle-income countries, as observed in the present study in which the transition was faster and the association between income and worse cardiovascular risk was inverted only among women⁹9. Samuel P, Antonisamy B, Raghupathy P, Richard J, Fall C. Socio-economic status and cardiovascular risk factors in rural and urban áreas of Velorre, Talminadu. South India. Int J Epidemio 2012; 41(5): 1315-27. http://doi.org/10.1093/ije/dys001
https://doi.org/http://doi.org/10.1093/i... ^,2323. Mayén AL, Marques-Vidal P, Paccaud F, Bovet P, Stringhini S. Socioeconomic determinants of dietary patterns in low and middle-income countries: a systematic review. Am J Clin Nutr 2014; 100(6): 1520-31. http://doi.org/10.3945/ajcn.114.089029
https://doi.org/http://doi.org/10.3945/a... . An Indian study on a population of an age similar to that of the present one detected a worsening of risk factors among their high-income subjects⁹9. Samuel P, Antonisamy B, Raghupathy P, Richard J, Fall C. Socio-economic status and cardiovascular risk factors in rural and urban áreas of Velorre, Talminadu. South India. Int J Epidemio 2012; 41(5): 1315-27. http://doi.org/10.1093/ije/dys001
https://doi.org/http://doi.org/10.1093/i... , whereas a study conducted in the United States on a Hispanic population revealed that, despite the older age of the sample, high-income was associated with a reduction of risk factors²⁴24. Giardina EV, Paul TK, Hayes D, Sciacca RR. Cardiovascular disease risk among young urban women. J Women Health (Lamchmt) 2016; 25(11): 1139-46. https://doi.org/10.1089/jwh.2015.5697
https://doi.org/https://doi.org/10.1089/... . The same has been found among elderly residents in São Paulo, Brazil, where low-income groups had higher CVD risk²⁵25. Massa KHC, Pabayo R, Lebrão ML, Chiavegatto Filho ADP. Environmental factors and cardiovascular diseases: the association of income inequality and green spaces in elderly residents of São Paulo, Brazil. BMJ Open 2016; 6: e011850. http://doi.org/10.1136/bmjopen-201601185
https://doi.org/http://doi.org/10.1136/b... .

The high-income women studied here showed a lower cardiovascular risk and completed the epidemiologic transition process before the men did. This fact may have been due to the greater concern of these women about consuming less caloric foods. Thus, their greater access to information and better financial conditions favor a healthy and balanced diet²⁵25. Massa KHC, Pabayo R, Lebrão ML, Chiavegatto Filho ADP. Environmental factors and cardiovascular diseases: the association of income inequality and green spaces in elderly residents of São Paulo, Brazil. BMJ Open 2016; 6: e011850. http://doi.org/10.1136/bmjopen-201601185
https://doi.org/http://doi.org/10.1136/b... . On the other hand, low-income women showed a higher caloric intake and were more sedentary, a fact that may have contributed to their higher prevalences of total obesity and abdominal obesity and of other cardiovascular risk factors²⁶26. Lang SJ, Abel GA, Mant J, Mullis R. Impact of socioeconomic deprivation on screening for cardiovascular disease risk in a primary prevention population: a cross-sectional study. BMJ Open. 2016; 6: e009984. http://doi.org/10.1136/bmjopen-2015-009984
https://doi.org/http://doi.org/10.1136/b... .

The greater practice of physical activity by high-income young adult women may be explained by their greater concern about having a “pleasant and healthy body”. Thus, due to their greater health awareness, they adhere better to the practice of physical activity. This may have contributed to the fact that their BMI values are lower, with consequent lower prevalences of obesity and higher HDL-cholesterol²⁷27. Lindgren M, Börjesson M, Ekblom O, Bergström G, Lappas G, Rosengren A. Physical activity pattern, cardiorespiratory fitness, and socioeconomic status in the SCAPIS pilot trial- A cross sectional study. Prev Med Rep 2016; 4; 44-9. http://doi.org/10.1016/j.pmedr.2016.04.010
https://doi.org/http://doi.org/10.1016/j... .

In agreement with another study, high-income women also showed lower prevalence of insulin resistance²⁸28. Tao X, Li J, Zhu X, Zhao B, Sun J, Ji L, et al. Association between socioeconomic status and metabolic control and diabetes complications: a cross-sectional nationwide study in Chinese adults with type 2 diabetes mellitus. Cardiovas Diabetol 2016; 15: 61. http://doi.org/10.1186/s12933-016-0376-7
https://doi.org/http://doi.org/10.1186/s... . Although the prevalence of diabetes is low among young adults, the lower presence of insulin resistance favors lower odds of developing diabetes. The high-income women in the present study also showed lower prevalence of MS, which placed them in a situation similar to that encountered in higher income countries²⁹29. Gannar F, de León CA, Díaz BB, Pérez MCR, Rodríguez IM, Dahmen FB, et al. Social class and metabolic syndrome in populations from Tunisia and Spain. Diabetol Meta Syndr. 2015; 7: 88. http://doi.org/10.1186/s13098-015-0084-6
https://doi.org/http://doi.org/10.1186/s... .

Higher income women exhibited a better cardiovascular risk profile than men belonging to the same income class, a result in agreement with a study conducted in the United States³⁰30. Winkleby MA, Kraemer HC, Ahn DK, Varady NA. Ethnic and socioeconomic differences in cardiovascular disease risk factors: findings for women from the Third National Health and Nutrition Examination Survey, 1988-1994. JAMA 1998; 280(4): 356-62. http://doi.org/10.1001/jama.280.4.356
https://doi.org/http://doi.org/10.1001/j... . This may be explained by the fact that high-income women pay more attention to a healthy diet, to weight reduction and to physical activity, with their education possibly having positive effects of an economic and psychosocial order and protecting against adverse situations.

Kandasamy and Anand³¹31. Kandasamy S, Anand SS. Cardiovascular disease among women from vulnerable populations: a review. Can J Cardiol 2018; 34(4): 450-7. http://doi.org/10.1016/j.cjca.2018.01.017
https://doi.org/http://doi.org/10.1016/j... pointed out that, because of the genetic and hormonal characteristics and contraceptive use, women have higher risk of increased cardiovascular risk factors and cardiovascular diseases when compared to men. In addition to these risks, these authors affirm that being a woman and having low family income induce more problems and risks, often due to an array of social and structural circumstances, such as fragmented health care, social isolation, language difficulties, violence, caregiving burden, stress at home and early childhood adversity. Besides that, those with the lowest family income are least likely to access health services resources and treatments.

CONCLUSION

Low-income women had a worse cardiovascular risk than high-income women, in agreement with the epidemiologic transition that has occurred in high-income countries. In contrast, among men, there was no difference in cardiovascular risk according to family income, suggesting that men are still in the intermediate phase of the epidemiologic transition. Although the present sample consisted of a young population, the prevalence of some cardiovascular risk factors was already high.

ACKNOWLEDGMENTS

The authors wish to thank all the persons who participated in the planning of the research and in data collection and typing, as well as the subjects who accepted to participate in the investigation.

REFERENCES

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