Variability in Cardiovascular Risk Factor Control in Patients with Heart Failure According to Gender and Socioeconomic Status

Abstract

Background:

Despite considerable evidence concerning heart failure (HF) risk factors, there is scarce information about the effect and degree of control regarding socioeconomic and gender inequalities.

Methods:

Cohort study including HF patients >40 years of age attended in 53 primary health care centers in Barcelona (Spain). Socioeconomic status (SES) was determined by an aggregated deprivation index (MEDEA) according to the neighborhood of residence. Logistic multivariable regression was performed to analyze differences in cardiovascular risk factor control, stratifying by SES and sex.

Results:

A total of 8235 HF patients were included. Mean age was 78.1 (standard deviation 10.2) years, and 56.0% were women. The most prevalent cardiovascular risk factors were hypertension, diabetes, and dyslipidemia. Blood pressure was the worst controlled factor in both genders with the lowest SES (odds ratio [OR] 0.56 95% confidence interval [CI] 0.56–0.71) and (OR 0.52, 0.46–0.71), respectively. In women, a social gradient was observed for glycemic and body mass index control, which were worse in the most unfavorable socioeconomic position (OR 0.54, 95% CI 0.38–0.77), and (OR 0.45, 95% CI 0.32–0.64), respectively. Men presented worse control of blood pressure (OR 0.55, 95% CI 0.42–0.71) and smoking habit (OR 0.67, 95% CI 0.47–0.90) in the most deprived socioeconomic bracket.

Conclusion:

Patients with HF in the most disadvantaged socioeconomic levels presented the worst degree of control for cardiovascular risk factors, and this negative effect was stronger in women.

Introduction

The management of chronic diseases such as heart failure (HF) is an increasing public health concern worldwide.¹ While in recent years, the overall HF incidence rate has declined, its prevalence has increased, suggesting that survival over time is longer, probably due to aging, better care, and HF treatment.^2
–4 Nevertheless, improvement in survival is modest, and mortality 5 years after diagnosis is still close to 48.2%.⁵

Despite the various health care systems that have been established socioeconomic inequalities continue to be present and persistent in industrialized countries.⁶

Studies have shown a worse prognosis regarding socioeconomic status (SES)^6

–9 psychosocial factors,^10
–12 place of residence,^13
–15 and gender.^16
–18 Despite the increased interest of several organizations in studying sex differences in cardiovascular diseases, only a small proportion of articles have been published on this topic in the last 10 years.¹⁹

Even though many predictors of mortality and hospitalization among HF patients have been well identified,²⁰ the degree of control of various HF risk factors according to SES or gender has not usually been analyzed, and whether the optimal control of the different cardiovascular risk factors is equitable remains uncertain.

Our study is therefore aimed at analyzing socioeconomic and gender inequalities in the degree of control of a number of risk factors (hypertension, diabetes, dyslipidemia, obesity, and smoking habit) of patients registered as HF in primary health care records.

Methods

A population-based, cohort study of patients >40 years of age with registered HF diagnosis (ICD-10: I50) attended in primary health care centers (Barcelona, Spain) between January 1, 2009, and December 31, 2012. The relationship between SES and gender in the control of cardiovascular risk factors was assessed.

Information was collected from the primary care electronic medical records through the SIDIAP database (Information System for the Development of Research in Primary Care System). This database incorporates sociodemographic (age, sex, and SES) and clinical information. All data were encrypted to ensure confidentiality and anonymization.

The ICD 10 codes selected to register risk factors were as follows: hypertension (I10–I15), obesity (E66), diabetes (E10–E14), dyslipidemia (E78), and smoking habit (F17). The analyzed comorbidities included the following: coronary heart disease (I20–I25), stroke (I63–I65), atrial fibrillation (I48), peripheral artery disease (I73), chronic kidney disease (N18), depression (F32–F33), chronic pulmonary obstructive disease (J44), and anemia (D50–D63). Information concerning the prescription of angiotensin-converting enzyme inhibitors, angiotensin receptor antagonists, beta-blockers, loop diuretics, and mineralocorticoid receptor antagonists was also collected.

The MEDEA Index²¹ was employed to determine SES. This is an aggregated model based on small areas (census tracts), including unemployment, percentage of manual and temporary workers, and population with insufficient education (less than primary school). The lowest quintile represents individuals with the most favorable socioeconomic position (Q1), and the upper one the worst (Q5). The index has been shown to be valid for urban areas as a proxy of individual SES.

For blood pressure, we used as gold standard the hypertension guide from the European Society of Cardiology 2018,²² and for glycemic control and low-density lipoprotein, the Diabetes and Dyslipidemia Guide from the European Society of Cardiology 2019.^23,24

Statistical analysis

A descriptive analysis was performed to categorize patient characteristics. Categorical variables were summarized by percentages, and continuous ones with mean and standard deviation (SD). To evaluate the relationship between the independent variables with the outcome of control according to SES and sex, the chi squared test and parametric analysis of variance (ANOVA) were used when appropriate.

The association between SES deprivation and gender with cardiovascular risk factor control was evaluated with multivariable logistic regression. We stratified the analysis of each variable according to sex, and adjusted each model for age and socioeconomic level.

Data analysis was performed using the statistical package STATA V 11.0 and R package.

Ethical considerations

The SIDIAP database ensures the anonymization of patients and guarantees confidentiality. The study was approved by the local Clinical Ethics Committee (Primary Health care University Research Institute IDIAPJGol), reference number P13/052.

Results

We included all patients >40 years of age registered with HF diagnosis (ICD-10: I50) from January 1, 2009, to December 31, 2012, in the electronic medical records of the 52 primary care centers in Barcelona belonging to the Institut Catala de la Salut.

Mean age was 78.1 (SD 10.2) years, and women represented 56.0% of the sample.

Characteristics of participants according to sex and SES

Table 1 presents the distribution of population according to the SES deprivation index stratified by sex. The most frequent risk factors associated with HF were hypertension 76.1%, diabetes 32.9%, dyslipidemia 29.6%, and obesity 22.0%.

Table 1.

Clinical Characteristics of Patients with Heart Failure According to Socioeconomic Deprivation (Q1: Less Disadvantaged to Q5: More Disadvantaged)

	Overall	Q1		p	Q2		p	Q3		p	Q4		p	Q5		p
	Overall	Women	Men	p	Women	Men	p	Women	Men	p	Women	Men	p	Women	Men	p
n = 8235		906	738		912	688		976	712		909	743		905	746
Age (mean, SD)	78.1 (10.2)	81.9 (9.2)	77.0 (10.8)	0.000	80.7 (8.9)	75.5 (11.0)	0.000	80.1 (8.5)	75.74 (10.8)	0.000	79.7 (8.9)	74.8 (10.4)	0.000	78.2 (9.4)	74.0 (11.1)	<0.001
Cardiovascular risk factors, %
Hypertension	6263 (76.1)	689 (76.0)	531 (71.9)	0.059	733 (80.3)	481 (69.9)	0.000	785 (80.4)	490 (68.8)	0.000	741 (81.5)	548 (73.7)	0.000	755 (83.4)	510 (68.3)	<0.001
Diabetes	2713 (32.9)	203 (22.4)	230 (31.1)	0.000	262 (28.7)	250 (36.3)	0.001	280 (28.6)	273 (38.3)	0.000	274 (30.1)	287 (38.6)	0.000	356 (39.3)	298 (39.9)	0.801
Dyslipidemia	2439 (29.6)	235 (25.9)	182 (24.6)	0.554	288 (31.5)	203 (29.5)	0.373	325 (33.3)	213 (29.9)	0.141	285 (31.3)	209 (28.1)	0.155	282 (31.1)	217 (29.0)	0.362
Obesity	1812 (22.0)	123 (13.5)	85 (11.5)	0.212	191 (20.9)	104 (15.1)	0.003	255 (26.1)	122 (17.1)	0.000	263 (28.9)	149 (20.0)	0.000	358 (39.5)	162 (21.7)	<0.001
Smoking habit	668 (8.10)	24 (2.6)	87 (11.7)	0.000	19 (2.2)	104 (15.1)	0.000	21 (2.3)	107 (15.0)	0.000	36 (3.9)	108 (14.5)	0.000	122 (2.6)	140 (18.7)	<0.001
Cardiovascular diseases, %
Coronary heart disease	2194 (26.6)	163 (17.9)	274 (37.1)	0.000	177 (19.4)	262 (38.0)	0.000	178 (18.2)	268 (37.6)	0.000	152 (16.7)	289 (38.9)	0.000	174 (19.2)	257 (34.4)	<0.001
Atrial fibrillation	2989 (36.3)	297 (32.7)	259 (35.0)	0.324	346 (37.9)	247 (35.9)	0.403	378 (38.7)	268 (37.6)	0.649	358 (39.3)	247 (33.2)	0.010	350 (38.6)	239 (32.0)	0.005
Stroke	826 (10.0)	63 (6.9)	81 (10.9)	0.004	84 (9.2)	80 (11.6)	0.114	82 (8.4)	101 (14.1)	0.000	83 (9.1)	76 (10.2)	0.452	84 (9.2)	92 (12.3)	0.046
Peripheral artery disease	503 (6.1)	29 (3.2)	52 (7.0)	0.000	18 (1.9)	76 (11.0)	0.000	33 (3.3)	78 (10.9)	0.000	31 (3.4)	68 (9.1)	0.000	33 (3.6)	85 (11.3)	<0.001
Other comorbidities, %
Anemia	730 (8.8)	71 (7.8)	49 (6.6)	0.353	85 (9.3)	53 (7.7)	0.254	94 (9.6)	71 (9.9)	0.816	76 (8.3)	65 (8.7)	0.779	113 (12.4)	53 (7.1)	<0.001
Chronic renal failure	1516 (18.4)	137 (15.1)	127 (17.2)	0.252	175 (19.1)	136 (19.7)	0.772	163 (16.7)	146 (20.5)	0.046	156 (17.1)	131 (17.6)	0.802	190 (20.9)	155 (20.7)	0.914
Depression	1363 (16.5)	177 (19.5)	79 (10.7)	0.000	212 (23.2)	71 (10.3)	0.000	229 (23.4)	77 (10.8)	0.000	197 (21.6)	63 (8.4)	0.000	198 (21.8)	60 (8.0)	<0.001
Chronic pulmonary obstructive disease	1326 (16.1)	56 (6.1)	143 (19.4)	0.000	78 (8.5)	161 (23.4)	0.000	98 (10.0)	200 (28.0)	0.000	92 (10.1)	184 (24.7)	0.000	83 (9.1)	231 (30.9)	<0.001
Drug therapy related to HF, %
Beta-blockers	2907 (35.3)	407 (44.9)	385 (52.1)	0.003	405 (44.4)	386 (56.1)	0.000	464 (47.5)	365 (51.2)	0.131	421 (46.3)	420 (56.5)	0.000	455 (50.2)	377 (50.5)	0.916
ACEi/ARB	6198 (75.2)	593 (65.4)	522 (70.7)	0.023	675 (74.0)	511 (74.2)	0.906	758 (77.6)	538 (75.5)	0.312	708 (77.8)	602 (81.0)	0.118	712 (78.6)	579 (77.6)	0.604
Loop diuretics	6238 (75.7)	625 (68.9)	511 (69.2)	0.911	681 (74.6)	487 (70.7)	0.083	747 (76.5)	538 (75.5)	0.643	732 (80.5)	566 (76.1)	0.032	750 (82.8)	601 (80.5)	0.226
MRA	1225 (14.8)	133 (14.6)	124 (16.8)	0.239	129 (14.1)	102 (14.8)	0.701	139 (14.2)	114 (16.0)	0.315	125 (13.7)	122 (16.4)	0.130	120 (13.2)	117 (15.6)	0.162

ACEi, angiotensin-converting enzyme inhibitors; ARB, angiotensin receptor antagonist; HR, heart failure; MRA, mineralocorticoid receptor antagonist; SD, standard deviation.

Women presented a higher prevalence of hypertension and obesity than men, particularly in the most socioeconomically deprived groups. In contrast, men were more commonly diabetics and smokers.

Regarding established cardiovascular diseases, atrial fibrillation and coronary heart disease represented the most common comorbidities (36.3% and 26.6%, respectively). Coronary heart disease and peripheral artery disease were more frequent in men, regardless of socioeconomic level. A higher percentage of atrial fibrillation was observed in women than men in the Q4 to Q5 deprivation levels.

Among patients with other comorbidities, in all SES, quintile depression was more common in women, and chronic obstructive pulmonary disease more frequently observed in men.

No consistent differences were found for HF prescribed treatment according to SES or gender, with the exception of beta-blockers, which were more common in men.

Control of cardiovascular risk factors

Figure 1 depicts the distribution of control of cardiovascular risk factors. Hypertension and smoking habit were the best controlled (74.8% and 92.0%, respectively). Men had better results in blood pressure and low-density lipoprotein, while women had better glycemic management and were more frequently nonsmokers.

FIG. 1.

Control of cardiovascular risk factors according sex among patients with HF. HF, heart failure.

Analyses according to SES, adjusted by age, revealed worse control of blood pressure, glycated hemoglobin, body mass index, and smoking habit in the most deprived strata (Table 2).

Table 2.

Control of Cardiovascular Risk Factors in Patients with Heart Failure According to Socioeconomic Deprivation Index (Q1: Less Deprivation to Q5: More Deprivation), Adjusted by Age and Sex

	SES	Crude analysis		p	Adjusted analysis		p
	SES	OR	95% CI	p	OR	95% CI	p
Blood pressure (≤140/≤90 mmHg)	1 (less disadvantaged)	1			1
	2	0.727	0.609–0.867	0.000	0.729	0.611–0.869	<0.001
	3	0.703	0.591–0.835	0.000	0.704	0.592–0.838	<0.001
	4	0.725	0.609–0.862	0.000	0.727	0.611–0.866	<0.001
	5 (more disadvantaged)	0.557	0.470–0.659	0.000	0.560	0.472–0.664	<0.001
HbA1C <7%	1 (less disadvantaged)	1			1
	2	0.920	0.712–1.189	0.526	0.933	0.722–1.206	0.600
	3	0.896	0.697–1.152	0.395	0.908	0.706–1.168	0.455
	4	0.824	0.642–1.059	0.131	0.850	0.661–1.093	0.208
	5 (more disadvantaged)	0.656	0.516–0.834	0.001	0.682	0.535–0.868	0.002
LDL (<100 mg/dL)	1 (less disadvantaged)	1			1
	2	1.141	0.952–1.368	0.152	1.143	0.953–1.370	0.148
	3	0.976	0.816–1.167	0.795	0.978	0.818–1.169	0.811
	4	1.057	0.884–1.264	0.538	1.060	0.886–1.268	0.520
	5 (more disadvantaged)	1.181	0.990–1.409	0.064	1.185	0.993–1.415	0.060
Body mass index (18.5–25.0 kg/m²)	1 (less disadvantaged)	1			1
	2	0.805	0.636–1.019	0.072	0.843	0.664–1.070	0.161
	3	0.699	0.553–0.884	0.003	0.728	0.574–0.923	0.009
	4	0.631	0.496–0.802	0.000	0.669	0.524–0.853	0.001
	5 (more disadvantaged)	0.611	0.479–0.779	0.000	0.677	0.529–0.865	0.002
Smoking habit	1 (less disadvantaged)	1			1
	2	0.869	0.666–1.134	0.303	0.908	0.684–1.205	0.507
	3	0.875	0.672–1.138	0.321	0.886	0.670–1.172	0.399
	4	0.854	0.656–1.112	0.243	0.955	0.722–1.263	0.750
	5 (more disadvantaged)	0.606	0.473–0.777	0.000	0.709	0.544–0.924	0.011

CI, confidence interval; HbA1C, glycosylated hemoglobin; LDL, low-density lipoprotein; OR, odds ratio; SES, socioeconomic status.

When stratifying patients according to sex and SES, we found that the population in the most disadvantaged socioeconomic quintile had the worst blood pressure control for both sexes (Table 3). In general, weight was the most difficult target to achieve. Nevertheless, women with greater SES presented a better proportion of recommended body mass index levels. Smoking habit showed a gradient in men: there were more smokers in the most socioeconomically deprived quintiles.

Table 3.

Control of Cardiovascular Risk Factors Among Patients with Heart Failure According to the Socioeconomic Deprivation Index by Sex (Q1: Less Deprivation to Q5: More Deprivation)

	N total	Women						Men
	N total	Q1	Q2	Q3	Q4	Q5	p	Q1	Q2	Q3	Q4	Q5	p
Blood pressure (SBP ≤140 and DBP ≤90 mmHg), n (%)	5656	640 (79.7)	607 (73.3)	667 (73.2)	628 (73.9)	594 (68.9)	<0.001	522 (81.5)	488 (77.3)	493 (76.0)	526 (76.2)	491 (70.6)	<0.001
Glycemic control (HbA1C ≤7%), n (%)	2306	212 (77.6)	252 (70.9)	292 (72.2)	258 (68.6)	300 (64.2)	0.002	149 (64.7)	209 (68.9)	205 (65.9)	220 (66.6)	209 (60.2)	0.193
Low-density lipoprotein (LDL <100 mg/dL), n (%)	2289	167 (33.0)	234 (38.1)	239 (34.9)	222 (34.6)	267 (39.3)	0.126	189 (50.1)	225 (51.1)	223 (46.7)	259 (50.5)	264 (51.1)	0.628
Body mass index (18.5–25.0 kg/m²), n (%)	814	104 (25.6)	90 (18.7)	85 (15.6)	77 (15.1)	63 (12.1)	<0.001	78 (20.3)	79 (20.2)	83 (19.4)	73 (16.7)	82 (19.6)	0.672
Smoking habit (non smoking), n (%)	7567	882 (97.3)	893 (97.9)	954 (97.7)	888 (97.6)	869 (96.0)	0.080	651 (88.2)	584 (84.8)	605 (84.9)	635 (85.4)	606 (81.2)	0.006

DBP, diastolic blood pressure; SBP, systolic blood pressure.

Multivariable adjusted analyses stratified by sex confirmed that in the most disadvantaged SES quintiles, blood pressure, glycemic levels, and weight were the worst controlled for women. In the case of men, we only observed a worse risk factor control for blood pressure and smoking habit (Fig. 2).

FIG. 2.

Control of cardiovascular risk factors in patients with HF according to socioeconomic deprivation and sex (Q1: less socioeconomic deprivation; Q5: more socioeconomic deprivation).

Discussion

In this study, we found that HF patients from the most disadvantaged socioeconomic levels presented the worst degree of control for blood pressure, glycemia, and body mass index, and were more frequently smokers. When stratifying by gender, these differences persisted in women for blood pressure, glycemia, and body mass index, and in men for blood pressure and smoking.

Compared with other published studies, our population was older, and women were more represented.^25,26 Such differences may be due to the specific characteristics of a Mediterranean population: Spanish women have the longest life expectancy in Europe.²⁷

The prevalence of cardiovascular factors observed in our cohort was similar to those reported in previous studies carried out in primary care in Spain.²⁸ We observed, however, differences between our data and those from other countries regarding the prevalence of cardiovascular risk factors and cardiovascular disease, in particular, hypertension, coronary heart disease, and smoking habit.^25,26

In relation to the analyses stratified by sex, women were older. In contrast to men, they presented hypertension and obesity more frequently, while coronary heart disease was less common. Such sex-related differences, including worse control of blood pressure, concur with those observed in previous studies.^29

–32 Although the causes have not been properly ascertained, it has been hypothesized that following adequate lifestyles leading to better control of cardiovascular risk factors is more difficult for women, probably due to income, social role, education, and culture.³³ In contrast, male HF patients with lower SES appear to be particularly affected by tobacco use disorders.³⁴

Socioeconomic position has been conceptualized and measured in a number of ways, including social class/occupation, neighborhood, socioeconomic factors, educational attainment, and income. We employed a complex index as a proxy of SES, and observed that patients in the most unfavorable SES quintile had the worst risk factor control. Low SES has been linked to the development of cardiovascular disease and may confer a risk that is equivalent to traditional risk factors.³⁵ A Danish article concluded that low income and educational level negatively affected survival of HF patients. The authors suggested that factors such as the prescribed medication and patient health literacy may be key to understanding the mechanisms behind socioeconomic inequalities.³⁶

Concerning the combined effect of gender and SES, a recent meta-analysis, including over 22 million individuals, concluded that there was a significant excess risk of cardiovascular disease in women with lower educational attainment compared to men.³⁷

Future research is required to understand the underlying mechanisms producing inequalities in the control of risk factors. Improving knowledge regarding the differences between genders with respect to SES may help define effective interventions in the most socioeconomically vulnerable populations.

Limitations and strengths

To the best of our knowledge, this article is the first to assess the combined roles of socioeconomic deprivation and gender with the degree of cardiovascular factor risk control in our country.

We analyzed a large sample of community-based patients, including a high percentage of women, unlike other studies where they are usually underrepresented.

Despite being an aggregate index, MEDEA is a well-tested proxy of individual socioeconomic deprivation. It has been demonstrated that the socioeconomic deprivation of a given area provides an approximation of characteristics that may affect individual health.³⁸

Some clinical information, such as left ventricular ejection fraction values and New York Heart Association (NYHA) functional class classification, was unavailable. Nevertheless, for the purpose of our study, it was not considered relevant.

Conclusion

Patients with HF in the most disadvantaged socioeconomic levels presented the worst degree of control for cardiovascular risk factors, and this negative effect was stronger in women.

Footnotes

Acknowledgments

The authors gratefully acknowledge the participation of the Catalan Health Institute, and the SIDIAP (Information System for the Development of Research in Primary Care System) in particular, which provided the database for the study.

Authors' Contributions

R.G. and M.-A.M. designed the study protocol, wrote the first draft of the article, interpreted the results, and reviewed the final version. R.G. and E.N. performed the statistical analyses. J.-M.V.-R. and E.V. contributed with the interpretation of results and the revision of the final version of the article.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This article has been supported by a grant from the Institut Universitari d'Investigació en Atenció Primària Jordi Gol (IDIAP Jordi Gol), providing data from the SIDIAP database. GRANT NUMBER: 4R15/008-1.

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