|Year : 2022 | Volume
| Issue : 1 | Page : 78
Social, economic, technological, and environmental factors affecting cardiovascular diseases: A systematic review and thematic analysis
Gisoo Alizadeh1, Kamal Gholipour2, Saber Azami-Aghdash3, Reza Dehnavieh4, Mohammad Asghari JafarAbadi5, Mehrdad Azmin6, Rahim Khodayari-Zarnaq7
1 Department of Health policy and Management, Iranian Center of Excellence in Health Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
2 Tabriz Health Services Management Research Center, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
3 Tabriz Health Services Management Research Center, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran
4 Health Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
5 Road Traffic Injury Research Center, Tabriz University of Medical Sciences; Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
6 Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
7 Department of Health policy and Management, Iranian Center of Excellence in Health Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences; Tabriz Health Services Management Research Center, Health Management and Safety Promotion Research Institute, Tabriz University of Medical Sciences, Tehran, Iran
|Date of Submission||02-Mar-2020|
|Date of Acceptance||27-Jul-2020|
|Date of Web Publication||27-Apr-2022|
School of Management and Medical Informatics, Daneshgah Street, Tabriz
Source of Support: None, Conflict of Interest: None
Background: Today, cardiovascular disease (CVD) is the leading cause of mortality in both sexes. There are several risk factors for heart diseases; some controllable, others not. However, socioeconomic, technological, and environmental factors can impact CVD as well as exclusive risk factors. Accurate identification and assessment of these factors are often difficult. In the present systematic review, we aimed to explore factors affecting CVD. Methods: Multiple databases (MEDLINE, Scopus, ISI Web of Science, and Cochrane) and gray literature were searched. The included studies described at least one determinant of CVD. The framework method was applied to analyze the qualitative data. Results: A total of 64 studies from 26 countries were included. The contextual determinants of CVD were categorized into 45 determinants, 15 factors, and 4 main social, economic, technological, and environmental categories. The 15 potentially reversible factors were identified as sociodemographic, violence, smoking, occupation, positive childhood experience, social inequalities, psychological distress, eating habits, neighborhood, family income, rapid technology, environmental pollution, living environments, noise, and disaster. Conclusions: Devolution and more efficient health policies are required to achieve further sustained reduction in CVD mortality, increase life expectancy, and reduce its associated risk factors. Policymakers should fully address the value of social, economic, technological, and environmental factors. In fact, a prevention agenda should be developed and updated collaboratively in terms of the determinant factors.
Keywords: Cardiovascular disease, economic, environmental, health system, social, technology
|How to cite this article:|
Alizadeh G, Gholipour K, Azami-Aghdash S, Dehnavieh R, JafarAbadi MA, Azmin M, Khodayari-Zarnaq R. Social, economic, technological, and environmental factors affecting cardiovascular diseases: A systematic review and thematic analysis. Int J Prev Med 2022;13:78
|How to cite this URL:|
Alizadeh G, Gholipour K, Azami-Aghdash S, Dehnavieh R, JafarAbadi MA, Azmin M, Khodayari-Zarnaq R. Social, economic, technological, and environmental factors affecting cardiovascular diseases: A systematic review and thematic analysis. Int J Prev Med [serial online] 2022 [cited 2022 May 19];13:78. Available from: https://www.ijpvmjournal.net/text.asp?2022/13/1/78/344216
| Introduction|| |
According to the Global Burden of Disease Study's report,,, noncommunicable diseases (NCDs) are the leading cause of mortality worldwide. The four main NCDs are cardiovascular diseases (CVD), cancers, respiratory diseases, and diabetes. Cardiovascular diseases remain the main cause of premature death and disability worldwide. The number of CVD-related deaths is expected to rise to 23.3 million by the year 2030. Furthermore, by 2030, medical burdens of CVD are predicted to increase by about 100%., The CVD risk factors were categorized into two groups of behavioral and metabolic risk factors. Behavioral risk factors include unhealthy diets (salty food, fat, and sugars), physical inactivity, addiction to alcohol and tobacco, high body mass index (BMI) and waist-to-hip ratio. Metabolic risk factors include hyperglycemia, hyperlipidemia, inflammation, and raised blood pressure., Moreover, socioeconomic discriminations, psychosocial stress, living in deprived conditions, and risky behaviors are associated with NCDs. A systematic review revealed that in many countries, the low socioeconomic status factors were drinking alcohol, tobacco use, and insufficient consumption of fruits and vegetables. The socioeconomic factors were inactivity and consuming excess fat, salt, and processed food. The results of some studies showed that having high-quality social relationships was linked to decreased health risks (e.g., immune functioning, cardiovascular functioning, and cognitive decline), while experiencing low-quality social relationships increased the risks.,, Actually, risk factors for NCDs are multi-dimensional, comprising biological, social, behavioral, economic, and environmental factors. Therefore, political, social, cultural, and economic issues need to be considered in the prevention and control of NCDs.
Prevention programs such as the “25 by 25” campaign aim to reduce premature mortality from CVD by 25% by 2025. In fact, they focus on reducing behavioral and metabolic influences on the risk of CVD, but the long-term success of such lifestyle-related decision-making is multifactorial. However, the prevention of CVD risk factors is a high-ranking priority for all health policy planners. Nevertheless, an understanding of the community and household determinants of major cardiovascular risk factors, which may vary by geographical region and cultural background, is needed to develop prevention strategies. For instance, context-dependent strategies must be evaluated to ensure their efficiency. Furthermore, interventions are needed to decrease barriers to cardiovascular healthiness. These strategies must encompass family and community contexts, small groups, interactive methods, culturally sensitive materials, and valid data sources.
Therefore, the aim of this study was to review the social, economic, technological, and environmental factors of CVDs. The result of this review can help policymakers and health managers in the decision-making process to develop effective interventions for CVD patients.
| Methods|| |
Using a systematic review method, this study was conducted to review published studies that had investigated the determinants of CVD.
A comprehensive database search for qualitative and quantitative studies and expert opinions between 2002 and 2019 was carried out in PubMed, Scopus, ISI Web of Science, and Cochrane. Reference lists of other reviews were hand-searched to find additional studies. The following keywords were searched: factors, strategy, driver, driving force, cardiovascular diseases, non-communicable diseases, heart attack, myocardial infarction, control, prevention, social, technological, environmental, economic, socio-cultural and ecological. The full search strategy has been provided as supplementary material. Where possible, authors were contacted to obtain full-text publications of relevant abstracts. Studies published only as an abstract were excluded. The search strategy proposed for the PubMed database is shown in [Table 1]. With some modifications, this strategy was used for the other databases as well.
Study inclusion criteria
Published studies associated with CVD and studies that described at least one CVD determinant were included. Conference paper abstracts (where full analysis was not available), case reports, and studies with low quality in methodology, based on the Joanna Briggs Institute (JBI) checklist, were excluded.
Study selection process
The title and abstract of each article were reviewed independently by two reviewers. The full texts of the studies were then retrieved and independently assessed for inclusion or exclusion by the reviewers. Disagreements on the eligibility of studies were resolved either through discussion between the reviewers or by a third party.
Assessment of the studies' reporting quality
The reporting qualities of the studies were evaluated by the JBI checklist. The JBI critical appraisal checklist is not intended to be used as a scoring system to determine the grade of the study, but to evaluate the risk of bias. The checklists consist of items that assess selection, performance, detection, and attrition bias, as well as trial designs. Items in the two checklists have four possible responses: “yes,” “no,” “unclear,” and “inapplicable.” Studies were excluded if they received less than four “yes” ratings in the Randomized Controlled Trial (RCT) and non-RCT checklists. Any disagreements on appraisal were resolved through discussion. Furthermore, the reviewers resolved their disagreements on study inclusion by arbitration and/or by a third reviewer. Full-text retrieval was performed for studies that met all prespecified inclusion criteria.
Data extraction, synthesis, and analysis
Considering the fact that this study was examining determinants, any article that referred to even one determinant was included. For example, articles that examined the impact of stress on CVD were included. Data on texts were extracted for quantitative studies. The extracted data included author, country, publication year, study description, objective, and results. The PRISMA flow diagram was used to select the included studies.
The analysis consisted of two steps. First, the characteristics of the studies were summarized by author, country, publication year, study description, objective, and results. The selected studies were fully reviewed, and the required data were extracted. Second, study results with particular focus on the determinant factors of CVD formed the basis of the descriptive factors. The Endnote X7 software was used to organize the studies, read the titles and abstracts, and identify duplicates.
| Results|| |
Study selection and characteristics
In the initial search, 5332 studies were identified. After screening the studies using the exclusion criteria, 274 studies were selected. Utilizing the reviews of the full texts, 210 studies were excluded from the study. However, studies were not omitted due to low methodology quality, which was checked using the JBI checklist. Finally, 64 studies were reviewed which had examined the determinants of CVD. [Figure 1] presents the results of this systematic review.
Details of the studies' characteristics were provided as supplementary material. The 64 included studies were of different designs: 2 clinical trials,, 2 case-controls,, 27 cross-sectional studies,,,,,,,,,,,,,,,,,,,,,,, and 33 cohorts.,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, The cohort methodology was implemented in most of the articles (51.6%). Most of the studies were from the USA (18.8%) and were published between 2011 and 2013 (25%). In addition, most studies had examined both sexes (79.7%). The longest follow-up period was 49 years. Most of the data were collected in a period of 1 to 10 years (75%) and the majority had a sample size ≥1000 (43.8%) [Table 2].
|Table 2: Characteristics of the studies included in the qualitative synthesis|
Click here to view
A total of 15 factors and 45 determinants were identified in 4 main categories. The 4 categories were identified as social, economic, technological, and environmental. The 15 factors were identified as sociodemographic, violence, smoking, occupation, positive childhood experience, social inequalities, psychological distress, eating habits, neighborhood, family income, rapid technology, environmental pollution, living environments, noise, and disaster. The determinants were described and the number of studies was indicated. [Table 3] includes categories, factors, determinants, and contributing studies.
|Table 3: Illustrative categories, factors, determinants and contributing studies|
Click here to view
Most determinants belonged to the social category, whereas the economic and technological categories consisted of the least number of determinants. In the social category, determinants were related to demographics, psychological and childhood conditions, type of diet, and dietary habits. Moreover, the emphasis was more on the impact of neighbors and social mechanisms. In addition, the inequality and inappropriate distribution of income at the individual and community level can lead to CVD. Air pollution and the structure of the living environment in terms of access to recreational facilities and physical activity are important. These factors are intermingled and can have bilateral or multilateral interactions. For example, violence during childhood and in the family exacerbates the increase in mental illnesses and can consequently cause CVD. Conceptual relationships between categories, factors, and determinants are presented in [Figure 2].
|Figure 2: Conceptual relationships between categories, factors, determinants, and cardiovascular disease|
Click here to view
| Discussion|| |
Determinants that cause CVD can also affect traditional risk factors. A total of 45 determinants were identified; the majority of these factors belonged to the social category. Based on this review's results, it seems that childhood, neighborhood, living environment, and social mechanisms are particularly important. Adopted health policies greatly impact the risk factors of illnesses and, eventually, the incidence of the disease. Political decisions and policymaking processes are influential in all areas, especially in the field of disease risk factors. In this regard, CVD can be affected by all functions of the health system which makes accessibility of care vitally important. Policies on physical education, transportation, food, work, green spaces, recreational facilities, and tobacco are crucial in this regard. In sum, the working environments, constructed environments, residential environments, urban forms, and green spaces are affected by policies and politics.
The social determinants of health are tools that help reveal how social processes interact globally, nationally, and individually with CVD. The Isfahan Healthy Heart Program revealed a correlation between smokers and three socioeconomic status (SES) determinants: employment, occupation, and income. Findings from population-based studies indicated the existence of an association between CVD and certain occupational factors and health behaviors and occupational groups (e.g. smoking, status, etc.). In industrialized countries, cardiovascular mortality is inversely correlated with socioeconomic level and type of occupation. The work environment can play an important role, including psychological stress, sedentary jobs, passive smoking, and shift work. Job stress, such as job strain and long working hours, is associated with a moderately high risk of coronary heart disease and strokes in Europe, the United States, and Japan. Findings from a meta-analysis suggest that workplace stress prevention could decrease the incidence of CVD. Even so, prevention of workplace stress would have a much smaller impact than standard risk factors such as smoking, etc.
Inappropriate socioeconomic conditions during childhood are associated with the risk of ischemic stroke, regardless of identified risk factors and adult SES. Evidence suggests that during pregnancy, the physiological state of a mother predisposes her new-born to adult diseases such as heart disease and stroke. Strong and consistent evidence, however, indicates that parental, social, childhood, and early life influences and inequalities in health services often lead to an increased risk of CVD in people living in high-income countries with low socioeconomic backgrounds. Childhood deprivation, marked by violence, neglect, and instability in the home, is a phenomenon that has a profound effect on individuals, communities, and society. Adverse experiences in children may be related to high rates of anxiety and lack of sufficient care, contributing to increased risk of adverse coping mechanisms. Adverse experiences of childhood can influence emotional and psychological development and increase susceptibility to mental health issues such as major depression and post-traumatic stress disorder (PTSD), correlated with CVD risk factors. Early-life adversity can also change biological performance in stress management pathways and lead to long-term adult stress responses. In high-income countries, the high prevalence of several behavioral and psycho-social risk factors among people with low SES reveals an inverse association of SES with the risk of CVD. In fact, poverty has been considered as one of the most important social determinants of heart disease worldwide. The Marmot Review results highlight that people living in England's poorest neighborhoods will die 7 years earlier on average than people living in the richest neighborhoods. Also the social gradient of health inequalities shows that the lower is the one's social and economic status, the poorer is the one's health. Socioeconomic deprivation is a strong independent indicator of the risk for heart failure and its adverse effects. The sociodemographic determinants of sudden cardiac deaths include lower SES, position in a social organization, social support, social exclusion and inequities, marital status, the role of employment, and stressful economic and social conditions. Three dimensions of social support have been distinguished: (a) emotional support offered by family members and other close people can improve self-esteem and strengthen the sense of identity; (b) support for evaluation, knowledge, advice, and guidance in difficult situations; (c) concrete support for practical assistance. All three dimensions are essential in order to maintain good cardiovascular health.
Depression can increase the risk of chronic heart disorders and death, either through direct pathophysiological mechanisms such as ventricular arrhythmias or by behavioral mechanisms. Chronic stress shifts the homeostatic balance with sustained sympathetic overdrive and decreased vagal tone in the autonomic nervous system. Regardless of the involvement or absence of depression, inflammation occurs in neurological, gastrointestinal, and cerebrovascular pathology. Endothelial dysfunction, a preamble to atherosclerosis and atherothrombosis, is closely associated with inflammation. Endothelial dysfunction was observed in depression, which may be a characteristic marker for this disorder. Nonetheless, social support can predict improvements in CVD patients. In contrast, the combination of social isolation and depression worsens the prognosis and accelerates the progression of CVD.,
In developing countries, urbanization has become a concern, as it affects the prevalence of risk factors for cardiovascular diseases. Psycho-social and behavioral mechanisms mediate the effects of the factors associated with urbanization on the risk of NCD mortality. For the CVD, it was explained that there are macro-social forces such as urbanization that affect the prevalence of major risk factors (i.e., dietary quality and tobacco use), which in turn are distributed differently within social groups. Furthermore, stressors in urban environments (noise, social isolation, and anxiety) were linked with the development of cardiovascular risk factors (hypertension and atherosclerosis). Due to urbanization, behavioral and environmental changes may increase the risk of CVD. Individual geographical location also affects CVD development. Living in the countryside, surrounded by meadows, trees, flowers, and plains is quite different from living in the city, where people suffer from traffic jams and noise pollution. Moreover, according to the World Health Organization, air pollution and traffic noise are the two major environmental pollutants that affect health. In 2010, the American Heart Association reported that cumulative evidence regarding air pollution was consistent with the causal relationship between exposure to PM2.5 and cardiovascular morbidity and mortality. Similarly, low neighborhood SES can influence myocardial infarction (MI) survival through inadequate leisure-time physical activity. Therefore, an intermediate mechanism between neighborhood SES and post-MI outcome is revealed and it can provide opportunities for prevention. In addition, living in a deprived area often impacts CVD survivors, placing them at a higher risk of frequent hospital admissions.
It may be more helpful to consider a chronic disease as an “eco-disease,” with its environmental and behavioral contributors, and consider nutritionally dependent chronic diseases as “eco-nutritional diseases.” Furthermore, socioeconomic and psychosocial factors exert influence on health, and also the development, progression, and prevention of diseases., Scientific evidence suggests that low SES, social isolation, psychosocial stress, hostility, and depression have a negative effect on CVD. Recommendations for promoting behavioral changes and the management of psychosocial and lifestyle factors in clinical practice include strategies for promoting a healthy lifestyle, improving interactions between healthcare providers and patients, implementing multimodal interventions, and managing psychosocial risk factors. Factors other than the major risk factors should be considered in health policies such as education, local governments, sports and recreational organizations, health services, mass media, and public departments.
Financial support and sponsorship
Tabriz University of Medical Sciences financially supported this study.
Conflicts of interest
There are no conflicts of interest.
GA, KG, RD, and RK contributed to the conception and/or design of the work. MA, KG, RK, and SA contributed to the acquisition, analysis, and/or interpretation of the data. MA and GA drafted the manuscript. RK, KG, SA, and GA critically revised the manuscript. All gave final approval and agreed to be accountable for all aspects of the work, ensuring integrity and accuracy.
| References|| |
Gakidou E, Afshin A, Abajobir AA, Abate KH, Abbafati C, Abbas KM, et al.
Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017;390:1345-422.
James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al
. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1789-858.
Roth GA, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al.
Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: A systematic analysis for the Global Burden of Disease Study 2017. Lancet 2018;392:1736-88.
Wang H, Abajobir AA, Abate KH, Abbafati C, Abbas KM, Abd-Allah F, et al.
Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970–2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017;390:1084-150.
Al-Mawali A. Non-communicable diseases: Shining a light on cardiovascular disease, Oman's biggest killer. Oman Med J 2015;30:227.
Organization WH. Global Status Report on Noncommunicable Diseases 2014. World Health Organization; 2014.
Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS Med 2006;3:e442.
Wilkins E, Wilson L, Wickramasinghe K, Bhatnagar P, Leal J, Luengo-Fernandez R, et al
European cardiovascular disease statistics 2017.
Benjamin EJ, Blaha MJ, Chiuve SE, Cushman M, Das SR, Deo R, et al.
Heart disease and stroke statistics-2017 update: A report from the American Heart Association. Circulation 2017;135:e146-603.
Nangia R, Singh H, Kaur K. Prevalence of cardiovascular disease (CVD) risk factors. Med J Armed Forces India 2016;72:315-9.
Mirdamadi A, Rafiei R, Kahazaipour G, Fouladi L. Selenium level in patients with heart failure versus normal individuals. Int J Prev Med 2019;10:210.
] [Full text]
Marmot M, Bell R. Social determinants and non-communicable diseases: Time for integrated action. BMJ 2019;364:l251.
Allen L, Williams J, Townsend N, Mikkelsen B, Roberts N, Foster C, et al.
Socioeconomic status and non-communicable disease behavioural risk factors in low-income and lower-middle-income countries: A systematic review. Lancet Glob Health 2017;5:e277-89.
Holt-Lunstad J, Smith TB, Baker M, Harris T, Stephenson D. Loneliness and social isolation as risk factors for mortality: A meta-analytic review. Perspect Psychol Sci 2015;10:227-37.
Holt-Lunstad J, Smith TB, Layton JB. Social relationships and mortality risk: A meta-analytic review. PLoS Med 2010;7:e1000316.
Holt-Lunstad J, Robles TF, Sbarra DA. Advancing social connection as a public health priority in the United States. Am Psychol 2017;72:517-30.
Heller O, Somerville C, Suggs LS, Lachat S, Piper J, Aya Pastrana N, et al.
The process of prioritization of non-communicable diseases in the global health policy arena. Health Policy Plan 2019;34:370-83.
Adgoy E. Social determinants of non-communicable disease. MOJ Public Health 2019;8:149-52.
Dugani S, Gaziano TA. 25 by 25: Achieving global reduction in cardiovascular mortality. Curr Cardiol Rep 2016;18:10.
Coorey GM, Neubeck L, Mulley J, Redfern J. Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: Systematic review with meta-synthesis of quantitative and qualitative data. Eur J Prev Cardiol 2018;25:505-21.
Stewart J, Manmathan G, Wilkinson P. Primary prevention of cardiovascular disease: A review of contemporary guidance and literature. JRSM Cardiovasc Dis 2017;6:2048004016687211. doi: 10.1177/2048004016687211.
Schultz WM, Kelli HM, Lisko JC, Varghese T, Shen J, Sandesara P, et al.
Socioeconomic status and cardiovascular outcomes: Challenges and interventions. Circulation 2018;137:2166-78.
Alizadeh G, Gholipour↱ K, Khosravi MF, Khodayari-Zarnaq R. Preventive community-based strategies of cardiovascular diseases in Iran: A multi-method study. Social Work Public Health 2020:177-86. doi: 10.1080/19371918.2020.1764432.
JB I. Joanna Briggs Institute Reviewers' Manual: 2014 edition/Supplement. Australia: The Joanna Briggs Institute, The University of Adelaide; 2014.
Danhauer SC, Oliveira B, Myll J, Berra K, Haskell W. Successful dietary changes in a cardiovascular risk reduction intervention are differentially predicted by biopsychosocial characteristics. Prev Med 2004;39:783-90.
Estruch R, Ros E, Salas-Salvadó J, Covas M-I, Corella D, Arós F, et al.
Primary prevention of cardiovascular disease with a Mediterranean diet. N Engl J Med 2013;368:1279-90.
Portrait F, Teeuwiszen E, Deeg D. Early life undernutrition and chronic diseases at older ages: The effects of the Dutch famine on cardiovascular diseases and diabetes. Soc Sci Med 2011;73:711-8.
Rahman M, Zaman M. Smoking and smokeless tobacco consumption: Possible risk factors for coronary heart disease among young patients attending a tertiary care cardiac hospital in Bangladesh. Public Health 2008;122:1331-8.
Egbujie BA, Igumbor EU, Puoane T. A cross-sectional study of socioeconomic status and cardiovascular disease risk among participants in the Prospective Urban Rural Epidemiological (PURE) Study. South Afr Med J 2016;106:900-6.
Papoutsou S, Briassoulis G, Wolters M, Peplies J, Iacoviello L, Eiben G, et al.
No breakfast at home: Association with cardiovascular disease risk factors in childhood. World Rev Nutr Diet 2016;114:45-6.
Janković S, Stojisavljević D, Janković J, Erić M, Marinković J. Association of socioeconomic status measured by education, and cardiovascular health: A population-based cross-sectional study. BMJ Open 2014;4:e005222.
Jiang J, Wufuer M, Simayi A, Nijiati M, Fan M, Zhu P, et al.
Cross-sectional study of sociodemographic patterning of risk factors for cardiovascular disease in three isolated-based subgroups of the Uyghur population in Xinjiang, China. BMJ Open 2013;3:e002279.
Damiani G, Federico B, Bianchi CB, Ronconi A, Basso D, Fiorenza S, et al
. Socio-economic status and prevention of cardiovascular disease in Italy: Evidence from a national health survey. Eur J Public Health 2011;21:591-6.
Hartung D, Stadeler M, Grieshaber R, Keller S, Jahreis G. Work and diet-related risk factors of cardiovascular diseases: Comparison of two occupational groups. J Occup Med Toxicol 2010;5:4.
Lee RE, Cubbin C. Neighborhood context and youth cardiovascular health behaviors. Am J Public Health 2002;92:428-36.
Panagiotakos DB, Pitsavos CE, Chrysohoou CA, Skoumas J, Toutouza M, Belegrinos D, et al
. The association between educational status and risk factors related to cardiovascular disease in healthy individuals: The ATTICA study. Ann Epidemiol 2004;14:188-94.
Kang MG, Koh SB, Cha BS, Park JK, Baik SK, Chang SJ. Job stress and cardiovascular risk factors in male workers. Prev Med 2005;40:583-8.
Hujova Z, Rostakova K. Several anthropometric predictors of cardiovascular disease in central Slovakian adults: Socioeconomic and educational differences. Bratisl Lek Listy 2013;114:31-5.
Panagiotakos DB, Pitsavos C, Stefanadis C. Dietary patterns: A Mediterranean diet score and its relation to clinical and biological markers of cardiovascular disease risk. Nutr Metab Cardiovasc Dis 2006;16:559-68.
De A, Podder G, Adhikari A, Haldar A, Banerjee J, De M. Comparative study of risk factors of cardiac diseases among urban and rural population. J Hum Genet 2013;13:15-9.
Chand MG, Rao RS. Appraisal of cardio vascular disease risk factors in a costal environment fishermen's urban slum of Visakhapatnam. IJHE 2007;21:53-8.
Mobley LR, Root ED, Finkelstein EA, Khavjou O, Farris RP, Will JC. Environment, obesity, and cardiovascular disease risk in low-income women. Am J Prev Med 2006;30:327-32. e1.
Oppert J, Thomas F, Charles M, Benetos A, Basdevant A, Simon C. Leisure-time and occupational physical activity in relation to cardiovascular risk factors and eating habits in French adults. Public Health Nutr 2006;9:746-54.
Kivimäki M, Virtanen M, Vartia M, Elovainio M, Vahtera J, Keltikangas-Järvinen L. Workplace bullying and the risk of cardiovascular disease and depression. Occup Environ Med 2003;60:779-83.
McKenzie LM, Crooks J, Peel JL, Blair BD, Brindley S, Allshouse WB, et al
. Relationships between indicators of cardiovascular disease and intensity of oil and natural gas activity in Northeastern Colorado. Environ. Res.2019;170:56-64.
Pereira G, Foster S, Martin K, Christian H, Boruff BJ, Knuiman M, et al.
The association between neighborhood greenness and cardiovascular disease: An observational study. BMC Public Health 2012;12:466.
Hansell AL, Blangiardo M, Fortunato L, Floud S, de Hoogh K, Fecht D, et al.
Aircraft noise and cardiovascular disease near Heathrow airport in London: Small area study. BMJ 2013;347:f5432.
Eriksson C, Nilsson ME, Willers SM, Gidhagen L, Bellander T, Pershagen G. Traffic noise and cardiovascular health in Sweden: The roadside study. Noise Health 2012;14:140-7. [Full text]
Joshi MD, Ayah R, Njau EK, Wanjiru R, Kayima JK, Njeru EK, et al
. Prevalence of hypertension and associated cardiovascular risk factors in an urban slum in Nairobi, Kenya: A population-based survey. BMC Public Health 2014;14:1177.
Maheswaran R, Haining RP, Brindley P, Law J, Pearson T, Fryers PR, et al.
Outdoor air pollution, mortality, and hospital admissions from coronary heart disease in Sheffield, UK: A small-area level ecological study. Eur Heart J 2005;26:2543-9.
Kim D, Kawachi I, Vander Hoorn S, Ezzati M. Is inequality at the heart of it? Cross-country associations of income inequality with cardiovascular diseases and risk factors. Soc Sci Med 2008;66:1719-32.
Valtorta NK, Kanaan M, Gilbody S, Hanratty B. Loneliness, social isolation and risk of cardiovascular disease in the English Longitudinal Study of Ageing. Eur J Prev Cardiol 2018;25:1387-96.
Machado LB, Silva BL, Garcia AP, Oliveira RA, Barreto SM, Maria de Jesus MF, et al.
Ideal cardiovascular health score at the ELSA-Brasil baseline and its association with sociodemographic characteristics. Int J Cardiol 2018;254:333-7.
Veronesi G, Ferrario MM, Kuulasmaa K, Bobak M, Chambless LE, Salomaa V, et al.
Educational class inequalities in the incidence of coronary heart disease in Europe. Heart 2016;102:958-65.
Slopen N, Chen Y, Guida JL, Albert MA, Williams DR. Positive childhood experiences and ideal cardiovascular health in midlife: Associations and mediators. Prev Med 2017;97:72-9.
Savelieva K, Pulkki-Råback L, Jokela M, Kubzansky LD, Elovainio M, Mikkilä V, et al
. Intergenerational transmission of socioeconomic position and ideal cardiovascular health: 32-year follow-up study. Health Psychol 2017;36:270-9.
Laitinen TT, Puolakka E, Ruohonen S, Magnussen CG, Smith KJ, Viikari JS, et al.
Association of socioeconomic status in childhood with left ventricular structure and diastolic function in adulthood: The Cardiovascular Risk in Young Finns Study. JAMA Pediatr 2017;171:781-7.
Slopen N, Glynn RJ, Buring JE, Lewis TT, Williams DR, Albert MA. Job strain, job insecurity, and incident cardiovascular disease in the Women's Health Study: Results from a 10-year prospective study. PLoS One 2012;7:e40512.
Veronesi G, Tunstall-Pedoe H, Ferrario MM, Kee F, Kuulasmaa K, Chambless LE, et al.
Combined effect of educational status and cardiovascular risk factors on the incidence of coronary heart disease and stroke in European cohorts: Implications for prevention. Eur J Prev Cardiol 2017;24:437-45.
Vedin O, Hagström E, Budaj A, Denchev S, Harrington RA, Koenig W, et al.
Tooth loss is independently associated with poor outcomes in stable coronary heart disease. Eur J Prev Cardiol 2016;23:839-46.
Castañeda SF, Buelna C, Giacinto RE, Gallo LC, Sotres-Alvarez D, Gonzalez P, et al.
Cardiovascular disease risk factors and psychological distress among Hispanics/Latinos: The Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Prev Med 2016;87:144-50.
Pujades-Rodriguez M, Timmis A, Stogiannis D, Rapsomaniki E, Denaxas S, Shah A, et al.
Socioeconomic deprivation and the incidence of 12 cardiovascular diseases in 1.9 million women and men: Implications for risk prediction and prevention. PLoS One 2014;9:e104671.
Meyer U, Schindler C, Bloesch T, Schmocker E, Zahner L, Puder JJ, et al.
Combined impact of negative lifestyle factors on cardiovascular risk in children: A randomized prospective study. J Adolesc Health 2014;55:790-5.
Appleton AA, Buka SL, Loucks EB, Rimm EB, Martin LT, Kubzansky LD. A prospective study of positive early-life psychosocial factors and favorable cardiovascular risk in adulthood. Circulation 2013;127:905-12.
Ramsay SE, Morris RW, Whincup PH, Papacosta AO, Thomas MC, Wannamethee SG. Prediction of coronary heart disease risk by Framingham and SCORE risk assessments varies by socioeconomic position: Results from a study in British men. Eur J Cardiovasc Prev Rehabil 2011;18:186-93.
Loucks EB, Lynch JW, Pilote L, Fuhrer R, Almeida ND, Richard H, et al.
Life-course socioeconomic position and incidence of coronary heart disease: The Framingham Offspring Study. Am J Epidemiol 2009;169:829-36.
Netterstrøm B, Kristensen TS, Sjøl A. Psychological job demands increase the risk of ischaemic heart disease: A 14-year cohort study of employed Danish men. Eur J Cardiovasc Prev Rehabil 2006;13:414-20.
Taheri M, Tavakol M, Akbari ME, Mohammadbeigi A, Abbasi M. Socio-economic status inequity in self rated health in patients with breast cancer. Open access Maced J Med Sci 2019;7:152-6.
Tunstall-Pedoe H, Woodward M. By neglecting deprivation, cardiovascular risk scoring will exacerbate social gradients in disease. Heart 2006;92:307-10.
Yoo H, Franke WD. Stress and cardiovascular disease risk in female law enforcement officers. Int Arch Occup Environ Health 2011;84:279-86.
Wattanakit K, Williams JE, Schreiner PJ, Hirsch AT, Folsom AR. Association of anger proneness, depression and low social support with peripheral arterial disease: The Atherosclerosis Risk in Communities Study. Vasc Med 2005;10:199-206.
Martínez-González MA, García-López M, Bes-Rastrollo M, Toledo E, Martínez-Lapiscina EH, Delgado-Rodriguez M, et al
. Mediterranean diet and the incidence of cardiovascular disease: A Spanish cohort. Nutr Metab Cardiovasc Dis 2011;21:237-44.
Panagiotakos D, Pitsavos C, Chrysohoou C, Palliou K, Lentzas I, Skoumas I, et al.
Dietary patterns and 5-year incidence of cardiovascular disease: A multivariate analysis of the ATTICA study. Nutr Metab Cardiovasc Dis 2009;19:253-63.
Critselis E, Panagiotakos DB, Georgousopoulou EN, Katsaounou P, Chrysohoou C, Pitsavos C, et al.
Exposure to second hand smoke and 10-year (2002–2012) incidence of cardiovascular disease in never smokers: The ATTICA cohort study. Int J Cardiol 2019;295:29-35.
Anderson JL, May HT, Horne BD, Bair TL, Hall NL, Carlquist JF, et al.
Relation of vitamin D deficiency to cardiovascular risk factors, disease status, and incident events in a general healthcare population. Am J Cardiol 2010;106:963-8.
Liu S, Buring JE, Sesso HD, Rimm EB, Willett WC, Manson JE. A prospective study of dietary fiber intake and risk of cardiovascular disease among women. J Am Coll Cardiol 2002;39:49-56.
Miller KA, Siscovick DS, Sheppard L, Shepherd K, Sullivan JH, Anderson GL, et al.
Long-term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med 2007;356:447-58.
Zhang L-w, Chen X, Xue X-d, Sun M, Han B, Li C-p, et al.
Long-term exposure to high particulate matter pollution and cardiovascular mortality: A 12-year cohort study in four cities in northern China. Environ Int 2014;62:41-7.
Hoffmann B, Moebus S, Stang A, Beck E-M, Dragano N, Möhlenkamp S, et al.
Residence close to high traffic and prevalence of coronary heart disease. Eur Heart J 2006;27:2696-702.
Bouillon K, Haddy N, Delaloge S, Garbay J-R, Garsi J-P, Brindel P, et al.
Long-term cardiovascular mortality after radiotherapy for breast cancer. J Am Coll Cardiol 2011;57:445-52.
Peters MN, Moscona JC, Katz MJ, Deandrade KB, Quevedo HC, Tiwari S, et al
. Natural disasters and myocardial infarction: the six years after Hurricane Katrina. InMayo Clinic Proceedings 2014;89:pp. 472-477). Elsevier.
Rich-Edwards JW, Mason S, Rexrode K, Spiegelman D, Hibert E, Kawachi I, et al.
Physical and sexual abuse in childhood as predictors of early-onset cardiovascular events in women. Circulation 2012;126:920-7.
Stene LE, Jacobsen GW, Dyb G, Tverdal A, Schei B. Intimate partner violence and cardiovascular risk in women: A population-based cohort study. J Womens Health 2013;22:250-8.
Kreatsoulas C, Anand SS. The impact of social determinants on cardiovascular disease. Can J Cardiol 2010;26:8C-13C.
Ferrie JE, Kivimäki M, Shipley MJ, Smith GD, Virtanen M. Job insecurity and incident coronary heart disease: The Whitehall II prospective cohort study. Atherosclerosis 2013;227:178-81.
Havranek EP, Mujahid MS, Barr DA, Blair IV, Cohen MS, Cruz-Flores S, et al
. Social determinants of risk and outcomes for cardiovascular disease: A scientific statement from the American Heart Association. Circulation 2015;132:873-98.
Gharipour M, Sadeghi M, Nouri F, Nezafati P, Qader SS, Taheri M, et al.
Socioeconomic determinants and metabolic syndrome: Results from the Isfahan Healthy Heart Program. Acta Biomed 2017;87:291-8.
Steptoe A, Kivimäki M. Stress and cardiovascular disease. Nat Rev Cardiol 2012;9:360.
Ferrario MM, Landsbergis P, Tsutsumi A, Li J, Hynek P, Krause N, et al.
Work environment: An opportunity for ground-breaking collaborations in cardiovascular disease prevention. SAGE Publications Sage UK: London, England; 2017.
Kivimäki M, Kawachi I. Work stress as a risk factor for cardiovascular disease. Curr Cardiol Rep 2015;17:74.
Xu S, Huang Y, Xiao J, Zhu W, Wang L, Tang H, et al
. The association between job strain and coronary heart disease: A meta-analysis of prospective cohort studies. Ann Med 2015;47:512-8.
Becher H, Palm F, Aigner A, Safer A, Urbanek C, Buggle F, et al.
Socioeconomic conditions in childhood, adolescence, and adulthood and the risk of ischemic stroke. Stroke 2016;47:173-9.
De Boo HA, Harding JE. The developmental origins of adult disease (Barker) hypothesis. Aust N Z J Obstet Gynaecol 2006;46:4-14.
Clark AM, DesMeules M, Luo W, Duncan AS, Wielgosz A. Socioeconomic status and cardiovascular disease: Risks and implications for care. Nat Rev Cardiol 2009;6:712-22.
Su S, Jimenez MP, Roberts CTF, Loucks EB. The role of adverse childhood experiences in cardiovascular disease risk: A review with emphasis on plausible mechanisms. Curr Cardiol Rep 2015;17:88.
Flores-Torres MH, Comerford E, Signorello L, Grodstein F, Lopez-Ridaura R, de Castro F, et al
. Impact of adverse childhood experiences on cardiovascular disease risk factors in adulthood among Mexican women. Child Abuse Negl 2020;99:104175.
Waldstein SR, Moody DLB, McNeely JM, Allen AJ, Sprung MR, Shah MT, et al.
Cross-sectional relations of race and poverty status to cardiovascular risk factors in the Healthy Aging in Neighborhoods of Diversity across the Lifespan (HANDLS) study. BMC Public Health 2016;16:258.
Hawkins NM, Jhund PS, McMurray JJ, Capewell S. Heart failure and socioeconomic status: Accumulating evidence of inequality. Eur J Heart Fail 2012;14:138-46.
Araujo González R, Ochoa Montes LA, López Tutusaus T. Determinantes sociodemográficos y muerte súbita cardiovascular. RCSP 2015;41:427-40.
Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL, et al.
2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts) Developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J 2016;37:2315-81.
Lane DA, Chong AY, Lip GY. Psychological interventions for depression in heart failure. Cochrane Database Syst Rev 2005:CD003329. doi: 10.1002/14651858.CD003329.pub2.
Halaris A. Inflammation-associated co-morbidity between depression and cardiovascular disease. Inflammation-Associated Depression: Evidence, Mechanisms and Implications: Springer; 2016. p. 45-70.
Miller TQ, Smith TW, Turner CW, Guijarro ML, Hallet AJ. A meta-analytic review of research on hostility and physical health. Psychol Bull 1996;119:322-48.
Xia N, Li H. Loneliness, social isolation, and cardiovascular health. Antioxid Redox Signal 2018;28:837-51.
Alsheikh-Ali AA, Omar MI, Raal FJ, Rashed W, Hamoui O, Kane A, et al.
Cardiovascular risk factor burden in Africa and the middle east: The Africa middle east cardiovascular epidemiological (ACE) study. PLoS One 2014;9:e102830.
ONDICHO ZM. Socio-demographic, lifestyle and psycho-social factors associated with overweight and obesity among health care workers in Kisumu East sub-county, Kenya (Doctoral dissertation, Maseno University).
Pou SA, Tumas N, Sánchez Soria D, Ortiz P, Díaz MdP. Large-scale societal factors and noncommunicable diseases: Urbanization, poverty and mortality spatial patterns in Argentina. Applied Geography 2017;86:32-40.
Armstrong AdC, Ladeia AMT, Marques J, Armstrong DMFdO, Silva AMLd, Morais Junior JCd, et al.
Urbanization is associated with increased trends in cardiovascular mortality among indigenous populations: The PAI study. Arq Bras Cardiol. 2018;110:240-5.
Masic I, Alajbegovic J. The significance of the psychosocial factors influence in pathogenesis of cardiovascular disease. Int J Prev Med 2013;4:1323.
Sørensen M, Pershagen G. Transportation noise linked to cardiovascular disease independent from air pollution. Eur Heart J 2019;40:604-6.
Gerber Y, Myers V, Goldbourt U, Benyamini Y, Drory Y, Infarction ISGoFAM. Neighborhood socioeconomic status and leisure-time physical activity after myocardial infarction: A longitudinal study. Am J Prev Med 2011;41:266-73.
Wahlqvist ML. Chronic disease prevention: A life-cycle approach which takesaccount of the environmental impact and opportunities of food, nutritionand public health policies—The rationale for an eco-nutritionaldisease nomenclature. Asia Pac J Clin Nutr 2002;11:S759-62.
Dorner T, Kiefer I, Kunze M, Rieder A. Genderaspekte sozioökonomischer und psychosozialer Faktoren bei kardiovaskulären Erkrankungen. WMW 2004;154:426-32.
Gupta S, Epari V, Bhatia S. Potential gains of screening family members of suspected coronary artery disease: A pilot study. Int J Prev Med 2019;10:148.
] [Full text]
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]