Logo of plosmedPLoS MedicineSubmit to PLoSGet E-mail AlertsContact UsPublic Library of Science (PLoS)View this Article
PLoS Med. Aug 2010; 7(8): e1000320.
Published online Aug 24, 2010. doi:  10.1371/journal.pmed.1000320
PMCID: PMC2927551

Will Cardiovascular Disease Prevention Widen Health Inequalities?

Summary Points

  • The primary prevention of cardiovascular disease (CVD) is dependent on the effective reduction of the major risk factors for CVD, particularly tobacco control and a healthier diet.
  • The high-risk approach to prevent CVD typically involves population screening. Those exceeding a risk threshold are then given lifestyle advice and/or tablets to reduce blood cholesterol and blood pressure.
  • Evidence suggests this high-risk approach typically widens socioeconomic inequalities. Such inequalities have been reported in screening, healthy diet advice, smoking cessation, statin and anti-hypertensive prescribing, and adherence.
  • The alternative approach is population-wide CVD prevention. For example, legislating for smoke-free public spaces, banning dietary transfats, or halving daily dietary salt intake. Such strategies are generally effective and cost-saving; there is also increasing evidence that they can reduce health inequalities.
  • We conclude that screening and treating high-risk individuals represents a relatively ineffective CVD prevention approach that typically widens social inequalities.

Introduction

Several high-income countries, including the United Kingdom, are tackling “health inequalities” [1]. In 2009, the various UK governments announced large-scale programmes to screen and treat cardiovascular risk [2]. The respective health ministers stated that the programmes would reduce health inequalities, although opposition parties generally predicted the opposite [3]. The potential effects of any screening policy on health inequalities clearly need to be urgently considered, not least in order to inform current policy development in the UK [4],[5] and internationally [6].

The primary prevention of cardiovascular disease (CVD) is dependent on the effective reduction of the major risk factors, particularly by reducing tobacco use and adopting a healthier diet [2]. However, the substantial excess burden of morbidity and mortality due to CVD in disadvantaged groups raises major challenges. Social gradients in the major cardiovascular risk factors can explain approximately three-quarters of this excess burden; smoking alone can explain more than half [7],[8].

Assessing the potential effect of risk factor reductions on socioeconomic inequalities in health is crucial. McLaren et al. usefully distinguish between “agentic” prevention strategies (which rely solely on individuals making and sustaining behaviour change) and “structural” strategies (which work through changes in the wider social environment [9]. There is increasing evidence to suggest that addressing CVD risk factors using “structural” whole-population approaches generally reduces social inequalities. There is also worrying preliminary evidence that screening and treating high-risk individuals (“agentic” strategies) might increase the inequalities gap. In this Policy Forum article, we review this evidence, and consider different potential approaches for reducing inequalities.

The Whole-Population Approach for Preventing CVD

Some two decades ago, Geoffrey Rose suggested that a small reduction in risk in a large number of people may prevent many more cases than treating a small number at higher risk [10]. He therefore cautioned against simply pursuing individual-level interventions targeted at changing risk profiles in this latter group. Rose instead advocated a dual strategy, also using a whole-population approach to change everyone's exposure. That approach would support policies that work directly on what Rose called “the underlying causes of disease”; for example, via statutory regulation and environmental controls, rather than indirectly by changing risk factors on a person-by-person basis. Whole-population interventions can indeed reduce risk factors across entire countries. National legislation and fiscal policies can be both effective and cost-saving, whether banning industrial transfats (Denmark), halving dietary salt in processed foods (Finland), or promoting smoke-free public spaces (Scotland, Ireland, Italy, and elsewhere) [11][14].

Growing international evidence now supports the Rose hypothesis [15][17]. Small reductions in population cholesterol concentrations, blood pressure, or smoking then translate into substantial reductions in cardiovascular events and deaths [17][19]. This evidence suggests that comprehensive policies can be more effective in reducing risk factors and improving health than a high-risk individual approach. Furthermore, identifying individuals with a threshold of a 20% 10-year CVD event risk would then necessitate multiple preventive treatments for one-quarter of the population. In the UK, this might decrease UK cardiovascular mortality by approximately 17% (assuming normal adherence). Conversely, country-wide policies to reduce cholesterol and smoking population levels by just 5% would decrease UK mortality substantially more, by about 26% [15]. Capewell et al. reported similar findings for the US population [18].

The Whole-Population Approach for Reducing Social Inequalities in CVD

There is increasing evidence to support health equity strategies that take a whole-population approach to CVD risk factors. This includes simply considering arithmetical principles. Disadvantaged groups experience a greater CVD burden. They are thus likely to gain extra benefit if a risk factor is uniformly reduced across the entire population, with a consequent reduction in absolute (but not necessarily relative) inequalities. This simple arithmetic was spelt out by Diederichsen and colleagues [20].

More recent support came from Kivimaki et al., who quantified the 15-year benefits of decreasing risk factors uniformly across a male population (reductions of 10 mmHg in blood pressure, 2 mmol/l in total cholesterol, and 1 mmol/l in glucose) [21]. Although relative inequalities would remain, such interventions might reduce the absolute mortality gap between rich and poor by approximately 70% [21].

Smoking rates and exposure to environmental tobacco smoke are higher in poorer groups in Scotland, which is consistent with other high-income countries [22]. However, following the Scottish smoke-free legislation in 2006, there was a substantial fall in hospital admissions for heart attack and “acute coronary syndrome” (involving a 14% reduction in smokers and a 21% fall in never smokers). This drop was uniform across social groups [13].

Strong regulatory policies, particularly those including increases in cigarette price, are also associated with declines in tobacco use of a similar magnitude across socioeconomic groups [23]. This suggests that, in the many countries where smoking rates are higher in poorer groups, the absolute benefit will be greater than in affluent groups. Indeed, men and women in lower socioeconomic groups appear more responsive to uniform increases in cigarette price than affluent groups [24],[25]. However, attention needs to be paid to how inequalities within disadvantaged groups can influence responses to population-wide interventions and their overall impacts [26].

Social differences are observed in diet, as in smoking. Thus, low-income families consume more saturated fat and fewer fruits and vegetables than more affluent families [27]. Strong supporting evidence for the effectiveness of a population-wide diet intervention comes from the United States. Folic acid fortification of cereals was introduced in 1996. Absolute social differences in blood folate levels were subsequently reduced by 67% [28]. Furthermore, comparable reductions in inequalities in dental caries followed water fluoridation [29]. The implications are clear. Eradication of dietary transfats, or halving the salt content of bread, would disproportionately benefit deprived groups.

Of course, the population approach is unlikely to totally abolish inequalities since many of the drivers of disadvantage lie even further upstream. For instance, structural interventions in the Ontario Smoke Free Strategy included smoking bans in enclosed public places and enclosed work places, laws on tobacco sales to minors, and restrictions on the display of tobacco products in retail outlets. Overall smoking rates in the province fell. However, 40% of aboriginal women and men are still smoking, as are 34% of adults with less than a secondary school education compared to 11% who had a bachelor's degree or higher [30].

The population approach has a strong ethical base. It is in step with the “stewardship” model of public health that places obligations on governments to enable conditions in which everyone can lead a healthy life [31]. Classic examples include legislating for clean drinking water, seatbelts, and food hygiene. Such principles have long underpinned broader policies to protect well-being, by regulating market economies and providing for basic needs [32]. There is also some support from the political right under the banner of “libertarian paternalism” or “nudge” (routinely presenting options to increase the likelihood that people will choose what they would on reflection most prefer) [33].

However, population-based structural approaches to reduce inequalities might be difficult to achieve. Such approaches ideally require concerted cross-sectoral efforts such as universal access to healthy food, reductions in work place stress, and access to safe environments for physical activity for all [32].

The High-Risk Approach for Preventing CVD

In the UK, the high-risk approach for preventing CVD is typified by the health checks programme Putting Prevention First, implemented in England [2]. All adults aged 40–74 years will be invited to be screened for CVD risk. Individuals found to exceed a 20% risk of a cardiovascular event in the next 10 years will be treated with a combination of lifestyle advice plus tablets to reduce blood cholesterol and blood pressure, as appropriate [2].

This is a controversial area. Manuel et al. recently “revisited” Rose [34]. Their influential article advocated the high-risk approach [34]. However, their methodology and conclusions were subsequently criticised by Whincup and others [35]. The methodological limitations identified by these critics meant that firstly, the Manuel analysis systematically over-estimated the likely benefit of individual strategies (by including patients with established CVD, inflating the numbers in the “high-risk” group, assuming that effectiveness in routine clinical practice equalled efficacy in RCTs, and ignoring under-treatment and poor long-term adherence). Secondly, they systematically under-estimated the contribution of population strategies (by conservatively assuming a 2% reduction in population cholesterol when falls of 10%–18% have been observed elsewhere, and by using an unvalidated model and also failing to mention that population approaches to prevention also reduce the pool of high-risk people requiring drug treatment) [35].

Likewise, Zulman et al. recently preferred a high-intensity treatment intervention in the US adult population [36]. However, their mortality estimates were 3-fold higher than previous publications [36]. This over-estimate probably reflected successive optimistic assumptions about effectiveness and long-term adherence [36],[37].

Furthermore, critics of the high-risk cardiovascular risk screening approach suggest that this strategy might have low effectiveness, leave substantial residual risk, and achieve a small population impact at high cost; as well as result in the medicalisation of previously healthy individuals. Furthermore, it does not address the root causes of the problem [38][40]. Equally seriously, this high-risk approach will almost certainly widen inequalities.

The High-Risk Approach May Worsen Social Inequalities in CVD

There is increasing evidence that inequalities in risk factors can widen when effects are mediated through individual-level changes in knowledge, motivation, and behaviour (for example, national health promotion campaigns and behavioural change programmes) [41],[42]. Furthermore, because such interventions do not work directly on population exposure to risk factors, they do not address inequalities in risk-factor profiles in subsequent cohorts.

“Agentic” interventions, which require mobilisation of an individual's resources, whether material or psychological, generally favour those with more resources, thus tending to increase social inequalities [9],[41],[42]. This parallels what Tudor Hart memorably described as the “Inverse Care Law”the availability of good medical care tends to vary inversely with the need for it in the population served [43]. Thus, the people in the poorest health gain the lowest net health benefit from the interventions [43]. Disadvantage can occur at every stage in the process, from the person's beliefs about health and disease, and actual health behaviour, to presentation, screening, risk assessment, negotiation, participation, programme persistence, and treatment adherence. Tugwell et al. usefully described this cumulative inequality as the “staircase effect” [44].

Inequalities have also been reported in the screening and detection of cancer as well as CVD. For instance, women who choose to attend the National Health Service (NHS) Breast Screening Programme come more from affluent areas [45].

In the US, Frohlich's analysis likewise suggested that even when individual-based interventions are widely applied (such as screening or health information campaigns), they may increase disparities [46]. Furthermore, examples of the inverse care law in CVD primary prevention prescribing have also been reported. Substantial socioeconomic gradients exist in statin use, both in the UK and in the Danish health care system, which aims, like the NHS, to ensure equity in medical care [47][49].

Likewise, inequalities in anti-hypertensive therapy have been reported. A recent study suggested that social and ethnic disparities in the detection and management of hypertension have persisted in the UK despite major investment in quality improvement initiatives, including pay for performance [50]. Long-term adherence (compliance) with primary prevention medications barely reaches 50%, and is often worse in more deprived groups [51][53]. Furthermore, inequalities in adherence have been specifically reported for both statins and anti-hypertensive medications [54],[55].

For smoking cessation, greater use and higher quit rates of cessation services by more advantaged individuals are a real concern [56]. Affluent smokers tend to receive more help, and are more likely to quit [57],[58]. Increasing quit rates in more affluent smokers were also recently reported in Inter99, the Danish trail of primary prevention in general practice [59]. Similar inequalities have also been reported in workplace smoking interventions [57].

With respect to dietary advice, US policies traditionally favour individual approaches over public health strategies. There, Kanjilal and colleagues recently reported bigger declines in CVD risk factors in more affluent groups [60]. Supporting evidence comes from a recent systematic review of nutritional interventions in individuals and groups [61]. In schools, fruit and vegetable consumption typically increased more in affluent families; interventions were correspondingly less effective in disadvantaged areas. Likewise, in a US primary care setting, interventions to reduce fat intake were less successful in blacks than in (more affluent) whites [61]. In Germany, the Cardiovascular Prevention Study compared three strategies involving advice from professionals and media. After 7 years, hypercholesterolaemia improved only in upper social groups, thereby increasing the gap between the health of rich and poor [62].

In England, a high-risk approach to CVD prevention that specifically prioritises disadvantaged groups and localities is being actively promoted. The National Institute for Health and Clinical Excellence recently published public health guidelines advising specific approaches for identifying and supporting people most at risk of dying prematurely [63]. Elsewhere, more innovative strategies are being developed for poor communities—for example, use of non-physician health care workers, financial incentives, and availability of low-cost generic “polypills” [64],[65]. Evidence to confirm the effectiveness and cost-effectiveness of such targeted strategies in reducing health inequalities is currently being gathered [66]. Results are eagerly awaited.

Combining the Population-Based and High-Risk Approaches?

Might a coordinated approach that integrates population-based and high-risk approaches be more effective? The Norsjo Community Intervention Program in Sweden is an example of a model that combines population health and health sector interventions. The program created a local health promotion collaboration between healthcare providers, grocery stores, schools, and municipal authorities. Primary care physicians contacted patients for systematic risk factor screening and counselling aimed at CVD risk reduction. Community interventions included changes in food labelling to make it easier to adhere to dietary recommendations. The predicted CVD mortality risk was reduced by 36% in the intervention area compared to 1% in a control community. Socioeconomically less privileged groups benefited more from the program [67].

Specifically Targeting High-Risk Populations?

Socioeconomically disadvantaged populations are susceptible to under-diagnosis of hypertension, diabetes, and hypercholesterolemia and also to suboptimal care for interventions to reduce risk. Risk factor modification through tailored interventions in high-risk groups might therefore produce considerable benefits; however, evaluation is urgently required.

Conclusions

Given the ubiquity of social and health inequalities, we should not be surprised if interventions to reduce CVD have differential effects, with advantaged groups deriving greater benefit than poorer groups. We have suggested that the potential for such unequal effects is greater for high-risk approaches, where change is contingent on action by individual patients and healthcare providers, compared with whole population approaches, where change is societal and instituted collectively by agencies with statutory responsibility for public health.

Operating mainly outside the health service, the population approach offers governments the opportunity to act directly on population exposure to risk factors. It thus addresses the major drivers of health and health inequalities [68]. Meanwhile, evidence that healthcare interventions can generate and compound risk-factor inequalities is steadily accumulating [42]. We therefore look forward to future analyses from Tugwell and other colleagues in the Cochrane Health Equity Field [44]. However, that is no excuse for delay.

In conclusion, there is evidence that CVD prevention strategies for screening and treating high-risk individuals may represent a relatively ineffective approach that typically widens social inequalities. In contrast, policy interventions to limit risk-factor exposure across populations appear cheaper and more effective; they could also contribute to levelling health across socioeconomic groups. The two approaches are complementary, and Rose's advocacy of a dual strategy may prove prophetic [10]. However, all future strategies aimed at improving population health will merit rigorous evaluation of their potential impact on inequities.

Acknowledgments

We thank many colleagues for their constructive comments, particularly Ann Capewell, David Taylor-Robinson, Mike Kelly, Margaret Whitehead, Robert Beaglehole, Martin Caraher, Sian Robinson, Robin Ireland, Klim McPherson, Margaret Thorogood, and Martin White.

Footnotes

SC was Vice-Chair of the NICE Programme Development Group on Cardiovascular Disease Prevention in Populations. HG has long advocated policies to reduce social inequalities. This paper arises from discussions at NICE, but does not necessarily reflect the views of NICE.

SC and HG are funded by The Higher Education Funding Council for England (HEFCE). HEFCE had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

1. Graham H. Health inequalities, social determinants and public health policy. Policy and Politics. 2009;37:463–479.
2. Department of Health. 2009. Putting prevention first. London: Department of Health. Available: http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_083822. Accessed 20 July 2010.
3. Zosia Kmietowicz. Five yearly checks for over 40s will save 650 lives a year, says government. BMJ. 2009;338:b1334. doi: 10.1136/bmj.b1334.
4. Department of Health. 2009. The government's response to The Health Select Committee report on health inequalities. London: Department of Health. Available: http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_099781. Accessed 20 July 2010.
5. The Marmot Review. 2010. Consultation on the first phase of the Strategic Review of Health Inequalities in England post 2010. Available: http://www.marmotreview.org/. Accessed 27 July 2010.
6. WHO Commission on Social Determinants of Health (WHO CSDH) Geneva: World Health Organization; 2008. Closing the gap in a generation: health equity through action on the social determinants of health. Commission on Social Determinants of Health Final Report.
7. Singh-Manoux A, Nabi H, Shipley M, et al. The role of conventional risk factors in explaining social inequalities in coronary heart disease: the relative and absolute approaches to risk. Epidemiology. 2008;9:599–605. [PMC free article] [PubMed]
8. Jha P, Peto R, Zatonski W, Boreham J, Jarvis MJ, et al. Social inequalities in male mortality, and in male mortality from smoking: indirect estimation from national death rates in England and Wales, Poland, and North America. Lancet. 2006;368:367–370. [PubMed]
9. McLaren L, McIntyre L, Kirkpatrick S. Rose's population strategy of prevention need not increase social inequalities in health. Int J Epidemiol. 2010;39:372–377. [PubMed]
10. Rose G. Oxford: Oxford University Press; 1992. The strategy of preventive medicine.
11. Stender S, Dyerberg J, Bysted A, Leth T, Astrup A. A trans world journey. Atheroscler. 2006;(Suppl 7):47–52. [PubMed]
12. Karppanen H, Mervaala E. Sodium intake and hypertension. Prog Cardiovasc Dis. 2006;49:59–75. [PubMed]
13. Pell JP, Haw S, Cobbe S, Newby DE, Pell AC, et al. Smoke-free legislation and hospitalizations for acute coronary syndrome. N Engl J Med. 2008;359:482–491. [PubMed]
14. Levy DT, Chaloupk FJ, Gitchell G. The effects of tobacco control policies on smoking rates: a tobacco control score card. J Public Health Manag Pract. 2004;10:338–53. [PubMed]
15. Emberson J, Whincup P, Morris R, Walker M, Ebrahim S. Evaluating the impact of population and high-risk strategies for the primary prevention of cardiovascular disease. Eur Heart J. 2004;25:484–491. [PubMed]
16. Wiklund O, Wilhelmsen L, Elmfeldt D, Wedel H, Valek J, et al. Alpha-lipoprotein cholesterol concentration in relation to subsequent myocardial infarction in hypercholesterolemic men. Atherosclerosis. 1980;37:47–53. [PubMed]
17. Unal B, Critchley J, Capewell S. Modelling the decline in CHD deaths in England and Wales, 1981-2000: comparing contributions from primary prevention and secondary prevention. BMJ. 2005;331:614–615. [PMC free article] [PubMed]
18. Capewell S, Ford ES, Croft JB, Critchley JA, Greenlund KJ, et al. Cardiovascular risk factor trends in the US population and options for reducing future CHD mortality. Bull World Health Organ. 2010;88:120–130. [PMC free article] [PubMed]
19. Murray CJ, Lauer JA, Hutubessy RC, Niessen L, Tomijima N, et al. Effectiveness and costs of interventions to lower systolic blood pressure and cholesterol: a global and regional analysis on reduction of cardiovascular-disease risk. Lancet. 2003;361:717–725. [PubMed]
20. Nilunger L, Diderichsen F, Burström B, Östlin P. Using risk analysis in Health Impact Assessment: the impact of different relative risks for men and women in different socio-economic groups. Health Policy. 2004;67:215–224. [PubMed]
21. Kivimäki M, Shipley MJ, Ferrie JE, Singh-Manoux A, Batty GD, et al. Estimating the impact of ‘best-practice’ interventions on reducing socioeconomic inequalities in coronary heart disease mortality in a working population: the Whitehall study. Lancet. 2008;372:1648–1654. [PubMed]
22. Edwards R, Hasselholdt CP, Hargreaves K, Probert C, Holford R, et al. Levels of second hand smoke in pubs and bars by deprivation and food-serving status: a cross-sectional study from North West England. BMC Public Health. 2006;6:42. doi: 10.1186/1471-2458-6-42. [PMC free article] [PubMed]
23. Schaap MM, Kunst AE, Leinsalu M, Regidor E, Ekholm O, et al. Effect of nation-wide tobacco control policies on smoking cessation in high and low educated groups in 18 European countries. Tob Control. 2008;17:248–255. [PubMed]
24. Townsend J, Roderick P, Cooper J. Cigarette smoking by socioeconomic group, sex, and age: effects of price, income, and health publicity. BMJ. 1994;309:923–927. [PMC free article] [PubMed]
25. Main C, Thomas S, Ogilvie D, Stirk L, Petticrew M, et al. Population tobacco control interventions and their effects on social inequalities in smoking: placing an equity lens on existing systematic reviews. BMC Public Health. 2008;8:178. [PMC free article] [PubMed]
26. Greaves L, Hemsing N. Women and tobacco control policies: social-structural and psychosocial contributions to vulnerability to tobacco use and exposure. Drug Alcohol Depend . 2009;104 (Suppl 1):S121–S130. [PubMed]
27. Food Standards Agency. Low income diet and nutrition survey. In: Nelson M, Erens B, Bates B, Church S, Boshier T, editors. Volumes 1–3 . TSO: London; 2007.
28. Dowd JB, Aiello AE. Did national folic acid fortification reduce socioeconomic and racial disparities in folate status in the US? Int J Epid. 2008;37:1059–1066. [PubMed]
29. NHS CRD. Systematic review of the efficacy and safety of the fluoridation of drinking water. 2000. Report 18. York: NHS Centre for Reviews and Dissemination, University of York.
30. Bierman AS, Ahmad F, Angus J, Glazier RH, Vahabi M, et al. Shiller SK, Bierman AS, editors. Burden of illness. 2009. The POWER report. Volume 1. Toronto: Project for an Ontario Women's Health Evidence-Based Report. Available: http://www.powerstudy.ca. Accessed 20 July 2010.
31. Nuffield Council on Bioethics. London: Nuffield Council on Bioethics; 2007. Public health: ethical issues.
32. Graham H. Buckingham: Open University Press; 2007. Unequal lives: health and socioeconomic inequalities.
33. McColl K. Betting on health. BMJ. 2009;338:b1456. doi: 10.1136/bmj.b1456. [PubMed]
34. Manuel DG, Lim J, Tanuseputro P, Anderson GM, Alter DA, et al. Revisiting Rose: strategies for reducing coronary heart disease. BMJ. 2006;332:659–662. doi: 10.1136/bmj.332.7542.659. [PMC free article] [PubMed]
35. Whincup PH, Emberson J, Morris R. 2006. Impact of population strategy greatly underestimated. BMJ 332: 659. http://www.bmj.com/cgi/eletters/332/7542/659#130902.
36. Zulman DM, Vijan S, Omenn GS, Hayward RA. The relative merits of population-based and targeted prevention strategies. Milbank Q. 2008;86:557–580. [PMC free article] [PubMed]
37. Capewell S, O'Flaherty M, Ford ES, Critchley JA. Potential reductions in United States coronary heart disease mortality by treating more patients. Am J Cardiol. 2009;103:1703–1709. [PubMed]
38. Ebrahim S. What is the best strategy for reducing deaths from heart disease? PLoS Med. 2005;2:e98. doi: 10.1371/journal.pmed.0020098. [PMC free article] [PubMed]
39. Sheridan SL, Crespo E. Does the routine use of global coronary heart disease risk scores translate into clinical benefits or harms? A systematic review of the literature. BMC Health Serv Res. 2008;8:60. [PMC free article] [PubMed]
40. Capewell S, Jackson R. Will screening individuals at high risk of cardiovascular events deliver large benefits? BMJ. 2008;337:a1395. doi: 10.1136/bmj.a1395. [PubMed]
41. Blaxter M. 2007. Evidence for the effect on inequalities in health of interventions designed to change behaviour. Bristol: Department of Social Medicine, University of Bristol. NICE BC 6-5. Available: http://www.nice.org.uk/nicemedia/pdf/EvidencefortheeffectonInequalitiesdesignedtochangebehavior.pdf. Accessed 20 July 2010.
42. White M, Adams J, Heywood P. How and why do interventions that increase health overall widen inequalities within populations? In: Babones S, editor. Health, inequality and society. Bristol: Policy Press; 2009.
43. Tudor Hart J. The inverse care law. Lancet. 1971;1971 1:405–412. [PubMed]
44. Tugwell P, de Savigny D, Hawker G, Robinson V. Applying clinical epidemiological methods to health equity: the equity effectiveness loop. BMJ. 2006;332:358–361. [PMC free article] [PubMed]
45. Banks E, Beral V, Cameron R, Hogg A, Langley N, et al. Comparison of various characteristics of women who do and do not attend for breast cancer screening. Breast Cancer Res. 2002;4:R1. [PMC free article] [PubMed]
46. Frohlich KL, Potvin L. The inequality paradox: the population approach and vulnerable populations. Am J Public Health. 2008;98:216–221. [PMC free article] [PubMed]
47. Payne RA, Maxwell SR. Deprivation-based risk scores: the re-emergence of postcode prescribing in the UK? J Cardiovasc Med (Hagerstown) 2009;10:157–160. [PubMed]
48. Blackman T. Statins, saving lives, and shibboleths. BMJ. 2007;334:902. doi: 10.1136/bmj.39163.563519.55. [PMC free article] [PubMed]
49. Thomsen RW, Johnsen SP, Olesen AV, Mortensen JT, Bøggild H, et al. Socioeconomic gradient in use of statins among Danish patients: population-based cross-sectional study. Br J Clin Pharm. 2005;60:534–542. [PMC free article] [PubMed]
50. Ashworth M, Millett C. Quality improvement in UK primary care: the role of financial incentives. J Ambul Care Manage. 2008;31:220–225. [PubMed]
51. Vrijens B, Vincze G, Kristanto P, Urquhart J, Burnier M. Adherence to prescribed antihypertensive drug treatments: longitudinal study of electronically compiled dosing histories. BMJ. 2008;336:1114–1117. [PMC free article] [PubMed]
52. Morisky D, Ang A, Krousel-Wood M, Ward HJ. predictive validity of a medication adherence measure in an outpatient setting. Clin Hypertension. 2008;10:348–354. [PMC free article] [PubMed]
53. Johnell K, Råstam L, Lithman T, Sundquist J, Merlo J. Low adherence with antihypertensives in actual practice: the association with social participation – a multilevel analysis. BMC Public Health. 2005;5:17. doi: 10.1186/1471-2458-5-17. [PMC free article] [PubMed]
54. Chaudhry HJ, McDermott B. Recognizing and improving patient non-adherence to statin therapy. Current Ather Rep. 2008;10:19–24. [PubMed]
55. Bouchard MH, Dragomir A, Blais L, Bérard A, Pilon D, et al. Impact of adherence to statins on coronary artery disease in primary prevention. Br J Clin Pharmacol. 2007;63:698–708. [PMC free article] [PubMed]
56. Low A, Unsworth L, Miller I. Avoiding the danger that stop smoking services may exacerbate health inequalities: building equity into performance assessment. BMC Public Health. 2007;7:198. [PMC free article] [PubMed]
57. Browning KK, Ferketich AK, Salsberry PJ, Wewers ME. Socioeconomic disparity in provider-delivered assistance to quit smoking. Nicotine Tob Res. 2008;10:55–61. doi: 10.1080/14622200701704905. [PubMed]
58. Bauld L, Judge K, Platt S. Assessing the impact of smoking cessation services on reducing health inequalities in England. Tob Control. 2007;16:400–404. [PMC free article] [PubMed]
59. Jakobsen M. Copenhagen: University of Copenhagen; 2009. Cardiovascular disease prevention: INTER99 [PhD dissertation].
60. Kanjilal S, Gregg EW, Cheng YJ, Zhang P, Nelson DE, et al. Socioeconomic status and trends in disparities in 4 major risk factors for cardiovascular disease among US adults, 1971-2002. Arch Intern Med. 2006;166:2348–2355. [PubMed]
61. Oldroyd J, Burns C, Lucas P, Haikerwal A, Waters E. The effectiveness of nutrition interventions on dietary outcomes by relative social disadvantage: a systematic review. J Epidemiol Community Health. 2008;62:573–579. doi: 10.1136/jech.2007.066357. [PubMed]
62. Helmert U, Shea S, Maschewsky-Schneider U. Social class and cardiovascular disease risk factor changes in West Germany 1984–1991. Eur J Public Health. 1995;1995 5:103–108. doi: 10.1093/eurpub/5.2.103.
63. NICE PHIAC. 2008. Identifying and supporting people most at risk of dying prematurely. London: National Institute for Health and Clinical Excellence. Available: http://www.nice.org.uk/guidance/PH15. Accessed 20 July 2010.
64. Beaglehole R, Epping-Jordan J, Patel V, Chopra M, Ebrahim S, et al. Improving the prevention and management of chronic disease in low-income and middle- income countries: a priority for primary health care. Lancet. 2007;372:940–949. [PubMed]
65. Cannon CP. Can the polypill save the world from heart disease? Lancet. 2009;373:1313–1314. [PubMed]
66. Lawson K, Fenwick E, Pell J. Cardiovascular disease strategies for identifying people at high risk of cost effectiveness of alternative screening. J Epid Community Health. 2009;63:93.
67. Weinehall L, Hellsten G, Boman K, Hallmans G, Asplund K, et al. Can a sustainable community intervention reduce the health gap? —10-year evaluation of a Swedish community intervention program for the prevention of cardiovascular disease. Scand J Public Health. 2001;(Suppl 56):59–68. [PubMed]
68. Macintyre S. Prevention and the reduction of health inequalities. BMJ. 200;320:1399–400. [PMC free article] [PubMed]

Articles from PLoS Medicine are provided here courtesy of Public Library of Science
PubReader format: click here to try

Formats:

Related citations in PubMed

See reviews...See all...

Cited by other articles in PMC

See all...

Links

  • PubMed
    PubMed
    PubMed citations for these articles

Recent Activity

Your browsing activity is empty.

Activity recording is turned off.

Turn recording back on

See more...