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1. Julia Critchley, St. George's, University of London, United Kingdom

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1. Julia Critchley, St. George's, University of London, United Kingdom

  1. 1. Julia CritchleyProfessor of EpidemiologySt George’s, University of London UKJune 13 2013Thanks: Simon Capewell, Martin O’Flaherty,Peter Phillimore, Susanne Logstrup, SophieO’Kelly, Muriel Mioulet, Lars Ryden, IlariaLeggeri, Robin Ireland, Philip James, HilaryGraham, Maddy Bajekal, Margaret Whitehead,Peter Whincup, Earl Ford, Pedro Marques-Vidal, Rosalind Raine, Sarah Wild, Ann CapewellFunding: EU, MRC, BHF, NIHRInequalities in CVD risk factorsCauses, Consequences & Challenges
  2. 2. Presentation Outline• Coronary Heart Disease (CHD)• Mortality trends• Risk factor trends• Socio-economic circumstance (SEC)• IMPACTsec: explaining recent mortality trends bySEC2
  3. 3. Trends in age-standardised mortality rates,Men 65+: Q1(affluent) vs Q5(deprived) 1982-2006Total mortality, per 100,000 CHD mortality, per 100,00030.01000.02000.03000.04000.05000.06000.07000.08000.09000.010000.01982198419861988199019921994199619982000200220042006Q1Q5National0.0500.01000.01500.02000.02500.03000.01982198419861988199019921994199619982000200220042006Q1Q5National
  4. 4. Systolic Blood Pressure (mm Hg):trends by deprivation quintilesMen 55+ Women 55+1301321341361381401421441461481501994199519961998*2001*2003*2006*2008*National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ51301321341361381401421441461481501994199519961998*2001*2003*2006*2008*National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ54
  5. 5. Diabetes (%): trends by deprivation quintilesMen 55+0%5%10%15%20%1994199820032006National IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5Women 55+0%5%10%15%20%1994199820032006National IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ55
  6. 6. Obesity (%): trends by deprivation quintilesMen 55+ Women 55+5%10%15%20%25%30%35%40%1995199619971998199920002001200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ55%10%15%20%25%30%35%40%1995199619971998199920002001200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ56
  7. 7. IMPACTsecexplaining recent UK mortality trends+ stratification by socio-economic circumstances(sec)7
  8. 8. 0500010000150002000025000q1 q2 q3 q4 q5ExpectedObservedCHD Mortality fall 2007 vs 2000by IMD quintilesTarget DPPs = 38, 0688Affluent Deprived
  9. 9. IMPACT modelExplaining the CHD mortality fall 1981-2000• 70% mortality fall due torisk factorreductions• 40%: due to evidence-based therapiesUnal, Critchley & Capewell Circulation 2004 109(9) 1101
  10. 10. IMPACT modelExplaining the CHD mortality fall 1981-2000• 70% mortality fall due torisk factorreductions• 40%: due to evidence-based therapies-80000-60000-40000-200000Unal, Critchley & Capewell Circulation 2004 109(9) 110168,230 fewerCHD deaths1981 2000
  11. 11. IMPACT modelExplaining the CHD mortality fall 1981-2000• 70% mortality fall due torisk factorreductions• 40%: due to evidence-based therapies-80000-60000-40000-200000Risk Factors worse +13%Risk Factors better -70%Treatments -40%Unal, Critchley & Capewell Circulation 2004 109(9) 110168,230 fewerCHD deaths1981 2000
  12. 12. IMPACT modelExplaining the CHD mortality fall 1981-2000• 70% mortality fall due torisk factorreductions• 40%: due to evidence-based therapies-80000-60000-40000-200000Risk Factors worse +13%Obesity (increase) +3.5%Diabetes (increase) +4.8%Physical activity (less) +4.4%Risk Factors better -70%Smoking -41%Cholesterol -9%Population BP fall -9%Deprivation -3%Other factors -8%Treatments -40%AMI treatments -8%Secondary prevention -11%Heart failure -12%Angina: CABG & PTCA -4%Angina: Aspirin etc -5%Hypertension therapies -3%Unal, Critchley & Capewell Circulation 2004 109(9) 110168,230 fewerCHD deaths1981 2000
  13. 13. -80000-60000-40000-2000002000 2007-20k-18k+4kIMPACTsec: CHD Deathsprevented England 2000-2007
  14. 14. -80000-60000-40000-20000038,000 fall(~90% explained)2000 2007-20k-18k+4kIMPACTsec: CHD Deathsprevented England 2000-2007Bajekal et al. Plos Medicine 2012 9:6
  15. 15. -80000-60000-40000-200000Risk Factors worse + 11%BMI (increase) + 2%Diabetes (increase) + 9%Risk Factors better -49%Smoking - 4%Cholesterol - 6%SBP fall - 33%Physical inactivity - 1%Fruit & Veg - 5%Treatments uptake change -52%AMI/NSTEACS - 1%2’ post MI - 9%2’ post-revasc - 2%Stable Angina - 13%Heart failure - 10%Hypertension therapies - 4%Hyperlipidemia Rx - 12%Unexplained 11%2000 2007-20k-18k+4kIMPACTsec: CHD Deathsprevented England 2000-200738,000 fall(~90% explained)Bajekal et al. Plos Medicine 2012 9:6
  16. 16. Distribution of deaths prevented bysocio-economic group (IMD quintiles)-10%0%10%20%30%40%50%60%IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5 EnglandPercentoftotalDPPsTreatments Risk factors UnexplainedAffluent Deprived16
  17. 17. Main overall messages• 35% CHD mortality decline accelerated after 2000• Nationally, the proportion of mortality decline explainedby Treatments and Risk Factorschanged from 40%:60% (in 1980-2000 period)to treatments 55%: 45% risk factors (since 2000)17
  18. 18. Main overall messages• CHD mortality decline accelerated post-2000 (35% fall)• Nationally, the proportion of mortality decline explainedby Treatments and Risk Factorschanged from 40%:60% (in 1980-2000 period)to 55%:45% (since 2000)• No SEC gradients in most treatment uptakes• Bigger than expected falls in population Blood Pressure• % unexplained by model:small in deprived, larger in affluent(range 2% Q5 to 20% Q1). Why?18
  19. 19. UK Risk Factortrends 2000-200719
  20. 20. UK Trends inNHS burden2000-200720
  21. 21. Smoking: trends by deprivation quintilesMen 55+5%10%15%20%25%30%35%40%45%50%1995199619971998199920002001200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ5Women 55+5%10%15%20%25%30%35%40%45%50%1995199619971998199920002001200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ521
  22. 22. Total Cholesterol (mmol/l):trends by deprivation quintilesMen 55+ Women 55+5.05.56.06.57.019941998200320062008National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ55.05.56.06.57.019941998200320062008National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ522
  23. 23. ‹#›
  24. 24. 24Trends in unstable angina admissions. Hospital admission rates byage, sex and socio-economic circumstance quintile (SEC) in 1999and 2007. Figure 2a: Men, 2b: Women. Source: Hospital Episode Statistics
  25. 25. 25Trends in heart failure admissions. Hospital admission rates by age, sex andsocio-economic circumstance quintile (SEC) in 1999 and 2007.a: Men, b: Women. Data source: Hospital Episode Statistics
  26. 26. Treatment trends2000-2007generally equitable(comprehensivenational health service)26
  27. 27. CVD PREVENTION27
  28. 28. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%BirthAtheromaArtery ThrombosisSurvival
  29. 29. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%BirthAtheromaArtery ThrombosisSurvival
  30. 30. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%BirthFirst Stroke orHeart AttackAtheromaArtery ThrombosisSurvival
  31. 31. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%SuddenDeath(common)LuckyTypicaldeclineNO SymptomsSymptomsBirthFirst Stroke orHeart AttackSurvival
  32. 32. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%SuddenDeath(common)LuckyTypicaldeclineNO SymptomsSymptomsBirthSecondary prevention Health servicesFirst Stroke orHeart AttackSurvival
  33. 33. CVD process: in an individualCapewell et al 2009Middle Age Age (years) Youth100%0%SuddenDeath(common)TypicaldeclineNO SymptomsSymptomsBirthPrimaryPreventionSecondary preventionFirst Stroke orHeart AttackHealth servicesDiseasePromotionSurvivalLucky
  34. 34. CVD Prevention in a POPULATIONCapewell et al 200970 Age (years)100%0%60PrimaryPreventionFirst Stroke orHeart Attack80MarketingSurvival
  35. 35. Capewell et al 200970 Age (years)100%0%60MoreMarketingPrimaryPrevention First Stroke orHeart Attack80CVD Prevention in a POPULATIONSurvival
  36. 36. Capewell et al 200970 Age (years)100%0%60MarketingEg  tobacco controlEFFECTIVEPrimaryPreventionDELAYED First Strokeor Heart Attack80CVD Prevention in a POPULATIONSurvival
  37. 37. Capewell et al 200970 Age (years)100%0%60HEALTH PROTECTIONEg by tobacco or saltlegislationEFFECTIVEPrimaryPreventionFirst Stroke or HeartAttack PREVENTED80CVD Prevention in a POPULATIONSurvival
  38. 38. CVD prevention strategies• High Risk Individual approach• Population-based approach
  39. 39. 130 160110SystolicBP0302010Prevalence%Blood Pressuredistribution in thepopulationCVD prevention approaches120 140 150
  40. 40. 130 160110SystolicBP0302010Prevalence%Blood Pressuredistribution in thepopulationCVD prevention: High risk individualapproach120SBP >140 mmHg140 150
  41. 41. 130 1601100302010Prevalence%Blood Pressuredistribution in thepopulation120BP >140 mmHgMedicationsCVD prevention: High risk individualapproachSystolicBP 140 150
  42. 42. 130 1601100302010Prevalence%Shifting BloodPressure distributionPopulation-based CVD prevention strategy120SystolicBP 140 150
  43. 43. 130 1601100302010Prevalence%Shifting BloodPressure distribution120SystolicBP 140 150Population-based CVD prevention strategy
  44. 44. 130 1601100302010Prevalence%Shifting BloodPressure distribution120Fewer BP >140 mmHgLess treatmentsSystolicBP 140 150Population-based CVD prevention strategy
  45. 45. – Farmers’ subsidies to stop dairy & beef ,& increase fruit & berry production (Finland)– Support food reformulation (All)Whole-population approach forpreventing CVD: successful policies
  46. 46. – Farmers’ subsidies to stop dairy & beef ,start fruit & berry production (Finland)– Support food reformulation (All)– Banning transfats (Denmark, Switzerland, Austria)– Slashing dietary salt (Finland)– Promoting smoke-free public spaces(Ireland, UK ,Italy etc)Whole-population approach forpreventing CVD: successful policies
  47. 47. Ireland: modelling reductions incardiovascular risk factorsPrimary PreventionPopulation Approach Risk Factors in everyoneVersusHigh Risk strategyusing statin& bloodpressuremedicationsBMC Public Health 2007 7 117
  48. 48. -1,500-1,300-1,100-900-700-500-300-100CHD prevention in Ireland 1985-2000:Population v. High RiskStrategiesDeaths prevented or postponed (Sensitivity analysis )C h o l e s t e r o lPopulationdietchangePopulationsecular BPtrendsHighRiskStatinsTreatingHighRiskDietchangeinCHDpatientsBloodPressureBMC Public Health 2007 7BMC Public Health.2007; 7:117.
  49. 49. -1,500-1,300-1,100-900-700-500-300-100CHD prevention in Ireland 1985-2000:Population v. High RiskStrategiesDeaths prevented or postponed (Sensitivity analysis )C h o l e s t e r o lPopulationdietchangePopulationsecular BPtrendsHighRiskStatinsTreatingHighRiskDietchangeinCHDpatientsBloodPressureBMC Public Health 2007 7 117
  50. 50. CVD PREVENTION& INEQUALITIES50
  51. 51. Will CVD preventionwiden health inequalities?Capewell & Graham PLoS Medicine 2010
  52. 52. UK Department of Health programme:NHS Health ChecksThe UK high riskapproachfor preventing CVDCapewell & Graham PLoS Medicine 2010
  53. 53. UK Department of Health programme:NHS Health Checks– All adults aged 40+ screened for CVD risk– If 20%+ risk CVD event in the next tenyears, treat with:• lifestyle advice plus• tablets to reduce cholesterol & blood pressureThe UK high riskapproachfor preventing CVDCapewell & Graham PLoS Medicine 2010
  54. 54. Tudor Hart’s “Inverse Care Law”Tugwell’s “staircase effect”J Tudor Hart . The inverse care law. Lancet 1971; 1; 405. P Tugwell; BMJ 2006; 332; 358Evidence that high riskapproachmay increase social inequalitiesCapewell & Graham PLoS Medicine 2010
  55. 55. Tudor Hart’s “Inverse Care Law”• The availability of good medical care tends tovary inversely with actual needTugwell’s “staircase effect” Disadvantage canoccur at every stage:– Health beliefs, health behaviour, presentationparticipation, persistence or adherenceJ Tudor Hart . The inverse care law. Lancet 1971; 1; 405. P Tugwell; BMJ2006; 332; 358Evidence that high riskapproachmay increase social inequalities
  56. 56. Prescribing gradientsLong term adherenceSmoking cessationNutrition interventions in individualsOldroyd J. JECH 2008; 62:573. Thomsen R W, Br J Clin Pharm. 2005; 60;534;Ashworth, M, QJof Amb Care Management: 2008; 31; 220;Vrijens B, BMJ 2008;336:1114; Morisky D. Clin Hypertension 2008; 10; 348Johnell K BMC Public Health 2005, 5:17 Chaudhry HJ. Current Ather.Rep 2008; 10; 19; Bouchard MH, Br J Clin Pharmacol. 2007 63(6): 698Evidence that high riskapproachmay increase social inequalities
  57. 57. Kivimaki, Marmot et al Lancet 200815 year risk of CHD death• calculated in British men aged 55• quantified the benefits of decreasing risk factors uniformlyacross population[systolic blood pressure 10mmHgtotal cholesterol 2mmol/l & glucose  1 mmol/l ]Evidence that whole POPULATION CVDprevention reduces social inequalities
  58. 58. Kivimaki, Marmot et al Lancet 200815 year risk of CHD death• calculated in British men aged 55• quantified the benefits of decreasing risk factors uniformlyacross population[systolic blood pressure 10mmHgtotal cholesterol 2mmol/l & glucose  1 mmol/l ]• Would reduce the absolute mortality gap between affluent &deprived by 70%Evidence that whole POPULATION CVDprevention reduces social inequalities
  59. 59. Diet interventionsFolic acid fortification of cereals (USA population1996)Dowd IJE 2008; 37(5):1059Evidence that whole POPULATION CVDprevention reduces social inequalities
  60. 60. Diet interventionsFolic acid fortification of cereals (USA population1996)Blood folate levels: Social gradients   70%Dowd IJE 2008; 37(5):1059Evidence that whole POPULATION CVDprevention reduces social inequalities
  61. 61. Smoking• cigarette price increases more effective indeprived groups Townsend BMJ 1994; 309; 923“increase in tobacco price may have the potentialto reduce smoking related health inequalities”Main Meta-analysis. BMC Public Health 2008; 8; 178Evidence that whole POPULATION CVDprevention reduces social inequalities
  62. 62. ♥High Risk Strategiesto screen & treat individualstypically widen social inequalitiesCVD prevention& health inequalitiesVERDICTCapewell & Graham PLoS Medicine 2010
  63. 63. ♥High Risk Strategiesto screen & treat individualstypically widen social inequalities♥Population wide policy interventionsusually narrow the inequalities gapCVD prevention& health inequalitiesVERDICTCapewell & Graham PLoS Medicine 2010
  64. 64. RESERVESLIDES64
  65. 65. 65
  66. 66. WHOCommissiononSocialDeterminantsof Health2008
  67. 67. Life expectancy at birth (men)Glasgow, Scotland (deprived suburb) 54India 61Philippines 65Lithuania 66Poland 71Mexico 72Cuba 75US 75UK 76WHO Commission on Social Determinants of Health 2008
  68. 68. Life expectancy at birth (men)Glasgow, Scotland (deprived suburb) 54India 61Philippines 65Lithuania 66Poland 71Mexico 72Cuba 75US 75UK 76Glasgow, Scotland (affluent suburb) 82WHO Commission on Social Determinants of Health 2008
  69. 69. • Improve conditions of daily life• Tackle the inequitable distribution ofpower, money & resources• Measure & understand the problemand assess the impact of actionWHO Commission onSocial Determinants ofHealthThree overarching recommendations:http://www.euro.who.int/socialdeterminants/publications/publications
  70. 70. • CHD Mortality trends Global & UK• UK trends by socio-economic circumstance (SEC):• CHD Mortality trends; risk factor trends• IMPACTsec: explaining recent UK mortality trends• DISCUSSION 1: Main research messages for L&GUK trends to 2020• Risk factors; Treatments; CHD mortality71
  71. 71. 72Major risk factors:projecting trends to 2020
  72. 72. Men0102030110120456199419982003200620082020Total cholesterol mmol/l24262830199420082020BMI kg/m2Q1Q2Q3Q4Q5Policy-targetsLow-riskMajor risk factors: projecting trends to 202073
  73. 73. Men0102030110120456199419982003200620082020Total cholesterol mmol/l24262830199420082020BMI kg/m2Q1Q2Q3Q4Q5Policy-targetsLow-riskMajor risk factors: projecting trends to 202074
  74. 74. Men010203040Smoking prevalence (%)010203040Diabetes prevalence (%)0102030405060708090Physical inactivity (%)110120130140150SBP mmHg456199419982003200620082020Total cholesterol mmol/l24262830199420082020BMI kg/m2Q1Q2Q3Q4Q5Policy-targetsLow-riskMajor risk factors: projecting trends to 2020 75
  75. 75. Men Women010203040Smoking prevalence (%)010203040Diabetes prevalence (%)0102030405060708090Physical inactivity (%)110120130140150SBP mmHg456199419982003200620082020Total cholesterol mmol/l24262830199420082020BMI kg/m2Q1Q2Q3Q4Q5Policy-targetsLow-risk010203040Smoking prevalence (%)010203040Diabetes prevalence (%)0102030405060708090Physical inactivity (%)110120130140150SBP mmHg456199419982003200620082020Total cholesterol mmol/l24262830199420082020BMI kg/m2Q1Q2Q3Q4Q5Policy-targetsLow-riskMajor risk factors: projecting trends to 2020 76
  76. 76. IMPACTsec 2020Future scenarios to 202077
  77. 77. IMPACTsec 2020Future scenarios to 2020: What will happen toCHD inequalities if recent trends continue, ortargets met, or low-risk levels achieved?• 3 scenarios• Project past trajectories forwards (from mid-1990s)• Health targets met for ALL social groups• ALL social groups reach the healthy low-riskprofile78
  78. 78. IMPACTsec 2020Future scenarios to 2020: What will happen toCHD inequalities if recent trends continue, ortargets met, or low-risk levels achieved?• 3 scenarios• Project past trajectories forwards (from mid-1990s)• Health targets met for ALL social groups• ALL social groups reach the healthy low-riskprofile• Only Risk Factor trends considered(assumed treatment uptakes remain equitable)79
  79. 79. IMPACTsec Deaths potentially prevented in 202030006000900012000Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5Men WomenTrends continue Policy targets Low-risk80Men
  80. 80. IMPACTsec Deaths potentially prevented in 202030006000900012000Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5Men WomenTrends continue Policy targets Low-risk81
  81. 81. IMPACTsec Deaths potentially prevented in 202030006000900012000Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5Men WomenTrends continue Policy targets Low-risk82
  82. 82. IMPACTsec Deaths potentially prevented in 202030006000900012000Q1 Q2 Q3 Q4 Q5 Q1 Q2 Q3 Q4 Q5Men WomenTrends continue Policy targets Low-risk8320,000 Fewer deaths 50,000 fewer deaths 75,000 fewer deaths
  83. 83. Policy implications of 2020 ‘scenarios’• Actuaries• Falls in overall mortality rates anticipated• Relative inequalities in CHD mortality likely to persist• Risk factor trajectories suggest that SEC differentialswill continue to widen (unless stronger policy actions)84
  84. 84. Policy implications of 2020 ‘scenarios’• Actuaries• Falls in overall mortality rates anticipated• Relative inequalities in CHD mortality likely to persist• Risk factor trajectories suggest that SEC differentialswill continue to widen (unless stronger policy actions)• Health Policy Interventions• Regulation & Legislation would have biggest impacton reducing risk factor levels, especially in disadvantaged(Capewell, NICE)• ?Target disadvantaged groups, aim to level-up to‘best’, ‘proportionate universalism’?85
  85. 85. DISCUSSION 2Burning questions for Istanbul?86
  86. 86. DISCUSSION 2Burning questions for Istanbul?87Trends inCHD,Cardiovasculardisease &commoncancers(NCDs) ?Increasinggapbetweenrich & poor:effects onCHD?Why recentpopulationfalls incholesterolor inbloodpressure?Futureeffects oftobaccolegislation?Transfatbans?
  87. 87. Key questions (Istanbul)1. What are the key policy changes or new drug developments thatwould affect mortality trends in the near future?2. How will the gap in life expectancy between SEC change over,say next 30 years?3. How will the gap in life expectancy between genders changeover, say next 30 years?4. What are the key drivers for the future fall in mortality fordifferent SEC?5. How would these mortality drivers affect different SEC?88
  88. 88. IMPACTsec team• Legal & General – Dr Madhavi Bajekal, Dr ShaunScholes, Hande Love• UCL – Prof Rosalind Raine,• Liverpool University – Prof Simon Capewell, Dr MartinO’Flaherty, Dr Nat Hawkins• Advisory Group89
  89. 89. Which factors explained ‘excess’ CHDmortality in Q5 compared to Q1?(PROVISIONAL ANALYSIS)90010002000300040005000600070008000900010000Excess CHD deaths:Q5 vs Q1, 20075.8k2.6kHigher treatmentsuptake in Q1 + 26%Lower risk factorlevels in Q1 + 58%% Unexplained by model + 16%1.6kQ1 Q5
  90. 90. 91010002000300040005000600070008000900010000Excess CHD deaths:Q5 vs Q1, 20075.8k2.6kTreatments uptake + 26%AMI/NSTEACS + 4%2’ post MI + 5%2’ post-revasc + 1%Stable Angina + 7%Heart failure + 9%1’ statin/hypertension + 0%Risk Factors + 58%BMI + 2%Diabetes + 11%Smoking + 26%Cholesterol (better Q5) - 3%SBP fall + 12%Physical inactivity + 1%Fruit & Veg + 10%Unexplained 16%1.6kQ1 Q5Which factors explained ‘excess’ CHDmortality in Q5 compared to Q1?(PROVISIONAL ANALYSIS)
  91. 91. • Treatments (numbers)a) Eligible patients – Acute MI, Angina, Heart Failureb) Treatment uptake: 10 (eg statins, BP ) + 20 preventionmedication+ surgical interventions (CABG, PTCA)c) Case fatality rate by diagnosis (one year)d) Estimated mortality red’n due to treatment (one year)Calculation• DPP for one year = a*b*c*d• Change DPP= DPP final – DPP baseParameters and calculation92
  92. 92. Treatments 1- eligible patient countsCondition Hospital CommunitySTEMI 60% AMI admissions(HES)NSTEMI + UnstableAngina(or NSTEACS)40% AMI admissions +100% UA admissions(HES)2’ post-revascularisation(CABG/PTCA/PCI)2000-2007 counts fromHES, adjusted forsurvival2’ post-MI GPRDChronic angina (no MI) GPRDHeart Failure 50% admissions (HES) 50% prevalence (GPRD)1’ lipid lowering drugs HSfE1’ hypertensive treatment HSfE93
  93. 93. Treatments 2 – medical therapiesCondition Drugs Interventions OtherSTEMI MINAP PPCI & thrombolysis(MINAP)CPR – H (MINAP)CPR – cmty (no change)NSTEMI + UnstableAnginaMINAP CABG/PCI (HES) CPR – H (MINAP)2’ post-revascularisation(CABG/PTCA)GPRD Rehabilitation (Bethell +National Audit)2’ post-MI GPRD Rehabilitation (Bethell +National Audit)Chronic angina (no MI) GPRDHeart Failure - H NHS Heart FailureSurvey, 2005Heart Failure - Cmty GPRD1’ lipid lowering drugs HSfE (no CHD)1’ hypertensivetreatmentHSfE (no CHD)94
  94. 94. Treatments 3 - challenges• Low or Negative Tx DPPs – because numbers admittedhigher in 2000 than 2007 eg for HF– Applied treatment uptake rates in 2000 to patient counts in2007. Difference gives net DPPs• Patient overlaps• Mants & Hicks adjustment to calc benefits from drugcombinations95
  95. 95. Risk Factor methods
  96. 96. Parameters and calculationContinuous measures– Systolic BP, BMI, total cholesterol, fruit and vegetableconsumption• Regression approach:(deaths base year)* (1-e (∆ in RF*beta coeff))Binary measures– Smoking, diabetes, physical activity• PARF (population attributable risk factor) approach:(deaths base year)* (PARF final – PARF base)97
  97. 97. Risk Factors 1 - descriptionRisk factor HSfE survey years DescriptionCurrent cigarette smoking 2000-7 Self-reported statusSBP (mmHg) 2000-7, except 2004 Mean of the 2nd and 3rd readingsFruit and vegetableconsumption2001-7 Measured in portions per dayBody Mass Index 2000-7 Weight (kg)/ height squared (m2)Total cholesterol (mmol/l) 1998, 2003, 2006 Subdivisible into those on lipid-loweringdrugs and those not on drugsPhysical (in) activity 1998, 2003, 2006 % not doing 30+ minutes of moderate orvigorous leisure –time activity at least 5days/ per week.Diabetes 1998, 2003, 2006 Doctor diagnosed diabetes, exclpregnancy98
  98. 98. Risk factors 2 - challenges• Sample sizes per year too small for precise estimates byage (7), sex (2) and SEC (5)• Fixed gradient approach used for SEC estimates– Pooled survey data (2000-07) by SEC and calc scaling factorfor each SEC relative to the national level for each age/sex groups– Applied SEC scaling factors to England values in 2000 & 2007(or nearest available year)– Where end-points 7+ years, adjusted down change estimates(eg *7/8 for 1998, 2006 est)99
  99. 99. Other model parametersTreatments• Case fatality rates: Canadian IMPACT• RRR due to Tx: Canadian IMPACT + updated to mostrecent published (Nat Hawkins)Risk Factors• Beta coeffs: US IMPACT + Cholesterol (ICELAND) + newFruit and Veg (Duchet)• Relative risk – US IMPACT100
  100. 100. Treatment uptake - summary• Uptake of all drugs increased in all SEC groups between2000 and 2007.• No socioeconomic gradients in the uptake of treatment -NHS delivering equitable service.• Treatments in the community increased most: eg drugtreatment for angina + 2’ prevention doubled, from around30% to over 60%.• However, uptake levels were still below optimal and needto increase further.101
  101. 101. Main overall messages• CHD mortality decline accelerated post-2000 (35% fall)• Nationally, the proportion mortality decline explainedby Treatments and Risk Factorschanged from 40:60 (in 1980-2000 period)to 55:45 (in post-2000 period)• No SEC gradient in Treatment uptake• Bigger than expected falls in population Blood Pressure• % unexplained by model small in deprived, larger inaffluent (range 2% Q5 to 20% Q1). Why?102
  102. 102. LIMITATIONS: With hindsight..• Extend time period – minimum 10 years (1997-2007)• Micro-level GPRD data:– for accurate drug combination uptake; compliance over year;– Eligible patients tightly defined, eg excluding MIs recorded10+ years ago, unconfirmed diagnosis?• Include upstream risk factors – eg psychosocialstatus – to explain the ‘unexplained’ part of the model?• Refine sensitivity analysis method: Credible limitsfor risk factor DPPs narrower than Tx – counter-intuitive!103
  103. 103. 104β Coefficients = % fall in CHD mortality perunit decrease in risk factors(from meta-analyses & cohorts , Ford et al, NEJM 2007 356 : 2388Cholesterol lowering PSC 2007 Reduction in CHD deaths 0.1mmol/l mean pop cholesterol   5%Fruit & Veg Duchet J Nutrition 20061 portion/day   4%Blood pressure PSC Lancet 2003 1 mm Hg Systolic BP   3.5% (log -0.035)Obesity Bogers, 20081 Kg/M2  BMI   2.5%Diabetes InterHEART, 20041%  diabetic population   2%Smoking InterHEART, 20041%  Smoking prevalence   1%Physical Activity InterHEART, 20041%  inactive population   0.3%Ford et al NEJM 2007
  104. 104. Population risk factor change 1980/2000:Impact on CHD Mortality US example3mmHg fall in systolic BP in women aged 55-64CHD deaths Beta Risk Factor Deathsin 1980 coefficient reduction prevented1980-2000 or postponed (DPP)a x β x c = a*(1-(EXPβ x c))26,350 x -0.035 x 3 = 2700 DPPSOURCESMortality Oxford PSC NHANESstatistics meta-analyses surveys105Ford et al NEJM 2007
  105. 105. AMI: Thrombolysis & Aspirin, Men 55-64 yearsPatients Treatment Relative Case Deaths preventedeligible uptake risk Fatality or postponed (DPP)reductiona x b x c x d = a x b x c x d102,280 X 21% x 0.26 x 0.054 = 303SOURCESHES MINAP Estess & FTT US/??statistics audits Meta-analyses106Treating individual CHD patients - impacton population CHD mortality: US exampleFord et al NEJM 2007
  106. 106. Trends in AMI admissions 1999-2006per 100,000 by deprivation quintilesMales (3 year average) Females (3 year average)1999 2000 2001 2002 2003 2004 2005 2006q1q2q3q4q50.050.0100.0150.0200.0250.0300.0350.01999 2000 2001 2002 2003 2004 2005 2006Q1Q2Q3Q4Q5107
  107. 107. GPRD Data fuzziness: MI & Angina(not to scale)Schematic diagram2006 – counts (pop prev inbrackets)Post MI(A)Other unspecifiedIHD(C)Angina in thecommunity(B)Post MI6,109 (2.3%)Other unspecifiedIHD9,222Angina in thecommunity15,658 (3.4%)(D)(E)(F)(G)2,686 6,3489,04817,553108
  108. 108. Fruit & veg (portions per day):trends by deprivation quintilesMen 55+ Women 55+2.53.03.54.04.55.0200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ52.53.03.54.04.55.0200220032004200520062007National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ5109
  109. 109. Meeting physical activityrecommendations (%):trends by deprivation quintilesMen 55+ Women 55+5%10%15%20%25%1998200320062008National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ55%10%15%20%25%1998200320062008National IMDQ1 IMDQ2IMDQ3 IMDQ4 IMDQ5110
  110. 110. Change in key risk factor levelsMen 25+ Age-standardised rates, by IMD quintiles5.205.255.305.355.405.455.505.555.605.65IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5mmol/lTotal Cholesterol: 1998 v 2006199820060.01.02.03.04.05.06.07.08.09.010.0IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5ASRper100Diabetes: 1998 v 2006111
  111. 111. Risk factor trends by SEC: adults aged 55+Annual % Δ Men WomenSignificantdecreaseacrossall SECgroupsSmoking SBP Total cholesterol Smoking  (x Q4)SBP Total cholesterol Significantincreaseacross allSEC groupsObesityDiabetesObesity (x Q2)DiabetesMixed pictureby SECPhys activity increase: Q1-Q3Fruit & veg increase: Q3Phys activity increase: Q1-Q4Fruit & veg increase: Q3-Q4112Q1 = least deprived; Q5 = most deprived Scholes, SSM 2010
  112. 112. UK 1984-2004Overall age-adjusted CHD mortality rates0.00100200300400500600700800900yearCHDratesper10^6menwomen2.7% per year (rate of decline)3.7%5.4%1.7%3.5%4.2%
  113. 113. Men 65 – 74 years• JoinPoint Analysis• 3 periods identified• annual percent changeincreasedUK Age-specificCHD mortality rates1984-2004Deaths per 1051600600
  114. 114. Rates Flattening inMen 45-54 years• 4 periods identified• annual percent changedecreasedMen 65 – 74 years• JoinPoint Analysis• 3 periods identified• annual percent changeincreasedUK Age-specificCHD mortality rates1984-2004Deaths per 1054020Deaths per 1051600600
  115. 115. Treatment trends2000-2007116
  116. 116. Myocardial infarction treatmentsTrends & socioeconomic gradients
  117. 117. • No socioeconomic gradients• Most therapies already high uptake• Clopidogrel uptake doubledMyocardial infarction treatmentsTrends & socioeconomic gradients
  118. 118. Secondary preventionTrends & socioeconomic gradients
  119. 119. • No socioeconomic gradients• Overall treatment levels approximately doubled• Absolute treatment uptake 60 to 70%Secondary preventionTrends & socioeconomic gradients
  120. 120. Chronic angina treatmentsTrends & socioeconomic gradients
  121. 121. • Socioeconomic gradients – greater uptake in mostdeprived• Overall treatment levels approximately tripled• Treatment levels lower than MI or secondary preventionChronic angina treatmentsTrends & socioeconomic gradients
  122. 122. Change in treatment: Statin &ACE-I/ARB uptake Men 55-7400.10.20.30.40.50.60.70.80.9IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5 EngStatins2000200700.10.20.30.40.50.60.70.80.9IMDQ1 IMDQ2 IMDQ3 IMDQ4 IMDQ5 EngACE-I/ARB20002007Affluent Deprived Affluent Deprived

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