Advertisement
Canadian Journal of Cardiology

Score of Adherence to 2016 European Cardiovascular Prevention Guidelines Predicts Cardiovascular and All-Cause Mortality in the General Population

      Abstract

      Background

      Guidelines on cardiovascular (CV) disease prevention promote healthy lifestyle behaviours and CV risk factor control to reduce CV risk. The effect of adherence to these guidelines on CV and all-cause mortality is not well known.

      Methods

      We assessed the effect of baseline adherence to “2016 European Guidelines on CV Disease Prevention in Clinical Practice” on long-term CV and all-cause mortality in a sample recruited from the French general population. Analysis was on the basis of the Third French Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) population-based survey (recruitment period: 1994-1997). We built an adherence score to European guidelines, considering adherence to recommendations for smoking, drinking, physical activity, body mass index, blood pressure, low-density and high-density lipoprotein cholesterol, fasting blood glucose, and diet at baseline. Vital status was obtained 18 years after inclusion. Statistical analysis was on the basis of multivariate Cox modelling.

      Results

      Adherence score was assessed in 1311 apparently healthy participants aged 35-64 years (73% men). During the follow-up, 186 deaths occurred (41 were due to a CV cause). Considering CV mortality, the adjusted hazard ratio for subjects in the fourth quartile of the adherence score (worse adherence) was 3.12 (95% confidence interval [CI], 1.62-6.01; P = 0.001), compared with subjects in the first, second, or third quartile (best adherence). Considering all-cause mortality, the adjusted hazard ratio for subjects in the fourth quartile of the adherence score was 2.27 (95% CI, 1.68-3.06; P < 0.001).

      Conclusions

      Better baseline adherence to European guidelines on CV disease prevention was associated with a significantly reduced long-term CV and all-cause mortality in a sample from the French general population.

      Résumé

      Contexte

      Les recommandations pour la prévention des maladies cardiovasculaires font la promotion de comportements correspondant à un mode de vie sain ainsi que du contrôle des facteurs de risque cardiovasculaire afin de réduire le risque cardiovasculaire. L’effet de l'observance à ces recommandations sur la mortalité cardiovasculaire et toutes causes confondues n’est pas bien connu.

      Méthodologie

      Nous avons évalué l’effet de l’observance aux Recommandations européennes sur la prévention des maladies cardiovasculaires en pratique clinique sur la mortalité cardiovasculaire et toutes causes confondues à long terme à partir d’un échantillon recruté en population générale française. Les analyses ont été fondées sur la troisième enquête française de surveillance des tendances et des déterminants des maladies cardiovasculaires (MONICA) (période de recrutement : 1994-1997). Nous avons établi un score d'observance aux recommandations européennes, en prenant en compte l'observance aux recommandations portant sur le tabagisme, la consommation d’alcool, l’activité physique, l’indice de masse corporelle, la pression artérielle, le cholestérol (LDL et HDL), la glycémie à jeun, ainsi que le régime alimentaire à l'inclusion. Le statut vital a été obtenu avec un recul de 18 ans après l’inclusion dans l’étude. L’analyse statistique a reposé sur un modèle de Cox.

      Résultats

      Le score d'observance a été obtenu pour 1311 participants apparemment en bonne santé âgés de 35 à 64 ans (73 % d’hommes). Au cours du suivi, 186 décès sont survenus (41 étaient attribuables à une cause cardiovasculaire). Pour la mortalité cardiovasculaire, le risque relatif ajusté pour les sujets appartenant au quatrième quartile du score d'observance (correspondant à la catégorie des sujets ayant la plus mauvaise observance) était de 3,12 (intervalles de confiance [IC] à 95 %, 1,62-6,01; p = 0,001), comparativement aux sujets du premier, du second et du troisième quartile (catégories correspondant à de meilleurs niveaux d'observance). Pour la mortalité toutes causes confondues, le risque relatif ajusté était de 2,27 (IC à 95 %, 1,68-3,06; p < 0,001).

      Conclusions

      Une observance accrue à l'inclusion des Recommandations européennes sur la prévention des maladies cardiovasculaires est associée à une réduction significative de la mortalité cardiovasculaire et toutes causes confondues à long terme au sein d’un échantillon issu de la population générale française.
      Guidelines on cardiovascular (CV) disease prevention promote healthy lifestyle behaviours and CV risk factor control to reduce CV risk. The effect of adherence to these guidelines on CV and all-cause mortality is not well known. Indeed, previous studies have assessed the effect of healthy lifestyle behaviours (such has exhibiting a healthy diet, regular physical activity, no or moderate alcohol consumption, weight control, and smoking abstinence) on CV
      • Khaw K.T.
      • Wareham N.
      • Bingham S.
      • et al.
      Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study.
      • Kvaavik E.
      • Batty G.D.
      • Ursin G.
      • Huxley R.
      • Gale C.R.
      Influence of individual and combined health behaviors on total and cause-specific mortality in men and women: the United Kingdom health and lifestyle survey [erratum in: 2010;170:998].
      • Petersen K.E.
      • Johnsen N.F.
      • Olsen A.
      • et al.
      The combined impact of adherence to five lifestyle factors on all-cause, cancer and cardiovascular mortality: a prospective cohort study among Danish men and women.
      and all-cause
      • Loef M.
      • Walach H.
      The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis.
      • Behrens G.
      • Fischer B.
      • Kohler S.
      • et al.
      Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men.
      • Carlsson A.C.
      • Wändell P.E.
      • Gigante B.
      • et al.
      Seven modifiable lifestyle factors predict reduced risk for ischemic cardiovascular disease and all-cause mortality regardless of body mass index: a cohort study.
      mortality but none of these studies have explored the combined effect of achieving healthy lifestyle behaviours and controlling CV risk factors. To our knowledge, only one study in the US general population has focused on such a combination (“ideal CV health behaviours or factors: not smoking; being physically active; having normal blood pressure, blood glucose, total cholesterol levels, and weight; and eating a healthy diet”) on long-term CV and all-cause mortality.
      • Yang Q.
      • Cogswell M.E.
      • Flanders W.D.
      • et al.
      Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.
      This study showed that long-term CV and all-cause mortality was lowered when the number of CV health behaviours or factors increased. No similar data are available in European populations.
      One difficulty when one wants to assess the effect of adherence to guidelines is how to discriminate adherent and nonadherent people. Most previous studies have used different cutoffs for dichotomizing adherent vs nonadherent participants, which makes comparisons between studies difficult, and is not precise enough to adequately capture the wide range of adherence levels that can be observed in a population. As previously described in a study on adherence to cancer prevention guidelines,
      • Kabat G.C.
      • Matthews C.E.
      • Kamensky V.
      • Hollenbeck A.R.
      • Rohan T.E.
      Adherence to cancer prevention guidelines and cancer incidence, cancer mortality, and total mortality: a prospective cohort study.
      and to better take into account the variability of lifestyle behaviours and risk factors that can be encountered in a population, we created a score of adherence on the basis of the combination of multiple categories of each lifestyle behaviour and risk factor.
      The aim of this study was to assess the effect of this score of adherence to 2016 European guidelines on CV disease prevention,
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • 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).
      baseline measurement of healthy lifestyle behaviours and CV risk factor control, on long-term CV and all-cause mortality, in a sample recruited from the French general population.

      Methods

      Study population and design

      A sample of 3402 subjects was randomly recruited from the general population to participate in the Third French Monitoring of Trends and Determinants in Cardiovascular Disease (MONICA) cross-sectional survey on the prevalence of CV risk factors.
      • Kuulasmaa K.
      • Tunstall-Pedoe H.
      • Dobson A.
      • et al.
      Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations.
      • Marques-Vidal P.
      • Ruidavets J.B.
      • Amouyel P.
      • et al.
      Change in cardiovascular risk factors in France, 1985-1997.
      Middle-aged men and women (35-64 years old), living in northern (Lille area), northeastern (Strasbourg area) or southwestern France (Toulouse area), were recruited between December 1994 and July 1997. Polling lists available in each town hall of the survey areas were used to obtain the stratified random sample. Stratification was applied according to centre, town size (rural vs urban), age, and sex to obtain 200 subjects in each 10-year age group (35-44, 45-54, and 55-64 years), sex, and centre. No incentive to participate (in particular no financial incentive) was offered. Written informed consent to participate in the study was obtained from each subject after full explanation of the nature of the research. The participation rate was 66%.
      • Marques-Vidal P.
      • Ruidavets J.B.
      • Amouyel P.
      • et al.
      Change in cardiovascular risk factors in France, 1985-1997.
      A diet survey (3 consecutive-day record of dietary consumptions) was carried out among a subsample of 1520 men and women selected from the population study. Subjects who did not participate to the diet survey were excluded from the analyses.
      Because we aimed to study apparently healthy people, subjects (n = 114) with the following previous medical histories were excluded from the analyses: ischemic heart disease (International Classification of Disease, 9th revision, codes 410.0 to 414.9), atherosclerotic cerebrovascular disease (433.0 to 438.9, except codes 437.3 to 437.7), atherosclerosis in other arteries such as aorta, renal, or lower limb arteries (440.0 to 440.9), chronic renal failure (585.0 to 585.9), chronic respiratory insufficiency (496.0 to 496.9), chronic heart failure (428.0 to 428.9), chronic liver disease or cirrhosis (571.0 to 571.9), and cancer, excluding benign neoplasms and in situ carcinoma (140.0 to 209.9 and 235.0 to 239.9).
      Vital status on December 31, 2013 was obtained for each participant through the national database that records each year all deaths occurring in French citizens living inside or outside the French Territory (Répertoire National d'Identification des Personnes Physiques [National Identification Register of Private Individuals]).

      CESP (Center for research in Epidemiology and Population Health), INSERM (French National Institute of Health and Medical Research) – Paris-Sud University. Implementation of edict n° 98–37. Available at: http://cesp.vjf.inserm.fr/svcd. Accessed June 8, 2017.

      This database is currently used to assess vital status in France. In previous similar works, the information brought by the Répertoire National d'Identification des Personnes Physiques database was compared with the data recorded in the civil registration. Less than 1.5% of discrepancies were noted between the 2 sources of data. All causes of death were obtained for participants who died before December 31, 2013. Main and associated causes of death were provided by the French National Institute of Health Research (CépiDc-INSERM), which systematically collects and codes (using the International Classification of Diseases coding system) data recorded on death certificates. Death from a CV cause (hypertensive disease, ischemic heart disease, conduction disorders, cardiac dysrhythmias, heart failure, atherosclerotic cerebrovascular disease, atherosclerosis, and sudden death) during the follow-up was assessed by a committee of 4 medical physicians every time CV disease was reported as the main cause of death, or when it was mentioned as an associated cause, if the main cause was a plausible complication of CV disease. Authorizations to use these data were obtained in accordance with the French law (Commission Nationale de l'Informatique et des Libertés: authorization 355152v1, September 3, 2008).
      The study protocol was approved by an institutional ethics committee (Comité Consultatif de Protection des Personnes dans la Recherche Biomédicale, Lille, France), on January 19, 1995 (CP 95/04) in accordance with the French law on human biomedical research and the Declaration of Helsinki.

      Questionnaires, measurements of clinical parameters, and laboratory methods

      Questionnaires, measurements of clinical parameters, and laboratory methods are described in the Supplemental Methods section of the Supplementary Material.

      Score of adherence to 2016 European CV prevention guidelines

      We built a score of adherence to 2016 European guidelines on CV disease prevention in clinical practice,
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • 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).
      including baseline smoking, drinking, and physical activity habits, control of body mass index, blood pressure, low-density lipoprotein and high-density lipoprotein cholesterol, fasting blood glucose, and diet quality (daily consumption of polyunsaturated, monounsaturated, and saturated fatty acids, sugar, sodium, fibre, fruits, vegetables, and fish) (Supplemental Table S1). The components of the score of adherence were those listed in the European guidelines as main targets of a healthy lifestyle.
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • 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).
      We created multiple categories of adherence for each component instead of arbitrary considering adherent vs nonadherent people. We have to note that people with lower adherence to CV prevention guidelines was not defined using a clinical point of view but in an epidemiological point of view. Indeed a participant with high blood pressure could have done his best and took different medications, but had high blood pressure because of resistant hypertension. The way the score was built is shown in Supplemental Table S1. Briefly, for each component, the level of adherence of a participant was estimated on a scale comprised of 3-6 levels, with the highest level corresponding to the worse adherence. The weight of the different components was chosen according to previously developed CV risk prediction algorithms.
      • Bérard E.
      • Bongard V.
      • Arveiler D.
      • et al.
      Ten-year risk of all-cause mortality: assessment of a risk prediction algorithm in a French general population.
      • Wilson P.W.
      • D'Agostino R.B.
      • Levy D.
      • et al.
      Prediction of coronary heart disease using risk factor categories.
      • Conroy R.M.
      • Pyörälä K.
      • Fitzgerald A.P.
      • et al.
      Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project.
      These different levels of adherence were finally added to obtain a total adherence score ranging from −3 (optimal adherence) to 27 points (minimal adherence) that we categorized into quartiles for statistical analyses (Supplemental Table S1). Among the 1406 apparently healthy people who participated in the dietary record, 95 (7%) had missing data for the adherence score, thus leading to a sample of 1311 subjects analyzed.

      Statistical analysis

      Statistical analysis was performed using STATA statistical software, release 11.2 (STATA Corp, College Station, TX). All reported P values were 2-sided and the significance threshold was < 0.05.
      We first described and compared the main characteristics of the participants according to quartiles of adherence score to European CV prevention guidelines. Categorical variables were compared between groups using the χ2 test (or Fisher exact test when necessary). Analysis of variance (ANOVA) was used to compare the distribution of continuous data (Kruskall-Wallis test was used when necessary).
      Survival analysis was then conducted. Events were cases of death (all-cause or CV death) and exposure was defined by the 4 groups (quartiles) of adherence score at baseline. For all-cause mortality, Kaplan-Meier survival curves were drawn and differences in survival functions were tested using the log rank test. Cumulative incidence functions and Gray test were used for CV mortality, in a competing risk setting, because other causes of death compete with CV causes. Adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) were assessed using a standard Cox model, for all-cause mortality, and a proportional subdistribution hazard model, which is an extension of the Cox model to the situation of competing risks,
      • Fine J.
      • Gray R.
      A proportional hazards model for the subdistribution of a competing risk.
      for CV mortality. Survival models were adjusted for energy intake (in kilocalories per day) and the following standard nonmodifiable risk factors: age, sex, educational level, and centre. Exposure to lipid-lowering drug, blood pressure-lowering drug, and hypoglycaemic drug was initially included in survival models as a potential confounder but was finally removed; first because it was not independently associated with CV or all-cause mortality, and second because adjusting for these drugs had no significant effect on the HRs related to the effect of the score of adherence. Because the log-linearity hypothesis was not fully respected, the following continuous variables were transformed into ordered categorical data: adherence score and energy intake (transformed into quartiles) and age (35-44, 45-54, and 55-64 years). The proportional hazard assumption was tested for each covariate using the “log log” plot method curves ([−ln (−ln [survival])], for each category of nominal covariate, vs ln [analysis time]). None of the assumptions could be rejected. First-order interactions between the adherence score and the independent covariates were tested in the survival models. None exceeded the significance threshold of 0.05.

      Results

      In Table 1 the main baseline characteristics of the study participants are described and compared according to quartiles of adherence score to 2016 European CV prevention guidelines. At baseline, 73% of the participants were men and 81% were 45-64 years old. As expected, the rate of CV risk factors increased significantly with the adherence score (the higher the score, the lower the adherence; Table 1). During the follow-up, 186 deaths occurred (93, 41, and 52 deaths were due to cancer, CV, and other cause, respectively). The median follow-up was 18 years (interquartile range: 17-18 years). Figure 1 shows predictors of CV and all-cause mortality in univariate survival analysis. Older age, male sex, northern France centre, smoking, high blood pressure (and antihypertensive drug treatment), high fasting blood glucose, and low polyunsaturated fatty acid consumption were significantly associated with higher CV and all-cause mortality risk. In addition, low educational level (less than high school completion), drinking, no or light physical activity, high body mass index, and low high-density lipoprotein cholesterol for men were significantly associated with higher all-cause mortality (Fig. 1). Moreover, for subjects in the fourth quartile of the adherence score (which corresponds to the worse adherence) long-term CV and all-cause mortality was significantly increased (Fig. 2). Considering CV mortality, the nonadjusted HR for subjects in the fourth quartile of the adherence score was 3.70 (95% CI, 2.00-6.84; P < 0.001), compared with subjects in the first, second, or third quartile. Considering all-cause mortality, the nonadjusted HR for subjects in the fourth quartile of the adherence score was 2.63 (95% CI, 1.97-3.51; P < 0.001; Fig. 1). After adjustment for nonmodifiable risk factors and energy intake (Table 2), the HR for subjects in the fourth quartile of the adherence score was 3.12 (95% CI, 1.62-6.01; P = 0.001), and 2.27 (95% CI, 1.68-3.06; P < 0.001) for CV and all-cause mortality, respectively. According to French vital statistics provided by the French National Institute of Health Research (CépiDc-INSERM) from 1995 to 2013, we assessed the number of preventable deaths (death occurred in subjects in the fourth quartile of adherence) on the population level. In the French population, during the 18-year follow-up, this number was 90,702 for CV mortality and 419,020 for all-cause mortality. Indeed, the attributable risk to the fourth quartile of adherence was 34% and 23% for long-term CV and all-cause mortality, respectively.
      Table 1Main characteristics of the study participants according to quartiles of Adherence Score to European cardiovascular prevention guidelines
      Total (N = 1311)Q1 (n = 344)Q2 (n = 339)Q3 (n = 308)Q4 (n = 320)P
      Age0.0004
       35-44 years253 (19.3)93 (27.0)66 (19.5)41 (13.3)53 (16.6)
       45-54 years547 (41.7)141 (41.0)137 (40.4)133 (43.2)136 (42.5)
       55-64 years511 (39.0)110 (32.0)136 (40.1)134 (43.5)131 (40.9)
      Men957 (73.0)199 (57.8)238 (70.2)245 (79.5)275 (85.9)
      Centre< 0.0001
       Northeastern France694 (52.9)213 (61.9)178 (52.5)152 (49.4)151 (47.2)
       Southwestern France314 (24.0)83 (24.1)84 (24.8)80 (26.0)67 (20.9)
       Northern France303 (23.1)48 (14.0)77 (22.7)76 (24.7)102 (31.9)
      Educational level < high school completion888 (67.7)217 (63.1)220 (64.9)205 (66.6)246 (76.9)0.0006
      Antihypertensive drug treatment206 (15.7)32 (9.3)48 (14.2)63 (20.5)63 (19.7)0.0001
      Lipid-lowering drug treatment162 (12.4)31 (9.0)45 (13.3)48 (15.6)38 (11.9)0.0768
      Hypoglycemic drug51 (3.9)7 (2.0)13 (3.8)14 (4.5)17 (5.3)0.1540
      Data are presented as n (%). Other characteristics of the study participants (components of Adherence Score) according to quartiles of Adherence Score are described in Supplemental Table S2.
      Q1-Q4, quartiles of distribution (Q1, lowest quartile to Q4, highest quartile). First (Q1) and fourth (Q4) quartiles of Adherence Score correspond to best and least adherence, respectively.
      Figure thumbnail gr1
      Figure 1(A) Predictors of cardiovascular mortality in univariate survival analysis and (B) predictors of all-cause mortality in univariate survival analysis. Quartiles were combined together when corresponding Hazard Ratios were similar. (1) Reference is 35-44 years old; (2) reference is Strasbourg centre (North-Eastern France); (3) reference is never smokers; (4) reference is nondrinking or drinking 1-2 drinks per day for men and 1 drink per day for women; (5) reference is no regular or light physical activity almost every week; (6) reference is BMI < 25; and (7) reference is blood pressure < 140 and 90 mmHg. Educational level < high school completion; ∗∗Men, ≥ 3 drinks per day; women, ≥ 2 drinks per day; ∗∗∗During at least 20 minutes at least 1 time a week. BMI, body mass index; BP, blood pressure; CI, confidence interval; FBG, fasting blood glucose; LA, least adherent; Mono, monounsaturated; NF, northern France; Poly, polyunsaturated; Q1, first quartile; Q2, second quartile; Q3, third quartile; Q4, fourth quartile; Ref, reference; Sat, saturated; SWF, southwestern France.
      Figure thumbnail gr2
      Figure 2Nonadjusted survival curves for the relation between Adherence Score to European CV prevention guidelines and (A) CV or (B) all-cause mortality. CIF, cumulative incidence function; CV, cardiovascular.
      Table 2Adjusted HRs for cardiovascular and all-cause mortality according to quartiles of Adherence Score to European cardiovascular prevention guidelines
      N = 1311Cardiovascular mortality (n = 41)All-cause mortality (n = 186)
      Events, nAdjusted
      Adjusted for centre, age, sex, educational level, and energy intake (kilocalories per day).
      HR
      95% CIPEvent, nAdjusted
      Adjusted for centre, age, sex, educational level, and energy intake (kilocalories per day).
      HR
      95% CIP
      Q1 (n = 344)51.00321.00
      Q2 (n = 339)71.110.35-3.490.858411.040.65-1.660.860
      Q3 (n = 308)71.130.36-3.580.830320.810.49-1.330.407
      Q4 (n = 320)223.401.24-9.310.017812.141.40-3.27< 0.001
      P value for trend0.010< 0.001
      Q1-2-3 (n = 991)191.001051.00
      Q4 (n = 320)223.121.62-6.010.001812.271.68-3.06< 0.001
      First (Q1) and fourth (Q4) quartiles correspond to most and least adherence, respectively.
      CI, confidence interval; HR, hazard ratio.
      Adjusted for centre, age, sex, educational level, and energy intake (kilocalories per day).

      Discussion

      In our sample of apparently healthy subjects recruited from the French general population, we found, after adjustment for nonmodifiable risk factors (and energy intake), that better baseline adherence to European guidelines on CV disease prevention is significantly associated with a reduced risk of long-term CV and all-cause mortality.
      These results are in line with other studies that have assessed the positive effect of healthy lifestyle behaviours (such as following a healthy diet, regularly practicing physical activity, having moderate alcohol consumption, controlling weight, and not smoking) on long-term CV
      • Khaw K.T.
      • Wareham N.
      • Bingham S.
      • et al.
      Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study.
      • Kvaavik E.
      • Batty G.D.
      • Ursin G.
      • Huxley R.
      • Gale C.R.
      Influence of individual and combined health behaviors on total and cause-specific mortality in men and women: the United Kingdom health and lifestyle survey [erratum in: 2010;170:998].
      • Petersen K.E.
      • Johnsen N.F.
      • Olsen A.
      • et al.
      The combined impact of adherence to five lifestyle factors on all-cause, cancer and cardiovascular mortality: a prospective cohort study among Danish men and women.
      and all-cause
      • Loef M.
      • Walach H.
      The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis.
      • Behrens G.
      • Fischer B.
      • Kohler S.
      • et al.
      Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men.
      • Carlsson A.C.
      • Wändell P.E.
      • Gigante B.
      • et al.
      Seven modifiable lifestyle factors predict reduced risk for ischemic cardiovascular disease and all-cause mortality regardless of body mass index: a cohort study.
      mortality in other populations (from Europe, the United States, and Asia). Moreover, a study conducted in the US general population showed that combining a higher number of CV health behaviours and factors (not smoking; being physically active; having normal blood pressure, blood glucose, total cholesterol levels, and weight; and eating a healthy diet) was associated with a lower risk of long-term CV and all-cause mortality.
      • Yang Q.
      • Cogswell M.E.
      • Flanders W.D.
      • et al.
      Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.
      To our knowledge, our study is the first to analyze the combined effect of lifestyle behaviours and risk factors on long-term CV and all-cause mortality, using a score of adherence on the basis of the European guidelines on CV disease prevention,
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • 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).
      with extensive adjustment for nonmodifiable risk factors in a representative sample of apparently healthy middle-aged subjects recruited from the general population. Using such a score of adherence aims at reflecting the global effect of CV health behaviours. The positive effect of adherence to CV risk prevention guidelines is not only observed for CV mortality but also for total mortality, thus indicating that CV healthy behaviours could also prevent the most common causes of death (such as cancer). However obtaining lifestyle changes among middle-aged adults is very difficult, because lifestyle is usually on the basis of longstanding behaviours, culture, education, and socioeconomic determinants. The European guidelines on CV disease prevention
      • Piepoli M.F.
      • Hoes A.W.
      • Agewall S.
      • 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).
      described strategies for medical caregivers to enhance counselling on behaviour changes. We believe that to efficiently obtain lifestyle changes at the population level, efforts of health professionals could stay fruitless without a deep involvement of public health policy makers. Promoting healthy lifestyle with healthy food choices, physical activity, and smoking abstinence is everyone's concern: health professionals, teachers, policy makers, media, sport clubs, associations fighting against diseases… Such a large involvement is supported by our results showing that engaging in healthy lifestyle behaviours and controlling CV risk factors is worthwhile for improving CV health and longevity.
      The main limits of this work first include its nonrandomized design leading to the introduction of confusion bias. However randomization is impossible in a study on the effect of adherence. Hence, our prospective observational follow-up exhibits the highest level of proof that can be provided. We adjusted the results for the main confounders (age, centre, sex, and educational level, which are known to be strongly associated with life expectancy) but we cannot exclude the remaining confounders. A second limit lies in the fact that adherence was assessed at baseline only. Potential changes in adherence during the follow-up period have thus not been captured. A third limit is that the dietary survey was performed only in a subsample of the initial study population and was on the basis of self-reported data. Finally, results on CV mortality are on the basis of a small number of deaths (n = 41). However, despite this small number, the increased risk of CV death for subjects in the fourth quartile of the adherence score is important and highly significant (adjusted HR, 3.12; 95% CI, 1.62-6.01; P = 0.001). We calculated that 41 deaths provide a power greater than 80% to detect an HR ≥ 2.5 with a 2-sided type I error rate of 5% (α = 0.05).
      • Machin D.
      • Campbell M.J.
      • Tan S.B.
      • Tan S.H.
      Sample Size Tables for Clinical Studies.
      Moreover, the results were similar when cause-specific (adjusted HR, 3.33; 95% CI, 1.76-6.28; P < 0.001; data not shown) and subdistribution hazard models were used.
      • Lau B.
      • Cole S.R.
      • Gange S.J.
      Competing risk regression models for epidemiologic data.
      • Latouche A.
      • Allignol A.
      • Beyersmann J.
      • Labopin M.
      • Fine J.P.
      A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions.
      In conclusion, better baseline adherence to European guidelines on CV disease prevention is significantly associated with a reduced risk of long-term CV and all-cause mortality in a sample recruited from the French general population.

      Acknowledgements

      The authors thank all of the investigators of the MONICA Project for their contribution to the compilation and validation of the data. We did appreciate the collaboration with the Institut National de la Statistique et des Etudes Economiques (INSEE) and the health centres in the 3 regions.

      Funding Sources

      This work was supported by the Institut National de la Santé et de la Recherche Médicale, the Direction Générale de la Santé; the Institut Pasteur de Lille, the University Hospital of Lille; the Fonds d'intervention en Santé Publique; the Mutuelle Générale de l'Education Nationale; Office National Interprofessionnel des VINS (ONIVINS); the Fondation de France; the Caisse Primaire d'Assurance Maladie (CPAM) of Selestat; the Fédération Française de Cardiologie; the Conseil Régional du Nord-Pas de Calais; Parke-Davis; Bayer Pharmaceuticals; and Centre de Recherche et d'Information Nutritionnelles (CERIN).
      The sponsors did not take part or interfere in the collection, analysis, and interpretation of the data; in the writing of the report; and in the decision to submit the report for publication.

      Disclosures

      The authors have no conflicts of interest to disclose.

      Supplementary Material

      References

        • Khaw K.T.
        • Wareham N.
        • Bingham S.
        • et al.
        Combined impact of health behaviours and mortality in men and women: the EPIC-Norfolk prospective population study.
        PLoS Med. 2008; 5: e12
        • Kvaavik E.
        • Batty G.D.
        • Ursin G.
        • Huxley R.
        • Gale C.R.
        Influence of individual and combined health behaviors on total and cause-specific mortality in men and women: the United Kingdom health and lifestyle survey [erratum in: 2010;170:998].
        Arch Intern Med. 2010; 170: 711-718
        • Petersen K.E.
        • Johnsen N.F.
        • Olsen A.
        • et al.
        The combined impact of adherence to five lifestyle factors on all-cause, cancer and cardiovascular mortality: a prospective cohort study among Danish men and women.
        Br J Nutr. 2015; 113: 849-858
        • Loef M.
        • Walach H.
        The combined effects of healthy lifestyle behaviors on all cause mortality: a systematic review and meta-analysis.
        Prev Med. 2012; 55: 163-170
        • Behrens G.
        • Fischer B.
        • Kohler S.
        • et al.
        Healthy lifestyle behaviors and decreased risk of mortality in a large prospective study of U.S. women and men.
        Eur J Epidemiol. 2013; 28: 361-372
        • Carlsson A.C.
        • Wändell P.E.
        • Gigante B.
        • et al.
        Seven modifiable lifestyle factors predict reduced risk for ischemic cardiovascular disease and all-cause mortality regardless of body mass index: a cohort study.
        Int J Cardiol. 2013; 168: 946-952
        • Yang Q.
        • Cogswell M.E.
        • Flanders W.D.
        • et al.
        Trends in cardiovascular health metrics and associations with all-cause and CVD mortality among US adults.
        JAMA. 2012; 307: 1273-1283
        • Kabat G.C.
        • Matthews C.E.
        • Kamensky V.
        • Hollenbeck A.R.
        • Rohan T.E.
        Adherence to cancer prevention guidelines and cancer incidence, cancer mortality, and total mortality: a prospective cohort study.
        Am J Clin Nutr. 2015; 101: 558-569
        • Piepoli M.F.
        • Hoes A.W.
        • Agewall S.
        • 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: 2315-2381
        • Kuulasmaa K.
        • Tunstall-Pedoe H.
        • Dobson A.
        • et al.
        Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations.
        Lancet. 2000; 355: 675-687
        • Marques-Vidal P.
        • Ruidavets J.B.
        • Amouyel P.
        • et al.
        Change in cardiovascular risk factors in France, 1985-1997.
        Eur J Epidemiol. 2004; 19: 25-32
      1. CESP (Center for research in Epidemiology and Population Health), INSERM (French National Institute of Health and Medical Research) – Paris-Sud University. Implementation of edict n° 98–37. Available at: http://cesp.vjf.inserm.fr/svcd. Accessed June 8, 2017.

        • Bérard E.
        • Bongard V.
        • Arveiler D.
        • et al.
        Ten-year risk of all-cause mortality: assessment of a risk prediction algorithm in a French general population.
        Eur J Epidemiol. 2011; 26: 359-368
        • Wilson P.W.
        • D'Agostino R.B.
        • Levy D.
        • et al.
        Prediction of coronary heart disease using risk factor categories.
        Circulation. 1998; 97: 1837-1847
        • Conroy R.M.
        • Pyörälä K.
        • Fitzgerald A.P.
        • et al.
        Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project.
        Eur Heart J. 2003; 24: 987-1003
        • Fine J.
        • Gray R.
        A proportional hazards model for the subdistribution of a competing risk.
        J Am Stat Assoc. 1999; 94: 496-509
        • Machin D.
        • Campbell M.J.
        • Tan S.B.
        • Tan S.H.
        Sample Size Tables for Clinical Studies.
        3rd Ed. Wiley-Blackwell, Oxford2009
        • Lau B.
        • Cole S.R.
        • Gange S.J.
        Competing risk regression models for epidemiologic data.
        Am J Epidemiol. 2009; 170: 244-256
        • Latouche A.
        • Allignol A.
        • Beyersmann J.
        • Labopin M.
        • Fine J.P.
        A competing risks analysis should report results on all cause-specific hazards and cumulative incidence functions.
        J Clin Epidemiol. 2013; 66: 648-653