Adherence to dietary guidelines is associated with significantly better health outcomes. Studies across the world shows that compliance with the guidelines was low, but data in Switzerland are lacking. Hence, we aimed to assess the 5-year trends in dietary compliance regarding food guidelines in Switzerland in a prospective, population-based observational study. Data from 2882 participants (1591 women, 35-75 years), from the first (2009-2012) and second (2014-2017) follow-up. Dietary intake was assessed using a validated food frequency questionnaire. Compliance with the guidelines of the Swiss society of nutrition was assessed at baseline and 5.5 years afterwards. Prevalence rates for compliance were calculated using the exact Poisson method. Factors associated with changes in compliance (never, shifter or maintainer) were assessed by multinomial logistic regression using "Never compliers" as reference. Overall, improvements in compliance to fruits (42.4% to 45.1%) vegetables (6.9% to 8.6%) and fish (66.6% to 60.5%) were found, while compliance to meat decreased (61.1% to 58.5%). The prevalence of participants complying with at least three dietary recommendations did not change (24.1% to 25.2%). During follow-up, only 11.6% of participants maintained compliance to at least three dietary recommendations, and 62.4% never managed to comply. Female gender and older age were associated with maintaining compliance during the two study periods. In conclusion, compliance with dietary guidelines is a dynamic status, and only a small fraction of the population achieves sustained compliance with at least three guidelines. Almost two thirds of the population never achieve compliance with three guidelines.
OBJECTIVE: To assess the effect of a governmentally-led center based child care physical activity program (Youp'la Bouge) on child motor skills.Patients and methods: We conducted a single blinded cluster randomized controlled trial in 58 Swiss child care centers. Centers were randomly selected and 1:1 assigned to a control or intervention group. The intervention lasted from September 2009 to June 2010 and included training of the educators, adaptation of the child care built environment, parental involvement and daily physical activity. Motor skill was the primary outcome and body mass index (BMI), physical activity and quality of life secondary outcomes. The intervention implementation was also assessed. RESULTS: At baseline, 648 children present on the motor test day were included (age 3.3 +/- 0.6, BMI 16.3 +/- 1.3 kg/m2, 13.2% overweight, 49% girls) and 313 received the intervention. Relative to children in the control group (n = 201), children in the intervention group (n = 187) showed no significant increase in motor skills (delta of mean change (95% confidence interval: -0.2 (-0.8 to 0.3), p = 0.43) or in any of the secondary outcomes. Not all child care centers implemented all the intervention components. Within the intervention group, several predictors were positively associated with trial outcomes: 1) free-access to a movement space and parental information session for motor skills 2) highly motivated and trained educators for BMI 3) free-access to a movement space and purchase of mobile equipment for physical activity (all p < 0.05). CONCLUSION: This "real-life" physical activity program in child care centers confirms the complexity of implementing an intervention outside a study setting and identified potentially relevant predictors that could improve future programs.Trial registration: Trial registration number: clinical trials.gov NCT00967460 http://clinicaltrials.gov/ct2/show/NCT00967460.
Evidence on the impact of legislative changes on individual alcohol consumption is limited. Using an observational study design, we assessed trends in individual alcohol consumption of a Swiss adult population following the public policy changes that took place between 1993 and 2014, while considering individual characteristics and secular trends. Cross-sectional study. Swiss general adult population. Data from 18 963 participants were collected between 1993 and 2014 (aged 18-75 years). We used data from the 'Bus Santé' study, an annual health survey conducted in random samples of the adult population in the State of Geneva, Switzerland. Individual alcohol intake was assessed using a validated food frequency questionnaire. Individual characteristics including education were self-reported. 7 policy changes (6 about alcohol and 1 about tobacco) that occurred between 1993 and 2014 defined 6 different periods. We predicted alcohol intake using quantile regression with multivariate analysis for each period adjusting for participants' characteristics and tested significance periods. Sensitivity analysis was performed including drinkers only, the 10th centile of highest drinkers and smoker's status. Between 1993 and 2014, participants' individual alcohol intake decreased from 7.1 to 5.4 g/day (24% reduction, p<0.001). Men decreased their alcohol intake by 34% compared with 22% for women (p<0.001). The decrease in alcohol intake remained significant when considering drinkers only (28% decrease, p<0.001) and the 10th centile highest drinkers (24% decrease, p<0.001). Consumption of all alcoholic beverages decreased between 1993 and 2014 except for the moderate consumption of beer, which increased. After adjustment for participants' characteristics and secular trends, no independent association between alcohol legislative changes and individual alcohol intake was found. Between 1993 and 2014, alcohol consumption decreased in the Swiss adult population independently of policy changes.
Harmful use of alcohol represents a large socioeconomic and disease burden and displays a socioeconomic status (SES) gradient. Several alcohol control laws were devised and implemented, but their equity impact remains undetermined.We ascertained if an SES gradient in hazardous alcohol consumption exists in Geneva (Switzerland) and assessed the equity impact of the alcohol control laws implemented during the last two decades. Repeated cross-sectional survey study. We used data from non-abstinent participants, aged 35-74 years, from the population-based cross-sectional Bus Santé study (n=16 725), between 1993 and 2014. SES indicators included educational attainment (primary, secondary and tertiary) and occupational level (high, medium and low). We defined four survey periods according to the implemented alcohol control laws and hazardous alcohol consumption (outcome variable) as >30 g/day for men and >20 g/day for women.The Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were used to quantify absolute and relative inequalities, respectively, and were compared between legislative periods. Lower educated men had a higher frequency of hazardous alcohol consumption (RII=1.87 (1.57; 2.22) and SII=0.14 (0.11; 0.17)). Lower educated women had less hazardous consumption ((RII=0.76 (0.60; 0.97)and SII=-0.04 (-0.07;-0.01]). Over time, hazardous alcohol consumption decreased, except in lower educated men.Education-related inequalities were observed in men in all legislative periods and did not vary between them. Similar results were observed using the occupational level as SES indicator. In women, significant inverse SES gradients were observed using educational attainment but not for occupational level. Population-wide alcohol control laws did not have a positive equity impact on hazardous alcohol consumption. Targeted interventions to disadvantaged groups may be needed to address the hazardous alcohol consumption inequality gap.
Harmful use of alcohol represents a large socioeconomic and disease burden and displays a socioeconomic status (SES) gradient. Several alcohol control laws were devised and implemented, but their equity impact remains undetermined.We ascertained if an SES gradient in hazardous alcohol consumption exists in Geneva (Switzerland) and assessed the equity impact of the alcohol control laws implemented during the last two decades. Repeated cross-sectional survey study. We used data from non-abstinent participants, aged 35-74 years, from the population-based cross-sectional Bus Santé study (n=16 725), between 1993 and 2014. SES indicators included educational attainment (primary, secondary and tertiary) and occupational level (high, medium and low). We defined four survey periods according to the implemented alcohol control laws and hazardous alcohol consumption (outcome variable) as >30 g/day for men and >20 g/day for women.The Slope Index of Inequality (SII) and Relative Index of Inequality (RII) were used to quantify absolute and relative inequalities, respectively, and were compared between legislative periods. Lower educated men had a higher frequency of hazardous alcohol consumption (RII=1.87 (1.57; 2.22) and SII=0.14 (0.11; 0.17)). Lower educated women had less hazardous consumption ((RII=0.76 (0.60; 0.97)and SII=-0.04 (-0.07;-0.01]). Over time, hazardous alcohol consumption decreased, except in lower educated men.Education-related inequalities were observed in men in all legislative periods and did not vary between them. Similar results were observed using the occupational level as SES indicator. In women, significant inverse SES gradients were observed using educational attainment but not for occupational level. Population-wide alcohol control laws did not have a positive equity impact on hazardous alcohol consumption. Targeted interventions to disadvantaged groups may be needed to address the hazardous alcohol consumption inequality gap.
To compare different definitions of multimorbidity to identify patients with higher health care resource utilization. We used a multinational retrospective cohort including 147,806 medical inpatients discharged from 11 hospitals in 3 countries (United States, Switzerland, and Israel) between January 1, 2010, and December 31, 2011. We compared the area under the receiver operating characteristic curve (AUC) of 8 definitions of multimorbidity, based on International Classification of Diseases codes defining health conditions, the Deyo-Charlson Comorbidity Index, the Elixhauser-van Walraven Comorbidity Index, body systems, or Clinical Classification Software categories to predict 30-day hospital readmission and/or prolonged length of stay (longer than or equal to the country-specific upper quartile). We used a lower (yielding sensitivity ≥90%) and an upper (yielding specificity ≥60%) cutoff to create risk categories. Definitions had poor to fair discriminatory power in the derivation (AUC, 0.61-0.65) and validation cohorts (AUC, 0.64-0.71). The definitions with the highest AUC were number of (1) health conditions with involvement of 2 or more body systems, (2) body systems, (3) Clinical Classification Software categories, and (4) health conditions. At the upper cutoff, sensitivity and specificity were 65% to 79% and 50% to 53%, respectively, in the validation cohort; of the 147,806 patients, 5% to 12% (7474 to 18,008) were classified at low risk, 38% to 55% (54,484 to 81,540) at intermediate risk, and 32% to 50% (47,331 to 72,435) at high risk. Of the 8 definitions of multimorbidity, 4 had comparable discriminatory power to identify patients with higher health care resource utilization. Of these 4, the number of health conditions may represent the easiest definition to apply in clinical routine. The cutoff chosen, favoring sensitivity or specificity, should be determined depending on the aim of the definition.
Cardiovascular disease (CVD) prevention is defined as a coordinated set of actions, at the population level or targeted at an individual, that are aimed at eliminating or minimizing the impact of CVDs and their related disabilities.1 CVD remains a leading cause of morbidity and mortality, despite improvements in outcomes. Age-adjusted coronary artery disease (CAD) mortality has declined since the 1980s, particularly in high-income regions.2 CAD rates are now less than half what they were in the early 1980s in many countries in Europe, due to preventive measures including the success of smoking legislation. However, inequalities between countries persist and many risk factors, particularly obesity3 and diabetes mellitus (DM),4 have been increasing substantially. If prevention was practised as instructed it would markedly reduce the prevalence of CVD. It is thus not only prevailing risk factors that are of concern, but poor implementation of preventive measures as well.5,6 Prevention should be delivered (i) at the general population level by promoting healthy lifestyle behaviour7 and (ii) at the individual level, i.e. in those subjects at moderate to high risk of CVD or patients with established CVD, by tackling unhealthy lifestyles (e.g. poor-quality diet, physical inactivity, smoking) and by optimising risk factors. Prevention is effective: the elimination of health risk behaviours would make it possible to prevent at least 80% of CVDs and even 40% of cancers.
Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (41071, 77299, 102318, 110413, 117787, 121584, 123885, 124243, 124282, 126925, 129378, 134309, 286284); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la 359 Recherche; Agency for Health Care Policy Research (HS06516); ALF/LUA research grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S; Althingi; American Heart Association (13POST16500011); Amgen; Andrea and Charles Bronfman Philanthropies; Ardix Medical; Arthritis Research UK; Association Diabe`te Risque Vasculaire; Australian National Health and Medical Research Council (241944, 339462, 389875, 389891, 389892, 389927, 389938, 442915, 442981, 496739, 552485, 552498); Avera Institute; Bayer Diagnostics; Becton Dickinson; BHF (RG/14/5/30893); Boston Obesity Nutrition Research Center (DK46200), Bristol-Myers Squibb; British Heart Foundation (RG/10/12/ 28456, RG2008/08, RG2008/014, SP/04/002); Medical Research Council of Canada; Canadian Institutes for Health Research (FRCN-CCT-83028); Cancer Research UK; Cardionics; Cavadis B.V., Center for Medical Systems Biology; Center of Excellence in Genomics; CFI; CIHR; City of Kuopio; CNAMTS; Cohortes Sante´ TGIR; Contrat de Projets E´tat-Re´gion; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF-1333- 00124, DFF-1331-00730B); County Council of Dalarna; Dalarna University; Danish Council for Strategic Research; Danish Diabetes Academy; Danish Medical Research Council; Department of Health, UK; Development Fund from the University of Tartu (SP1GVARENG); Diabetes Hilfs- und Forschungsfonds Deutschland; Diabetes UK; Diabetes Research and Wellness Foundation Fellowship; Donald W. Reynolds Foundation; Dr Robert Pfleger-Stiftung; Dutch Brain Foundation; Dutch Diabetes Research Foundation; Dutch Inter University Cardiology Institute; Dutch Kidney Foundation (E033); Dutch Ministry of Justice; the DynaHEALTH action No. 633595, Economic Structure Enhancing Fund of the Dutch Government; Else Kro¨ner-Fresenius-Stiftung (2012_A147, P48/08//A11/08); Emil Aaltonen Foundation; Erasmus University Medical Center Rotterdam; Erasmus MC and Erasmus University Rotterdam; the Municipality of Rotterdam; Estonian Government (IUT20-60, IUT24-6); Estonian Research Roadmap through the Estonian Ministry of Education and Research (3.2.0304.11-0312); European Research Council (ERC Starting Grant and 323195:SZ-245 50371-GLUCOSEGENESFP7-IDEAS-ERC); European Regional Development Fund; European Science Foundation (EU/QLRT-2001-01254); European Commission (018947, 018996, 201668, 223004, 230374, 279143, 284167, 305739, BBMRI-LPC-313010, HEALTH-2011.2.4.2-2-EUMASCARA, HEALTH-2011-278913, HEALTH-2011-294713-EPLORE, HEALTH-F2- 2008-201865-GEFOS, HEALTH-F2-2013-601456, HEALTH-F4-2007-201413, HEALTH-F4-2007-201550-HYPERGENES, HEALTH-F7-305507 HOMAGE, IMI/ 115006, LSHG-CT-2006-018947, LSHG-CT-2006-01947, LSHM-CT-2004-005272, LSHM-CT-2006-037697, LSHM-CT-2007-037273, QLG1-CT-2002-00896, QLG2-CT2002-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ0103, 01ZZ0403, 01ZZ9603, 03IS2061A, 03ZIK012); Federal State of Mecklenburg-West Pomerania; Fe´de´ration Franc¸aise de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Fondation Leducq; Food Standards Agency; Foundation for Strategic Research; French Ministry of Research; FRSQ; Genetic Association Information Network (GAIN) of the Foundation for the NIH; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); GlaxoSmithKline; Greek General Secretary of Research and Technology; Go¨teborg Medical Society; Health and Safety Executive; Healthcare NHS Trust; Healthway; Western Australia; Heart Foundation of Northern Sweden; Helmholtz Zentrum Mu¨nchen—German Research Center for Environmental Health; Hjartavernd; Ingrid Thurings Foundation; INSERM; InterOmics (PB05 MIUR-CNR); INTERREG IV Oberrhein Program (A28); Interuniversity Cardiology Institute of the Netherlands (ICIN, 09.001); Italian Ministry of Health (ICS110.1/RF97.71); Italian Ministry of Economy and Finance (FaReBio di Qualita`); Marianne and Marcus Wallenberg Foundation; the Ministry of Health, Welfare and Sports, the Netherlands; J.D.E. and Catherine T, MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health; Juho Vainio Foundation; Juvenile Diabetes Research Foundation International; KfH Stiftung Pra¨ventivmedizin e.V.; King's College London; Knut and Alice Wallenberg Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); La Fondation de France; Leenaards Foundation; Lilly; LMUinnovativ; Lundberg Foundation; Magnus Bergvall Foundation; MDEIE; Medical Research Council UK (G0000934, G0601966, G0700931, MC_U106179471, MC_UU_12019/1); MEKOS Laboratories; Merck Sante´; Ministry for Health, Welfare and Sports, The Netherlands; Ministry of Cultural Affairs of Mecklenburg-West Pomerania; Ministry of Economic Affairs, The Netherlands; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science, The Netherlands; Ministry of Science, Education and Sport in the Republic of Croatia (108-1080315-0302); MRC centre for Causal Analyses in Translational Epidemiology; MRC Human Genetics Unit; MRC-GlaxoSmithKline pilot programme (G0701863); MSD Stipend Diabetes; National Institute for Health Research; Netherlands Brain Foundation (F2013(1)-28); Netherlands CardioVascular Research Initiative (CVON2011-19); Netherlands Genomics Initiative (050-060-810); Netherlands Heart Foundation (2001 D 032, NHS2010B280); Netherlands Organization for Scientific Research (NWO) and Netherlands Organisation for Health Research and Development (ZonMW) (56-464- 14192, 60-60600-97-118, 100-001-004, 261-98-710, 400-05-717, 480-04-004, 480-05-003, 481-08-013, 904-61-090, 904-61-193, 911-11-025, 985-10-002, Addiction-31160008, BBMRI–NL 184.021.007, GB-MaGW 452-04-314, GB-MaGW 452-06-004, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MW 940-38-011, Middelgroot-911-09-032, NBIC/BioAssist/RK 2008.024, Spinozapremie 175.010.2003.005, 175.010.2007.006); NATURE COMMUNICATIONS | DOI:10.1038/ncomms14977 ARTICLE NATURE COMMUNICATIONS | 8:14977 | DOI:10.1038/ncomms14977 | www.nature.com/naturecommunications 13 Neuroscience Campus Amsterdam; NHS Foundation Trust; National Institutes of Health (1RC2MH089951, 1Z01HG000024, 24152, 263MD9164, 263MD821336, 2R01LM010098, 32100-2, 32122, 32108, 5K99HL130580-02, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, AG13196, CA047988, DA12854, DK56350, DK063491, DK078150, DK091718, DK100383, DK078616, ES10126, HG004790, HHSN268200625226C, HHSN268200800007C, HHSN268201200036C, HHSN268201500001I, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, HL043851, HL45670, HL080467, HL085144, HL087660, HL054457, HL119443, HL118305, HL071981, HL034594, HL126024, HL130114, KL2TR001109, MH66206, MH081802, N01AG12100, N01HC55015, N01HC55016, N01C55018, N01HC55019, N01HC55020, N01HC55021, N01HC55022, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, N01HG65403, N01WH22110, N02HL6-4278, N01-HC-25195, P01CA33619, R01HD057194, R01HD057194, R01AG023629, R01CA63, R01D004215701A, R01DK075787, R01DK062370, R01DK072193, R01DK075787, R01DK089256, R01HL53353, R01HL59367, R01HL086694, R01HL087641, R01HL087652, R01HL103612, R01HL105756, R01HL117078, R01HL120393, R03 AG046389, R37CA54281, RC2AG036495, RC4AG039029, RPPG040710371, RR20649, TW008288, TW05596, U01AG009740, U01CA98758, U01CA136792, U01DK062418, U01HG004402, U01HG004802, U01HG007376, U01HL080295, UL1RR025005, UL1TR000040, UL1TR000124, UL1TR001079, 2T32HL007055-36, T32GM074905, HG002651, HL084729, N01-HC25195, UM1CA182913); NIH, National Institute on Aging (Intramural funding, NO1-AG-1-2109); Northern Netherlands Collaboration of Provinces; Novartis Pharma; Novo Nordisk; Novo Nordisk Foundation; Nutricia Research Foundation (2016-T1); ONIVINS; Parnassia Bavo group; Pierre Fabre; Province of Groningen; Pa¨ivikki and Sakari Sohlberg Foundation; Påhlssons Foundation; Paavo Nurmi Foundation; Radboud Medical Center Nijmegen; Research Centre for Prevention and Health, the Capital Region of Denmark; the Research Institute for Diseases in the Elderly; Research into Ageing; Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center; Roche; Royal Society; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Government Health Directorates, Chief Scientist Office (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Socie´te´ Francophone du 358 Diabe`te; State of Bavaria; Stiftelsen fo¨r Gamla Tja¨narinnor; Stockholm County Council (560183, 592229); Strategic Cardiovascular and Diabetes Programmes of Karolinska Institutet and Stockholm County Council; Stroke Association; Swedish Diabetes Association; Swedish Diabetes Foundation (2013-024); Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20120197, 20150711); Swedish Research Council (0593, 8691, 2012-1397, 2012-1727, and 2012-2215); Swedish Society for Medical Research; Swiss Institute of Bioinformatics; Swiss National Science Foundation (3100AO-116323/1, 31003A-143914, 33CSCO-122661, 33CS30-139468, 33CS30-148401, 51RTP0_151019); Tampere Tuberculosis Foundation; Technology Foundation STW (11679); The Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Ministry of the Flemish Community (G.0880.13, G.0881.13); The Great Wine Estates of the Margaret River Region of Western Australia; Timber Merchant Vilhelm Bangs Foundation; Topcon; Tore Nilsson Foundation; Torsten and Ragnar So¨derberg's Foundation; United States – Israel Binational Science Foundation (Grant 2011036), Umeå University; University Hospital of Regensburg; University of Groningen; University Medical Center Groningen; University of Michigan; University of Utrecht; Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) (b2011036); Velux Foundation; VU University's Institute for Health and Care Research; Va¨stra Go¨taland Foundation; Wellcome Trust (068545, 076113, 079895, 084723, 088869, WT064890, WT086596, WT098017, WT090532, WT098051, 098381); Wissenschaftsoffensive TMO; Yrjo¨ Jahnsson Foundation; and Åke Wiberg Foundation