The Impact of Metabolic Syndrome and Lifestyle Habits on the Risk of the First Event of Cardiovascular Disease: Results from a Cohort Study in Lithuanian Urban Population
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Sample
2.2. Sociodemographic and Lifestyle Factors
2.3. Biochemical Indicators and Diagnostic Criteria of the Metabolic Syndrome
2.4. Statistical Analysis
3. Results
4. Discussion
4.1. Strengths
4.2. Limitations
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- 2018 Ageing Report: Policy Challenges for Ageing Societies. Available online: https://ec.europa.eu/info/news/economy-finance/policy-implications-ageing-examined-new-report-2018-may-25_en (accessed on 4 September 2019).
- Courtin, E.; Jemiai, N.; Mossialos, E. Mapping support policies for informal carers across the European Union. Health Policy 2014, 118, 84–94. [Google Scholar] [CrossRef] [Green Version]
- WHO. Cardiovascular Diseases (CVDs). Available online: https://www.who.int/cardiovascular_diseases/en/ (accessed on 4 September 2019).
- Lithuanian Health Statistics. Available online: http://hi.lt/html/en/health_statistic.htm (accessed on 4 September 2019).
- Causes of Death Statistics, Eurostat 9/2018. Available online: http://ec.europa.eu/eurostat/statistics-explained/index.php/Causes_of_death_statistics# (accessed on 4 September 2019).
- Luksiene, D.; Baceviciene, M.; Jureniene, K.; Bernotiene, G.; Rėklaitienė, R.; Radisauskas, R.; Tamosiunas, A. All-cause and cardiovascular mortality risk estimation using different definitions of metabolic syndrome in Lithuanian urban population. Prev. Med. 2012, 55, 299–304. [Google Scholar] [CrossRef]
- Bacevičienė, M.; Lukšienė, D.I.; Bernotienė, G.; Tamošiūnas, A. Estimation of all-cause and cardiovascular mortality risk in relation to leisure-time physical activity: A cohort study. Medicina 2012, 48, 93. [Google Scholar] [CrossRef]
- Luksiene, D.; Tamosiūnas, A.; Virviciūte, D.; Radišauskas, R. The Prognostic Value of Combined Smoking and Alcohol Consumption Habits for the Estimation of Cause-Specific Mortality in Middle-Age and Elderly Population: Results from a Long-Term Cohort Study in Lithuania. BioMed Res. Int. 2017, 2017, 1–12. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Peasey, A.; Bobak, M.; Kubinova, R.; Malyutina, S.; Pajak, A.; Tamosiunas, A.; Pikhart, H.; Nicholson, A.; Marmot, M. Determinants of cardiovascular disease and other non-communicable diseases in Central and Eastern Europe: Rationale and design of the HAPIEE study. BMC Public Health 2006, 6, 255. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Norkus, A.; Ostrauskas, R.; Sulcaite, R.; Baranauskiene, E.; Baliutaviciene, D. Classification and diagnosis of diabetes mellitus (methodology recommendations). Lith. Endocrinol. 2000, 3, 234–241. [Google Scholar]
- Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation 2002, 106, 3143. [CrossRef]
- Luksiene, D.I.; Baceviciene, M.; Tamosiunas, A.; Daugeliene, E.; Kranciukaite, D. Health, alcohol and psychosocial factors in Eastern Europe study: Dietary patterns and their association with socio-demographic factors in the Lithuanian urban population of Kaunas city. Int. J. Public Health 2011, 56, 209–216. [Google Scholar] [CrossRef] [Green Version]
- Skosyrev, E.; Glimm, E. Power analysis for multivariable Cox regression models. Stat. Med. 2019, 38, 88–99. [Google Scholar] [CrossRef]
- World Health Organization MONICA Project; MONICA Manual: Geneva, Switzerland, 1990.
- Passarino, G.; De Rango, F.; Montesanto, A. Human longevity: Genetics or Lifestyle? It takes two to tango. Immun. Ageing 2016, 13, 12. [Google Scholar] [CrossRef] [Green Version]
- Tamosiunas, A.; Klumbiene, J.; Petkeviciene, J.; Radisauskas, R.; Vikhireva, O.; Luksiene, D.; Virviciute, D. Trends in major risk factors and mortality from main non-communicable diseases in Lithuania, 1985–2013. BMC Public Health 2016, 16, 717. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Menotti, A.; Puddu, P.E.; Maiani, G.; Catasta, G. Lifestyle behavior and lifetime incidence of heart diseases. Int. J. Cardiol. 2015, 201, 293–299. [Google Scholar] [CrossRef] [PubMed]
- Assi, H.R.; Ziv, A.; Dankner, R. The metabolic syndrome and its components are differentially associated with chronic diseases in a high-risk population of 350 000 adults: A cross-sectional study. Diabetes/Metabolism Res. Rev. 2019, 35, e3121. [Google Scholar] [CrossRef] [PubMed]
- Ju, S.Y.; Lee, J.Y.; Kim, D.H. Association of metabolic syndrome and its components with all-cause and cardiovascular mortality in the elderly: A meta-analysis of prospective cohort studies. Medicine (Baltimore) 2017, 96, e8491. [Google Scholar] [CrossRef]
- Kotseva, K.; De Bacquer, D.; De Backer, G.; Ryden, L.; Jennings, C.; Gyberg, V.; Abreu, A.; Aguíar, C.; Conde, A.C.; Davletov, K.; et al. Lifestyle and risk factor management in people at high risk of cardiovascular disease. A report from the European Society of Cardiology European Action on Secondary and Primary Prevention by Intervention to Reduce Events (EUROASPIRE) IV cross-sectional survey in 14 European regions. Eur. J. Prev. Cardiol. 2016, 23, 2007–2018. [Google Scholar]
- Piepoli, M.F.; Hoes, A.W.; Agewall, S.; Albus, C.; Brotons, C.; Catapano, A.L.; Cooney, M.T.; Corrà, U.; Cosyns, B.; Deaton, C.; 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. [Google Scholar] [CrossRef]
- Menotti, A.; Puddu, P.E.; Lanti, M.; Maiani, G.; Catasta, G.; Fidanza, A.A. Lifestyle habits and mortality from all and specific causes of death: 40-year follow-up in the Italian Rural Areas of the Seven Countries Study. J. Nutr. Health Aging 2014, 18, 314–321. [Google Scholar] [CrossRef]
- Aune, D.; Giovannucci, E.; Boffetta, P.; Fadnes, L.T.; Keum, N.; Norat, T.; Greenwood, D.C.; Riboli, E.; Vatten, L.J.; Tonstad, S. Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. Int. J. Epidemiol. 2017, 46, 1029–1056. [Google Scholar] [CrossRef]
- Foscolou, A.; Magriplis, E.; Tyrovolas, S.; Soulis, G.; Bountziouka, V.; Mariolis, A.; Piscopo, S.; Valacchi, G.; Anastasiou, F.; Gotsis, E.; et al. Lifestyle determinants of healthy ageing in a Mediterranean population: The multinational MEDIS study. Exp. Gerontol. 2018, 110, 35–41. [Google Scholar] [CrossRef] [Green Version]
- Stefler, D.; Pikhart, H.; Kubinova, R.; Pajak, A.; Stepaniak, U.; Malyutina, S.; Simonova, G.; Peasey, A.; Marmot, M.G.; Bobak, M. Fruit and vegetable consumption and mortality in Eastern Europe: Longitudinal results from the Health, Alcohol and Psychosocial Factors in Eastern Europe study. Eur. J. Prev. Cardiol. 2016, 23, 493–501. [Google Scholar] [CrossRef] [Green Version]
- Hajishafiee, M.; Saneei, P.; Benisi-Kohansal, S.; Esmaillzadeh, A. Cereal fiber intake and risk of mortality from all causes, CVD, cancer and inflammatory diseases: A systematic review and meta-analysis of prospective cohort studies. Br. J. Nutr. 2016, 116, 343–352. [Google Scholar] [CrossRef] [PubMed]
- Tang, G.-Y.; Meng, X.; Li, Y.; Zhao, C.-N.; Liu, Q.; Li, H.-B. Effects of Vegetables on Cardiovascular Diseases and Related Mechanisms. Nutrients 2017, 9, 857. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ekblom-Bak, E.; Ekblom, B.; Vikström, M.; de Faire, U.; Hellénius, M.L. The importance of non-exercise physical activity for cardiovascular health and longevity. Br. J. Sports Med. 2014, 48, 233–238. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Martinez-Gomez, D.; Esteban-Cornejo, I.; Lopez-Garcia, E.; García-Esquinas, E.; Sadarangani, K.P.; Veiga, O.L.; Rodriguez-Artalejo, F. Physical activity less than the recommended amount may prevent the onset of major biological risk factors for cardiovascular disease: A cohort study of 198 919 adults. Br. J. Sports Med. 2018, 52. [Google Scholar] [CrossRef]
- Zhang, D.; Liu, X.; Liu, Y.; Sun, X.; Wang, B.; Ren, Y.; Zhao, Y.; Zhou, J.; Han, C.; Yin, L.; et al. Leisure-time physical activity and incident metabolic syndrome: A systematic review and dose-response meta-analysis of cohort studies. Metabolism 2017, 75, 36–44. [Google Scholar] [CrossRef]
Type of Food | 1st Factor | 2nd Factor | 3rd Factor | 4th Factor | 5th Factor |
---|---|---|---|---|---|
Fresh Vegetables, Fruit | Increased Consumption of Meat and Low Cereals | Sweets | Boiled Vegetables and Potatoes | Chicken, Fsh, and Eggs | |
Fresh vegetables | 0.739 | ||||
Fresh fruit | 0.697 | ||||
Fresh carrots | 0.485 | ||||
Natural juice | 0.439 | ||||
Cereals, porridge | −0.651 * | ||||
Meat products (sausage) | 0.651 | ||||
Meat | 0.638 | ||||
Sweets | 0.848 | ||||
Sweet pastries | 0.845 | ||||
Potatoes | 0.693 | ||||
Boiled vegetables | 0.626 | ||||
Chicken | 0.711 | ||||
Fish | 0.594 | ||||
Eggs | 0.447 |
Variables | Men | Women | ||
---|---|---|---|---|
The First Event of CVD | The Frst Event of CVD | |||
No | Yes | No | Yes | |
N = 1778 | N = 298 | N = 2021 | N = 160 | |
Mean age, years (SD) | 59.2 (7.6) | 62.5 (7.2) *** | 58.6 (7.7) | 63.6 (6.8) *** |
Metabolic syndrome (%) | 20.9 | 29.5 *** | 29.4 | 44.4 *** |
Mean metabolic syndrome components (SD) | 1.7 (1.1) | 2.0 (1.2) *** | 1.9 (1.4) | 2.4 (1.3) *** |
Increased waist circumference (%) (for men ≥102 cm; for women ≥88 cm) | 23.1 | 35.2 *** | 46.4 | 60.6 *** |
Elevated triglycerides level (%) (≥1.7 mmol/L) | 23.1 | 29.9 ** | 22.4 | 30.6 * |
Low HDL cholesterol level (%) (for men <1.0 mmol/L, for women <1.3 mmol/L) | 9.4 | 13.1 * | 19.9 | 35.0 *** |
Increased fasting glucose level (%) (≥6.1 mmol/L) | 27.4 | 28.9 | 28.4 | 25.6 |
Arterial hypertension (%) (>130/85 mm Hg) | 82.3 | 89.6 *** | 68.7 | 83.8 *** |
Smoking status (%) | ||||
Never | 41.3 | 32.2 ** | 81.4 | 85.6 |
Former | 27.1 | 31.2 | 7.0 | 3.8 |
Current | 31.6 | 36.6 | 11.6 | 10.6 |
Physically active (%) | 69.1 | 67.1 | 82.5 | 83.1 |
Education level (%) | ||||
Primary | 5.4 | 10.7 ** | 5.2 | 13.8 ** |
Vocational | 8.6 | 15.8 *** | 7.7 | 10.0 |
Secondary | 32.3 | 28.5 | 24.5 | 22.5 |
College | 18.8 | 15.8 | 27.6 | 30.6 |
University | 34.9 | 29.2 | 35.0 | 23.1 ** |
Nutrition factors (%) | ||||
1st “Fresh vegetables and fruits” | 49.5 | 48.0 | 60.2 | 49.4 ** |
2nd “Increased consumption of meat and low cereals” | 66.1 | 61.7 | 37.0 | 31.9 |
3rd “Sweets” | 51.0 | 42.6 ** | 53.6 | 56.3 |
4th “Boiled vegetables and potatoes” | 55.5 | 54.7 | 45.7 | 45.0 |
5th “Chicken, fish, and eggs” | 58.2 | 60.4 | 46.7 | 48.1 |
Variables | Men | Women | ||
---|---|---|---|---|
Model 1 | Model 2 | Model 1 | Model 2 | |
HR (95% CI) | HR (95% CI) | HR (95% CI) | HR (95% CI) | |
Metabolic syndrome | 1.57 (1.23–2.02) | 1.53 (1.18–1.97) | 1.57 (1.15–2.15) | 1.56 (1.14–2.15) |
Nutrition factors | ||||
1st “Fresh vegetables and fruits” | 0.91 (0.81–1.01) | 0.95 (0.85–1.07) | 0.81 (0.70–0.93) | 0.80 (0.69–0.93) |
2nd “Increased consumption of meat and low cereals” | 1.06 (0.93–1.20) | 0.98 (0.86–1.12) | 1.12 (0.95–1.31) | 1.08 (0.92–1.28) |
3rd “Sweets” | 0.89 (0.79–1.00) | 0.92 (0.82–1.03) | 0.89 (0.75–1.04) | 0.91 (0.78–1.07) |
4th “Boiled vegetables and potatoes” | 0.98 (0.87–1.10) | 0.97 (0.86–1.10) | 1.00 (0.86–1.16) | 1.00 (0.86–1.16) |
5th “Chicken, fish, and eggs” | 1.05 (0.94–1.17) | 1.05 (0.94–1.18) | 0.99 (0.84–1.15) | 0.96 (0.82–1.13) |
Smoking status (%) | ||||
Never | 1 | 1 | 1 | 1 |
Former | 1.54 (1.16–2.05) | 1.43 (1.07–1.90) | 0.90 (0.39–2.06) | 0.92 (0.40–2.11) |
Current | 2.04 (1.54–2.72) | 1.94 (1.45–2.60) | 1.67 (0.98–2.85) | 1.58 (0.92–2.73) |
Physical activity (%) | ||||
Physically inactive | 1 | 1 | 1 | 1 |
Physically active | 0.78 (0.61–0.99) | 0.85 (0.66–1.09) | 0.99 (0.66–1.50) | 1.13 (0.74–1.73) |
Education level (%) | ||||
Primary | 1 | 1 | 1 | 1 |
Vocational | 1.23 (0.78–1.94) | 1.16 (0.74–1.83) | 0.74 (0.39–1.41) | 0.79 (0.41–1.52) |
Secondary | 0.78 (0.51–1.20) | 0.78 (0.51–1.20) | 0.82 (0.47–1.43) | 0.85 (0.48–1.49) |
College | 0.70 (0.44–1.12) | 0.76 (0.48–1.22) | 1.01 (0.59–1.73) | 1.21 (0.70–2.09) |
University | 0.66 (0.43–1.00) | 0.72 (0.48–1.10) | 0.61 (0.35–1.06) | 0.75 (0.43–1.34) |
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Jasiukaitienė, V.; Lukšienė, D.; Tamošiūnas, A.; Radišauskas, R.; Bobak, M. The Impact of Metabolic Syndrome and Lifestyle Habits on the Risk of the First Event of Cardiovascular Disease: Results from a Cohort Study in Lithuanian Urban Population. Medicina 2020, 56, 18. https://doi.org/10.3390/medicina56010018
Jasiukaitienė V, Lukšienė D, Tamošiūnas A, Radišauskas R, Bobak M. The Impact of Metabolic Syndrome and Lifestyle Habits on the Risk of the First Event of Cardiovascular Disease: Results from a Cohort Study in Lithuanian Urban Population. Medicina. 2020; 56(1):18. https://doi.org/10.3390/medicina56010018
Chicago/Turabian StyleJasiukaitienė, Vilma, Dalia Lukšienė, Abdonas Tamošiūnas, Ričardas Radišauskas, and Martin Bobak. 2020. "The Impact of Metabolic Syndrome and Lifestyle Habits on the Risk of the First Event of Cardiovascular Disease: Results from a Cohort Study in Lithuanian Urban Population" Medicina 56, no. 1: 18. https://doi.org/10.3390/medicina56010018
APA StyleJasiukaitienė, V., Lukšienė, D., Tamošiūnas, A., Radišauskas, R., & Bobak, M. (2020). The Impact of Metabolic Syndrome and Lifestyle Habits on the Risk of the First Event of Cardiovascular Disease: Results from a Cohort Study in Lithuanian Urban Population. Medicina, 56(1), 18. https://doi.org/10.3390/medicina56010018