Submitted:
02 May 2023
Posted:
03 May 2023
You are already at the latest version
Abstract
Keywords:
1. Introduction
2. Materials and Methods
2.1. Study Design and Population
2.2. Sociodemographic, Lifestyle Factors, and Psychological Well-Being
2.3. Objective Measurements
2.4. Statistical Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Official statistics portal. The population of Lithuania (edition 2021) Causes of death. Available online: https://osp.stat.gov.lt/lietuvos-gyventojai-2021/mirtingumas/gyventoju-mirties-priezastys (accessed on 10 March, 2023).
- Timmis, A.; Vardas, P.; Townsend, N.; Torbica, A.; Katus, H.; De Smedt, D.; Gale, C.P.; Maggioni, A.P.; Petersen, S.E.; Huculeci, R.; et al. European Society of Cardiology: cardiovascular disease statistics 2021. Eur. Heart J. 2022, 43, 716–799. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization (WHO). Physical activity. 2021. Available online: https://www.who.int/news-room/fact-sheets/detail/physical-activity (accessed on 16 March, 2023).
- Saint-Maurice, P.F.; Coughlan, D.; Kelly, S.P.; Keadle, S.K.; Cook, M.B.; Carlson, S.A.; Fulton, J.E.; Matthews, C.E. Association of Leisure-Time Physical Activity Across the Adult Life Course with All-Cause and Cause-Specific Mortality. JAMA Netw. Open. 2019, 2, e190355. [Google Scholar] [CrossRef]
- WHO guidelines on physical activity and sedentary behaviour. 2020. Available online: https://www.who.int/publications/i/item/9789240015128 (accessed on 20 February, 2023).
- 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]
- Sapranaviciute-Zabazlajeva, L.; Luksiene, D.; Virviciute, D.; Bobak, M.; Tamosiunas, A. Link between healthy lifestyle and psychological well-being in Lithuanian adults aged 45-72: a cross-sectional study. BMJ Open. 2017, 7, e014240. [Google Scholar] [CrossRef] [PubMed]
- Hyde, M.; Wiggins, R.D.; Higgs, P.; Blane, D. A measure of quality of life in early old age: the theory, development and properties of a need’s satisfaction model (CASP-19). Aging Ment Health 2003, 7, 186–194. [Google Scholar] [CrossRef] [PubMed]
- 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, 3143–3421. [CrossRef]
- Prineas, R.J.; Crow, R.S.; Blackburn, H.W. The Minnesota code manual of electrocardiographic findings: standards and procedures for measurement and classification. Boston Mass: J. Wright, 1982; p 229.
- Rose, G.A.; Blackburn, H.; Gillum, R.F. Cardiovascular survey methods. World Heal Organ - Monogr Ser. 1982; p 56.
- Hayes, A.F. Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Little TD (ed) Guilford Press. 2013; p 507.
- World Health Organization (WHO). Global action plan on physical activity 2018-2030. Available online: https://apps.who.int/iris/bitstream/handle/10665/272722/9789241514187-eng.pdf (accessed on 20 February, 2023).
- Kannel, W.B; Sorlie, P. Some Health Benefits of Physical Activity: The Framingham Study. Arch. Intern. Med. 1979, 139, 857–861. [Google Scholar] [CrossRef]
- Li, J.; Siegrist, J. Physical activity and risk of cardiovascular disease--a meta-analysis of prospective cohort studies. Int. J. Environ. Res. Public Health 2012, 9, 391–407. [Google Scholar] [CrossRef]
- Kodama, S.; Saito, K.; Tanaka, S.; Maki, M.; Yachi, Y.; Asumi, M.; Sugawara, A.; Totsuka, K.; Shimano, H.; Ohashi, Y.; et al. Cardiorespiratory Fitness as a Quantitative Predictor of All-Cause Mortality and Cardiovascular Events in Healthy Men and Women: A Meta-analysis. JAMA 2009, 301, 2024–2035. [Google Scholar] [CrossRef]
- Saklayen, M.G. The Global Epidemic of the Metabolic Syndrome. Curr. Hypertens. Rep. 2018, 20, 12. [Google Scholar] [CrossRef]
- Serrano-Sánchez, J.A.; Fernández-Rodríguez, M.J.; Sanchis-Moysi, J.; del Cristo Rodríguez-Pérez, M.; Marcelino-Rodríguez, I.; de León, A.C. Domain and intensity of physical activity are associated with metabolic syndrome: A population-based study. PLoS One 2019, 14, e0219798. [Google Scholar] [CrossRef]
- Gallardo-Alfaro, L.; Bibiloni, M.D.M.; Mateos, D.; Ugarriza, L.; Tur, J.A. Leisure-Time Physical Activity and Metabolic Syndrome in Older Adults. Int. J. Environ. Res. Public Health 2019, 16, 3358. [Google Scholar] [CrossRef] [PubMed]
- Gallardo-Alfaro, L.; Bibiloni, M.; Bouzas, C.; Mascaró, C.M.; Martínez-González, M.Á.; Salas-Salvadó, J.; Corella, D.; Schröder, H.; Alfredo Martínez, J.A.; Alonso-Gómez, A.M.; et al. Physical activity and metabolic syndrome severity among older adults at cardiovascular risk: 1-Year trends. Nutr. Metab. Cardiovasc. Dis. 2021, 31, 2870–2886. [Google Scholar] [CrossRef]
- Gallardo-Alfaro, L.; Bibiloni, M.D.M.; Mascaró, C.M.; Montemayor, S.; Ruiz-Canela, M.; Salas-Salvadó, J.; Corella, D.; Fitó, M.; Romaguera, D.; Vioque, J.; et al. Leisure-Time Physical Activity, Sedentary Behaviour and Diet Quality are Associated with Metabolic Syndrome Severity: The PREDIMED-Plus Study. Nutrients 2020, 12, 1013. [Google Scholar] [CrossRef]
- Sagawa, N.; Rockette-Wagner, B.; Azuma, K.; Ueshima, H.; Hisamatsu, T.; Takamiya, T.; El-Saed, A.; Miura, K.; Kriska, A.; Sekikawa, A. Physical activity levels in American and Japanese men from the ERA-JUMP Study and associations with metabolic syndrome. J. Sport Heal. Sci. 2020, 9, 170–178. [Google Scholar] [CrossRef] [PubMed]
- Uemura, H.; Katsuura-Kamano, S.; Iwasaki, Y.; Arisawa, K.; Hishida, A.; Okada, R.; Tamura, T.; Kubo, Y.; Ito, H.; Oze, I.; et al. Independent relationships of daily life activity and leisure-time exercise with metabolic syndrome and its traits in the general Japanese population. Endocrine 2019, 64, 552–563. [Google Scholar] [CrossRef] [PubMed]
- Morseth, B.; Jacobsen, B.K.; Emaus, N.; Wilsgaard, T.; Jørgensen, L. Secular trends and correlates of physical activity: The Tromsø Study 1979-2008. BMC Public Health 2016, 16, 1215. [Google Scholar] [CrossRef] [PubMed]
- Lounassalo, I.; Hirvensalo, M.; Palomäki, S.; Salin, K.; Tolvanen, A.; Pahkala, K.; Rovio, S.; Fogelholm, M.; Yang, X.; Hutri-Kähönen, N.; et al. Life-course leisure-time physical activity trajectories in relation to health-related behaviors in adulthood: the Cardiovascular Risk in Young Finns study. BMC Public Health 2021, 21, 533. [Google Scholar] [CrossRef]
- Salin, K.; Kankaanpää, A.; Hirvensalo, M,; Lounassalo, I. ; Yang, X.; Magnussen, C.G.; Hutri-Kähönen, N.; Rovio, S.; Viikari, J.; Raitakari, O.T.; et al. Smoking and physical activity trajectories from childhood to midlife. Int. J. Environ. Res. Public Health 2019, 16, 974. [Google Scholar] [CrossRef]
- Min, S.; Masanovic, B.; Bu, T.; Matic, R.M.; Vasiljevic, I.; Vukotic, M.; Li, J.; Vukovic, J.; Fu, T.; Jabucanin, B.; et al. The Association Between Regular Physical Exercise, Sleep Patterns, Fasting, and Autophagy for Healthy Longevity and Well-Being: A Narrative Review. Front. Psychol. Sec. Health Psychology 2021, 12, 803421. [Google Scholar] [CrossRef] [PubMed]

| Physical Activity Levels / Tertiles | Men | Women | ||
|---|---|---|---|---|
| Min–max* | Mean (SD) | Min–max* | Mean (SD) | |
| Physically inactive (1st tertile) | 0.0–10.0 | 5.8 (3.1) | 0.0–13.5 | 8.6 (3.4) |
| Moderately physically active (2nd tertile) | 10.5–19.5 | 14.7 (2.6) | 14.0–22.0 | 17.5 (2.6) |
| Higher physically active (3rd tertile) | 20.0–42.0 | 26.8 (5.9) | 22.5–42.0 | 29.2 (5.1) |
| Variables | MEN n=3065 |
WOMEN n=3705 |
P |
|---|---|---|---|
| Age, years, mean ± SD | 57.3±7.87 | 57.1±7.84 | 0.217 |
| Education, % | <0.001 | ||
| Secondary and lower | 46.8 | 37.5 | |
| College and higher | 53.2 | 62.5 | |
| Metabolic syndrome, % | 27.5 | 33.8 | <0.001 |
| Arterial hypertension (≥130/85 mm/Hg), % | 83.4 | 69.7 | <0.001 |
| Increased waist circumference, % | |||
| Men ≥102 cm, women ≥88 cm | 27.3 | 48.6 | <0.001 |
| HDL cholesterol, | |||
| Men <1.0 mmol/L, women <1.3 mmol/L, % | 12.1 | 23.2 | <0.001 |
| Triglycerides ≥1.7 mmol/L, % | 28.3 | 25.0 | 0.001 |
| Fasting glucose ≥6.1 mmol/L, %, | 30.8 | 30.9 | 0.475 |
| Psychological well-being groups | 0.004 | ||
| Higher | 52.8 | 56.3 | |
| Lower | 47.2 | 43.7 | |
| Regular smoking, % | 37.7 | 13.6 | <0.001 |
| Nutrition habits, % | |||
| More frequent consumption of fresh fruit and vegetables | 51.1 | 59.4 | <0.001 |
| More frequent consumption of sweets | 51.4 | 48.9 | 0.020 |
| More frequent consumption of cereals, and infrequent consumption of meat | 32.7 | 58.0 | <0.001 |
| More frequent consumption of meat, potatoes, and eggs | 61.4 | 42.6 | <0.001 |
| More frequent consumption of chicken and fish | 55.4 | 49.3 | <0.001 |
| Prevalence of IHD at baseline survey, % | 21.0 | 22.3 | 0.197 |
| IHD status | ||||
|---|---|---|---|---|
| Without IHD HR (95 % CI) |
P | With IHD HR (95 % CI) |
P | |
| MEN | N=2422 | N=643 | ||
| Physically inactive | 1 | 1 | ||
| Moderately physically active | 0.54 (0.33–0.89) | 0.016 | 0.69 (0.43–1.10) | 0.121 |
| Higher physically active | 0.60 (0.37–0.95) | 0.031 | 0.54 (0.32–0.91) | 0.021 |
| WOMEN | N=2877 | N=828 | ||
| Physically inactive | 1 | 1 | ||
| Moderately physically active | 0.75 (0.40–1.39) | 0.354 | 0.41 (0.19–0.89) | 0.025 |
| Higher physically active | 0.73 (0.38–1.38) | 0.331 | 0.54 (0.25–1.18) | 0.123 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
