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3101MCID_676f0872af95eba5d503de68 34176347 Pekka J Jousilahti[author] Jousilahti, Pekka J[Full Author Name] jousilahti, pekka j[Author] trying2...
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1651-19055022022MarScandinavian journal of public healthScand J Public HealthThe effects of long-term physical activity interventions in communities: Scoping review in the Nordic countries.272286272-28610.1177/14034948211020599Aims: Physical activity (PA) is an important part of maintaining good overall health. Currently, the number of insufficiently physically active adults and children is alarmingly high worldwide. To tackle the challenge, several interventions have been conducted, however, current knowledge on intervention effectiveness is still inconclusive. This scoping review aimed to summarize the effects of long-term PA interventions across all age groups in the Nordic countries. Methods: A scoping review was conducted by including all age groups and interventions lasting more than 12 months. The aims of the interventions had to focus on increasing PA and/or fitness. The Behaviour Change Wheel framework was used to describe components of the intervention functions. Results: Initially, 1937 studies were identified. Twelve intervention studies fulfilled the inclusion criteria and were included in the analysis. From the included studies, seven focused on children and/or their parents and five on working-age adult populations. Most of the studies built on theoretical backgrounds and included several behaviour change functions. A hindering factor for synthesis was variation in measurement methods: both subjective and objective outcome measures were reported. Among all age groups, intervention effects on PA were modest. Conclusions: There was no clear evidence of increased PA or fitness from long-term interventions in communities. However, even small improvements in PA are important for increasing PA at a population level and enhancing public health. More research is required for evidence-based community and public health planning.HaverinenElsi HEH0000-0003-4963-2845Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.ElonheimoHanna MHM0000-0003-4441-3432Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.TolonenHanna KHKDepartment of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.JousilahtiPekka JPJDepartment of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.WennmanHeini J CHJCDepartment of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.engJournal ArticleReview20210628
SwedenScand J Public Health1008835031403-4948IMAdultChildExerciseHumansInfantScandinavian and Nordic CountriesUnited StatesPhysical activitybehaviour changecommunityfitnessinterventionDeclaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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1464-360X2942019Aug01European journal of public healthEur J Public HealthPreventable premature deaths (PYLL) in Northern Dimension partnership countries 2003-13.626630626-63010.1093/eurpub/cky278Objective was to measure preventable premature loss of life in countries from same geographical area but with considerable differences in social and economic development. By comparing inter-country differences and similarities in premature mortality, acceleration of health-in-all-policies is enhanced.Preventable premature deaths were described by Potential Years of Life Lost (PYLL). Data consisted of death registers for 2003, 2009 and 2013. PYLL-rates were age-standardized by using standard OECD population from 1980 and expressed as sum of lost life years per 100 000 citizens.In Northern Dimension area, PYLL-rates had declined from 2003 to 2013. In 2013, worst PYLL-rate was in Belarus 9851 and best in Sweden 2511. PYLL-rates among men were twice as high as among women. Most premature losses (1023) were due to external causes. Malignant neoplasms came second (921) and vascular diseases third (816). Alcohol was also an important cause (270) and country differences were over 10-fold.In ND-area, the overall development of public health has been good during 2003-13. Nevertheless, for all countries foci for public health improvement and learning from each other could be identified. Examining the health of populations in countries from relatively similar geographical area with different social history and cultures can provide them with evidence-based tools for health-in-all-policies to advocate health promotion and disease prevention. Gender differences due to preventable premature deaths are striking. The higher the national PYLL-rate, the bigger the PYLL-rate difference between men and women and the loss of human capital.© The Author(s) 2019. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.VienonenMikko AMAManagement Consulting Group, Finnish Consulting Group, Helsinki, Finland.JousilahtiPekka JPJDepartment of Public Solutions, National Institute for Health and Welfare, Helsinki, Finland.MackiewiczKarolinaKBaltic Region Healthy Cities Association, Turku, Finland.OganovRafael GRGDepartment of Comorbidity Prevention, National Research Centre for Preventive Medicine under the Ministry of Health, Moscow, Russian Federation.PisarykVital MVMRepublican Scientific and Practical Center for Medical Technologies, Minsk, Belarus.DenissovGleb RGREstonian Registry of Causes of Death, National Institute of Health Development, Tallinn, Estonia.NurmUlla-KarinUKNorthern Dimension Partnership of Public Health and Social Wellbeing Secretariat, Stockholm, Sweden.PuduleIvetaIDepartment of Health Statistics, Centre for Disease Prevention and Control, Riga, Latvia.GureviciusRomualdas JRJCenter for Health Statistics, Institute of Hygiene, Vilnus, Lithuania.ZabłockiBartosz MBMDepartment of Public Health, Ministry of Health, Warsaw, Poland.FribergMarita IMIDepartment of Health Statistics, Public Health Agency, Solna, Sweden.KrasilnikovIgor AIASociety for Organizational Responsibility, Strategic LLC, Saint Petersburg, Russian Federation.KoistinenVeli OVOManagement Consulting Group, Finnish Consulting Group, Helsinki, Finland.VohlonenIlkka JIJDepartment of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.engComparative StudyJournal ArticleResearch Support, Non-U.S. Gov't
EnglandEur J Public Health92049661101-1262IMAdultAge FactorsAgedAged, 80 and overCause of DeathtrendsEstoniaepidemiologyFemaleFinlandepidemiologyForecastingGermanyepidemiologyHumansLatviaepidemiologyLife ExpectancytrendsLithuaniaepidemiologyMaleMiddle AgedMortality, PrematuretrendsPolandepidemiologyPreventive Medicinestatistics & numerical dataRepublic of BelarusepidemiologySex FactorsSwedenepidemiology
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1658-31752532004MarSaudi medical journalSaudi Med JPrevalence and 10-year secular trend of obesity in Oman.346351346-51To determine the prevalence of overweight and obesity by age, gender and region and to assess the difference between rural and urban populations and determine the trends of the past decade.Analysis of nationally represented samples from 2 cross-sectional surveys conducted in 1991 and 2000, containing 5,086 and 6,400 Omani citizens aged >or=20 years. Body mass index (BMI) (weight in kg) divided by height (in meters squared) was calculated using measured height and weight data. Overweight was defined as BMI 25-29.9 kg/m2 and obesity as BMI >or= 30 kg/m2.In the year 2000, the age adjusted prevalence of obesity reached 16.7% in men, compared to 10.5% in 1991 (p<0.001). In women, the prevalence was 23.8% in 2000, compared to 25.1% in 1991 (p=0.231). Similarly, the prevalence of overweight increased among men, from 28.8-32.1% (p=0.011) and decreased among women, from 29.5-27.3% (p=0.053). When obesity and overweight were combined, there was a significant increase in men (9.5%; p for the change <0.001) and decrease in women (3.5%; p for the change <0.003). Obesity and overweight combined was markedly more common in the Southern part of Oman (70%) compared to Northern areas (32-57%). People living in urban areas were more obese (21.1%) than those living in the rural communities (13.1%) (p<0.001).The prevalence of obesity is high in Oman and has increased predominantly among men. Primary prevention programs are needed to counteract this condition and its cardiovascular and metabolic complications.Al-LawatiJawad AJADepartment of Non-Communicable Diseases Control, Ministry of Health, Sultanate of Oman. jallawat@omantel.net.omJousilahtiPekka JPJengJournal Article
Saudi ArabiaSaudi Med J79094410379-5284IMAdultAgedAged, 80 and overBody Mass IndexCultureFemaleHumansLife StyleMaleMiddle AgedObesityepidemiologyOmanepidemiologyPrevalenceRural Populationstatistics & numerical dataUrban Populationstatistics & numerical data
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Publications by Pekka J Jousilahti | LitMetric

Publications by authors named "Pekka J Jousilahti"

Physical activity (PA) is an important part of maintaining good overall health. Currently, the number of insufficiently physically active adults and children is alarmingly high worldwide. To tackle the challenge, several interventions have been conducted, however, current knowledge on intervention effectiveness is still inconclusive.

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Background: Objective was to measure preventable premature loss of life in countries from same geographical area but with considerable differences in social and economic development. By comparing inter-country differences and similarities in premature mortality, acceleration of health-in-all-policies is enhanced.

Methods: Preventable premature deaths were described by Potential Years of Life Lost (PYLL).

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Objective: To determine the prevalence of overweight and obesity by age, gender and region and to assess the difference between rural and urban populations and determine the trends of the past decade.

Methods: Analysis of nationally represented samples from 2 cross-sectional surveys conducted in 1991 and 2000, containing 5,086 and 6,400 Omani citizens aged >or=20 years. Body mass index (BMI) (weight in kg) divided by height (in meters squared) was calculated using measured height and weight data.

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