Advancing the global physical activity agenda: recommendations for future research by the 2020 WHO physical activity and sedentary behavior guidelines development group.

BACKGROUND: In July, 2019, the World Health Organization (WHO) commenced work to update the 2010 Global Recommendations on Physical Activity for Health and established a Guideline Development Group (GDG) comprising expert public health scientists and practitioners to inform the drafting of the 2020 Guidelines on Physical Activity and Sedentary Behavior. The overall task of the GDG was to review the scientific evidence and provide expert advice to the WHO on the amount of physical activity and sedentary behavior associated with optimal health in children and adolescents, adults, older adults (> 64 years), and also specifically in pregnant and postpartum women and people living with chronic conditions or disabilities. METHODS: The GDG reviewed the available evidence specific to each sub-population using systematic protocols and in doing so, identified a number of gaps in the existing literature. These proposed research gaps were discussed and verified by expert consensus among the entire GDG. RESULTS: Evidence gaps across population sub-groups included a lack of information on: 1) the precise shape of the dose-response curve between physical activity and/or sedentary behavior and several of the health outcomes studied; 2) the health benefits of light-intensity physical activity and of breaking up sedentary time with light-intensity activity; 3) differences in the health effects of different types and domains of physical activity (leisure-time; occupational; transportation; household; education) and of sedentary behavior (occupational; screen time; television viewing); and 4) the joint association between physical activity and sedentary time with health outcomes across the life course. In addition, we acknowledge the need to conduct more population-based studies in low- and middle-income countries and in people living with disabilities and/or chronic disease, and to identify how various sociodemographic factors (age, sex, race/ethnicity, socioeconomic status) modify the health effects of physical activity, in order to address global health disparities. CONCLUSIONS: Although the 2020 WHO Guidelines for Physical Activity and Sedentary Behavior were informed by the most up-to-date research on the health effects of physical activity and sedentary time, there is still substantial work to be done in advancing the global physical activity agenda.

Estimating expected life-years and risk factor associations with mortality in Finland: cohort study.

OBJECTIVE: To develop a tool to inform individuals and general practitioners about benefits of lifestyle changes by providing estimates of the expected age of death (EAD) for different risk factor values, and for those who plan and decide on preventive activities and health services at population level, to calculate potential need for these. DESIGN: Prospective cohort study to estimate EAD using a model with 27 established risk factors, categorised into four groups: (1) sociodemographic background and medical history, (2) lifestyles, (3) life satisfaction, and (4) biological risk factors. We apply a Poisson regression model on the survival data split into 1-year intervals. PARTICIPANTS: Total of 38 549 participants aged 25-74 years at baseline of the National FINRISK Study between 1987 and 2007. PRIMARY OUTCOME MEASURES: Register-based comprehensive mortality data from 1987 to 2014 with an average follow-up time of 16 years and 4310 deaths. RESULTS: Almost all risk factors included in the model were statistically significantly associated with death. The largest influence on the EAD appeared to be a current heavy smoker versus a never smoker as the EAD for a 30-year-old man decreased from 86.8 years, which corresponds to the reference values of the risk factors, to 80.2 years. Diabetes decreased EAD by >6.6 years. Whole or full milk consumers had 3.4 years lower EAD compared with those consuming skimmed milk. Physically inactive men had 2.4 years lower EAD than those with high activity. Men who found their life almost unbearable due to stress had 2.8 years lower EAD. CONCLUSIONS: The biological risk factors and lifestyles, and the factors connected with life satisfaction were clearly associated with EAD. Our model for estimating a person's EAD can be used to motivate lifestyle changes.

From monitoring to action: utilising health survey data in national policy development and implementation in Finland.

BACKGROUND: Health interview and examination surveys provide valuable information for policy, practice and research purposes. Appropriate use of high-quality, representative and timely population data can indirectly help the citizens to live healthier and longer lives. The aim of this study was to review how health survey data have supported health policy making, health research and everyday health care in Finland. METHODS: Data were collected by focused interviews with ten Finnish senior experts from the Ministry of Social Affairs and Health, political parties, National Institute for Health and Welfare, universities, and health associations. RESULTS: Most interviewees agreed that health surveys have positively affected the health of the population over the past 50 years - through health strategies, care guidelines, legislation, research, prevention programs, risk calculators, and healthier products on the market. There is also a need for further development: the latest research results should be provided in a nutshell for politicians, and effective tools should be developed more for health care professionals' use. The coverage of health information on children, adolescents, oldest old, disabled persons, migrants and ethnic minorities should be improved. CONCLUSIONS: Sound health policy and its successful implementation require extensive national cooperation and new communication strategies between policy makers, researchers, health care professionals, health service providers - and citizens. The future health information system in Finland should better cover all population groups. To obtain more comprehensive health information, the possibilities for register linkages should be secured and register data should be further evaluated and developed to serve health monitoring purposes.

Gender, age and socioeconomic variation in 24-hour physical activity by wrist-worn accelerometers: the FinHealth 2017 Survey.

Assessing movement over 24 hours increases our understanding of the total physical activity level and its patterns. In the FinHealth 2017 Survey, a population-based health examination study, 940 participants between 25 and 93 years were instructed to wear an accelerometer (Actigraph GT9X Link) on their non-dominant wrist for 24 hours on 7 consecutive days. Physical activity information was extracted from 100-Hz triaxial 60-second epoch data as average vector magnitude counts per minute (VM cpm). Results were analyzed by gender, 10-year age-groups, employment status, and education. Hourly means were plotted and compared. Analyses included 915 participants (44% men) who wore the device at least 10 hours on 4 or more days, with mean wear time being 149.5 hours (standard deviation of 615.2 minutes).Women had higher average VM cpm than men (p < 0.001), with significant gender differences in all age-groups until 65 years and older. Total physical activity was lower with age, unemployment, and retirement, where the hourly patterns mirrored the findings. Our findings agree with previous large-scale wrist-accelerometry data, but extend current knowledge by providing data on gender and socioeconomic variation in physical activity across 24 hours in a population-based adult sample representing a broad age range.

Individual and environmental factors associated with green exercise in urban and suburban areas.

In this study, we mainly aimed to explore the associations of personal and socio-demographic factors, and the supply of green areas and built sports facilities with green exercise (GE). We also compared the residents of the core urban area and suburban areas according to the level of leisure time physical activity (LTPA) they had. A population-based sample of 3730 adults (aged 25-101 y) from Finland, filled out a questionnaire in 2015. Variables describing the supply of green areas and built sports facilities were objectively calculated. The green areas were classified into small (<25 ha), middle-sized (25-150 ha) and large (>150 ha) areas to reflect their qualities for GE. The data analysis methods included multinomial logistic regression, t-, and Chi Square tests. Our results indicate that having a short distance to at least a middle-sized green area and high nature relatedness are important for participation in GE, both in core urban and suburban areas. More factors were found to be related to GE in the suburban areas compared to core urban areas and among the low LTPA compared to the high LTPA group.

Participation rates by educational levels have diverged during 25 years in Finnish health examination surveys.

Background: Declining participation rates in health examination surveys may impair the representativeness of surveys and introduce bias into the comparison of results between population groups if participation rates differ between them. Changes in the characteristics of non-participants over time may also limit comparability with earlier surveys. Methods: We studied the association of socio-economic position with participation, and its changes over the past 25 years. Occupational class and educational level are used as indicators of socio-economic position. Data from six cross-sectional FINRISK surveys conducted between 1987 and 2012 in Finland were linked to national administrative registers, which allowed investigation of the differences between survey participants and non-participants. Results: Our results show that individuals with low occupational class or low level of education were less likely to participate than individuals with high occupational class or high level of education. Participation rates decreased in all subgroups of the population but the decline was fastest among those with low level of education. Conclusions: The differences in participation rates must be taken into account to avoid biased estimates because socio-economic position has also been shown to be strongly related to health, health behaviour and biological risk factors. Particular attention should be paid to the recruitment of the less-educated population groups.

What explains the socioeconomic status gap in activity? Educational differences in determinants of physical activity and screentime.

BACKGROUND: Designing evidence-based interventions to address socioeconomic disparities in health and health behaviours requires a better understanding of the specific explanatory mechanisms. We aimed to investigate a comprehensive range of potential theoretical mediators of physical activity (PA) and screen time in different socioeconomic status (SES) groups: a high SES group of high school students, and a low SES group of vocational school students. The COM-B system, including the Theoretical Domains Framework (TDF), was used as a heuristic framework to synthesise different theoretical determinants in this exploratory study. METHODS: Finnish vocational and high school students (N = 659) aged 16-19, responded to a survey assessing psychological, social and environmental determinants of activity (PA and screen time). These determinants are mappable into the COM-B domains: capability, opportunity and motivation. The outcome measures were validated self-report measures for PA and screen time. The statistical analyses included a bootstrapping-based mediation procedure. RESULTS: Regarding PA, there were SES differences in all of the COM-B domains. For example, vocational school students reported using less self-monitoring of PA, weaker injunctive norms to engage in regular PA, and fewer intentions than high school students. Mediation analyses identified potential mediators of the SES-PA relationship in all of three domains: The most important candidates included self-monitoring (CI95 for b: 0.19-0.47), identity (0.04-0.25) and material resources available (0.01-0.16). However, SES was not related to most determinants of screentime, where there were mainly gender differences. Most determinants were similarly related with both behaviours in both SES groups, indicating no major moderation effect of SES on these relationships. CONCLUSIONS: This study revealed that already in the first years of educational differentiation, levels of key PA determinants differ, contributing to socioeconomic differences in PA. The analyses identified the strongest mediators of the SES-PA association, but additional investigation utilising longitudinal and experimental designs are needed. This study demonstrates the usefulness of combining constructs from various theoretical approaches to better understand the role of distinct mechanisms that underpin socioeconomic health behaviour disparities.

Socio-demographic and behavioral variation in barriers to leisure-time physical activity.

INTRODUCTION: We examined the socio-demographic and behavioral determinants of perceived barriers to leisure-time physical activity (LTPA) in a population-based sample of working-aged adults. METHODS: Data comprised the National FINRISK 2002 Study, a population-based health examination study. Analyses were restricted to those aged 25-64 years and who perceived that their amount of LTPA did not reach sufficient levels. They reported barriers to LTPA, defined as a lack of time, motivation and lack of companionship to be active with, as well as high expenses. Age, education, household income, employment status, family type, physical activity, smoking and body mass index (BMI) were included as explanatory variables. RESULTS: Lack of time was the most frequent barrier. Each barrier was explained by a different set of factors that also varied between genders. The strongest and most systematic associations with the barriers were found for age, employment status and family type. Lack of time was less often reported as a barrier among the unemployed, singles without children and older people. Lacking motivation as a barrier was most common among singles without children. High expenses as a barrier was more often reported by the unemployed, and less often reported in the highest income group. CONCLUSIONS: When considering actions to promote LTPA, there is not one single solution, because the perceived barriers vary by population subgroups.

Social capital and all-cause mortality among Finnish men and women aged 30-79.

BACKGROUND: More knowledge is needed about how various dimensions of social capital associate with mortality either independently or mediated by other factors. In this cohort study, individual-level social capital was assessed as a possible predictor of all-cause mortality. METHODS: A 9-year mortality follow-up was conducted for participants of a nationally representative Health 2000 Survey carried out in 2000-01. The survey included a personal interview, self-administered questionnaires and a health examination. Response rates to different items varied between 80 and 88%. Due to the item non-response, missing values were replaced by using multiple imputation. Participants (N = 6377) were 30-79 years old at the baseline. During the follow-up period, 245 women and 340 men died. Cox regression models were used to assess the association between social capital and mortality. We analysed three dimensions of social capital: social support, social participation and trust. Their association with the risk of death was adjusted for several socio-demographic factors, health behaviours, health and biological risk factors. RESULTS: Unactive social participation was associated with higher mortality risk even when adjusting for the other factors. The association was stronger among men [hazard ratio (HR) = 1.56] than women (HR = 1.42). The other two dimensions of social capital were associated with mortality when only age was adjusted for, but this association disappeared when social participation was included in the explanatory model. CONCLUSIONS: Active social participation protects against early death. This association is partly mediated through health behaviour and to a minor extent also through health.

Secular trends and educational differences in the incidence of type 2 diabetes in Finland, 1972-2007.

Type 2 diabetes prevalence is rising globally, and varies by socio-economic position. Amongst other factors, rising prevalence may reflect increasing incidence. Worldwide, few studies have examined population-level longitudinal trends in incident type 2 diabetes, and reports on secular trends in diabetes incidence by socio-economic measures such as educational attainment are lacking. Finland has a long-standing, comprehensive disease surveillance infrastructure. Using data collected over four decades from serial FINRISK surveys, the National Drug Reimbursement Register and the National Causes of Death Register, we examined secular trends in type 2 diabetes incidence in Finland from the 1970s to 2007. The diabetes status of 38,689 FINRISK participants aged 30-59 years at baseline assessment and without diagnosed diabetes at the time was followed for 10 years. Among men, incidence of diagnosed, pharmacologically managed type 2 diabetes increased over time. Compared with men surveyed in the 1970s, diabetes incidence was higher among men in the 1980s (adjusted HR 1.44, 95% CI 1.13-1.84) and 1990s (adjusted HR 1.72, 1.32-2.24). Body mass index explained some, but not all of this variation. Increases occurred predominantly among men with low (adjusted HR 1980s: 2.07, 95% CI 1.28-3.35; adjusted HR 1990s: 2.12, 95% CI 1.28-3.53) and middle (adjusted HR 1980s: 1.30, 95% CI 0.85-1.99; adjusted HR 1990s: 1.65, 95% CI 1.05-2.60) educational attainment. No secular changes were apparent among women. This rising diabetes incidence among men over recent decades has occurred despite Finland's sustained health promotion efforts. Renewed public health campaigns are urgently required. In addition to population-level initiatives, lower educational strata should be specifically targeted.

Childhood adversities and socioeconomic position as predictors of leisure-time physical inactivity in early adulthood.

BACKGROUND: Limited knowledge exists on how childhood social, health-related and economic circumstances predict adult physical inactivity. Our aim was a) to examine how various childhood adversities and living conditions predict leisure-time physical inactivity in early adulthood and b) to find out whether these associations are mediated through the respondent's own education. METHODS: Young adults aged 18-29 were used from the Health 2000 Study of the Finnish. The cross-sectional data were based on interviews and questionnaires including retrospective information on childhood circumstances. The analyses were carried out on 68% of the original sample (N = 1894). The outcome measure was leisure-time physical inactivity. RESULTS: Only a few of the 11 childhood adversities were related with physical activity in early adulthood. Having been bullied at school was associated with physical inactivity independently of the other childhood circumstances and the respondent's own education. Low parental education predicted leisure-time physical inactivity in men and the association was mediated by the respondent's own education. Respondents with only primary or vocational education were more likely to be physically inactive during leisure-time compared with those with secondary or higher education. CONCLUSIONS: There is some evidence that few specific childhood adversities, especially bullying at school, have long-lasting effects on physical activity levels.

The association between physical activity and maternal sleep during the postpartum period.

Physical activity is associated with improved sleep quality and duration in the general population, but its effect on sleep in postpartum women is unknown. We examined cross-sectional and longitudinal associations between hours/week of self-reported domain-specific and overall moderate to vigorous physical activity (MVPA) and sleep quality and duration at 3- and 12-months postpartum among a cohort of 530 women in the Pregnancy, Infection, and Nutrition Postpartum Study. MVPA was not associated with sleep quality or duration at 3-months postpartum. At 12-months postpartum, a 1 h/week increase in recreational MVPA was associated with higher odds of good (vs. poor) sleep quality (odds ratio, OR 1.14; 95 % confidence interval, CI, 1.03-1.27) and a 1 h/week increase in child/adult care MVPA was associated with lower odds of good (vs. poor) sleep quality (OR = 0.93; 95 % CI 0.88-0.99). A 1 h/week increase in child/adult care MVPA (OR 1.08, 95 % CI 1.00-1.16) was associated with higher odds of long sleep duration and 1 h/week increases in indoor household (OR 1.09, 95 % CI 1.01-1.18) and overall MVPA (OR 1.04, 95 % CI 1.01-1.07) were associated with higher odds of short (vs. normal) sleep duration. Comparing 3-months postpartum to 12-months postpartum, increased work MVPA was associated with good sleep quality (OR 2.40, 95 % CI 1.12-5.15) and increased indoor household MVPA was associated with short sleep duration (OR 1.85, 95 % CI 1.05-3.27) as measured at 12-months postpartum. Selected domains of MVPA and their longitudinal increases were associated with sleep quality and duration at 12-months postpartum. Additional research is needed to elucidate whether physical activity can improve postpartum sleep.

Educational differences in self-rated physical fitness among Finns.

BACKGROUND: The high educated live longer and healthier lives when compared to the low educated. Physical fitness as a health indicator reflects the level of physical activity along with other health-influencing factors such as obesity, smoking, chronic diseases and individual training effects. Studies support that self-rated physical fitness correlates with objectively measured physical fitness well. However, the educational differences in self-rated physical fitness are not known. METHODS: Our aim was to study educational differences in self-rated physical fitness in Finnish population. The data were collected in 2007 for a cross-sectional population based National FINRISK Study. The analyzed data included 2722 men and 3108 women aged 25 to 74 years. Statistical method was ordinal logistic regression. RESULTS: Longer educational career was associated with better self-rated physical fitness. The educational differences in self-rated physical fitness were largely explained by health behavior. Leisure-time physical activity explained fully and body mass index partly the educational differences in self-rated physical fitness among men. The combination of body mass index, history of chronic diseases and smoking explained the differences fully among men and partly among women. Leisure-time, occupational and commuting physical activities, body mass index, history of chronic diseases and smoking together explained all educational differences in self-rated physical fitness among both genders. CONCLUSIONS: Although educational differences in self-rated physical fitness were found, they were explained by health behavior related factors. Leisure-time physical activity offered the strongest single explanation for the educational differences in self-rated physical fitness. Thus, possibilities for leisure-time physical activity should be increased especially among the low educated.

Leisure time physical activity in a 22-year follow-up among Finnish adults.

BACKGROUND: The aim of this study was to explore long-term predictors of leisure time physical activity in the general population. METHODS: This study comprised 718 men and women who participated in the national Mini-Finland Health Survey from 1978-1980 and were re-examined in 2001. Participants were aged 30-80 at baseline. Measurements included interviews, health examinations, and self-administered questionnaires, with information on socioeconomic position, occupational and leisure time physical activity, physical fitness, body mass index, smoking, alcohol consumption, and physical functional capacity. Analyses included persons who were working and had no limitations in functional capacity at baseline. RESULTS: The strongest predictor of being physically active at the follow-up was participation in physical activity at baseline, with an OR 13.82 (95%CI 5.50-34.70) for 3 or more types of regular activity, OR 2.33 (95%CI 1.22-4.47) for 1-2 types of regular activity, and OR 3.26 (95%CI 2.07-5.15) for irregular activity, as compared to no activity. Other determinants for being physically active were moving upwards in occupational status, a high level of baseline occupational physical activity and remaining healthy weight during the follow-up. CONCLUSIONS: To prevent physical inactivity among older adults, it is important to promote physical activity already in young adulthood and in middle age and to emphasize the importance of participating in many types of physical activity.

Health behaviours as mediating pathways between socioeconomic position and body mass index.

BACKGROUND: Low socioeconomic position is widely reported to associate with high body mass index (BMI). We, however, lack scientific evidence if health behaviours mediate the association between socioeconomic position and BMI. PURPOSE: The aims of the study were to explore associations of education and income with BMI and to study the mediating pathways through health behaviours. METHOD: Study population comprised 3,995 Finnish men and women aged 25 to 64 years who participated in a cross-sectional, population-based FINRISK 2002 Study. Participants' height and weight were measured to calculate BMI. Self-administered questionnaire assessed education, household income, leisure time physical activity, sitting behaviour, dietary habits, smoking, and alcohol consumption. Structural equation modelling with latent variables was applied to estimate age-adjusted direct and indirect associations between variables. RESULTS: Most health behaviours mediated the association between socioeconomic position and BMI. Strongest and most consistent mediators were diet and sitting in men and women, as well as leisure time physical activity in women. Health behaviours clustered strongly with each other. CONCLUSIONS: The strongest indirect associations between socioeconomic position and BMI were mediated through variables related to energy balance, i.e. diet and sedentariness. To reduce the socioeconomic variation in overweight and obesity, the main focus should be on food and sedentary behaviours while also taking into account the gender differences and clustering of unhealthy behaviours.

Effects of childhood socio-economic conditions on educational differences in leisure-time physical activity.

BACKGROUND: Our purpose was to assess the direct and indirect contribution of childhood socio-economic conditions to educational differences in leisure-time physical activity among women and men. METHODS: Population-based data were derived from a representative sample of Finns aged >or=30 years (N = 7112) as part of Health 2000 Survey. Multinomial logistic regression analysis was applied. Leisure-time physical activity was divided into inactivity, moderate and high activity. RESULTS: Childhood socio-economic conditions had both a direct and indirect effect through adulthood socio-economic conditions on educational differences in leisure-time physical activity. The direct effect of childhood socio-economic conditions on educational differences in inactivity was stronger than its indirect effects through adulthood socio-economic conditions and other health behaviours and related factors. Adulthood socio-economic conditions had a considerable indirect effect on educational differences in leisure-time physical activity through other adulthood health behaviours and related factors among men. CONCLUSIONS: In order to narrow educational differences in leisure-time physical activity, we should secure a childhood environment that enables a physically active lifestyle, support leisure-time physical activity in diverse occupational groups, guarantee equal physical activity possibilities across different educational careers and support those with insufficient material resources.

Occupational class differences in leisure-time physical inactivity--contribution of past and current physical workload and other working conditions.

OBJECTIVE: Our aim was to examine the contribution of past and current physical workload to occupational class differences in leisure-time physical inactivity. METHODS: Data were taken from the Finnish population-based Health 2000 Survey of employees aged >or=30 years (N=3355). We assessed physical activity during leisure time using a questionnaire and dichotomized responses to inactive versus active. Occupational class was classified into white- and blue-collar worker. Adjustments were made for current work-related factors, other measures of socioeconomic position, clinically diagnosed chronic diseases, other health behaviors, and history of physical workload. We applied sequential logistic regression to the analyses. RESULTS: Inactivity during leisure time was more common in blue-collar employees than in their white-collar counterparts [women odds ratio (OR) 1.50, 95% confidence interval (95% CI) 1.12-2.00; men OR 1.66, 95% CI 1.30-2.12]. These occupational differences were not due to working hours, work schedule, or chronic diseases. Among women, current job strain decreased the occupational differences in leisure-time physical inactivity slightly (OR 1.37, 95% CI 0.99-1.04). Education and household income contributed to occupational differences for men (OR 1.45, 95% CI 1.02-2.07), but had no additional effect among women. The occupation differences in leisure-time physical inactivity disappeared after adjusting for smoking and body mass index in women (OR 1.33, 95% CI 0.97-1.83) and men (OR 1.27, 95% CI 0.88-1.82) and were further attenuated after adjusting for history of physical workload among men (OR 1.07, 95% CI 0.67-1.72). CONCLUSIONS: Having a long history of exposure to physical work (among men) and a high current job strain (among women) contributed to occupational class differences in leisure-time physical inactivity.

Physical activity beliefs, barriers, and enablers among postpartum women.

BACKGROUND AND METHODS: Physical activity during postpartum is both a recommended and an essential contributor to maternal health. Understanding the beliefs, barriers, and enablers regarding physical activity during the postpartum period can more effectively tailor physical activity interventions. The objective of this study was to document self-reported beliefs, barriers, and enablers to physical activity among a cohort of women queried at 3 and 12 months postpartum. Five questions about beliefs and two open-ended questions about their main barriers and enablers regarding physical activity and exercise were asked of 667 women at 3 months postpartum. Among the sample, 530 women answered the same questions about barriers and enablers to physical activity at 12 months postpartum. RESULTS: Agreement on all five beliefs statements was high (>or=89%), indicating that women thought that exercise and physical activity were appropriate at 3 months postpartum, even if they continued to breastfeed. For the cohort, the most common barriers to physical activity at both 3 and 12 months postpartum were lack of time (47% and 51%, respectively) and issues with child care (26% and 22%, respectively). No barrier changed by more than 5% from 3 to 12 months postpartum. For the cohort, the most common enablers at 3 months postpartum were partner support (16%) and desire to feel better (14%). From 3 to 12 months postpartum, only one enabler changed by >5%; women reported baby reasons (e.g., baby older, healthier, not breastfeeding, more active) more often at 12 months than at 3 months postpartum (32% vs. 10%). Environmental/policy and organizational barriers and enablers were reported less often than intrapersonal or interpersonal barriers at both time points. CONCLUSIONS: A number of barriers and enablers were identified for physical activity, most of which were consistent at 3 and 12 months postpartum. This study provides information to create more successful interventions to help women be physically active postpartum.

Trends and socioeconomic differences in overweight among physically active and inactive Finns in 1978-2002.

OBJECTIVE: The aim was to study the associations of physical activity and socioeconomic status with overweight from 1978 to 2002 and to explore whether the trend in overweight was different across educational groups or leisure time and commuting physical activity groups. METHOD: The study population comprised 37,084 women and 34,191 men who participated in cross-sectional postal surveys carried out annually from 1978 to 2002. The surveys included independent nationally representative random samples of Finns aged 25 to 64 years. Information on weight, height, leisure time and commuting physical activity was self-reported. The level of education was obtained from national register data. Overweight was defined as a body mass index (kg/m2) of 25 or higher. RESULTS: Overweight was more prevalent among the physically inactive and lower educated. The prevalence of overweight increased over time. Across the study years, those men and women who participated in leisure time or commuting physical activity had a lower prevalence of overweight in all educational groups. The increase in the prevalence of overweight followed a similar pattern in all physical activity and education groups. CONCLUSION: Engagement in physical activity has not prevented an increase in the prevalence of overweight in any socioeconomic group among Finnish men and women from 1978 to 2002.