Leisure-time physical activity is associated with socio-economic status beyond income – Cross-sectional survey of the Northern Finland Birth Cohort 1966 study

Huikari, Sanna; Junttila, Hanna; Ala‐Mursula, Leena; Jämsä, Timo; Korpelainen, Raija; Miettunen, Jouko; Svento, Rauli; Korhonen, Marko

doi:10.1016/j.ehb.2020.100969

Cited by 14 publications

(11 citation statements)

References 44 publications

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“…The results remained stable regardless of the measurement type of physical activity. According to previous literature, higher education has been shown to be related to higher physical activity (30,31). Similarly, higher physical activity has been shown to be related to higher incomes (32–35).…”

Section: Discussionmentioning

confidence: 99%

The Individual-Level Productivity Costs of Physical Inactivity

Kari

Nerg

Huikari

et al. 2022

Medicine &Amp; Science in Sports &Amp; Exercise

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Purpose: This study estimated the long-term individual-level productivity costs of physical inactivity. Methods: The data were drawn from the Northern Finland Birth Cohort 1966, to which the productivity cost variables (sick leaves and disability pensions) from Finnish registries were linked. Individuals (N = 6261) were categorized into physical activity groups based on their level of physical activity, which was measured in three ways: 1) self-reported leisure-time moderate-to vigorous-intensity physical activity (MVPA) at 46 yr old, 2) longitudinal self-reported leisure-time MVPA at 31-46 yr old, and 3) accelerometer-measured overall MVPA at 46 yr old. The human capital approach was applied to calculate the observed costs (years 2012-2020) and the expected costs (years 2012-2031). Results: The results showed that the average individual-level productivity costs were higher among physically inactive compared with the costs among physically active. The results were consistent regardless of the measurement type of physical activity or the period used. On average, the observed long-term productivity costs among physically inactive individuals were €1900 higher based on self-reported MVPA, €1800 higher based on longitudinal MVPA, and €4300 higher based on accelerometer-measured MVPA compared with the corresponding productivity costs among physically active individuals. The corresponding difference in the expected costs was €2800, €1200, and €8700, respectively. Conclusions: The results provide evidence that productivity costs differ according to an individual's level of physical activity. Therefore, investments in physical activity may decrease not only the direct healthcare costs but also the indirect productivity costs paid by the employee, the employer, and the government.

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Section: Discussionmentioning

confidence: 99%

The Individual-Level Productivity Costs of Physical Inactivity

Kari

Nerg

Huikari

et al. 2022

Medicine &Amp; Science in Sports &Amp; Exercise

Self Cite

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“…The SLOTH model, developed by Cawley in 2004, considers the allocation of time to various activities. This model assumes that individuals choose how to spend their time according to utility and cost [64,65]. Thus, the decision to spend time on passive entertainment activities is related to a lower level of education and this could be reflected in children's behavior.…”

Section: Discussionmentioning

confidence: 99%

Screen Time and Parents’ Education Level Are Associated with Poor Adherence to the Mediterranean Diet in Spanish Children and Adolescents: The PASOS Study

Wärnberǵ

Pérez-Farinós

Benavente-Marín

et al. 2021

JCM

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The aim of this study is to evaluate if screen time and parents’ education levels are associated with adherence to a Mediterranean dietary pattern. This cross-sectional study analyzed a representative sample of 3333 children and adolescents (8 to 16 years) included in the Physical Activity, Sedentarism, lifestyles and Obesity in Spanish youth (PASOS) study in Spain (which ran from March 2019 to February 2020). Data on screen time (television, computer, video games, and mobile phone) per day, Mediterranean diet adherence, daily moderate or vigorous physical activity, and parents’ education levels were gathered using questionnaires. A descriptive study of the variables according to sex and parents’ education level was performed. Logistic regression models (adjusted by sex and weight status) were fitted to evaluate the independent association between screen time and Kids’ level of adherence to the Mediterranean diet (KIDMED) index, as well as some of its items. A greater amount of screen time was associated with worse adherence to the Mediterranean diet; a lower consumption of fruit, vegetables, fish, legumes, and nuts; and a greater consumption of fast food, sweets, and candies. A lower parents’ education level was associated with worse adherence to the Mediterranean diet. It is necessary to promote the responsible, limited use of screen time, especially in children with parents with a lower education level.

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“…Lower education and income levels have already been shown to be associated with lower involvement in PA in both males and females of all ages, and that an inverse relationship exists between social economic status and sedentary time, compounding the concern in our set up. Individuals in the lower socio economic strata have more sitting and screen-time compared to those of the higher socio economic statuses [24][25][26][27][28]. Local data is minimal however, and this paucity of data from lower socio-economic countries contribute the current recommendation of need for more work to adequately demonstrate how socioeconomic status impacts PA involvement [29].…”

Section: Introductionmentioning

confidence: 99%

Physical activity engagement in Eldoret, Kenya, during COVID-19 pandemic

Magutah

Mbuthia

2022

PLOS Glob Public Health

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The World Health Organization (WHO) recommends that individuals of all ages participate in regular physical activity (PA) for optimal health and to support with the control of multiple non-communicable diseases. In Kenya however, involvement in PA across the general population is low and there is an increase in sedentary lifestyles in both rural and urban areas. An inverse relationship exists between socioeconomic status and involvement in PA. The novel COVID-19 ushered in associated control measures to limit the spread of the virus. These measures included staying at home, social distancing, and closure of physical spaces such as gyms, public parks, sports grounds, outdoor playing areas and schools. The impact was immediate, impacting patterns and routines of PA in Kenya. The primary aim of this study was to verify if COVID-19 affected PA prevalence and patterns amongst adults in Eldoret, Kenya. The secondary aim was to ascertain if the modification in behaviour is consistent amongst individuals from different socioeconomic backgrounds. We used a cross-sectional study to examine self-reported PA data amongst 404 participants. All participants were ≥18 years and resided in Eldoret, Kenya. Data were collected using a self-administered, structured questionnaire adapted from the WHO Global Physical Activity Questionnaire (WHO GPAQ). The characteristics of participants’ is summarized using descriptive statistics, and bivariate analyses for measures of associations of variables was done using Chi-squared and Fishers exact tests. Binary logistic regressions were performed to adjust for the various factors and report associations between variables. The p-value considered for significant differences was set at <0.05. Participants in this study had mean age of 30.2±9.8 years. Almost 90% of the participants were not aware of the current WHO guidelines on PA, 9% stopped PA engagement after COVID-19 was first reported in Kenya, and only 25% continued regular PA. Less than half maintained PA intensity after the advent of COVID-19, with almost half reporting a drop. Males had a drop in time taken per PA session while females maintained session lengths after COVID-19 (p = 0.03). Males preferred gym-setup or mixed-type PA while females opted for indoor (home) aerobics before and after COVID-19 (p = 0.01, p = 0.02 respectively). Compared to males, females were less likely to achieve both vigorous- and moderate-intensity PA recommendations (p<0.01 and p = 0.02 respectively). Zone of residence was associated with participation in aerobic PA (p = 0.04; 95% CI = 0.02499–0.96086) and, similarly, level of education was associated with knowledge of WHO recommendations for PA (p = 0.01; 95% CI = -1.7544 - -0.2070). A majority of the urban population of Eldoret, Kenya and especially those with lower level of education are unaware of WHO recommendations for PA, and 30% of them have not engaged in any form of PA for many years. The majority that report involvement in PA do not achieve the WHO recommended threshold levels of PA. The results also indicated that COVID-19 has negatively affected intensity of PA, and that there has been an increase in time spent sitting/reclining amongst individuals in the higher socio-economic classes and specifically amongst females.

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Leisure-time physical activity is associated with socio-economic status beyond income – Cross-sectional survey of the Northern Finland Birth Cohort 1966 study

Cited by 14 publications

References 44 publications

The Individual-Level Productivity Costs of Physical Inactivity

The Individual-Level Productivity Costs of Physical Inactivity

Screen Time and Parents’ Education Level Are Associated with Poor Adherence to the Mediterranean Diet in Spanish Children and Adolescents: The PASOS Study

Physical activity engagement in Eldoret, Kenya, during COVID-19 pandemic

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