Do differences in sport participation contribute to socioeconomic health inequalities? Evidence from the Lifelines cohort study on all-cause mortality, diabetes and obesity.

Little is known about the role of sport participation in socioeconomic health inequalities. We studied the association between different aspects of sport participation with all-cause mortality, type 2 diabetes mellitus (T2DM) and obesity, including inequalities between socioeconomic subpopulations. Using the Dutch Lifelines cohort study (n = 84,230), we assessed the associations of sport participation, as well as the amount, intensity, type and number of sports, with all-cause mortality, T2DM and obesity in individuals. We studied the effect of sport participation on health outcomes within and between educational categories. Outcomes were compared with moderate to vigorous physical activity (MVPA). Sport participation was significantly associated with lower mortality (HR = 0.81), T2DM (HR = 0.70), and obesity (HR = 0.77). No significant additional effects of the amount or intensity of sport participation were found, while participating in teams sport was associated with significantly lower mortality (HR = 0.53) compared with other types of sport. These effects were similar among educational categories. Sport participation explained between 11% (T2DM and obesity) and 22% (mortality) of health inequalities between educational categories. This was more than twice the effect size of MVPA. The sensitivity analysis with net income as the socioeconomic indicator showed similar results. Our results suggest that to reduce socioeconomic differences in health, public health policies should focus on increasing sport participation in groups with a low socioeconomic status, rather than increasing the amount or intensity of sport participation, or MVPA in general.

The impact of the Covid-19 crisis on socioeconomic differences in physical activity behavior: Evidence from the Lifelines COVID-19 cohort study.

Covid-19 and measures to contain spreading the disease have led to changed physical activity behavior. This study aims to investigate the relationship between socioeconomic status (SES) and changes in the amount of moderate to vigorous physical activity (MVPA) during the Covid-19 crisis. Using the Dutch Lifelines Covid-19 cohort study (n = 17,749), the amount of MVPA was measured at 15 time-points between March and December 2020, and compared with the amount before the Covid19 pandemic. For SES, the population was stratified in three education and income levels. Logistic regression models were used to estimate the odds ratio (OR) and confidence interval (CI) of altered MVPA for low and high SES groups, with the middle SES category as the reference group. A clear socioeconomic gradient in changes in MVPA behavior was observed. Low educated individuals had significantly higher odds (OR = 1.14; CI: 1.03-1.27) of decreasing MVPA, while the high educated had significantly lower odds of decreased MVPA (OR = 0.84, CI: 0.79-0.90). Both low education (OR = 0.87; CI: 0.77-0.98) and low income (OR = 0.85; CI 0.78-0.92) had significantly lower odds to increase MVPA, while high education (OR = 1.21, CI: 1.12-1.30) and high income (OR = 1.17; CI: 1.07-1.28) had significantly higher odds to increase MVPA. Most findings were consistent over the full research period. Socioeconomic inequalities in MVPA have increased during the Covid-19 pandemic, even when Covid-19 containment measures were relaxed. Our findings suggest that future public health policies need to increase efforts to improve physical activity behavior with an even larger focus on low SES groups.

How are lifestyle factors associated with socioeconomic differences in health care costs? Evidence from full population data in the Netherlands.

INTRODUCTION: There is a strong socioeconomic gradient in health care costs. However, little is known about the role of lifestyle factors in the association between health care costs and socioeconomic status (SES). This study investigates variation in the association between lifestyle indicators and health care costs between and within neighborhoods with similar SES. METHOD: Using 2016 whole-population data for all 790 neighborhoods of the Netherlands, we estimated the association between neighborhood average health care cost performance (i.e., health care costs adjusted for population age and gender) and neighborhood socioeconomic status (NSES) and four lifestyle indicators - smoking, alcohol consumption, exercise and sport club membership. Additionally, using regression analysis, we explored the multivariate relationship between average health care cost performance, NSES and lifestyle indicators. RESULTS: Neighborhoods with proportionally fewer smokers and more sport club members had significantly lower average health care costs. Remarkably, neighborhoods with more people who complied with the recommended maximum alcohol consumption had significantly higher health care costs. These findings were consistent within and between neighborhoods with different SES levels. Neighborhoods with more compliance with exercise guidelines had lower health care costs. However, this relationship was inconsistent across different NSES levels, with the largest cost reductions found in the most deprived neighborhoods. CONCLUSION: Our findings suggest that prevention policies aimed at reducing the number of smokers and increasing sport club membership may reduce health care costs across all NSES groups, while increasing compliance with physical exercise norms may be effective mainly in low SES neighborhoods.

Increased Physical Activity in Preparation for a Women-Only Mass Participation Sport Event: A Framework for Estimating the Health Impact.

Mass participation sporting events (MPSEs) are increasing in popularity. However, little research exists into the potential value of these events for improving public health by enhancing physical activity (PA). The aim of this study is to estimate the health impact of increased physical activity as a result of preparing for an MPSE. Participants of a mass participation women-only running event were asked if they performed additional PA in preparation of the event, including the length (weeks) and intensity (min per week). Additionally, self-reported change in health status was evaluated. Based on these results, we have developed a framework for estimating the cumulatively gained quality adjusted life years (QALYs) and monetary value thereof. Of the respondents (N = 468; mean age 42.3 ± 11.9 years), 32% performed additional vigorous PA in preparation of the event, with an average of 63 min per week over 8.8 weeks. Performing additional vigorous PA significantly improved the odds of self-rated health. The estimated total health impact of participants preparing for the Marikenloop was 6.6 QALYs gained with a corresponding monetary value between EUR 133,000 and EUR 532,000. We believe our health impact framework helps to understand that MPSEs can be a notable part of the public health domain.

Neighborhood Socioeconomic Status and Health Care Costs: A Population-Wide Study in the Netherlands.

Objectives. To identify disparities in several types of insured health care costs in the Netherlands across neighborhoods with different socioeconomic statuses and to assess the room for improvement. Methods. We used 2015 Dutch whole-population registry data to estimate the age- and gender-specific cost structure by neighborhood for total, specialist, pharmaceutical, and mental health care. Classifying neighborhoods by the quintile of their neighborhood socioeconomic status (NSES), we determined differences in observed and expected health care costs for several scenarios of NSES improvement. Results. From low to high NSES, we found a clear downward gradient in health care costs. Total health care costs would drop by 7.3% if each neighborhood's cost structure was equal to that of the most affluent neighborhoods. The potential for cost reduction appeared highest for females, for age groups between 40 and 60 years, and for pharmaceutical care. Conclusions. Low NSES is associated with relatively high health care costs, and represents considerable potential for cost savings in health care. Public Health Implications. Our research suggests that policies aimed at improving the socioeconomic determinants of health locally may be pivotal in containing health care costs.