Maartje M. Schaap

Bio: Maartje M. Schaap is an academic researcher from Erasmus University Rotterdam. The author has contributed to research in topics: Public health & Population. The author has an hindex of 9, co-authored 12 publications receiving 3340 citations.

Socioeconomic Inequalities in Health in 22 European Countries

Abstract: A b s t r ac t Background Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. Methods We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. Results In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. Conclusions We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care.

Socioeconomic Inequalities in Health in 22 European Countries

Abstract: Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe.

Effect of nationwide tobacco control policies on smoking cessation in high and low educated groups in 18 European countries

Abstract: Background: Recently a scale was introduced to quantify the implementation of tobacco control policies at country level. Our study used this scale to examine the potential impact of these policies ...

Inequalities in health by social class dimensions in European countries of different political traditions

Abstract: textObjective: To compare inequalities in self-perceived health in the population older than 50 years, in 2004, using Wright's social class dimensions, in nine European countries grouped in three political traditions (Social democracy, Christian democracy and Late democracies). Methods: Cross-sectional design, including data of the Survey of Health, Ageing and Retirement in Europe (Sweden, Denmark, Austria, France, Germany, The Netherlands, Spain, Italy and Greece). The population aged from 50 to 74 years was included. Absolute and relative social class dimension inequalities in poor self-reported health and long-term illness were determined for each sex and political tradition. Relative inequalities were assessed by fitting Poisson regression models with robust variance estimators. Results: Absolute and relative health inequalities by social class dimensions are found in the three political traditions, but these differences are more marked in Late democracies and mainly among women. For example the prevalence ratio of poor self-perceived health comparing poorly educated women with highly educated women, was 1.75 (95% CI: 1.39-2.21) in Late democracies and 1.36 (95% CI: 1.21-1.52) in Social democracies. The prevalence differences were 24.2 and 13.7%, respectively. Conclusion: This study is one of the first to show the impact of different political traditions on social class inequalities in health. These results emphasize the need to evaluate the impact of the implementation of public policies.

Socioeconomic Inequalities in Health in 22 European Countries

Abstract: A b s t r ac t Background Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. Methods We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. Results In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. Conclusions We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care.

Neuroscience, Molecular Biology, and the Childhood Roots of Health Disparities: Building a New Framework for Health Promotion and Disease Prevention

Abstract: A scientific consensus is emerging that the origins of adult disease are often found among developmental and biological disruptions occurring during the early years of life. These early experiences can affect adult health in 2 ways—either by cumulative damage over time or by the biological embedding of adversities during sensitive developmental periods. In both cases, there can be a lag of many years, even decades, before early adverse experiences are expressed in the form of disease. From both basic research and policy perspectives, confronting the origins of disparities in physical and mental health early in life may produce greater effects than attempting to modify health-related behaviors or improve access to health care in adulthood.

The Social Determinants of Health: It's Time to Consider the Causes of the Causes:

Abstract: During the past two decades, the public health community’s attention has been drawn increasingly to the social determinants of health (SDH)—the factors apart from medical care that can be influenced by social policies and shape health in powerful ways. We use “medical care” rather than “health care” to refer to clinical services, to avoid potential confusion between “health” and “health care.” The World Health Organization’s Commission on the Social Determinants of Health has defined SDH as “the conditions in which people are born, grow, live, work and age” and “the fundamental drivers of these conditions.” The term “social determinants” often evokes factors such as health-related features of neighborhoods (e.g., walkability, recreational areas, and accessibility of healthful foods), which can influence health-related behaviors. Evidence has accumulated, however, pointing to socioeconomic factors such as income, wealth, and education as the fundamental causes of a wide range of health outcomes. This article broadly reviews some of the knowledge accumulated to date that highlights the importance of social—and particularly socioeconomic— factors in shaping health, and plausible pathways and biological mechanisms that may explain their effects. We also discuss challenges to advancing this knowledge and how they might be overcome.

The Association Between Income and Life Expectancy in the United States, 2001-2014

Abstract: Importance The relationship between income and life expectancy is well established but remains poorly understood. Objectives To measure the level, time trend, and geographic variability in the association between income and life expectancy and to identify factors related to small area variation. Design and Setting Income data for the US population were obtained from 1.4 billion deidentified tax records between 1999 and 2014. Mortality data were obtained from Social Security Administration death records. These data were used to estimate race- and ethnicity-adjusted life expectancy at 40 years of age by household income percentile, sex, and geographic area, and to evaluate factors associated with differences in life expectancy. Exposure Pretax household earnings as a measure of income. Main Outcomes and Measures Relationship between income and life expectancy; trends in life expectancy by income group; geographic variation in life expectancy levels and trends by income group; and factors associated with differences in life expectancy across areas. Results The sample consisted of 1 408 287 218 person-year observations for individuals aged 40 to 76 years (mean age, 53.0 years; median household earnings among working individuals, $61 175 per year). There were 4 114 380 deaths among men (mortality rate, 596.3 per 100 000) and 2 694 808 deaths among women (mortality rate, 375.1 per 100 000). The analysis yielded 4 results. First, higher income was associated with greater longevity throughout the income distribution. The gap in life expectancy between the richest 1% and poorest 1% of individuals was 14.6 years (95% CI, 14.4 to 14.8 years) for men and 10.1 years (95% CI, 9.9 to 10.3 years) for women. Second, inequality in life expectancy increased over time. Between 2001 and 2014, life expectancy increased by 2.34 years for men and 2.91 years for women in the top 5% of the income distribution, but by only 0.32 years for men and 0.04 years for women in the bottom 5% ( P r = −0.69, P r = 0.72, P r = 0.42, P r = 0.57, P Conclusions and Relevance In the United States between 2001 and 2014, higher income was associated with greater longevity, and differences in life expectancy across income groups increased over time. However, the association between life expectancy and income varied substantially across areas; differences in longevity across income groups decreased in some areas and increased in others. The differences in life expectancy were correlated with health behaviors and local area characteristics.