Widening inequalities in self-rated health by material deprivation? A trend analysis between 2001 and 2011 in Germany

Pförtner, Timo-Kolja; Elgar, Frank J.

doi:10.1136/jech-2015-205948

Cited by 20 publications

(29 citation statements)

References 56 publications

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“…Pheiffer [19] observed that many risk factors for NCDs were not captured in FE regression analysis and noted that important variables can be excluded from analysis by using certain panel analysis methods, leading to distorted results [20,21].…”

Section: Discussionmentioning

confidence: 99%

“…In general, panel data are analyzed with an FE regression which addresses the limitations of crosssectional and time-series analyses and considers attributes inherent to survey units [18]. However, since unobserved endogenous attributes are not always associated with observed attributes, a pooled OLS regression should be run on adult population data [20,21,24]. This is in line with the aforementioned finding that important variables that may influence a dependent variable cannot be identified if only an FE panel regression is run on panel data that undergo little change, leading to distorted results [20,21].…”

Section: Discussionmentioning

confidence: 99%

“…However, since unobserved endogenous attributes are not always associated with observed attributes, a pooled OLS regression should be run on adult population data [20,21,24]. This is in line with the aforementioned finding that important variables that may influence a dependent variable cannot be identified if only an FE panel regression is run on panel data that undergo little change, leading to distorted results [20,21]. Furthermore, since health-related variables such as SRH are affected by socioeconomic characteristics, a pooled OLS regression is often preferred when analyzing healthrelated panel data [20][21][22].…”

Section: Discussionmentioning

confidence: 99%

“…In the present study as well, socioeconomic variables were found to have no effects on SRH in the FE panel regression, whereas the pooled OLS regression, which included the socioeconomic variables identified marital status, housing type, educational level, living expenses, and economic activity as influential variables for SRH. Since these important variables affecting SRH, rarely show significant intra-individual variability, care should be taken to identify them by varying the analysis method [20,21,40,41].…”

Section: Discussionmentioning

confidence: 99%

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Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

Yoon¹

2020

Preprint

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Background: The health status of an individual is determined by socio-economic factors and behavioral factors. Socio-economic factors include marital status, educational level, living expenses, and housing type, among others. The differences of health status across individuals are mainly determined by these socioeconomic factors, which cannot be altered in a short run. However, even if the socioeconomic factors cannot be altered in the short run, there are ways for an individual to improve the health status in a relatively short period of time. These are behavioral factors, such as physical activities and management of depression. Methods: We provided evidence of the first statement by running a pooled OLS regression with self-rated health (SRH) as dependent variable and with walking, management of depression, sex, age, marital status, educational level, housing type, living expenses, and economic activity as independent variables. We proved the second statement by running a fixed-effect panel regression with the same dependent and independent variables. The 2010–2013 Korea Health Panel Survey data were used for analysis. Subjects were 34,436 adults (≥19 years) in 8,609 panel groups. Results: All the variables, including socio-economic variables as well as behavioral variables, were significant in the Pooled OLS regression. Whereas behavioral variables, such as walking and management of depression, were significant in the fixed-effect panel regression, socio-economic variables were not. The reason is that socio-economic variables are stable and not variant for an individual in the short-run.Conclusion: Whereas the differences of health status across individuals are mainly determined by socioeconomic factors, the health of an individual is significantly affected by his/her behavior. It is shown that regular walking and reduction of depression are important in improving SRH. There is a need for strategies designed to address depression and aging and encourage walking.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

Yoon¹

2020

Preprint

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“…Numerous studies have observed a close link between poverty and ill health [ 1 – 4 ], and the risk of getting a longstanding illness increases over the life course [ 5 ]. However, the extent to which illness leads to limitations in everyday life varies according to several factors, including type, stage and intensity of the health problem, personal perception of the situation, and available economic resources.…”

Section: Introductionmentioning

confidence: 99%

Material deprivation and health: a longitudinal study

Tøge

Bell

2016

BMC Public Health

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BackgroundDoes material deprivation affect the consequences of ill health? Answering this question requires that we move beyond the effects of income. Longitudinal data on material deprivation, longstanding illness and limiting longstanding illness enables investigations of the effects of material deprivation on risk of limiting longstanding illness. This study investigates whether a shift from affording to not affording a car predicts the probability of limiting longstanding ill (LLSI).MethodsThe 2008–2011 longitudinal panel of Statistics on Income, Social Inclusion and Living Conditions (EU-SILC) is utilised. Longitudinal fixed effects logit models are applied, using LLSI as dependent variable. Transition from affording a car to not affording a car is used as a proxy for material deprivation. All models are controlled for whether the person becomes longstanding ill (LSI) as well as other time-variant covariates that could affect the results.ResultsThe analysis shows a statistically significant increased odds ratio of LLSI when individuals no longer can afford a car, after controlling for confounders and LSI in the previous year (1.129, CI = 1.022–1.248). However, when restricting the sample to observations where respondents report longstanding illness the results are no longer significant (1.032, CI = 0.910–1.171).ConclusionThe results indicate an individual level effect of material deprivation on LLSI, suggesting that material resources can affect the consequences of ill health.

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Soziale Netzwerke und gesundheitliche Ungleichheiten – eine neue Perspektive für die Forschung

Klärner¹,

Gamper

Keim‐Klärner³

et al. 2019

Soziale Netzwerke Und Gesundheitliche Ungleichheiten

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Sag mir, wie viel Deine Freunde verdienen, und ich sage Dir, ob Du rauchst, welche Krankheiten Du hast und wie alt Du werden wirst!" Ein Teil dieser Aussage dürfte für all jene, die sich für den Zusammenhang von sozialer Ungleichheit und Gesundheit interessieren, vertraut sein. Menschen mit vergleichsweise niedrigerem sozioökonomischem Status tragen höhere gesundheitliche Risiken, werden häufiger krank und sie sterben auch früher als jene, die ein höheres

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Widening inequalities in self-rated health by material deprivation? A trend analysis between 2001 and 2011 in Germany

Abstract: Inequality in SRH by material deprivation was relatively stable; however, an observed quadratic trend coincided with active and passive labour market reforms in Germany in early 2005.

Cited by 20 publications

References 56 publications

Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

Material deprivation and health: a longitudinal study

Soziale Netzwerke und gesundheitliche Ungleichheiten – eine neue Perspektive für die Forschung

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