It Will Take a Global Movement to Curb Corruption in Health Systems; Comment on “We Need to Talk About Corruption in Health Systems”

Corruption in health systems is a problem around the world. Prior research consistently shows that corruption is detrimental to population health. Yet public health professionals are slow to address this complicated issue on a global scale. In the editorial entitled “We Need to Talk About Corruption in Health Systems” concern with the general lack of discourse on this topic amongst health professionals is highlighted. In this invited commentary three contributing factors that hamper public dialogue on corruption are discussed. These include (i) corrupt acts are often not illegal, (ii) government and medical professionals continued acceptance of corruption in the health systems, and (iii) lack of awareness within the general public on the extent of the problem. It is advocated that a global movement that is fully inclusive needs to occur to eradicate corruption

Socioeconomic inequalities in mortality and repeated measurement of explanatory risk factors in a 25 Years follow-up

Background Socioeconomic inequalities in mortality can be explained by different groups of risk factors. However, little is known whether repeated measurement of risk factors can provide better explanation of socioeconomic inequalities in health. Our study examines the extent to which relative educational and income inequalities in mortality might be explained by explanatory risk factors (behavioral, psychosocial, biomedical risk factors and employment) measured at two points in time, as compared to one measurement at baseline. Methods and Findings From the Norwegian total county population-based HUNT Study (years 1984–86 and 1995–1997, respectively) 61 513 men and women aged 25–80 (82.5% of all enrolled) were followed-up for mortality in 25 years until 2009, employing a discrete time survival analysis. Socioeconomic inequalities in mortality were observed. As compared to their highest socioeconomic counterparts, the lowest educated men had an OR (odds ratio) of 1.41 (95% CI 1.29–1.55) and for the lowest income quartile OR = 1.59 (1.48–1.571), for women OR = 1.35 (1.17–1.55), and OR = 1.40 (1.28–1.52), respectively. Baseline explanatory variables attenuated the association between education and income with mortality by 54% and 54% in men, respectively, and by 69% and 18% in women. After entering time-varying variables, this attainment increased to 63% and 59% in men, respectively, and to 25% (income) in women, with no improvement in regard to education in women. Change in biomedical factors and employment did not amend the explanation. Conclusions Addition of a second measurement for risk factors provided only a modest improvement in explaining educational and income inequalities in mortality in Norwegian men and women. Accounting for change in behavior provided the largest improvement in explained inequalities in mortality for both men and women, as compared to measurement at baseline. Psychosocial factors explained the largest share of income inequalities in mortality for men, but repeated measurement of these factors contributed only to modest improvement in explanation. Further comparative research on the relative importance of explanatory pathways assessed over time is needed

Association between education and mortality and income and mortality, 29,766 men 25–80 years, 1984/86–2009.

<p>Note: OR = odds ratio CI = confidence interval</p><p>OR was adjusted for age and age squared.</p><p>Age adjusted mortality rate / 100 000 person years was standardized by means of direct standardization (World standard population).</p><p>Values in bold do not include the OR 1.00.</p><p>Association between education and mortality and income and mortality, 29,766 men 25–80 years, 1984/86–2009.</p

Taking welfare state regime research globally: An application of the Wood and Gough typology to individual health

Seldom do studies on welfare regimes and health take a global perspective. Usually most research on this genre concentrates on high-income countries only, few studies include low-and middle-income countries, and even fewer examinations combine a large number of countries to obtain a worldwide view. For this, we need global welfare regime typologies that would allow for such examinations. Given this, we investigated the usefulness of the Wood and Gough welfare regime typology on 49 countries by examining the association between welfare regimes and self-reported individual disability worldwide. The World Health Survey data were examined on 207 818 people from 49 countries using the welfare regime classification developed by Wood and Gough. Multilevel logistic regression was used to investigate links between disability and welfare regimes while also accounting for individual-level socioeconomic factors. Variations in individual disability prevalence were found within the different welfare regimes. For example, odds of poor health prevalence for citizens within the insecurity Sub-Saharan African regime as compared with the European-conservative regime were OR = 1.83 95 per cent CI: 0.85-3.95. Living in a state-organized regime was associated with lower odds of disability prevalence, as higher odds of disability prevalence were observed in all non-state regimes (with the exception of the productivist regime). For instance, the people in the productivist regime of East Asia reported similar prevalence of poor health odds as compared with the European-conservative regime (OR = 0.94 95 per cent CI: 0.45-1.99). This short report found that the Wood and Gough typology enables the study of welfare regimes and health globally, and appears to be a useful tool in welfare regime type research. The productivist regime seems to have health protective features that are on par with European welfare state regimes. We recommend that this finding is investigated further in future empirical analyses. Social Theory & Health (2011) 9, 355-366. doi:10.1057/sth.2011.19; published online 12 October 201

Socioeconomic inequalities in smoking in low and mid income countries: positive gradients among women?

In Southern Europe, smoking among older women was more prevalent among the high educated than the lower educated, we call this a positive gradient. This is dominant in the early stages of the smoking epidemic model, later replaced by a negative gradient. The aim of this study is to assess if a positive gradient in smoking can also be observed in low and middle income countries in other regions of the world. We used data of the World Health Survey from 49 countries and a total of 233,917 respondents. Multilevel logistic regression was used to model associations between individual level smoking and both individual level and country level determinants. We stratified results by education, occupation, sex and generation (younger vs. older than 45). Countries were grouped based on GDP and region. In Eastern Europe and the Eastern Mediterranean, we observed a positive gradient in smoking among older women and a negative gradient among younger women. In Sub-Saharan Africa and Latin America no clear gradient was observed: inequalities were relatively small. In South-East Asia and East Asia a strong negative gradient was observed. Among men, no positive gradients were observed, and like women the strongest negative gradients were seen in South-East Asia and East Asia. A positive socio-economic gradient in smoking was found among older women in two regions, but not among younger women. But contrary to predictions derived from the smoking epidemic model, from a worldwide perspective the positive gradients are the exception rather than the rul

Assessing where vulnerable groups fare worst: a global multilevel analysis on the impact of welfare regimes on disability across different socioeconomic groups

Background Investigations on health differences within welfare states between low- and high-socioeconomic groups are mainly conducted in Europe. With the aim of gaining global insight on the extent welfare regimes influence personal disability for the most vulnerable, we explore how these health differences vary between low- and high-socioeconomic groups. Methods The World Health Survey data were analysed on 199 595 adults from 46 countries using the welfare regime classification developed by Wood and Gough. Multilevel logistic regression was used to estimate welfare regime differences in self-reported disability according to individual educational attainment and employment status. Results As compared with the low educated in the European-conservative regime, the odds of having a higher prevalence of disability was found among low-educated people residing in the informal-security regime of South Asia, with OR being 3.16 (95% CI 2.23 to 4.47). While state-organised regimes seemed to offer more protection against disability to the low educated, the productivist regime of East Asia trailed closely behind, with OR being 1.10 (95% CI 0.76 to 1.60) for the low educated. Similar findings were also observed in the unemployed. Conclusions State-organised regimes of Europe and the productivist regime of East Asia seem to contain protecting features against disability for all citizens and especially for the most vulnerable. Apart from the productivist regime of East Asia, the low educated and the unemployed seem to carry the greatest health burden within more insecure regimes, highlighting a deficiency in social provisions within these regimes aimed at protecting the most vulnerabl

Sick regimes and sick people: a multilevel investigation of the population health consequences of perceived national corruption

There is a paucity of empirical work on the potential population health impact of living under a regime marred by corruption. African countries differ in the extent of national corruption, and we explore whether perceived national corruption is associated with population health across all rungs of society. World Health Survey data were analysed on 72 524 adults from 20 African countries. The main outcome was self-reported poor general health. Multilevel logistic regression was used to assess the association between poor health and perceived corruption, while jointly accounting for individual- and country-level human development factors. In this research, we use Transparency International's corruption perception index (CPI), which measures 'both administrative and political corruption' on a 0-10 scale. A higher score pertains to a higher rate of perceived corruption within society. We also examined effect modification by gender, age and socio-economic status. Higher national corruption perception was consistently associated with an increase in poor health prevalence, also after multivariable adjustments, with odds ratio (OR) of 1.62 (95% CI: 1.01-2.60). Stratified analyses by age and gender suggested this same pattern in all subgroups. Positive associations between poor health and perceived corruption were evident in all socio-economic groups, with the association being somewhat more positive among less educated people (OR = 1.61, 95% CI: 1.01-2.58) than among more educated people (OR = 1.40, 95% CI: 0.83-2.37). This study is a cautious first step in empirically testing the general health consequences of corruption. Our results suggest that higher perceived national corruption is associated with general health of both men and women within all socio-economic groups across the lifespan. Further research is needed using more countries to assess the magnitude of the health consequences of corruptio

Odds ratios and proportional change for mortality by income in women 25–80 years.

<p>Note: OR for lowest income quartile compared to highest income quartile. Adjusted for age and age squared.</p><p>All nested models were significantly improved based on the -2 Log Likelihood (-2LL) test</p><p>AIC = Akaike information criterion BIC = Bayesian information criterion</p><p>Odds ratios and proportional change for mortality by income in women 25–80 years.</p

Odds ratios and proportional change for mortality by income in men 25–80 years.

<p>Note: OR for lowest income quartile compared to highest income quartile. Adjusted for age and age squared.</p><p>All nested models were significantly improved based on the -2 Log Likelihood (-2LL) test.</p><p>AIC = Akaike information criterion BIC = Bayesian information criterion</p><p>Odds ratios and proportional change for mortality by income in men 25–80 years.</p

Odds ratios and proportional change for mortality by education in women 25–80 years.

<p>Note: OR for low education compared to high education. Adjusted for age and age squared.</p><p>All nested models were significantly improved based on the -2 Log Likelihood (-2LL) test</p><p>AIC = Akaike information criterion BIC = Bayesian information criterion</p><p>Odds ratios and proportional change for mortality by education in women 25–80 years.</p