Aim

Our objective was to test the hypothesis that the prevalence of Type 2 diabetes increases with increasing regional deprivation even after controlling for individual socio-economic status



Methods

We pooled cross-sectional data from five German population-based studies The data set contained information on n = 11 688 study participants (men 501%) aged 45–74 years, of whom 1008 people had prevalent Type 2 diabetes (men 562%) Logistic multilevel regression was performed to estimate odds ratios (OR) and 95% confidence intervals (CI) for diabetes prevalence We controlled for sex, age and lifestyle risk factors, individual socio-economic status and regional deprivation, based on a new small-area deprivation measure, the German Index of Multiple Deprivation



Results

Adjusted for sex, age, body mass index (BMI), physical activity, smoking status and alcohol consumption, the prevalence of Type 2 diabetes showed a stepwise increase in risk with increasing area deprivation [OR 188 (95% CI 116–304) in quintile 4 and OR 214 (95% CI 129–355) in quintile 5 compared with the least deprived quintile 1], even after controlling for individual socio-economic status Focusing on individual socio-economic status alone, the risk of having diabetes was significantly higher for low compared with medium or high educational level [OR 146 (95% CI 124–171)] and for the lowest compared with the highest income group [OR 153 (95% CI 118–199)]



Conclusion

Regional deprivation plays a significant part in the explanation of diabetes prevalence in Germany independently of individual socio-economic status The results of the present study could help to target public health measures in deprived regions

The impact of regional deprivation and individual socio-economic status on the prevalence of Type 2 diabetes in Germany. A pooled analysis of five population-based studies.

Tackling inequalities in health: an agenda for action

Depression in middle-aged and older first generation migrants in Europe: Results from the Survey of Health, Ageing and Retirement in Europe (SHARE)

Unmet health care needs are determined as the difference between the services judged necessary and the services actually received, and stem from barriers related to accessibility, availability and acceptability. This study aims to examine the prevalence of unmet needs and to identify the socioeconomic and health status factors that are associated with unmet needs. A cross-sectional study was conducted in Greece in 2010 and involved data from 1,000 consenting subjects (>18 years old). Multiple binary logistic regression analysis was applied to investigate the predictors of unmet needs and to determine the relation between the socio-demographic characteristics and the accessibility, availability and acceptability barriers. Ninety nine participants (9.9%) reported unmet health needs during the 12 months prior to the research. The most frequently self-reported reasons were cost and lack of time. Youth, parenthood, physician consultations, and poor mental health increased the likelihood of unmet needs. Women were less likely to report accessibility and availability than acceptability barriers. Educational differences were evident and individuals with primary and secondary education were associated with significantly more accessibility and availability barriers compared with those with tertiary education. Unmet health needs pose a significant challenge to the health care system, especially given the difficult current financial situation in Greece. It is believed that unmet health needs will continue to increase, which will widen inequalities in health and health care access.

Investigating Unmet Health Needs in Primary Health Care Services in a Representative Sample of the Greek Population

Using survey data from the 2009 wave of the European Union Statistics on Income and Living Conditions, this study examines the determinants of unmet needs for medical and dental care in European countries. Special emphasis is put on the impact of health system characteristics. Four factors are taken into account: the density of doctors or dentists, the rules governing access to practitioners, the method of paying primary care physicians, and the amount of out-of-pocket payments. The analysis is carried out using multilevel logistic regression models. Separate regressions are estimated for medical and dental services. The dependent variable is whether respondents reported that, at least once in the last 12 months, they needed care but did not receive it. The estimation results show that the probability of experiencing unmet medical or dental needs varies noticeably across countries. This inter-country variability seems to be partly explained by the differences in the financing of health care. Indeed, a positive link is found between the share of households' out-of-pocket payments in total health expenditure and the probability of unmet needs. The other contextual factors do not seem to play a significant role.

Health system characteristics and unmet care needs in Europe: an analysis based on EU-SILC data

Studies on the association between access to health care and household income have rarely included an assessment of 'forgone care', but this indicator could add to our understanding of the inverse care law. We hypothesize that reporting forgone care is more prevalent in low income groups. The study is based on the 'Survey of Health, Ageing and Retirement in Europe (SHARE)', focusing on the non-institutionalized population aged 50 years or older. Data are included from France, Germany, Greece, Italy and Sweden. The dependent variable is assessed by the following question: During the last twelve months, did you forgo any types of care because of the costs you would have to pay, or because this care was not available or not easily accessible? The main independent variable is household income, adjusted for household size and split into quintiles, calculating the quintile limits for each country separately. Information on age, sex, self assessed health and chronic disease is included as well. Logistic regression models were used for the multivariate analyses. The overall level of forgone care differs considerably between the five countries (e.g. about 10 percent in Greece and 6 percent in Sweden). Low income groups report forgone care more often than high income groups. This association can also be found in analyses restricted to the subsample of persons with chronic disease. Associations between forgone care and income are particularly strong in Germany and Greece. Taking the example of Germany, forgone care in the lowest income quintile is 1.98 times (95% CI: 1.08–3.63) as high as in the highest income quintile. Forgone care should be reduced even if it is not justified by an 'objective' need for health care, as it could be an independent stressor in its own right, and as patient satisfaction is a strong predictor of compliance. These efforts should focus on population groups with particularly high prevalence of forgone care, for example on patients with poor self assessed health, on women, and on low income groups. The inter-country differences point to the need to specify different policy recommendations for different countries.

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Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study

Raphael Kiess

Papers

Association between forgone care and household income among the elderly in five Western European countries – analyses based on survey data from the SHARE-study