Background: Population segmentation and risk stratification are important strategies for allocating resources in public health, health care and social care. Social exclusion, which is defined as... Show moreBackground: Population segmentation and risk stratification are important strategies for allocating resources in public health, health care and social care. Social exclusion, which is defined as the cumulation of disadvantages in social, economic, cultural and political domains, is associated with an increased risk of health problems, low agency, and as a consequence, a higher need for health and social care. The aim of this study is to test social exclusion against traditional social stratifiers to identify high-risk/high-need population segments.Methods: We used data from 33,285 adults from the 2016 Public Health Monitor of four major cities in the Netherlands. To identify at-risk populations for cardiovascular risk, cancer, low self-rated health, anxiety and depression symptoms, and low personal control, we compared relative risks (RR) and population attributable fractions (PAF) for social exclusion, which was measured with the Social Exclusion Index for Health Surveys (SEI-HS), and four traditional social stratifiers, namely, education, income, labour market position and migration background.Results: The analyses showed significant associations of social exclusion with all the health indicators and personal control. Particular strong RRs were found for anxiety and depression symptoms (7.95) and low personal control (6.36), with corresponding PAFs of 42 and 35%, respectively. Social exclusion was significantly better at identifying population segments with high anxiety and depression symptoms and low personal control than were the four traditional stratifiers, while the two approaches were similar at identifying other health problems. The combination of social exclusion with a low labour market position (19.5% of the adult population) captured 67% of the prevalence of anxiety and depression symptoms and 60% of the prevalence of low personal control, as well as substantial proportions of the other health indicators.Conclusions: This study shows that the SEI-HS is a powerful tool for identifying high-risk/high-need population segments in which not only ill health is concentrated, as is the case with traditional social stratifiers, but also a high prevalence of anxiety and depression symptoms and low personal control are present, in addition to an accumulation of social problems. These findings have implications for health care practice, public health and social interventions in large cities. Show less
Spek, L. van der; Sanglier, S.; Mabeya, H.M.; Akker, T. van den; Mertens, P.L.J.M.; Houweling, T.A.J. 2020
Background Caesarean section (C-section) rates are often low among the poor and very high among the better-off in low- and middle-income countries. We examined to what extent these differences are... Show moreBackground Caesarean section (C-section) rates are often low among the poor and very high among the better-off in low- and middle-income countries. We examined to what extent these differences are explained by medical need in an African context. Methods We analyzed electronic records of 12,209 women who gave birth in a teaching hospital in Kenya in 2014. C-section rates were calculated by socioeconomic position (SEP), using maternal occupation (professional, small business, housewife, student) as indicator. We assessed if women had documented clinical indications according to hospital guidelines and if socioeconomic differences in C-section rates were explained by indication. Results Indication for C-section according to hospital guidelines was more prevalent among professionals than housewives (16% vs. 9% of all births). The C-section rate was also higher among professionals than housewives (21.1% vs. 15.8% [OR 1.43; 95%CI 1.23-1.65]). This C-section rate difference was largely explained by indication (4.7 of the 5.3 percentage point difference between professionals and housewives concerned indicated C-sections, often with previous C-section as indication). Repeat C-sections were near-universal (99%). 43% of primary C-sections had no documented indication. Over-use was somewhat higher among professionals than housewives (C-section rate among women without indication: 6.6 and 5.5% respectively), which partly explained socioeconomic differences in primary C-section rate. Conclusions Socioeconomic differences in C-section rates can be largely explained by unnecessary primary C-sections and higher supposed need due to previous C-section. Prevention of unnecessary primary C-sections and promoting safe trial of labor should be priorities in addressing C-section over-use and reducing inequalities. Tweetable abstract Unnecessary primary C-sections and ubiquitous repeat C-sections drive overall C-section rates and C-section inequalities. Show less
Background. One way to achieve universal health coverage (UHC) in low- and middle-income countries (LMIC) is the implementation of health insurance schemes. A robust and up to date overview of... Show moreBackground. One way to achieve universal health coverage (UHC) in low- and middle-income countries (LMIC) is the implementation of health insurance schemes. A robust and up to date overview of empirical evidence assessing and substantiating health equity impact of health insurance schemes among specific vulnerable populations in LMICs beyond the more common parameters, such as income level, is lacking. We fill this gap by conducting a systematic review of how social inclusion affects access to equitable health financing arrangements in LMIC. Methods. We searched 11 databases to identify peer-reviewed studies published in English between January 1995 and January 2018 that addressed the enrolment and impact of health insurance in LMIC for the following vulnerable groups: female-headed households, children with special needs, older adults, youth, ethnic minorities, migrants, and those with a disability or chronic illness. We assessed health insurance enrolment patterns of these population groups and its impact on health care utilization, financial protection, health outcomes and quality of care. Results.The comprehensive database search resulted in 44 studies, in which chronically ill were mostly reported (67%), followed by older adults (33%). Scarce and inconsistent evidence is available for individuals with disabilities, female-headed households, ethnic minorities and displaced populations, and no studies were yielded reporting on youth or children with special needs. Enrolment rates seemed higher among chronically ill and mixed or insufficient results are observed for the other groups. Most studies reporting on health care utilization found an increase in health care utilization for insured individuals with a disability or chronic illness and older adults. In general, health insurance schemes seemed to prevent catastrophic health expenditures to a certain extent. However, reimbursements rates were very low and vulnerable individuals had increased out of pocket payments. Conclusion. Despite a sizeable literature published on health insurance, there is a dearth of good quality evidence, especially on equity and the inclusion of specific vulnerable groups in LMIC. Evidence should be strengthened within health care reform to achieve UHC, by redefining and assessing vulnerability as a multidimensional process and the investigation of mechanisms that are more context specific. Show less
