During the COVID-19 pandemic, the bidirectional relationship between policy and data reliability has been a challenge for researchers of the local municipal health services. Policy decisions on population specific test locations and selective registration of negative test results led to population differences in data quality. This hampered the calculation of reliable population specific infection rates needed to develop proper data driven public health policy. https://doi.org/10.1007/s12508-023-00377-y
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There is increasing evidence that humans are not living sustainably. There are three major drivers of the unsustainable approach: population, consumption and the growth economy. There is widespread denial about these issues, but they clearly need to be addressed if we are to achieve any of the possible sustainable futures. The first and second versions of the ‘World Scientists Warning to Humanity’ both highlight the problem of increasing human population, as do the IPCC and IPBES reports. However, all have been largely ignored. The size of an ecologically sustainable global population is considered, taking into account the implications of increasing per capita consumption. The paper then discusses the reasons why society and academia largely ignore overpopulation. The claim that discussing overpopulation is ‘anti-human’ is refuted. Causal Layered Analysis is used to examine why society ignores data that do not fit with its myths and metaphors, and how such denial is leading society towards collapse. Non-coercive solutions are then considered to reach an ecologically-sustainable human population. LinkedIn: https://www.linkedin.com/in/helenkopnina/
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Peak oxygen uptake (V'O2peak) is recognised as the best expression of aerobic fitness. Therefore, it is essential that V'O2peak reference values are accurate for interpreting a cardiopulmonary exercise test (CPET). These values are country specific and influenced by underlying biological ageing processes. They are normally stratified per paediatric and adult population, resulting in a discontinuity at the transition point between prediction equations. There are currently no age-related reference values available for the lifespan of individuals in the Dutch population. The aim of this study is to determine the best-fitting regression model for V'O2peak in the healthy Dutch paediatric and adult populations in relation to age. In this retrospective study, CPET cycle ergometry results of 4477 subjects without reported somatic diseases were included (907 females, age 7.9-65.0 years). Generalised additive models were employed to determine the best-fitting regression model. Cross-validation was performed against an independent dataset consisting of 3518 subjects (170 females, age 6.8-59.0 years). An additive model was the best fitting with the largest predictive accuracy in both the primary (adjusted R2=0.57, standard error of the estimate (see)=556.50 mL·min-1) and cross-validation (adjusted R2=0.57, see=473.15 mL·min-1) dataset. This study provides a robust additive regression model for V'O2peak in the Dutch population.
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Background: Research in maternity care is often conducted in mixed low and high-risk or solely high-risk populations. This limits generalizability to the low-risk population of pregnant women receiving care from Dutch midwives. To address this limitation, 24 midwifery practices in the Netherlands bring together routinely collected data from medical records of pregnant women and their offspring in the VeCaS database. This database offers possibilities for research of physiological pregnancy and childbirth. This study explores if the pregnant women in VeCaS are a representative sample for the national population of women who receive primary midwife-led care in the Netherlands. Methods: In VeCaS we selected a low risk population in midwife-led care who gave birth in 2015. We compared population characteristics and birth outcomes in this study cohort with a similarly defined national cohort, using Chi Square and two side t-test statistics. Additionally, we describe some birth outcomes and lifestyle factors. Results: Midwifery practices contributing to VeCaS are spread over the Netherlands, although the western region is underrepresented. For population characteristics, the VeCaS cohort is similar to the national cohort in maternal age (mean 30.4 years) and parity (nulliparous women: 47.1% versus 45.9%). Less often, women in the VeCaS cohort have a non-Dutch background (15.7% vs 24.4%), a higher SES (9.9% vs 23.7%) and live in an urbanised surrounding (4.9% vs 24.8%). Birth outcomes were similar to the national cohort, most women gave birth at term (94.9% vs 94.5% between 37 + 0–41+ 6 weeks), started labour spontaneously (74.5% vs 75.5%) and had a spontaneous vaginal birth (77.4% vs 77.6%), 16.9% had a home birth. Furthermore, 61.1% had a normal pre-pregnancy BMI, and 81.0% did not smoke in pregnancy. Conclusions: The VeCaS database contains data of a population that is mostly comparable to the national population in primary midwife-led care in the Netherlands. Therefore, the VeCaS database is suitable for research in a healthy pregnant population and is valuable to improve knowledge of the physiological course of pregnancy and birth. Representativeness of maternal characteristics may be improved by including midwifery practices from the urbanised western region in the Netherlands.
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The so called Second Demographic Transition (Lesthaeghe and Van der Kaa, 1986), which surfaced in the sixties of the twentieth century in Western Europe and North America, resulted from a significant change in the pattern of norms and values. This again resulted in delayed fertility, a declining population when there was no replenishment through "replacement migration” and an increasing variety of household structures (with a rising number of one-person households). The rise in life expectancy coupled with a declining fertility, evolved into a gradual ageing of the population.The concept of ‘unbalanced population decline’ (Van Nimwegen and Heering 2009) enables us, while studying population decline, to take into account different motives underlying the decision to migrate during the life course; young people migrating in search of higher education and job opportunities and elderly clustering in places with a high facility level. This unbalanced population decline is taking place in some rural parts and smaller towns in the Netherlands. Especially the two migration flows mentioned above determine the structure of the population and the possibilities for effective family, kin and other social support systems for the elderly.Method:Analysis using amongst others recent demographic data from de community of Oldambt (Netherlands)Results:It will be shown that the effects of the demographic transition in the North of the Netherlands are accelerated because of unbalanced population decline. Furthermore it will be argued that because of this combination in parts of the Northern Netherlands family, kin and social support systems for the elderly are deteriorating more rapidly than in other parts of the county.Conclusion:Combined effects of demographic transition and unbalanced population decline urge for a reconsideration of the possibilities to rely on family, kin and other social support systems in different regions in the Netherlands.
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OBJECTIVE: The prevalence of multimorbidity has risen considerably because of the increase in longevity and the rapidly growing number of older individuals. Today, only little is known about the influence of multimorbidity on cognition in a normal healthy aging population. The primary aim of the present study was to investigate the effect of multimorbidity on cognition over a 12-year period in an adult population with a large age range. METHODS: Data were collected as part of the Maastricht Aging Study (MAAS), a prospective study into the determinants of cognitive aging. Eligible MAAS participants (N = 1763), 24-81 years older, were recruited from the Registration Network Family Practices (RNH) which enabled the use of medical records. The association between 96 chronic diseases, grouped into 23 disease clusters, and cognition on baseline, at 6 and 12 years of follow-up, were analyzed. Cognitive performance was measured in two main domains: verbal memory and psychomotor speed. A multilevel statistical analysis, a method that respects the hierarchical data structure, was used. RESULTS: Multiple disease clusters were associated with cognition during a 12-year follow-up period in a healthy adult population. The disease combination malignancies and movement disorders multimorbidity also appeared to significantly affect cognition. CONCLUSIONS: The current results indicate that a variety of medical conditions adversely affects cognition. However, these effects appear to be small in a normal healthy aging population.
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During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
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Recent years have seen a massive growth in ethical and legal frameworks to govern data science practices. Yet one of the core questions associated with ethical and legal frameworks is the extent to which they are implemented in practice. A particularly interesting case in this context comes to public officials, for whom higher standards typically exist. We are thus trying to understand how ethical and legal frameworks influence the everyday practices on data and algorithms of public sector data professionals. The following paper looks at two cases: public sector data professionals (1) at municipalities in the Netherlands and (2) at the Netherlands Police. We compare these two cases based on an analytical research framework we develop in this article to help understanding of everyday professional practices. We conclude that there is a wide gap between legal and ethical governance rules and the everyday practices.
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Background: Although maternity care is linked to improved health outcomes, it is often insufficiently tailored to the needs of low socioeconomic position (SEP) majority population women in high-income countries, leading to obstacles in achieving good health. Cultural competence can contribute to access to adequate care, but no systematic assessment has been conducted. This study aims to examine current evidence about the aspects of cultural competence of maternity care professionals caring for low socioeconomic position (SEP) majority population women. Methods: A scoping review was conducted. Search terms were based on the PCC elements (Participants, Concepts, and Context). Data-extraction and analysis were performed by two researchers according to a predetermined procedure. Data were grouped in the main themes of the Seeleman-framework (2009) and subsequently inductively analyzed. Results: Out of 6954 articles, 35 were eligible for data analysis. To create an overview of available evidence quality assessment of the included studies was not performed. Health professionals express a lack of knowledge and skills to assess socio-economic vulnerabilities in women and to refer to other care options regarding socio-economic vulnerabilities. Although positive experiences with professionals were mentioned, many women experience negative attitudes in terms of a lack of respect and stigmatization issues. Professionals lack the skills to build good relationships with women. Both women and health professionals reported poor communication and collaboration with health care colleagues and with social services. Conclusions: The cultural competence of health professionals in maternity care needs improvement. Professionals should be equipped with sufficient knowledge to identify deprived women and their needs and be trained in skills to effectively communicate and build care relationships. Future research should focus on the reflections of health professionals on their professional role regarding low SEP majority population women. The conditions and maternity care systems health professionals work in to serve low SEP majority women should be studied more closely. Results call for a debate about the scope of professional practice and logistical care structures regarding maternity care for low SEP majority population women. Clinical trial number: Not applicable.
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Over the past few years, there has been an explosion of data science as a profession and an academic field. The increasing impact and societal relevance of data science is accompanied by important questions that reflect this development: how can data science become more responsible and accountable while also responding to key challenges such as bias, fairness, and transparency in a rigorous and systematic manner? This Patterns special collection has brought together research and perspective from academia, the public and the private sector, showcasing original research articles and perspectives pertaining to responsible and accountable data science.
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