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This paper explores neighborhood-built environment features related to ‘better than expected’ and ‘as expected’ early childhood development outcomes (ECD) in 14 Australian disadvantaged communities. This paper draws from mixed methods data collected in the Kids in Communities Study – an Australian investigation of community effects on ECD – in communities across five states and territories. In total, 93 interviews and 30 focus groups were conducted with service providers and parents, and geographic information systems were used to create built environment measures for each local community. Housing factors (e.g. better affordability, tenure, less high-density public housing) were consistently related to disadvantaged local communities with ‘better than expected’ ECD outcomes. Physical access to services and public transport, living in a walkable area, having high-quality public open space, and a mix of local destinations was perceived to be consistently important by community members in disadvantaged communities regardless of ECD outcomes. Findings may help policymakers to consider neighborhood features that contribute to better ECD outcomes.

Contains fulltext : 252060.pdf (Publisher’s version ) (Open Access), BACKGROUND: To assess trends in the quality of care for COVID-19 patients at the ICU over the course of time in the Netherlands. METHODS: Data from the National Intensive Care Evaluation (NICE)-registry of all COVID-19 patients admitted to an ICU in the Netherlands were used. Patient characteristics and indicators of quality of care during the first two upsurges (N = 4215: October 5, 2020-January 31, 2021) and the final upsurge of the second wave, called the 'third wave' (N = 4602: February 1, 2021-June 30, 2021) were compared with those during the first wave (N = 2733, February-May 24, 2020). RESULTS: During the second and third wave, there were less patients treated with mechanical ventilation (58.1 and 58.2%) and vasoactive drugs (48.0 and 44.7%) compared to the first wave (79.1% and 67.2%, respectively). The occupancy rates as fraction of occupancy in 2019 (1.68 and 1.55 vs. 1.83), the numbers of ICU relocations (23.8 and 27.6 vs. 32.3%) and the mean length of stay at the ICU (HRs of ICU discharge = 1.26 and 1.42) were lower during the second and third wave. No difference in adjusted hospital mortality between the second wave and the first wave was found, whereas the mortality during the third wave was considerably lower (OR = 0.80, 95% CI [0.71-0.90]). CONCLUSIONS: These data show favorable shifts in the treatment of COVID-19 patients at the ICU over time. The adjusted mortality decreased in the third wave. The high ICU occupancy rate early in the pandemic does probably not explain the high mortality associated with COVID-19.

OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was.80, and the Brier score was.18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity.

There is increasing international interest in place-based approaches to improve early childhood development (ECD) outcomes. The available data and evidence are limited and precludes well informed policy and practice change. Developing the evidence-base for community-level effects on ECD is one way to facilitate more informed and targeted community action. This paper presents overall final findings from the Kids in Communities Study (KiCS), an Australian mixed methods investigation into community-level effects on ECD in five domains of influence-physical, social, governance, service, and sociodemographic. Twenty five local communities (suburbs) across Australia were selected based on 'diagonality type' i.e. whether they performed better (off-diagonal positive), worse (off-diagonal negative), or 'as expected' (on-diagonal) on the Australian Early Development Census (AEDC) relative to their socioeconomic profile. The approach was designed to determine replicable and modifiable factors that were separate to socioeconomic status. Between 2015-2017, stakeholder interviews (n = 146), parent and service provider focus groups (n = 51), and existing socio-economic and early childhood education and care administrative data were collected. Qualitative and quantitative data analyses were undertaken to understand differences between 14 paired disadvantaged local communities (i.e. on versus off-diagonal). Further analysis of qualitative data elicited important factors for all 25 local communities. From this, we developed a draft set of 'Foundational Community Factors' (FCFs); these are the factors that lay the foundations of a good community for young children.

Contains fulltext : 225472.pdf (Publisher’s version ) (Closed access), OBJECTIVES: Assessment of all-cause mortality of intracerebral hemorrhage and ischemic stroke patients admitted to the ICU and comparison to the mortality of other critically ill ICU patients classified into six other diagnostic subgroups and the general Dutch population. DESIGN: Observational cohort study. SETTING: All ICUs participating in the Dutch National Intensive Care Evaluation database. PATIENTS: All adult patients admitted to these ICUs between 2010 and 2015; patients were followed until February 2017. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of all 370,386 included ICU patients, 7,046 (1.9%) were stroke patients, 4,072 with ischemic stroke, and 2,974 with intracerebral hemorrhage. Short-term mortality in ICU-admitted stroke patients was high with 30 days mortality of 31% in ischemic stroke and 42% in intracerebral hemorrhage. In the longer term, the survival curve gradient among ischemic stroke and intracerebral hemorrhage patients stabilized. The gradual alteration of mortality risk after ICU admission was assessed using left-truncation with increasing minimum survival period. ICU-admitted stroke patients who survive the first 30 days after suffering from a stroke had a favorable subsequent survival compared with other diseases necessitating ICU admission such as patients admitted due to sepsis or severe community-acquired pneumonia. After having survived the first 3 months after ICU admission, multivariable Cox regression analyses showed that case-mix adjusted hazard ratios during the follow-up period of up to 3 years were lower in ischemic stroke compared with sepsis (adjusted hazard ratio, 1.21; 95% CI, 1.06-1.36) and severe community-acquired pneumonia (adjusted hazard ratio, 1.57; 95% CI, 1.39-1.77) and in intracerebral hemorrhage patients compared with these groups (adjusted hazard ratio, 1.14; 95% CI, 0.98-1.33 and adjusted hazard ratio, 1.49; 95% CI, 1.28-1.73). CONCLUSIONS: Stroke patients who need intensive care treatment have a high

Disadvantaged communities tend to have poorer early childhood development outcomes. Access to safe, secure, and stable housing is a well-known social determinant of health but there is a need to examine key features of neighbourhood housing that reduce early childhood development inequities. The 2012 Australian Early Development Census (AEDC), a population-wide measure of early childhood development, and the Australian Bureau of Statistics Socio-economic Index for Areas Index of Relative Socio-economic Disadvantage were used to select fourteen disadvantaged local communities in five Australian states and territories based on those performing better (off-diagonal), or as expected (on-diagonal) on the AEDC relative to their socio-economic profile. Between 2015–2017, qualitative and quantitative housing data were collected in the local communities. In total, 87 interviews with stakeholders, 30 focus groups with local service providers and parents, and Australian Census dwelling information were analysed. A comparative case study approach was used to examine differences in housing characteristics (e.g., public housing, density, affordability, and tenure) between disadvantaged local communities performing ‘better than expected’ and ‘as expected’ on early childhood development. Perceived better housing affordability, objectively measured housing tenure (ownership) and perceived and objectively measured lower-density public housing were housing characteristics that emerged as points of difference for disadvantaged local communities where children had relatively better early childhood development outcomes. These characteristics are potential modifiable and policy sensitive housing levers for reducing early childhood development inequities.

© 2017 Published by the BMJ Publishing Group Limited. Introduction: Healthy childhood development in the early years is critical for later adult health and well-being. Early childhood development (ECD) research has focused primarily on individual, family and school factors, but largely ignored community factors. The Kids in Communities Study (KiCS) will test and investigate community-level influences on child development across Australia. Methods and analysis: Cross-sectional mixed-methods study exploring community-level effects in 25 Australian local communities; selection based on community socioeconomic status (SES) and ECD using the Australian Early Development Census (AEDC), a population measure of child development, to create a local community 'diagonality type', that is, those performing better or worse (off-diagonal), or as expected (on-diagonal) on the AEDC relative to their SES. Data collection includes stakeholder interviews, parent and service provider focus groups, and surveys with general community residents and service providers, mapping of neighbourhood design and local amenities and services, analysis of policy documents, and the use of existing sociodemographic and early childhood education and care data. Quantitative data will be used to test associations between local community diagonality type, and ECD based on AEDC scores. Qualitative data will provide complementary and deeper exploration of these same associations. Ethics and dissemination: The Royal Children's Hospital Human Research Ethics Committee approved the study protocol (#30016). Further ethics approvals were obtained from State Education and Health departments and Catholic archdioceses where required. ECD community-level indicators will eventually be derived and made publically available. Findings will be published in peer-reviewed journals, community reports, websites and policy briefs to disseminate results to researchers, and key stakeholders including policymakers, practitioners

© 2017 Elsevier Ltd The relationship between features of the neighbourhood built environment and early child development was investigated using area-level data from the Australian Early Development Census. Overall 9.0% of children were developmentally vulnerable on the Physical Health and Well-being domain, 8.1% on the Social Competence domain and 8.1% on the Emotional Maturity domain. After adjustment for socio-demographic factors, Local Communities with the highest quintile of home yard space had significantly lower odds of developmental vulnerability on the Emotional Maturity domain. Residing in a Local Community with fewer main roads was associated with a decrease in the proportion of children developmentally vulnerable on the Social Competence domain. Overall, sociodemographic factors were more important than aspects of the neighbourhood physical environment for explaining variation between Local Communities in the developmental vulnerability of children.

Aims.Childhood maltreatment and a family history of a schizophrenia spectrum disorder (SSD) are each associatedwith social-emotional dysfunction in childhood. Both are also strong risk factors for adult SSDs, and social-emotionaldysfunction in childhood may be an antecedent of these disorders. We used data from a large Australian populationcohort to determine the independent and moderating effects of maltreatment and parental SSDs on early childhoodsocial-emotional functioning.Methods.The New South Wales Child Development Study combines intergenerational multi-agency data using recordlinkage methods. Multiple measures of social-emotional functioning (social competency, prosocial/helping behaviour,anxious/fearful behaviour; aggressive behaviour, and hyperactivity/inattention) on 69 116 kindergarten children (age∼5 years) were linked with government records of child maltreatment and parental presentations to health servicesfor SSD. Multivariable analyses investigated the association between maltreatment and social-emotional functioning,adjusting for demographic variables and parental SSD history, in the population sample and in sub-cohorts exposedand not exposed to parental SSD history. We also examined the association of parental SSD history and social-emotionalfunctioning, adjusting for demographic variables and maltreatment.Results.Medium-sized associations were identified between maltreatment and poor social competency, aggressive be-haviour and hyperactivity/inattention; small associations were revealed between maltreatment and poor prosocial/help-ing and anxious/fearful behaviours. These associations did not differ greatly when adjusted for parental SSD, and weregreater in magnitude among children withno historyof parental SSD. Small associations between parental SSD and poorsocial-emotional functioning remained after adjusting for demographic variables and maltreatment.Conclusions.Childhood maltreatment and history of parental SSD are associated independently w

Purpose: The initial aim of this multiagency, multigenerational record linkage study is to identify childhood profiles of developmental vulnerability and resilience, and to identify the determinants of these profiles. The eventual aim is to identify risk and protective factors for later childhood-onset and adolescent-onset mental health problems, and other adverse social outcomes, using subsequent waves of record linkage. The research will assist in informing the development of public policy and intervention guidelines to help prevent or mitigate adverse longterm health and social outcomes. Participants: The study comprises a population cohort of 87 026 children in the Australian State of New South Wales (NSW). The cohort was defined by entry into the first year of full-time schooling in NSW in 2009, at which time class teachers completed the Australian Early Development Census (AEDC) on each child (with 99.7% coverage in NSW). The AEDC data have been linked to the children's birth, health, school and child protection records for the period from birth to school entry, and to the health and criminal records of their parents, as well as mortality databases. Findings to date: Descriptive data summarising sex, geographic and socioeconomic distributions, and linkage rates for the various administrative databases are presented. Child data are summarised, and the mental health and criminal records data of the children's parents are provided. Future plans: In 2015, at age 11 years, a self-report mental health survey was administered to the cohort in collaboration with government, independent and Catholic primary school sectors. A second record linkage, spanning birth to age 11 years, will be undertaken to link this survey data with the aforementioned administrative databases. This will enable a further identification of putative risk and protective factors for adverse mental health and other outcomes in adolescence, which can then be tested in subsequent record linkages.

Item does not contain fulltext, PURPOSE: The relationship between the number of patients admitted to an intensive care unit (ICU) volume and mortality is currently the subject of debate. After implementation of a national guideline in 2006, all Dutch ICUs have been classified into three levels based on ICU size, patient volume, ventilation days, and staffing. The goal of this study is to investigate the association between ICU level and mortality of ICU patients in the Netherlands. METHODS: We analyzed data from 132,159 patients admitted to 87 ICUs between January 1, 2009 and October 1, 2011. Logistic GEE analyses were performed to assess the influence of ICU level on in-hospital mortality and 90-day mortality in the total ICU population and in different ICU subgroups while adjusting for severity of illness by APACHE IV. Results : No significant differences were found in the adjusted in-hospital mortality of the total ICU population and in different subgroups admitted to level 1, 2 and 3 ICUs. In-hospital mortality in level 2 and 3 ICUs as opposed to level 1 ICUs was 1.06 (0.93-1.22) and 1.10 (0.94-1.29), respectively, and 90-day mortality was 0.92 (0.80-1.06) and 1.01 (0.88-1.17). CONCLUSION: We demonstrated that ICU level was not associated with significant differences in the case-mix adjusted in-hospital and long-term mortality of ICU patients. This finding is in contrast with some earlier studies suggesting a volume-outcome relationship. Our results may be explained by the successful implementation of nationwide mandatory quality requirements and adequate staffing in all three levels of ICUs over the last years.

Socio-environmental factors, including the neighbourhoods in which children live and grow, are key determinants of children’s developmental outcomes. Thus, it is important to examine and consider the relationships between these factors and the multiple contexts that influence children. Drawing on a broad disciplinary range of existing research, we aimed to develop a conceptual model of neighbourhood effects influencing early childhood development. The neighbourhood effects literature was reviewed with a specific focus on existing models and frameworks. This review was then further expanded through consultation with our cross-disciplinary research collaboration (Kids in Communities Study Collaboration). From this a theoretical model specific to early childhood development was developed. The hypothesised model comprised five interconnected domains: physical, social, service, socio-economic, and governance. A small trial of indicator measurement was conducted and findings were used to make a series of recommendations regarding measures or indicators which might provide useful and effective for neighbourhood effects research. The proposed model provides a useful and novel conceptual framework for classifying neighbourhood effects research. By synthesising disparate but related areas of research, the resultant five domains provide a useful approach to understanding and measuring child development in the context of community and environment, therefore advancing knowledge in this area. Expanding the current neighbourhood effects paradigm to accommodate broader constructs appears critical in considering the multiple environments that may act as key determinants of children’s wellbeing and psychosocial outcomes.

Item does not contain fulltext, OBJECTIVE: Following two randomized controlled trials that demonstrated reduced mortality and better neurological outcome in cardiac arrest patients, mild therapeutic hypothermia was implemented in many intensive care units. Up to now, no large observational studies have confirmed the beneficial effects of mild therapeutic hypothermia. DESIGN: Internet-based survey combined with a retrospective, observational study. PATIENTS: All patients admitted to an intensive care unit in The Netherlands after cardiac arrest from January 1, 1999 until January 1, 2009. DATA SOURCE: Dutch National Intensive Care Evaluation database. METHODS: The moment of implementation of mild therapeutic hypothermia for each hospital participating in the Dutch National Intensive Care Evaluation database was determined with an Internet survey. To compare mortality before and after implementation of mild therapeutic hypothermia, the odds ratio adjusted for Simplified Acute Physiology Score II score, age, gender, propensity score, and in- or out-of-hospital cardiac arrest was calculated. Patients were excluded if 1) they were admitted to an intensive care unit that did not respond to the survey, 2) they were admitted within 3 months after implementation of mild therapeutic hypothermia, 3) they had a Glasgow Coma Scale score of >8, or 4) they did not satisfy the Simplified Acute Physiology Score II inclusion criteria. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 13,962 patients were admitted to an intensive care unit following cardiac arrest. In total 8,645 patients were excluded, 5,544 because of a Glasgow Coma Scale score of >8. Of the resultant 5,317 patients, 1,547 patients were treated before and 3,770 patients after implementation of mild therapeutic hypothermia. Patients admitted after implementation of mild therapeutic hypothermia had lower minimal and maximal temperatures (p < .0001) during the first 24 hrs on the intensive care unit compared to patients admitted before im