Conceptualizing childhood health problems using survey data: a comparison of key indicators

<p>Abstract</p> <p>Background</p> <p>Many definitions are being used to conceptualize child health problems. With survey data, commonly used indicators for identifying children with health problems have included chronic condition checklists, measures of activity limitations, elevated service use, and health utility thresholds. This study compares these different indicators in terms of the prevalence rates elicited, and in terms of how the subgroups identified differ.</p> <p>Methods</p> <p>Secondary data analyses used data from the National Longitudinal Survey of Children and Youth, which surveyed a nationally representative sample of Canadian children (n = 13,790). Descriptive analyses compared healthy children to those with health problems, as classified by any of the key indicators. Additional analyses examined differences between subgroups of children captured by a single indicator and those described as having health problems by multiple indicators.</p> <p>Results</p> <p>This study demonstrates that children captured by any of the indicators had poorer health than healthy children, despite the fact that over half the sample (52.2%) was characterized as having a health problem by at least one indicator. Rates of child ill health differed by indicator; 5.6% had an activity limitation, 9.2% exhibited a severe health difficulty, 31.7% reported a chronic condition, and 36.6% had elevated service use. Further, the four key indicators captured different types of children. Indicator groupings differed on child and socio-demographic factors. Compared to children identified by more than one indicator, those identified only by the severe health difficulty indicator displayed more cognitive problems (p < 0.0001), those identified only by the chronic condition checklist had a greater likelihood of reporting allergies or asthma (p < 0.0001), and those identified as having elevated service use only were more affluent (p = 0.01) and showed better overall health (p < 0.0001). Children identified by only a single indicator were less likely to have serious health problems than those identified by two or more indicators.</p> <p>Conclusion</p> <p>We provide information useful to researchers when selecting indicators from survey data to identify children with health problems. Researchers and policy makers need to be aware of the impact of such definitions on prevalence rates as well as on the composition of children classified as being in poor health.</p

Using GIS to create synthetic disease outbreaks

BACKGROUND: The ability to detect disease outbreaks in their early stages is a key component of efficient disease control and prevention. With the increased availability of electronic health-care data and spatio-temporal analysis techniques, there is great potential to develop algorithms to enable more effective disease surveillance. However, to ensure that the algorithms are effective they need to be evaluated. The objective of this research was to develop a transparent user-friendly method to simulate spatial-temporal disease outbreak data for outbreak detection algorithm evaluation. A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment. RESULTS: The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment. CONCLUSION: This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance

Using Canadian administrative health data to measure the health of caregivers of children with and without health problems: A demonstration of feasibility.

Introduction Caregivers of children with health problems experience poorer health than the caregivers of healthy children. To date, population-based studies on this issue have primarily used survey data. Objectives We demonstrate that administrative health data may be used to study these issues, and explore how non-categorical indicators of child health in administrative data can enable population-level study of caregiver health. Methods Dyads from Population Data British Columbia (BC) databases, encompassing nearly all mothers in BC with children aged 6-10 years in 2006, were grouped using a non-categorical definition based on diagnoses and service use. Regression models examined whether four maternal health outcomes varied according to indicators of child health. Results 162,847 mother-child dyads were grouped according to the following indicators: Child High Service Use (18%) vs. Not (82%), Diagnosis of Major and/or Chronic Condition (12%) vs. Not (88%), and Both High Service Use and Diagnosis (5%) vs. Neither (75%). For all maternal health and service use outcomes (number of physician visits, chronic condition, mood or anxiety disorder, hospitalization), differences were demonstrated by child health indicators. Conclusions Mothers of children with health problems had poorer health themselves, as indicated by administrative data groupings. This work not only demonstrates the research potential of using routinely collected health administrative data to study caregiver and child health, but also the importance of addressing maternal health when treating children with health problems. Keywords Population data, linked data, case-mix, children with special health care need

The health and psychosocial functioning of caregivers of children with neurodevelopmental disorders

Purpose: Children with neurodevelopmental disorders (Neuro) pose complex parenting challenges, particularly if the condition co-occurs with behaviour problems. Such challenges are likely to impact caregiver health and well-being. This study explores the extent to which caregivers of children with both Neuro and behaviour problems differ in their physical and psychosocial outcomes from caregivers of children with either condition or neither condition. Method: The first wave of data collected in the National Longitudinal Survey of Children and Youth in Canada (1994) was used to identify four groups of caregivers of 4-to 11-year-old children: caregivers of children with a Neuro disorder and externalising behaviour problems (Both; n = 414), caregivers of children with a Neuro disorder only (Neuro Only; n = 750), caregivers of children with an externalising behaviour problem only (Ext Only; n = 1067), and caregivers of children with neither health condition (Neither; n = 7236). Results: Caregivers in the Both group were least likely to report excellent or very good health, and more frequently reported chronic conditions such as asthma, arthritis, back problems, migraine headaches, and limitations in activities as compared to the Neither group. This group also exhibited higher depression scores, experienced more problematic family functioning and reported lower social support than the Neither group. Scores for caregivers in the Ext Only and Neuro Only groups tended to lie between the Both and Neither group scores and often did not differ from one another. Conclusions: Caregivers of children with both neurovelopmental disorders and behaviour problems exhibited a greater number of health and psychosocial problems. While addressing children's behaviour problems, health care professionals should also consider caregiver physical and psychosocial health, as this may also have an impact on children's well-being

The OncoSim-Breast Cancer Microsimulation Model

Background: OncoSim-Breast is a Canadian breast cancer simulation model to evaluate breast cancer interventions. This paper aims to describe the OncoSim-Breast model and how well it reproduces observed breast cancer trends. Methods: The OncoSim-Breast model simulates the onset, growth, and spread of invasive and ductal carcinoma in situ tumours. It combines Canadian cancer incidence, mortality, screening program, and cost data to project population-level outcomes. Users can change the model input to answer specific questions. Here, we compared its projections with observed data. First, we compared the model&rsquo;s projected breast cancer trends with the observed data in the Canadian Cancer Registry and from Vital Statistics. Next, we replicated a screening trial to compare the model&rsquo;s projections with the trial&rsquo;s observed screening effects. Results: OncoSim-Breast&rsquo;s projected incidence, mortality, and stage distribution of breast cancer were close to the observed data in the Canadian Cancer Registry and from Vital Statistics. OncoSim-Breast also reproduced the breast cancer screening effects observed in the UK Age trial. Conclusions: OncoSim-Breast&rsquo;s ability to reproduce the observed population-level breast cancer trends and the screening effects in a randomized trial increases the confidence of using its results to inform policy decisions related to early detection of breast cancer

Health Among Caregivers of Children With Health Problems: Findings From a Canadian Population-Based Study

Objectives. We used population-based data to evaluate whether caring for a child with health problems had implications for caregiver health after we controlled for relevant covariates

Changes over time in the health of caregivers of children with health problems: Growth-curve findings from a 10-year Canadian population-based study

Objectives. We used Canadian population-based data to examine changes in the health of caregivers of children with complex health problems compared with caregivers of healthy children over a 10-year time period. Methods. The National Longitudinal Survey of Children and Youth collected data biennially from 9401 children and their caregivers in 6 waves from 1994–1995 to 2004–2005. We conducted growth-curve analyses of these data to model self-reported general health and depressive symptoms for 4 groups of caregivers: caregivers of healthy children, and caregivers of children with 1, 2, or at least 3 of 4 conceptually distinct indicators of child health problems. We modeled covariates for children (age, gender, only-child status) and caregivers (age, gender, education, income, marital status). Results. After we controlled for covariates, caregiver health outcomes worsened incrementally with increasing complexity of child health problems. Change in self-reported general health and depressive symptoms over the 10-year period was consistent across all groups of caregivers. Conclusions. Poorer health among caregivers of children with health problems can persist for many years and is associated with complexity of child health problems. Attention to parental health should form a component of health care services for children with health problems