Demographic profile of families and children in the Study to Explore Early Development (SEED): Case-control study of autism spectrum disorder

The Study to Explore Early Development (SEED) is designed to enhance knowledge of autism spectrum disorder characteristics and etiologies

Early life influences on child weight outcomes in the Study to Explore Early Development

We examined associations between child body mass index at 2–5 years and maternal pre-pregnancy body mass index, gestational weight gain, and rapid weight gain during infancy in children with autism spectrum disorder, developmental delays, or population controls. The Study to Explore Early Development is a multi-site case–control study of children, aged 2–5 years, classified as autism spectrum disorder (n = 668), developmental delays (n = 914), or population controls (n = 884). Maternal gestational weight gain was compared to the Institute of Medicine recommendations. Rapid weight gain was a change in weight-for-age z-scores from birth to 6 months > 0.67 standard deviations. After adjusting for case status, mothers with pre-pregnancy overweight/obesity were 2.38 times (95% confidence interval: 1.96–2.90) more likely, and mothers who exceeded gestational weight gain recommendations were 1.48 times (95% confidence interval: 1.17–1.87) more likely, to have an overweight/obese child than other mothers (P < 0.001). Children with autism spectrum disorder showed the highest frequency of rapid weight gain (44%) and were 3.47 times (95% confidence interval: 1.85–6.51) more likely to be overweight/obese as children with autism spectrum disorder without rapid weight gain (P < 0.001). Helping mothers achieve a healthy pre-pregnancy body mass index and gestational weight gain represent important targets for all children. Healthy infant growth patterns carry special importance for children at increased risk for an autism spectrum disorder diagnosis

Cost-effectiveness of interventions for increasing the possession of functioning smoke alarms in households with pre-school children: a modelling study

Background The UK has one of the highest rates for deaths from fire and flames in children aged 0-14 years compared to other high income countries. Evidence shows that smoke alarms can reduce the risk of fire-related injury but little exists on their cost-effectiveness. We aimed to compare the cost effectiveness of different interventions for the uptake of 'functioning' smoke alarms and consequently for the prevention of fire-related injuries in children in the UK. Methods We carried out a decision model-based probabilistic cost-effectiveness analysis. We used a hypothetical population of newborns and evaluated the impact of living in a household with or without a functioning smoke alarm during the first 5 years of their life on overall lifetime costs and quality of life from a public health perspective. We compared seven interventions, ranging from usual care to more complex interventions comprising of education, free/low cost equipment giveaway, equipment fitting and/or home safety inspection. Results Education and free/low cost equipment was the most cost-effective intervention with an estimated incremental cost-effectiveness ratio of [pound sign]34,200 per QALY gained compared to usual care. This was reduced to approximately £4,500 per QALY gained when 1.8 children under the age of 5 were assumed per household. Conclusions Assessing cost-effectiveness, as well as effectiveness, is important in a public sector system operating under a fixed budget restraint. As highlighted in this study, the more effective interventions (in this case the more complex interventions) may not necessarily be the ones considered the most cost-effective

Mode shifting in school travel mode: examining the prevalence and correlates of active school transport in Ontario, Canada

<p>Abstract</p> <p>Background</p> <p>Studies examining the correlates of school transport commonly fail to make the distinction between morning and afternoon school trips. The purpose of this study was to examine the prevalence and correlates of mode shift from passive in the morning to active in the afternoon among elementary and secondary school students in Ontario, Canada.</p> <p>Methods</p> <p>Data were derived from the 2009 cycle of the Ontario Student Drug Use and Health Survey (OSDUHS). 3,633 students in grades 7 through 12 completed self-administered questionnaires. Socio-demographic, behavioural, psychological, and environmental predictors of active school transport (AST) were assessed using logistic regression.</p> <p>Results</p> <p>Overall, 47% and 38% of elementary school students reported AST to and from school, respectively. The corresponding figures were 23% and 32% for secondary school students. The prevalence of AST varied temporarily and spatially. There was a higher prevalence of walking/biking found for elementary school students than for secondary school students, and there was an approximate 10% increase in AST in the afternoon. Different correlates of active school transport were also found across elementary and secondary school students. For all ages, students living in urban areas, with a shorter travel time between home and school, and having some input to the decision making process, were more likely to walk to and from school.</p> <p>Conclusions</p> <p>Future research examining AST should continue to make the analytic distinction between the morning and afternoon trip, and control for the moderating effect of age and geography in predicting mode choice. In terms of practice, these variations highlight the need for school-specific travel plans rather than 'one size fits all' interventions in promoting active school transport.</p

Syndromic Autism: progressing beyond current levels of description

Genetic syndrome groups at high risk of autism comorbidity, like Down syndrome and fragile X syndrome, have been presented as useful models for understanding risk and protective factors involved in the emergence of autistic traits. Yet despite reaching clinical thresholds, these ‘syndromic’ forms of autism appear to differ in significant ways from the idiopathic or ‘non-syndromic’ autism profile. We explore alternative mechanistic explanations for these differences and propose a developmental interpretation of syndromic autism that takes into account the character of the genetic disorder. This interpretation anticipates syndrome-specific autism phenotypes, since the neurocognitive and behavioural expression of the autism is coloured by syndromically defined atypicalities. To uncover the true nature of comorbidities and of autism per se, we argue that it is key to extend definitions of autism to include the perceptual and neurocognitive characteristics of the disorder and then apply this multilevel conceptualization to the study of syndromic autism profiles

All Are Not Created Equal: Assessing Initial Driving Self-Regulation Behaviors Among Older Adults

Introduction: Mobility is closely tied to the ability to safely drive. In older adulthood, many people begin to avoid difficult driving situations, such as driving at night, during rush hour, on freeways, or in unfamiliar areas. Reasons for such avoidance include driving self-regulation (SR; an intentional response to perceived difficulty), lifestyle changes, or preference. Most previous research has not made distinctions between these reasons, has not compared driving avoidance situations, and has not differentiated between those early in the SR process from those farther along. This study addressed those issues by comparing each of the aforementioned driving avoidance behaviors as one's initial SR behavior. Methods: A total of 1554 older drivers from the AAA Longitudinal Research on Aging Drivers study were analyzed. Multinomial regression was used to determine how demographics, function, and driving-related factors were related to a difference in the odds of reporting one initial SR behavior compared to each of the others. Results: The most common initial SR behavior was avoidance of nighttime driving (57.59%), followed by avoidance of rush hour driving (26.96%), driving in unfamiliar areas (10.81%), and driving on freeways (4.63%). A variety of demographic and function variables were associated with a difference in the odds of the initial SR behaviors, including gender, race, income, anxiety, driving responsibility, having rides available, driving abilities, and driving comfort. Conclusions: Nighttime avoidance is the most common initial SR behavior. Variables specifically related to situational driving comfort and driving ability were the best predictors of differences in driving SR.http://deepblue.lib.umich.edu/bitstream/2027.42/193063/2/1-s2.0-S2214140521003406-main.pdfPublished versio

The Effects of Demographics, Functioning, and Perceptions on the Relationship between Self-Reported and Objective Measures of Driving Exposure and Patterns among Older Adults.

The exploratory study reported here was intended to examine: how strongly subjectively reported driving avoidance behaviors (commonly referred to as self-regulation) and exposure were related to their objectively measured counterparts and whether it depended on the specific behavior; the extent to which gender and age play a role in the association between subjectively reported driving avoidance behaviors and exposure and their objectively measured counterparts; and the extent to which demographics, health and functioning, driving-related perceptions, and cognition influence the association between subjective and objective driving avoidance behaviors overall. The study used data from the Longitudinal Research on Aging Drivers (LongROAD) study, a multisite, prospective cohort study designed to generate empirical data for understanding the role of medical, behavioral, environmental, and technological factors in driving safety during the process of aging. Objective driving measures were derived from GPS/datalogger data from 2131 LongROAD participants’ vehicles. The corresponding subjective measures came from a comprehensive questionnaire administered to participants at baseline that asked them to report on their driving exposure, patterns, and other aspects of driving. Several other variables used in the analyses came from the comprehensive questionnaire and an in-person clinical assessment administered to participants at baseline. A series of simple linear and logistic models were fitted to examine the relationship between the subjective and objective driving measures of interest, and a multivariable analysis was conducted to examine the potential role of selected factors in the relationship between objective and subjective driving avoidance behaviors. Results of the models are presented and overall findings are discussed within the context of the existing research literature.http://deepblue.lib.umich.edu/bitstream/2027.42/193082/2/nihms959301.pdfPublished versio