343 research outputs found

    Intergenerational change and familial aggregation of body mass index

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    The relationship between parental BMI and that of their adult offspring, when increased adiposity can become a clinical issue, is unknown. We investigated the intergenerational change in body mass index (BMI) distribution, and examined the sex-specific relationship between parental and adult offspring BMI. Intergenerational change in the distribution of adjusted BMI in 1,443 complete families (both parents and at least one offspring) with 2,286 offspring (1,263 daughters and 1,023 sons) from the west of Scotland, UK, was investigated using quantile regression. Familial correlations were estimated from linear mixed effects regression models. The distribution of BMI showed little intergenerational change in the normal range (\25 kg/m2), decreasing overweightness (25– \30 kg/m2) and increasing obesity (C30 kg/m2). Median BMI was static across generations in males and decreased in females by 0.4 (95% CI: 0.0, 0.7) kg/m2; the 95th percentileincreased by 2.2 (1.1, 3.2) kg/m2 in males and 2.7 (1.4, 3.9) kg/m2 in females. Mothers’ BMI was more strongly associated with daughters’ BMI than was fathers’ (correlation coefficient (95% CI): mothers 0.31 (0.27, 0.36), fathers 0.19 (0.14, 0.25); P = 0.001). Mothers’ and fathers’ BMI were equally correlated with sons’ BMI (correlation coefficient: mothers 0.28 (0.22, 0.33), fathers 0.27 (0.22, 0.33). The increase in BMI between generations was concentrated at the upper end of the distribution. This, alongside the strong parent-offspring correlation, suggests that the increase in BMI is disproportionally greater among offspring of heavier parents. Familial influences on BMI among middle-aged women appear significantly stronger from mothers than father

    Adiposity in early, middle and later adult life and cardiometabolic risk markers in later life; findings from the British regional heart study.

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    OBJECTIVES: This research investigates the associations between body mass index (BMI) at 21, 40-59, 60-79 years of age on cardiometabolic risk markers at 60-79 years. METHODS: A prospective study of 3464 British men with BMI measured at 40-59 and 60-79 years, when cardiometabolic risk was assessed. BMI at 21 years was ascertained from military records, or recalled from middle-age (adjusted for reporting bias); associations between BMI at different ages and later cardiometabolic risk markers were examined using linear regression. Sensitive period, accumulation and mobility life course models were devised for high BMI (defined as BMI≥75th centile) and compared with a saturated BMI trajectory model. RESULTS: At ages 21, 40-59 and 60-79 years, prevalences of overweight (BMI≥25 kg/m2) were 12%, 53%, 70%, and obesity (≥30 kg/m2) 1.6%, 6.6%, and 17.6%, respectively. BMI at 21 years was positively associated with serum insulin, blood glucose, and HbA1c at 60-79 years, with increases of 1.5% (95%CI 0.8,2.3%), 0.4% (0.1,0.6%), 0.3% (0.1,0.4%) per 1 kg/m2, respectively, but showed no associations with blood pressure or blood cholesterol. However, these associations were modest compared to those between BMI at 60-79 years and serum insulin, blood glucose and HbA1c at 60-79 years, with increases of 8.6% (8.0,9.2%), 0.7% (0.5,0.9%), and 0.5% (0.4,0.7%) per 1 kg/m2, respectively. BMI at 60-79 years was also associated with total cholesterol and blood pressure. Associations for BMI at 40-59 years were mainly consistent with those of BMI at 60-79 years. None of the life course models fitted the data as well as the saturated model for serum insulin. A sensitive period at 50 years for glucose and HbA1c and sensitive period at 70 years for blood pressure were identified. CONCLUSIONS: In this cohort of men who were thin compared to more contemporary cohorts, BMI in later life was the dominant influence on cardiovascular and diabetes risk. BMI in early adult life may have a small long-term effect on diabetes risk

    Realities of bridge resilience in Small Island Developing States

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    Small Island Developing States (SIDS) are acknowledged as particularly vulnerable to extreme climate events; however, the realities for transport infrastructure and bridges are still poorly studied. Assessing bridges in this context can be challenging due to data scarcity, a lack of local standards, and uncertainty due to climate change. While bridges are designed to connect transport networks, they also carry energy, water, and communication networks, making them critical cascading failure points worthy of special attention in terms of risk assessment and resilience measures. We explore what resilience actually means for the design and management of SIDS bridge infrastructure by applying a post disaster forensics and systems approach that is not reliant on complex methods or large amounts of data. To demonstrate the practicality of our approach, we apply it to the island of Dominica, which is regularly impacted by both tropical storms and hurricanes. Our results document the extreme conditions for infrastructure and nearby settlements and the complex interrelated physical processes that occur during these events. We reflect on the implications for design approaches for bridges under these conditions and detail specific recommendations on how the resilience of existing and new bridges can be enhanced through practical measures that are achievable, even within the constraints experienced by those managing bridge infrastructure in SIDS contexts. This work adds to the growing number of studies exploring forensic disaster investigation and systems thinking, but is the first to explore bridge resilience in SIDS

    Process evaluation for complex interventions in primary care: understanding trials using the normalization process model

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    Background: the Normalization Process Model is a conceptual tool intended to assist in understanding the factors that affect implementation processes in clinical trials and other evaluations of complex interventions. It focuses on the ways that the implementation of complex interventions is shaped by problems of workability and integration.Method: in this paper the model is applied to two different complex trials: (i) the delivery of problem solving therapies for psychosocial distress, and (ii) the delivery of nurse-led clinics for heart failure treatment in primary care.Results: application of the model shows how process evaluations need to focus on more than the immediate contexts in which trial outcomes are generated. Problems relating to intervention workability and integration also need to be understood. The model may be used effectively to explain the implementation process in trials of complex interventions.Conclusion: the model invites evaluators to attend equally to considering how a complex intervention interacts with existing patterns of service organization, professional practice, and professional-patient interaction. The justification for this may be found in the abundance of reports of clinical effectiveness for interventions that have little hope of being implemented in real healthcare setting

    Estimating prevalence of overweight and obesity at the neighborhood level: the value of maternal height and weight data available on birth certificate records

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    <p>Abstract</p> <p>Objective</p> <p>To determine the value of maternal height and weight data on birth certificate records when estimating prevalence of overweight and obese adults at the neighborhood level.</p> <p>Research Design and Methods</p> <p>Regression analysis was used to determine how much variation in the percentage of the adult population with a body mass index (BMI) of ≥ 25 (based on survey data) could be accounted for by the percentage of mothers with BMI ≥ 25 (based on birth certificate data) -- alone and in combination with other sociodemographic characteristics of census tracts.</p> <p>Results</p> <p>Alone, the percentage of mothers with BMI ≥ 25 explained more than half (R<sup>2 </sup>= .52) of the variation in the percentage of all residents in census tracts with BMI ≥ 25; in combination with several measures of the sociodemographic characteristics of the census tracts, 75% ( R<sup>2 </sup>= 75.2) of the variation is explained.</p> <p>Conclusions</p> <p>Maternal height and weight data available from birth certificate records may be useful for identifying neighborhoods with relatively high or low prevalence of adult residents who are overweight or obese. This is especially true if used in combination with readily available census data.</p

    The home environment and childhood obesity in low-income households: indirect effects via sleep duration and screen time

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    Background Childhood obesity disproportionally affects children from low-income households. With the aim of informing interventions, this study examined pathways through which the physical and social home environment may promote childhood overweight/obesity in low-income households. Methods Data on health behaviors and the home environment were collected at home visits in low-income, urban households with either only normal weight (n = 48) or predominantly overweight/obese (n = 55) children aged 6–13 years. Research staff conducted comprehensive, in-person audits of the foods, media, and sports equipment in each household. Anthropometric measurements were collected, and children’s physical activity was assessed through accelerometry. Caregivers and children jointly reported on child sleep duration, screen time, and dietary intake of foods previously implicated in childhood obesity risk. Path analysis was used to test direct and indirect associations between the home environment and child weight status via the health behaviors assessed. Results Sleep duration was the only health behavior associated with child weight status (OR = 0.45, 95% CI: 0.27, 0.77), with normal weight children sleeping 33.3 minutes/day longer on average than overweight/obese children. The best-fitting path model explained 26% of variance in child weight status, and included paths linking chaos in the home environment, lower caregiver screen time monitoring, inconsistent implementation of bedtime routines, and the presence of a television in children’s bedrooms to childhood overweight/obesity through effects on screen time and sleep duration. Conclusions This study adds to the existing literature by identifying aspects of the home environment that influence childhood weight status via indirect effects on screen time and sleep duration in children from low-income households. Pediatric weight management interventions for low-income households may be improved by targeting aspects of the physical and social home environment associated with sleep

    Impacts of climate change on plant diseases – opinions and trends

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    There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

    Design and descriptive results of the "Growth, Exercise and Nutrition Epidemiological Study In preSchoolers": The GENESIS Study

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    BACKGROUND: The Growth, Exercise and Nutrition Epidemiological Study in preSchoolers (GENESIS) attempts to evaluate the food and nutrient intakes, as well as growth and development of a representative sample of Greek toddlers and preschool children. In the current work the study design, data collection procedures and some preliminary data of the GENESIS study are presented. METHODS: From April 2003 to July 2004, 1218 males and 1156 females 1 to 5 years old, stratified by parental educational level (Census 1999), were examined from 105 nurseries in five counties. Approximately 300 demographic, lifestyle, physical activity, dietary, anthropometrical and DNA variables have been recorded from the study population (children and parents). RESULTS: Regarding anthropometrical indices, boys were found to be taller than girls at all ages (P < 0.05) and heavier only for the age period from 1 to 3 years old (P < 0.05). No significant differences were found between genders regarding the prevalence of at risk of overweight (16.5% to 18.6% for boys and 18.5 to 20.6 % for girls) and overweight (14.0% to 18.9% for boys and 12.6% to 20.0% for girls). Additionally, boys older than 2 years of age were found to have a higher energy intake compared to girls (P < 0.05). A similar tendency was observed regarding the mean dietary intake of fat, saturated fat, carbohydrates and protein with boys exhibiting a higher intake than girls in most age groups (P < 0.05). CONCLUSION: The prevalence of overweight in the current preschool population is considerably high. Future but more extensive analyses of the GENESIS data will be able to reveal the interactions of the parameters leading to this phenomenon
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