Service evaluation of the GOALS family-based childhood obesity treatment intervention during the first 3 years of implementation.

Objectives: To evaluate the impact of the GOALS (Getting Our Active Lifestyles Started) family-based childhood obesity treatment intervention during the first 3 years of implementation. Design: Single-group repeated measures with qualitative questionnaires. Setting: Community venues in a socioeconomically deprived, urban location in the North-West of England. Participants: 70 overweight or obese children (mean age 10.5 years, 46% boys) and their parents/carers who completed GOALS between September 2006 and March 2009. Interventions: GOALS was a childhood obesity treatment intervention that drew on social cognitive theory to promote whole family lifestyle change. Sessions covered physical activity (PA), diet and behaviour change over 18 2 h weekly group sessions (lasting approximately 6 months). A Template for Intervention Description and Replication (TIDieR) checklist of intervention components is provided. Primary and secondary outcome measures: The primary outcome measure was child body mass index (BMI) z-score, collected at baseline, post-intervention and 12 months. Secondary outcome measures were child selfperceptions, parent/carer BMI and qualitative changes in family diet and PA (parent/carer questionnaire). Results: Child BMI z-score reduced by 0.07 from baseline to post-intervention (p<0.001) and was maintained at 12 months (p<0.05). There was no change in parent/carer BMI or child self-perceptions, other than an increase in perceived social acceptance from baseline to post-intervention (p<0.05). Parents/carers reported positive changes to family PA and dietary behaviours after completing GOALS. Conclusions: GOALS completion was associated with small improvements in child BMI z-score and improved family PA and dietary behaviours. Several intervention modifications were necessary during the implementation period and it is suggested childhood obesity treatment interventions need time to embed before a definitive evaluation is conducted. Researchers are urged to use the TIDieR checklist to ensure transparent reporting of interventions and facilitate the translation of evidence to practice

Predicting adult obesity from childhood obesity : A systematic review and meta-analysis

A systematic review and meta-analysis was performed to investigate the ability of simple measures of childhood obesity such as body mass index (BMI) to predict future obesity in adolescence and adulthood. Large cohort studies, which measured obesity both in childhood and in later adolescence or adulthood, using any recognized measure of obesity were sought. Study quality was assessed. Studies were pooled using diagnostic meta-analysis methods. Fifteen prospective cohort studies were included in the meta-analysis. BMI was the only measure of obesity reported in any study, with 200,777 participants followed up. Obese children and adolescents were around five times more likely to be obese in adulthood than those who were not obese. Around 55% of obese children go on to be obese in adolescence, around 80% of obese adolescents will still be obese in adulthood and around 70% will be obese over age 30. Therefore, action to reduce and prevent obesity in these adolescents is needed. However, 70% of obese adults were not obese in childhood or adolescence, so targeting obesity reduction solely at obese or overweight children needs to be considered carefully as this may not substantially reduce the overall burden of adult obesity

The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: a pooled analysis.

BACKGROUND: The effects of systolic blood pressure (SBP), serum total cholesterol (TC), fasting plasma glucose (FPG), and body mass index (BMI) on the risk of cardiovascular diseases (CVD) have been established in epidemiological studies, but consistent estimates of effect sizes by age and sex are not available. METHODS: We reviewed large cohort pooling projects, evaluating effects of baseline or usual exposure to metabolic risks on ischemic heart disease (IHD), hypertensive heart disease (HHD), stroke, diabetes, and, as relevant selected other CVDs, after adjusting for important confounders. We pooled all data to estimate relative risks (RRs) for each risk factor and examined effect modification by age or other factors, using random effects models. RESULTS: Across all risk factors, an average of 123 cohorts provided data on 1.4 million individuals and 52,000 CVD events. Each metabolic risk factor was robustly related to CVD. At the baseline age of 55-64 years, the RR for 10 mmHg higher SBP was largest for HHD (2.16; 95% CI 2.09-2.24), followed by effects on both stroke subtypes (1.66; 1.39-1.98 for hemorrhagic stroke and 1.63; 1.57-1.69 for ischemic stroke). In the same age group, RRs for 1 mmol/L higher TC were 1.44 (1.29-1.61) for IHD and 1.20 (1.15-1.25) for ischemic stroke. The RRs for 5 kg/m(2) higher BMI for ages 55-64 ranged from 2.32 (2.04-2.63) for diabetes, to 1.44 (1.40-1.48) for IHD. For 1 mmol/L higher FPG, RRs in this age group were 1.18 (1.08-1.29) for IHD and 1.14 (1.01-1.29) for total stroke. For all risk factors, proportional effects declined with age, were generally consistent by sex, and differed by region in only a few age groups for certain risk factor-disease pairs. CONCLUSION: Our results provide robust, comparable and precise estimates of the effects of major metabolic risk factors on CVD and diabetes by age group

Estimating the burden of disease attributable to four selected environmental risk factors in South Africa

The first South African National Burden of Disease study quantified the underlying causes of premature mortality and morbidity experienced in South Africa in the year 2000. This was followed by a Comparative Risk Assessment to estimate the contributions of 17 selected risk factors to burden of disease in South Africa. This paper describes the health impact of exposure to four selected environmental risk factors: unsafe water, sanitation and hygiene; indoor air pollution from household use of solid fuels; urban outdoor air pollution and lead exposure.The study followed World Health Organization comparative risk assessment methodology. Population-attributable fractions were calculated and applied to revised burden of disease estimates (deaths and disability adjusted life years, [DALYs]) from the South African Burden of Disease study to obtain the attributable burden for each selected risk factor. The burden attributable to the joint effect of the four environmental risk factors was also estimated taking into account competing risks and common pathways. Monte Carlo simulation-modeling techniques were used to quantify sampling, uncertainty.Almost 24 000 deaths were attributable to the joint effect of these four environmental risk factors, accounting for 4.6% (95% uncertainty interval 3.8-5.3%) of all deaths in South Africa in 2000. Overall the burden due to these environmental risks was equivalent to 3.7% (95% uncertainty interval 3.4-4.0%) of the total disease burden for South Africa, with unsafe water sanitation and hygiene the main contributor to joint burden. The joint attributable burden was especially high in children under 5 years of age, accounting for 10.8% of total deaths in this age group and 9.7% of burden of disease.This study highlights the public health impact of exposure to environmental risks and the significant burden of preventable disease attributable to exposure to these four major environmental risk factors in South Africa. Evidence-based policies and programs must be developed and implemented to address these risk factors at individual, household, and community levels

The age-specific quantitative effects of metabolic risk factors on cardiovascular diseases and diabetes: A pooled analysis

BACKGROUND: The effects of systolic blood pressure (SBP), serum total cholesterol (TC), fasting plasma glucose (FPG), and body mass index (BMI) on the risk of cardiovascular diseases (CVD) have been established in epidemiological studies, but consistent estimates of effect sizes by age and sex are not available. METHODS: We reviewed large cohort pooling projects, evaluating effects of baseline or usual exposure to metabolic risks on ischemic heart disease (IHD), hypertensive heart disease (HHD), stroke, diabetes, and, as relevant selected other CVDs, after adjusting for important confounders. We pooled all data to estimate relative risks (RRs) for each risk factor and examined effect modification by age or other factors, using random effects models. RESULTS: Across all risk factors, an average of 123 cohorts provided data on 1.4 million individuals and 52,000 CVD events. Each metabolic risk factor was robustly related to CVD. At the baseline age of 55-64 years, the RR for 10 mmHg higher SBP was largest for HHD (2.16; 95% CI 2.09-2.24), followed by effects on both stroke subtypes (1.66; 1.39-1.98 for hemorrhagic stroke and 1.63; 1.57-1.69 for ischemic stroke). In the same age group, RRs for 1 mmol/L higher TC were 1.44 (1.29-1.61) for IHD and 1.20 (1.15-1.25) for ischemic stroke. The RRs for 5 kg/m(2) higher BMI for ages 55-64 ranged from 2.32 (2.04-2.63) for diabetes, to 1.44 (1.40-1.48) for IHD. For 1 mmol/L higher FPG, RRs in this age group were 1.18 (1.08-1.29) for IHD and 1.14 (1.01-1.29) for total stroke. For all risk factors, proportional effects declined with age, were generally consistent by sex, and differed by region in only a few age groups for certain risk factor-disease pairs. CONCLUSION: Our results provide robust, comparable and precise estimates of the effects of major metabolic risk factors on CVD and diabetes by age group.Peer reviewe

Mortality attributable to excess adiposity in England and Wales in 2003 and 2015: explorations with a spreadsheet implementation of the Comparative Risk Assessment methodology

Our aim was to estimate the burden of fatal disease attributable to excess adiposity in England and Wales in 2003 and 2015 and to explore the sensitivity of the estimates to the assumptions and methods used

Secular Declines in the Association Between Obesity and Mortality in the United States

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86831/1/j.1728-4457.2011.00429.x.pd