Claire Griffiths

The use of measures of obesity in childhood for predicting obesity and the development of obesity-related diseases in adulthood: a systematic review and meta-analysis

BACKGROUND It is uncertain which simple measures of childhood obesity are best for predicting future obesity-related health problems and the persistence of obesity into adolescence and adulthood. OBJECTIVES To investigate the ability of simple measures, such as body mass index (BMI), to predict the persistence of obesity from childhood into adulthood and to predict obesity-related adult morbidities. To investigate how accurately simple measures diagnose obesity in children, and how acceptable these measures are to children, carers and health professionals. DATA SOURCES Multiple sources including MEDLINE, EMBASE and The Cochrane Library were searched from 2008 to 2013. METHODS Systematic reviews and a meta-analysis were carried out of large cohort studies on the association between childhood obesity and adult obesity; the association between childhood obesity and obesity-related morbidities in adulthood; and the diagnostic accuracy of simple childhood obesity measures. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and a modified version of the Quality in Prognosis Studies (QUIPS) tool. A systematic review and an elicitation exercise were conducted on the acceptability of the simple measures. RESULTS Thirty-seven studies (22 cohorts) were included in the review of prediction of adult morbidities. Twenty-three studies (16 cohorts) were included in the tracking review. All studies included BMI. There were very few studies of other measures. There was a strong positive association between high childhood BMI and adult obesity [odds ratio 5.21, 95% confidence interval (CI) 4.50 to 6.02]. A positive association was found between high childhood BMI and adult coronary heart disease, diabetes and a range of cancers, but not stroke or breast cancer. The predictive accuracy of childhood BMI to predict any adult morbidity was very low, with most morbidities occurring in adults who were of healthy weight in childhood. Predictive accuracy of childhood obesity was moderate for predicting adult obesity, with a sensitivity of 30% and a specificity of 98%. Persistence of obesity from adolescence to adulthood was high. Thirty-four studies were included in the diagnostic accuracy review. Most of the studies used the least reliable reference standard (dual-energy X-ray absorptiometry); only 24% of studies were of high quality. The sensitivity of BMI for diagnosing obesity and overweight varied considerably; specificity was less variable. Pooled sensitivity of BMI was 74% (95% CI 64.2% to 81.8%) and pooled specificity was 95% (95% CI 92.2% to 96.4%). The acceptability to children and their carers of BMI or other common simple measures was generally good. LIMITATIONS Little evidence was available regarding childhood measures other than BMI. No individual-level analysis could be performed. CONCLUSIONS Childhood BMI is not a good predictor of adult obesity or adult disease; the majority of obese adults were not obese as children and most obesity-related adult morbidity occurs in adults who had a healthy childhood weight. However, obesity (as measured using BMI) was found to persist from childhood to adulthood, with most obese adolescents also being obese in adulthood. BMI was found to be reasonably good for diagnosing obesity during childhood. There is no convincing evidence suggesting that any simple measure is better than BMI for diagnosing obesity in childhood or predicting adult obesity and morbidity. Further research on obesity measures other than BMI is needed to determine which is the best tool for diagnosing childhood obesity, and new cohort studies are needed to investigate the impact of contemporary childhood obesity on adult obesity and obesity-related morbidities. STUDY REGISTRATION This study is registered as PROSPERO CRD42013005711. FUNDING The National Institute for Health Research Health Technology Assessment programme.

Cross‐Sectional Comparisons of BMI and Waist Circumference in British Children: Mixed Public Health Messages

Research suggests that there has been a leveling off in obesity prevalence occurring in the child population. However, a concern with the evidence base is that all of the studies have relied upon the use of BMI. The purpose of this study was to compare waist circumference (WC), BMI, and waist‐to‐height ratio (WHtR) data in three different sample of children (total number: 14,697) typically aged 11–12 years. Obesity prevalence defined by BMI did not change significantly between measurement years (2005 boys 20.6%, girls 18.0%; 2006 boys 19.3%, girls 17.3%; 2007 boys 19.8%, girls 16.4%). Obesity prevalence defined by WC was considerably higher especially, in girls (2005 boys 26.3%, girls 35.6%; 2006 boys 20.3%, girls 28.2%; 2007 boys 22.1%, girls 30.1%). The prevalence of children defined as “at risk” according to WHtR (2005 boys 23.3%, girls 21.1%; 2006 boys 16.7%, girls 15.6%; 2007 boys 17.6%, girls 17.2%) was found to be between obesity prevalence, estimated using BMI and WC. This data are the most up to date collection that includes BMI and WC in three large samples of children and clearly demonstrates inconsistencies between different measurements based on current classification systems. There is a need to understand the relationship between BMI and WC, with growth and health risk to establish a consistent public health message that is easily understood by the public.

A cross sectional study investigating the association between exposure to food outlets and childhood obesity in Leeds, UK

BackgroundCurrent UK policy in relation to the influence of the ‘food environment’ on childhood obesity appears to be driven largely on assumptions or speculations because empirical evidence is lacking and findings from studies are inconsistent. The aim of this study was to investigate the number of food outlets and the proximity of food outlets in the same sample of children, without solely focusing on fast food.MethodsCross sectional study over 3 years (n = 13,291 data aggregated). Body mass index (BMI) was calculated for each participant, overweight and obesity were defined as having a BMI >85th (sBMI 1.04) and 95th (sBMI 1.64) percentiles respectively (UK90 growth charts). Home and school neighbourhoods were defined as circular buffers with a 2 km Euclidean radius, centred on these locations. Commuting routes were calculated using the shortest straight line distance, with a 2 km buffer to capture varying routes. Data on food outlet locations was sourced from Leeds City Council covering the study area and mapped against postcode. Food outlets were categorised into three groups, supermarkets, takeaway and retail. Proximity to the nearest food outlet in the home and school environmental domain was also investigated. Age, gender, ethnicity and deprivation (IDACI) were included as covariates in all models.ResultsThere is no evidence of an association between the number of food outlets and childhood obesity in any of these environments; Home Q4 vs. Q1 OR = 1.11 (95% CI = 0.95-1.30); School Q4 vs. Q1 OR = 1.00 (95% CI 0.87 – 1.16); commute Q4 vs. Q1 OR = 0.1.00 (95% CI 0.83 – 1.20). Similarly there is no evidence of an association between the proximity to the nearest food outlet and childhood obesity in the home (OR = 0.77 [95% CI = 0.61 – 0.98]) or the school (OR = 1.01 [95% CI 0.84 – 1.23]) environment.ConclusionsThis study provides little support for the notion that exposure to food outlets in the home, school and commuting neighbourhoods increase the risk of obesity in children. It seems that the evidence is not well placed to support Governmental interventions/recommendations currently being proposed and that policy makers should approach policies designed to limit food outlets with caution.

Area-level deprivation and adiposity in children: is the relationship linear?

Objective:It has been suggested that childhood obesity is inversely associated with deprivation, such that the prevalence is higher in more deprived groups. However, comparatively few studies actually use an area-level measure of deprivation, limiting the scope to assess trends in the association with obesity for this indicator. Furthermore, most assume a linear relationship. Therefore, the aim of this study was to investigate associations between area-level deprivation and three measures of adiposity in children: body mass index (BMI), waist circumference (WC) and waist-to-height ratio (WHtR).Design:This is a cross-sectional study in which data were collected on three occasions a year apart (2005–2007).Subjects:Data were available for 13 333 children, typically aged 11–12 years, from 37 schools and 542 lower super-output areas (LSOAs).Measures:Stature, mass and WC. Obesity was defined as a BMI and WC exceeding the 95th centile according to British reference data. WHtR exceeding 0.5 defined obesity. The Index of Multiple Deprivation affecting children (IDACI) was used to determine area-level deprivation.Results:Considerable differences in the prevalence of obesity exist between the three different measures. However, for all measures of adiposity the highest probability of being classified as obese is in the middle of the IDACI range. This relationship is more marked in girls, such that the probability of being obese for girls living in areas at the two extremes of deprivation is around half that at the peak, occurring in the middle.Conclusion:These data confirm the high prevalence of obesity in children and suggest that the relationship between obesity and residential area-level deprivation is not linear. This is contrary to the ‘deprivation theory’ and questions the current understanding and interpretation of the relationship between obesity and deprivation in children. These results could help make informed decisions at the local level.

Using Geographic Information Systems to measure retail food environments: Discussion of methodological considerations and a proposed reporting checklist (Geo-FERN)

Abstract Geographic Information Systems (GIS) are widely used to measure retail food environments. However the methods used are hetrogeneous, limiting collation and interpretation of evidence. This problem is amplified by unclear and incomplete reporting of methods. This discussion (i) identifies common dimensions of methodological diversity across GIS‐based food environment research (data sources, data extraction methods, food outlet construct definitions, geocoding methods, and access metrics), (ii) reviews the impact of different methodological choices, and (iii) highlights areas where reporting is insufficient. On the basis of this discussion, the Geo‐FERN reporting checklist is proposed to support methodological reporting and interpretation. HighlightsGIS methods pertaining to the retail food environment (RFE) are varied.Reporting of GIS methods pertaining to the RFE are often unclear or incomplete.Evaluation and interpretation of research is limited due to inconsistent reporting.The Geo‐FERN checklist supports clear and comprehensive reporting.The Geo‐FERN checklist also supports critical appraisal of RFE research.

Physical Activity and Sedentary Behavior Clustering: Segmentation to Optimize Active Lifestyles

BACKGROUND Increasingly the health impacts of physical inactivity are being distinguished from those of sedentary behavior. Nevertheless, deleterious health prognoses occur when these behaviors combine, making it a Public Health priority to establish the numbers and salient identifying factors of people who live with this injurious combination. METHODS Using an observational between-subjects design, a nonprobability sample of 22,836 participants provided data on total daily activity. A 2-step hierarchical cluster analysis identified the optimal number of clusters and the subset of distinguishing variables. Univariate analyses assessed significant cluster differences. RESULTS High levels of sitting clustered with low physical activity. The Ambulatory & Active cluster (n = 6254) sat for 2.5 to 5 h·d(-1) and were highly active. They were significantly younger, included a greater proportion of males and reported low Indices of Multiple Deprivation compared with other clusters. Conversely, the Sedentary & Low Active cluster (n = 6286) achieved ≤60 MET·min·wk(-1) of physical activity and sat for ≥8 h·d(-1). They were the oldest cluster, housed the largest proportion of females and reported moderate Indices of Multiple Deprivation. CONCLUSIONS Public Health systems may benefit from developing policy and interventions that do more to limit sedentary behavior and encourage light intensity activity in its place.

How different data sources and definitions of neighbourhood influence the association between food outlet availability and body mass index: a cross-sectional study

Inconsistencies in methodologies continue to inhibit understanding of the impact of the environment on body mass index (BMI). To estimate the effect of these differences, we assessed the impact of using different definitions of neighbourhood and data sets on associations between food outlet availability within the environment and BMI. Previous research has not extended this to show any differences in the strength of associations between food outlet availability and BMI across both different definitions of neighbourhood and data sets. Descriptive statistics showed differences in the number of food outlets, particularly other food retail outlets between different data sets and definitions of neighbourhood. Despite these differences, our key finding was that across both different definitions of neighbourhood and data sets, there was very little difference in size of associations between food outlets and BMI. Researchers should consider and transparently report the impact of methodological choices such as the definition of neighbourhood and acknowledge any differences in associations between the food environment and BMI.

Physical activity assessment for public health: efficacious use of the single-item measure

OBJECTIVES The accurate mass assessment of physical activity is essential for effective Public Health policy and practice. Combined with a desire to minimize participant burden, the self-reported single-item physical activity screening measure has become increasingly attractive and widespread. To help reduce any potential misclassification, refining this instrumentation in line with any changes in prescribed activity levels is essential to optimize accuracy. STUDY DESIGN This study compares the levels of agreement, sensitivity and specificity for the single-item measure versus International Physical Activity Questionnaire (IPAQ) using current physical activity recommendations. METHODS Agreement was assessed in a non-probability sample of 7650 adults. The κ statistic, sensitivity and specificity were used to assess agreement between the tools for classifying participants as sufficiently active for health (≥150 min of physical activity per week) or not, and being classified as inactive (<30 of minutes of physical activity per week) or not. RESULTS The single-item measure showed weak agreement with the IPAQ for identifying participants who met the current physical activity guidelines (κ = 0.13, 95% CI 0.12 to 0.14), sensitivity was 18.7% and specificity was 97.2%. For the classification of inactive participants it showed a moderate agreement with IPAQ (κ = 0.45, 95% CI 0.43 to 0.47), sensitivity was 74.2% and specificity was 79.7%. CONCLUSIONS The single-item measure had a low diagnostic capacity compared to IPAQ. Further research is needed if it is to be used in large scale surveys and interventions where screening for sufficiently active or inactive individuals is the goal.

Associations between the combined physical activity environment, socioeconomic status, and obesity: a cross-sectional study

Aims: This study investigates associations between the combined physical activity environment and obesity and explores any sub-group effects by individual-level socioeconomic status. Methods: In a large cross-sectional cohort (n = 22,889) from the Yorkshire Health Study, body mass index was calculated using self-reported height and weight and obesity was defined as a body mass index ≥ 30. The physical activity environment was split into ‘unfavourable physical activity’, ‘moderately favourable physical activity’ and ‘favourable physical activity’ environments. This was based on the count of parks and physical activity facilities within a 2 km radial buffer centred on home addresses. A favourable physical activity environment was defined as having ≥1 physical activity facility and ≥1 park, unfavourable as having no physical activity facility and park and any other combinations defined as moderately favourable. Logistic regression (odds ratios) identified associations with obesity. Results: Relative to ‘unfavourable physical activity environments’, individuals within favourable physical activity environments were less likely to be obese (odds ratio = 0.90; 95% confidence interval = 0.82–0.97), and there was no effect for moderately favourable environment. Furthermore, once stratified by education level, this relationship was only present for those of higher education. Conclusion: Our findings provide novel UK evidence and is one of the first papers internationally that highlights the importance of considering the interplay of individual-level socioeconomic factors when investigating associations between the physical activity environment and obesity.

Access and quality of parks and associations with obesity: A cross-sectional study

Public health is increasingly engaging with multi-faceted obesity prevention efforts. Although parks represent key community assets for broader public health, they may not be distributed equitably and associations with obesity are equivocal. We investigated park access and quality relative to deprivation and obesity with individual-level data from the Yorkshire Health Study. Compared to the least deprived areas, the moderately and most deprived areas had a greater park access and park quality in terms of features and amenities. However, parks in the moderately and most deprived areas also had the most safety concerns and incivilities. Although deprivation was associated with obesity, contrary to current policy guidance, both park access and quality appear less important for understanding variations in obesity within this study. Although sub-group analyses by deprivation tertile revealed that low quality park amenities in highly and moderately deprived areas may be important for understanding obesity prevalence, all other associations were non-significant.