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1.
Figure

Figure. From: Differences Between the Perceived and Actual Age of Overweight Onset in Children and Adolescents.

The relationship between actual age of overweight onset, on the basis of growth chart data, and child's self-reported age of overweight onset, accounting for child's current age (A); the relationship between parent-reported age of child's overweight onset and child's self-reported age of overweight onset, controlling for child's current age (B); the relationship between actual age of overweight onset, on the basis of growth chart data, and parent-reported age of child's overweight onset (C); Bland-Altman comparison between actual age of overweight onset, on the basis of growth chart data, and the difference between actual and child's self-reported age of onset, accounting for child's current age (D).

Marian Tanofsky-Kraff, et al. MedGenMed. 2006;8(3):18-18.
2.
Figure 1.

Figure 1. From: Cognitive Function and Overweight in Preschool Children.

Association between cognitive function at age 4 years (1-standard-deviation (SD) change in cognitive test score) and change in weight status between ages 4 years and 6 years in the Menorca Cohort, Spain, 1997–2003. The reference group (“Healthy”) was children who maintained a healthy weight status between ages 4 years and 6 years. “Unhealthy” children were those who maintained an unhealthy weight status between ages 4 years and 6 years (were at risk of becoming overweight or were overweight). Children in the “Worsened” group were those whose weight status worsened between ages 4 years and 6 years (shifted from healthy weight to at risk of overweight or overweight, or from at risk of overweight to overweight). Children in the “Improved” group were those whose weight status improved between ages 4 years and 6 years (shifted from overweight or at risk of overweight to healthy weight, or from overweight to at risk of overweight). Odds ratios (ORs) were adjusted for age, school grade, psychologist, body mass index (weight (kg)/height (m)2) z score at age 4 years, body mass index z score2 at age 4 years, child's sex, birth weight and height, gestational age, maternal smoking during pregnancy, maternal education, maternal age, prepregnancy height and body mass index, breastfeeding, maternal smoking at child's age 4 years, number of siblings at child's age 4 years, and child's consumption of sweetened beverages, sweets, and meat at age 4 years. Bars, 95% confidence interval (CI).

Mònica Guxens, et al. Am J Epidemiol. 2009 August 15;170(4):438-446.
3.
Figure 1

Figure 1. From: Early-Life Overweight Trajectory and CKD in the 1946 British Birth Cohort Study.

Early-life overweight latent class profiles for males (n = 2,564). Solid line and circles, never overweight (71.4%); dashed line and diamonds, prepubertal-only overweight (21.0%); dotted line and triangles, pubertal-onset overweight (5.0%); and dot-dashed line and squares, always overweight (2.7%).

Richard J. Silverwood, et al. Am J Kidney Dis. 2013 August;62(2):276-284.
4.
Figure 2

Figure 2. From: Early-Life Overweight Trajectory and CKD in the 1946 British Birth Cohort Study.

Early-life overweight latent class profiles for females (n = 2,320). Solid line and circles, never overweight (80.6%); dashed line and diamonds, prepubertal-only overweight (8.9%); dotted line and triangles, pubertal-onset overweight (6.6%); and dot-dashed line and squares, always overweight (3.9%).

Richard J. Silverwood, et al. Am J Kidney Dis. 2013 August;62(2):276-284.
5.
Figure 2

Figure 2. Scatter plots of relations of implicit (IAT) and explicit weight bias as a function of three weight indicators (BMI, percentage of overweight and underweight people) at the national level.. From: Overweight People Have Low Levels of Implicit Weight Bias, but Overweight Nations Have High Levels of Implicit Weight Bias.

Note. The weight bias scores ranges from +2 to -2 for the IAT and from +3 to -3 for the explicit, with 0 indicating no relative preference between thin people over overweight people. More positive scores indicate a preference for thin people over overweight people, while more negative scores indicate a preference for overweight people over thin people.

Maddalena Marini, et al. PLoS One. 2013;8(12):e83543.
6.
Fig. 1

Fig. 1. From: Residual stigma: Psychological distress among the formerly overweight.

Elevated suicide attempts, any depressive disorders, and any anxiety disorders in the formerly overweight group, compared with the subsequently overweight and consistently normal weight groups during past year. Note: *p < .05, **p < .01, ***p < .0001. Odds ratios are adjusted for age, sex, income, and number of chronic-physical-health conditions. There were no significant differences between the formerly overweight group and the consistently overweight group with respect to any depressive disorder and any anxiety disorder. However, the formerly overweight group demonstrated significantly elevated odds for suicide attempts, compared with the consistently overweight group.

Becca R. Levy, et al. Soc Sci Med. 2012 July;75(2):297-299.
7.
FIGURE 2

FIGURE 2. From: The presence of friends increases food intake in youth123.

Mean (±SE) energy intake from nutrient-dense and energy-dense foods. Left panel: results of a mixed regression model indicated an interaction of the partners' weight status on consumption of nutrient-dense foods (P < 0.02). Overweight participants eating with an overweight partner (n = 20) consumed more nutrient-dense food than did overweight participants eating with a nonoverweight eating partner (n = 25). Nonoverweight participants eating with other nonoverweight participants (n = 60) consumed more nutrient-dense foods than did nonoverweight partners eating with an overweight eating partner. Right panel: interaction of partners' weight status on consumption of energy-dense foods (P < 0.02). Overweight participants eating with an overweight partner consumed more energy-dense foods than did overweight participants eating with a nonoverweight eating partner. Nonoverweight participants eating with other nonoverweight participants consumed more energy-dense foods than did nonoverweight partners eating with an overweight eating partner.

Sarah-Jeanne Salvy, et al. Am J Clin Nutr. 2009 August;90(2):282-287.
8.
Figure 1

Figure 1. From: Global Gender Disparities in Obesity: A Review.

Worldwide gender disparities in overweight and obesity prevalence. To illustrate gender disparities in overweight and obesity, we calculated the mean difference between female and male prevalence of overweight (or obesity). The bars >0 indicate the mean percentage of greater female (than male) overweight or obesity, whereas the bars <0 indicate the mean percentage of male (than female) overweight or obesity; thus, the greater the magnitude of the bar, the greater the gender disparity is in overweight or obesity. A, The mean percentage of difference between female and male overweight and obesity prevalence by World Bank income group. B, the mean percentage of difference between female and male overweight and obesity prevalence by World Bank region. OECD, Organisation for Economic Co-operation and Development.

Rebecca Kanter, et al. Adv Nutr. 2012 July;3(4):491-498.
9.
Figure 3

Figure 3. Offspring born by CS have higher incidence of overweight.. From: Mode of Delivery and Offspring Body Mass Index, Overweight and Obesity in Adult Life: A Systematic Review and Meta-Analysis.

Forest Plot showing the pooled gender, unadjusted OR for incidence of overweight in adult offspring, by mode of delivery.

Karthik Darmasseelane, et al. PLoS One. 2014;9(2):e87896.
10.
Figure 1.

Figure 1. From: The Potentially Modifiable Burden of Incident Heart Failure Due to Obesity.

The median generalized impact fraction and attributable fraction (with 2.5%–97.5% simulation intervals) derived from 10,000 bootstrap data sets using the case-load weighted-sum method, given 10 scenarios of reduced prevalence of obesity and overweight, Atherosclerosis Risk in Communities Study, 1987–2003. Scenarios for the reduced prevalence of overweight and obesity are as follows: 1) 15% reduction in obesity, shift obese to overweight; 2) 15% reduction in obesity, shift obese to normal weight; 3) 15% reduction in obesity and overweight, shift down 1 category; 4) 15% reduction in obesity and overweight, down to normal weight; 5) 30% reduction in obesity, shift obese to overweight; 6) 30% reduction in obesity, shift obese to normal weight; 7) 30% reduction in obesity and overweight, shift down 1 category; 8) 30% reduction in obesity and overweight, shift to normal weight; 9) attributable fraction, complete elimination of obesity; 10) attributable fraction, complete elimination of obesity and overweight. Bars, 95% simulation interval.

Laura R. Loehr, et al. Am J Epidemiol. 2010 October 1;172(7):781-789.
11.
Figure 2

Figure 2. From: Fundal Height Growth Curve for Underweight and Overweight and Obese Pregnant Women in Thai Population.

Fundal height (FH) of underweight and overweight and obese pregnant women as screened by different growth curves; (a) underweight pregnant women versus normal population curve; (b) underweight pregnant women versus underweight curve; (c) overweight and obese pregnant women versus normal curve; (d) overweight and obese pregnant women versus overweight and obese curve.

Jirawan Deeluea, et al. ISRN Obstet Gynecol. 2013;2013:657692.
12.
Figure 1

Figure 1. From: Impact of Simulated Ostracism on Overweight and Normal-Weight Youths' Motivation to Eat and Food Intake.

Top panel: Responses for food per trial (SE) performed by overweight (n=11) and normal-weight (n= 18) participants in the ostracism condition. Overweight youth in the ostracism condition responded more for food than overweight youth in the inclusion/control condition (p < .05). Bottom Panel: Responses for food per trial (SE) performed by overweight (n = 10) and normal-weight (n = 20) participants in the inclusion/control condition. Normal-weight youth in the ostracism condition responded less for food than normal-weight youth in the inclusion/control condition (p < .001).

Sarah-Jeanne Salvy, et al. Appetite. ;56(1):39-45.
13.
Figure 4

Figure 4. Forest plot on the association between SNP alleles and overweight in case-control studies by ethnicity.. From: Association between Variants of the Leptin Receptor Gene (LEPR) and Overweight: A Systematic Review and an Analysis of the CoLaus Study.

Figure 4a: Forest plot on the association between Q223R alleles and overweight in case-control studies by ethnicity. Overall association from random effects meta-analysis (odds ratio and 95% confidence intervals) and stratification by ethnic groups are shown, as well as heterogeneity by means of I2 value for overall measure and for subgroups. Figure 4b: Forest plot on the association between K109R alleles and overweight in case-control studies by ethnicity. Overall association from random effects meta-analysis (odds ratio and 95% confidence intervals) and stratification by ethnic groups are shown, as well as heterogeneity by means of I2 value for overall measure and for subgroups. Data from the CoLaus study are included for the Caucasian population, stratified by sex. Figure 4c: Forest plot on the association between K656N alleles and overweight in case-control studies by ethnicity. Overall association from random effects meta-analysis (odds ratio and 95% confidence intervals) and stratification by ethnic groups are shown, as well as heterogeneity by means of I2 value for overall measure and for subgroups.

Nicole Bender, et al. PLoS One. 2011;6(10):e26157.
14.
Figure 1

Figure 1. From: One Size Does Not Fit All: Identifying Risk Profiles for Overweight in Adolescent Population Subsets.

Displays the classification tree structure, including important variables, percent overweight, and the number of adolescents in each segment. NO = not overweight, O = overweight.

Rhonda BeLue, et al. J Adolesc Health. 2009 November;45(5):517-524.
15.
Figure 3

Figure 3. Insulin effects on beta activity in lean and overweight subjects.. From: Cerebrocortical Beta Activity in Overweight Humans Responds to Insulin Detemir.

A: Comparison of the insulin detemir effect on beta activity with the effects human insulin in lean and overweight subjects. The figure shows beta activity from human insulin experiments in 12 lean and 34 overweight subjects and from insulin detemir experiments in 10 overweight subjects. Data from corresponding saline experiments have been subtracted. In the second step of the clamps beta activity was significantly higher in lean than in overweight subjects (p = 0.031) and higher with insulin detemir than with human insulin in overweight subjects (p = 0.040). B: Relationship between body-mass-index (BMI) and cerebral effects of insulin. The change in beta activity induced by human insulin (filled circles and open rhombs) was negatively correlated with BMI (r = −0.38, p = 0.0086) under hyperinsulinemic euglycemic clamped conditions as previously published [15]. The open rhombs represent the data obtained from the insulin experiment of 10 overweight subjects who additionally participated in the insulin detemir experiment. The change in beta activity induced by insulin detemir infusion is shown as open squares. An arrow indicates the corresponding values of each subject and illustrates the enhancement of cerebrocortical action of insulin detemir compared to human insulin. To account for lower glucose disposal in the insulin detemir experiments, the effect of insulin detemir on beta activity has been multiplied with the individual ratio of the glucose infusion rates (GIRhuman insulin/GIRinsulin detemir).

Otto Tschritter, et al. PLoS ONE. 2007;2(11):e1196.
16.
Figure 4

Figure 4. From: Sensitization and habituation of motivated behavior in overweight and non-overweight children.

Motivated responding (mean ± SEM) on variable ratio 120 second schedules of reinforcement for overweight or non-overweight children who did or did not sensitize. Sensitization interacted with overweight status to influence responding across time blocks (p < 0.001). No differences in the rate of habituation were observed between overweight and non-overweight children who did not sensitize, but slower habituation was observed for the overweight in comparison to the non-overweight children (p = 0.003).

Leonard H. Epstein, et al. Learn Motiv. ;39(3):243-255.
17.
Figure 2

Figure 2. Secular trends in prevalence of overweight according to different gender and type of school from 2006 to 2009.. From: Secular Trends in Prevalence of Overweight and Obesity from 2006 to 2009 in Urban Asian Indian Adolescents Aged 14-17 Years.

Caption: Prevalence of overweight (in percentage, y-axis) in males, females, privately-funded and government-funded schools (x-axis) in year 2006 (white bars) and 2009 (black bars); p value<0.05 was considered significant; Overweight was defined as 85th percentile of age and gender specific cut-offs of body mass index in Asian Indians [23].

Deepak Kumar Gupta, et al. PLoS One. 2011;6(2):e17221.
18.
Fig. 1

Fig. 1. Prediction of the BMI by the association of inflammation and intracranial vault-adjusted brain region. From: Obesity-mediated inflammation may damage the brain circuit that regulates food intake.

Each group represents the results of the classification by the logistic regression. The true lean are the lean individuals that are predicted as lean, the false overweight and obese are the lean people that are predicted as overweight and obese, the true overweight and obese are the overweight and obese individuals that are predicated as overweight and obeses and the false lean are the overweight and obese people that are predicted as lean.

Fanny Cazettes, et al. Brain Res. ;1373:101-109.
19.
Figure 2

Figure 2. From: Prevalence of overweight and obese children between 1989 and 1998: population based series of cross sectional studies.

Annual increase in proportion of overweight and obese children; χ2 for trend in overweight 71.1 (P<0.001) for boys and 33.1 (P<0.001) for girls, for trend in obesity 48.3 (P<0.001) for boys and 7.3 (P=0.007) for girls. Proportion of overweight and obese boys becomes greater than girls in early 1990s and remains so

Peter Bundred, et al. BMJ. 2001 February 10;322(7282):326-326.
20.
Fig. 1

Fig. 1. From: Raised BMI cut-off for overweight in Greenland Inuit - a review.

Distribution of BMI among 20–29-year-old men in East Greenland in 1963 (n=176). The WHO definition of overweight renders 31% of young hunters overweight. Defining overweight by an Inuit 90-percentile sets the cut-off point at 27.9 kg/m2 in Inuit men (from ref. 10).

Stig Andersen, et al. Int J Circumpolar Health. 2013;72:10.3402/ijch.v72i0.21086.

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